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Intra-Household Distribution of Assets and Wealth in Ecuador

Permanent Link: http://ufdc.ufl.edu/UFE0044657/00001

Material Information

Title: Intra-Household Distribution of Assets and Wealth in Ecuador
Physical Description: 1 online resource (205 p.)
Language: english
Creator: Twyman, Jennifer Lynn
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: assets -- bargaining -- gender -- intra-household -- wealth
Food and Resource Economics -- Dissertations, Academic -- UF
Genre: Food and Resource Economics thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This dissertation is comprised of three essays that explore the intra-household distribution ofassets and wealth in Ecuador. The first essay focuses on gender differences in the likelihood of homeownership as well as the differences in housing wealth. The second essay examines the relationship between the intra-household distribution of assets and wealth and egalitarian decision-making in regards to the decisions about employment and spending one’s own income. Finally, the third essay investigates how farm management decisions are related to asset ownership and wealth. Using the bargaining power framework, we propose that the intra-household distribution of assets and wealth impacts how decisions are made within the household since it gives an indication of the spouses’ relative bargaining positions. If most of the wealth is owned by the husband (wife) then we would expect him (her) to make most of the decisions but a more equal distribution would result in more egalitarian decision-making practices. We use data from the UF-FLACSO 2010 Ecuador Household Asset Survey, a nationally representative survey that collected sex-disaggregated data regarding asset ownership and wealth from 2,892 households. We find that although there are no gender differences in the likelihood of homeownership or in the amount of housing wealth, there are several gender differences in the factors predicting home ownership and housing wealth. In terms of household decision-making, in households in which only women own real estate (compared to those in whichneither husband nor wife own real estate) women are more likely to make autonomous decisions. In households with a fairly equal distribution of wealth and when both spouses own real estate couples are more likely to make egalitarian decisions. Finally, with respect to farm management, the great majority of women land owners are involved in making agricultural decisions; their participation in fieldwork is strongly correlated to their participation in such decision-making. Although the intra-household distribution of wealth is not related toagricultural decision-making among landowning women, women’s ownership of agricultural equipment is associated with women’s participation in agricultural decisions. Overall, these results indicate that the intra-household distribution of asset ownership and wealth are related to how couples make decisions.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jennifer Lynn Twyman.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Deere, Carmen.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044657:00001

Permanent Link: http://ufdc.ufl.edu/UFE0044657/00001

Material Information

Title: Intra-Household Distribution of Assets and Wealth in Ecuador
Physical Description: 1 online resource (205 p.)
Language: english
Creator: Twyman, Jennifer Lynn
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: assets -- bargaining -- gender -- intra-household -- wealth
Food and Resource Economics -- Dissertations, Academic -- UF
Genre: Food and Resource Economics thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This dissertation is comprised of three essays that explore the intra-household distribution ofassets and wealth in Ecuador. The first essay focuses on gender differences in the likelihood of homeownership as well as the differences in housing wealth. The second essay examines the relationship between the intra-household distribution of assets and wealth and egalitarian decision-making in regards to the decisions about employment and spending one’s own income. Finally, the third essay investigates how farm management decisions are related to asset ownership and wealth. Using the bargaining power framework, we propose that the intra-household distribution of assets and wealth impacts how decisions are made within the household since it gives an indication of the spouses’ relative bargaining positions. If most of the wealth is owned by the husband (wife) then we would expect him (her) to make most of the decisions but a more equal distribution would result in more egalitarian decision-making practices. We use data from the UF-FLACSO 2010 Ecuador Household Asset Survey, a nationally representative survey that collected sex-disaggregated data regarding asset ownership and wealth from 2,892 households. We find that although there are no gender differences in the likelihood of homeownership or in the amount of housing wealth, there are several gender differences in the factors predicting home ownership and housing wealth. In terms of household decision-making, in households in which only women own real estate (compared to those in whichneither husband nor wife own real estate) women are more likely to make autonomous decisions. In households with a fairly equal distribution of wealth and when both spouses own real estate couples are more likely to make egalitarian decisions. Finally, with respect to farm management, the great majority of women land owners are involved in making agricultural decisions; their participation in fieldwork is strongly correlated to their participation in such decision-making. Although the intra-household distribution of wealth is not related toagricultural decision-making among landowning women, women’s ownership of agricultural equipment is associated with women’s participation in agricultural decisions. Overall, these results indicate that the intra-household distribution of asset ownership and wealth are related to how couples make decisions.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jennifer Lynn Twyman.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Deere, Carmen.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044657:00001


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1 INTRA HOUSEHOLD DISTRIBUTION OF ASSETS AND WEALTH IN ECUADOR By JENNIFER TWYMAN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012

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2 2012 Jennifer Twyman

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3 To my parents, family, and friends, who have always supported me over the years

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4 ACKNOWLEDGMENTS I would like to thank everyone who made it possible for me to write this dissertation and obtain my PhD. M any people have supported me over the years and I appreciate all of them I thank my advisor, Carmen Diana Deere, for her support and guidance throughout the research process. I also thank my committee members, Pilar U seche, James Sterns, and Andres Blanco for all the suggestions and encouragement. T he preliminary dissertation fieldwork grant I received from the Center for Latin American Studies that made it possible to begin fieldwork in Ecuador was greatly appreciated I am also thankful to ESPOL and FLACSO Ecuador for hosting me during my stay in Ecuador. Thanks to Zachary Catanzarite for his efforts in cleaning the data and his help ful conversations and suggestions regarding different data analyses presented in this dissertation Thanks also to my friends Gina Alvarado and Maria Bampasidou for the helpful comments and suggestions as well as being there for me and helping to keep me motivated. And, a special thanks to my parents who have always supported and encouraged me to follow my dreams.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ ........ 10 LIST OF ABBREVIATIONS ................................ ................................ ........................... 11 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 Theoretical Considerations ................................ ................................ ..................... 15 Bargaining Power and Marital Regimes ................................ ........................... 18 ................................ .............. 20 Bargaining Power and the Importance of Perceptions ................................ ..... 21 Gaps in the Literature ................................ ................................ ....................... 22 Hypotheses and Findings ................................ ................................ ....................... 24 Setting ................................ ................................ ................................ ..................... 25 Survey Design and Data Collection ................................ ................................ ........ 27 Outline and Objectives ................................ ................................ ............................ 30 2 IS THERE A GENDER GAP IN HOUSING? MARITAL PROPERTY RIGHTS IN ECUADOR ................................ ................................ ................................ .............. 33 Literature Review ................................ ................................ ................................ .... 34 Data and Methods ................................ ................................ ................................ .. 41 Results ................................ ................................ ................................ .................... 46 Comparing Owners and Non Owners ................................ .............................. 48 Multivariate Analysis ................................ ................................ ......................... 49 Discus sion and Concluding Thoughts ................................ ................................ ..... 55 3 ASSET OWNERSHIP AND DECISION MAKING IN DUAL HEADED HOUSEHOLDS IN ECUADOR ................................ ................................ ............... 72 Context ................................ ................................ ................................ ................... 77 Data ................................ ................................ ................................ ........................ 78 Conceptual Framework ................................ ................................ ........................... 84 Methods ................................ ................................ ................................ .................. 91 Results ................................ ................................ ................................ .................... 93 making as Reported by Women Themselves ................................ ................................ ................................ ... 95

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6 Comparison of the Work and Spending Decision Models (as Reported by Women) ................................ ................................ ................................ ......... 99 making as Reported by Men ....................... 100 Comparison of the Work and Spending Decision Models (as Reported by Men) ................................ ................................ ................................ ............ 102 n making ................................ ................................ ................................ ......... 103 Husband and Wife Agree that She Makes the Decision Autonomously ......... 106 Comparison of the Work and Spending Decision Models Agree Autonomous ................................ ................................ ................................ 107 Comparison of the Models of Agree Autonomous and those of Women and ................................ ................................ .......................... 108 Egalitaria n Decision making ................................ ................................ ........... 111 Comparison of the Work and Spending Decision Models Egalitarian .......... 114 Discussion and Concluding Thoughts ................................ ................................ ... 115 4 LAND OWNERSHIP AND AGRICULTURAL DECISION MAKING ...................... 144 Gender and Agriculture ................................ ................................ ......................... 144 ................................ ................................ ....... 146 Land and Development ................................ ................................ ......................... 148 Gender and Productivity ................................ ................................ ....................... 150 Objectives ................................ ................................ ................................ ............. 152 Data ................................ ................................ ................................ ...................... 152 Models ................................ ................................ ................................ .................. 155 Sub samples and Dependent Variables ................................ ......................... 156 Independent Variables and Hypotheses ................................ ......................... 158 Results ................................ ................................ ................................ .................. 160 Regressi on Results of the Paired Sample ................................ ...................... 163 ...... 166 Discussion and Concluding Thoughts ................................ ................................ ... 170 5 CONCLUSION ................................ ................................ ................................ ...... 188 LIST OF REFERENCES ................................ ................................ ............................. 197 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 205

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7 LIST OF TABLES Table page 2 1 The household distribution of homeownership by sex (of owner occupied homes) ................................ ................................ ................................ ............... 60 2 2 Distribution of dwelling tenure by household in Ecuador, 2010 .......................... 61 2 3 Form of dwelling acquisition by rural and urban households in Ecuador, 2010 .. 61 2 4 Type of financing for purchased or constructed homes (n = 1,528) .................... 61 2 5 L ist of variables and their definitions. ................................ ................................ .. 62 2 6 Descriptive statistics for categorical variables, composition (percent) of adult sample in Ecuador 2010 ................................ ................................ ..................... 64 2 7 Descriptive statistics for continuous variables of adult sample in Ecuador, 2010 ................................ ................................ ................................ ................... 65 2 8 Descriptive statistics for continuous variables of household sample in Ecuador, 2010 ................................ ................................ ................................ .... 65 2 9 Logistic regression results for model of homeownership in Ecuador, 2010 ........ 66 2 10 Logistic regression results for models of homeownership in Ecuador, 2010 ...... 67 2 11 Conditional logit regression results for model of homeownership in Ecuador, 2010 ................................ ................................ ................................ ................... 68 2 12 Ordinary least squares regression o f housing wealth (in thousands of USD) of homeowners in Ecuador, 2010 ................................ ................................ ....... 69 2 13 Ordinary least squares regression of housing wealth (in thousands of USD) by sex of homeowners in Ecuador, 2010 ................................ ............................ 70 2 14 Ordinary least squares regression of housing wealth (in thousands of USD) of homeowners in Ecuador, 2010 (with fixed effects) ................................ ......... 71 3 1 .... 120 3 2 How each spouse reports making their respective decision, Ecuador 2010 ..... 121 3 3 making as reported by her and her husband, Ecuador 2010. ................................ ................................ ................................ .. 122 3 4 Symmetry in decision making Whether both members of the couple make the decision regarding themselves in a similar fashion, Ecuador 2010 ............ 123

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8 3 5 The distribution of joint decision making, Ecuador 2010 ................................ .. 123 3 6 Degree of agreement by spouses on how partner makes the decision, Ecuador 2010 ................................ ................................ ................................ ... 124 3 7 Symmetry and agreement: egalitarian decision making, Ecuador 2010 ........... 125 3 8 Descriptive statistics of the binary dependent variables, Ecuado r 2010 ........... 125 3 9 Descriptive statistics for categorical variables, composition (percent) of sample of couples, Ecuador 2010 (n = 1 ,776) ................................ ................. 126 3 10 Descriptive statistics for continuous variables of sample of couples, Ecuador 2010 ................................ ................................ ................................ ................. 127 3 11 Logistic regression results for models of autonomous decision making for the decision to work; Ecuador, 2010 ................................ ................................ ....... 128 3 12 Logistic regression results for models of autonomous decision making for the decision to spend; Ecuador, 2010 ................................ ................................ .... 130 3 13 Logistic regression results for models of women's autonomous decision making for the decision to work as perceived by husbands; Ecuador, 2010 .... 132 3 14 Logistic regression results for models of autonomous decision making for the decision to spend as reported by men; Ecuador, 2010 ................................ ..... 134 3 15 Logistic regression results for models of women reporting autonomous decision making for the decision to work and men agr ee; Ecuador, 2010 ........ 136 3 16 Logistic regression results for models of women reporting autonomous decision making for the decision t o spend and men agree; Ecuador, 2010 ..... 138 3 17 Logistic regression results for models of egalitarian decision making for the decis ion to work; Ecuador, 2010 ................................ ................................ ....... 140 3 18 Logistic regression results for models egalitarian decision making for the decision to spend and; Ecuador, 2010 ................................ ............................. 142 4 1 The participation of partnered female landowners in agricultural decisions by type of ownership as rep orted by partnered landowning women ...................... 174 4 2 Composition (percent) of sample of partnered women and men in each level of the index of women's participation in agricultural decision making, Ecuador 2010 ................................ ................................ ................................ ................. 175 4 3 Descriptive statistics for continuous variables of paired sample, Ecuador 2010 ................................ ................................ ................................ ................. 175

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9 4 4 Descriptive statistics for continuous variables of sample of parcels reported on by partnered women who report on agricultural decision making, Ecuador 2010 ................................ ................................ ................................ ................. 176 4 5 Descriptive statistics for continuous variables of sample of parcels reported on by partnered men who report agricultural decision making, Ecuador 2010 176 4 6 Descriptive statis tics for categorical variables, composition (percent) of samples, Ecuador 2010 ................................ ................................ .................... 177 4 7 OLS regression results for models of the index of women's participation in agricultural decision making ( paired sample -women); Ecuador, 2010 ............ 178 4 8 OLS regression results for models of the index of women's participation in agricultural decision making ( paired sample -men); Ecuador, 2010 ................. 180 4 9 Logistic regression results for models of women's participation in the decision about what to cultivate (sample of all partnered women); Ecuador, 2010 ........ 182 4 10 Multinomial logistic regression results for models of women's participation in the decision about what to cultivate (sample of all partnered women); Ecuador, 2010 ................................ ................................ ................................ .. 1 84 4 11 Logistic regression results for models women's participation in the decision about what to cultivate (sample of all partnered men); Ecuador, 2010 ............. 186

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10 LIST OF FIGURES Figure page 1 1 Empowerment framework (adapted from Kabeer 1999). ................................ .... 32 2 1 Wealth portfolios by wealth qui ntile and overall, Ecuador 2010 .......................... 60 2 2 Form of homeownership, Ecuador 2011 ................................ ............................. 63

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11 LIST OF ABBREVIATION S DHS Demographic and Health Survey EAFF Encuesta de Activos Florida FLACSO ( UF FLACSO 2010 Ecuador Household Asset Survey) ENDEMAIN Encuesta Demogrfica y de Salud Materna y Infantil (Demographic and Maternal and Infant Health Survey) FLACSO Facultad Latinoamericano de Ciencia s Sociales (Latin American Faculty of Social Sciences) IESS Instituto Ecuatoriano de Seguridad Social (Ecuadorian Institute of Social Security) LSMS Living Standards Measurement Study MIDUVI Ministerio de Desarrollo Urbana y Vivienda del Ecuador UF University of Florida

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy INTRA HOUSEHOLD DISTRIBUTION OF ASSETS AND W EALTH IN ECUADOR By Jennifer Twyman August 2012 Chair: Carmen Diana Deere Major: Food and Resource Economics This dissertation is comprised of three essays that explore the intra household distribution of assets and wealth in Ecuador. The first essay focuses on gender differences in the likelihood of homeownership as well as the differences in housing wealth. The second essay examines the relationship between the intra household distribution of assets and wealth and egalitarian decision making in regards to the investigates how farm management decisions are related to asset ownership and wealth. Using the bargaining power framework, we propose that the intra household distribution of assets and wealth impacts how decisions are made within the household since it gives an indication of bargaining positions. If most of the wealth is owned by the husband (wife) then we would expect him (her) to make most of the decisions but a more equal distribution would result in more egalitarian decision making practices. We use data from the UF FLACSO 2010 Ecuador Household Asset Survey, a nationally representative survey that collected sex disaggregated data regarding asset ownership a nd wealth from 2,892 households

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13 We find that although there are no gender differences in the likelihood of homeownership or in the amount of housing wealth, there are several gender differences in the factors predicting homeownership and housing wealth. In terms of household decision making in households in which only women own real estate (compa red to those in which neither husband nor wife own real estate) women are more likely to make autonomous decisions. In households with a fairly equal distribution of wealth and when both spouses own real estate couples are more likely to make egalitarian d ecision s Finally, with respect to farm management, the great majority of women land owners are involved in making agricultural decisions ; their participation in fieldwork is strongly correlated to their participation in such decision making Although the intra household distribution of wealth is not related to agricultural decision making among landowning women own ership of agricultural equipment is associated Overall, t hese results indicate th at the intra household distribution of asset ownership and wealth are related to how couples make decisions

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14 CHAPTER 1 INTRODUCTION This dissertation is one piece of a large, international project called In Her Name: Measuring the Gender Asset Gap in Ecuador, Ghana and India. The project was specifically designed to collect data on asset ownership and wealth by individuals within household s. The data collected from t he Ecuador project, called Assets, Poverty and Gender Inequalities is the basis for this dissertation, 1 which examines the intra household distribution of physical and financial assets and wealth and how it is related to househ old decision making Although i t is often assumed that individual asset ownership and wealth influence how decisions are made within households, few studies have directly examined the link. This dissertation begins to fill this gap in the literature by exp loring these issues in three essays. The first one focuses on gender differences in the likelihood of homeownership and in housing wealth. The second essay examines the relationship between household decision making and the intra household distribution of assets and wealth. Finally, the third essay investigates the link between farm management decisions and the intra household distribution of assets and wealth. But first, t his chapter defines assets and wealth and explains why we would expect the intra hous ehold distribution to impact decision making This dissertation focuses on physical and financial assets and the wealth associated with them. Physical and financial assets include housing, land, other real estate, businesses, livestock, agricultural equipment and installations, consumer durables, and savings (both formal and inf ormal). Wealth is then measured as the 1 Carmen Diana Deere from University of Florida (UF) was the principal investigator (PI) and Jacqueline Contreras from Facultad Latinoamericano de Ciencias Sociales in Ecuador (FLACSO Ecuador) was the co coord inator on this project; it also involved other researchers (myself included) from UF and FLACSO Ecuador

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15 sales/market value of these assets as reported by respondents (or in the case of saving, the amount saved). 2 Carmen Diana Deere and Cheryl Doss (2006) explain the importance of studying wealth; they argue that wealth and assets have value not only in terms of their use but also to the extent that they can be converted to cash, in which case they can be used to meet consumption needs. Also, a ssets may generate income including profits and rent s they often increase in v alue over time, and they can be used as collateral for obtaining a loan. Furthermore, asset ownership and wealth provide social status to current and future generations. Theoretical Considerations To address the questions of why and how assets and wealth i mpact how decisions are made within households, a description of the bargaining power framework is warranted. The bargaining power model of household decision making is one of many economic household models (see Agnes Quisumbing 2010) These models are use d by economists to predict how households make economic decisions, like how much of their budget to allocate towards different types of consumption goods. Traditionally economists have used the unitary household model to estimate household expenditures and other types of economic decisions (Quisumbing 2010) Frank Ellis ( 1988 ) presented a household model of peasant economics which included both production and consumption activities within households; however, this model too was unitary (see Elizabeth Katz 1991). Unitary models assume that all household members share common preferences or that one person makes all the decisions (either 2 owned by more than one person, the value was divided equally among all the owners to get the over the value of the asset, the value reported by the owner was taken as the value. If both principal adults wer e determined to be owners, then the average reported value was used.

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16 in his/her self interest or in the best interest of all the household members) to maximize the household utility. Collecti ve models, including cooperative and non cooperative are now more widely used. The bargaining power model, a type of cooperative household model, is often used in feminist economic studies of household decision making (see Greta Friedemann Snchez 2008 A gnes Quisumbing and John Maluccio 2003, Bina Agarwal 1994, Deere and Doss 2006 ) Although several feminist economists have criticized the bargaining model (see Katz 1991, 1997, and Bina Agarwal 1997) it is still widely used w ithin feminist economics beca use it allows for different preferences and it recognizes that spouses 3 have different bargaining power which influence s decision making within households. One of the biggest criticisms of the bargaining model is that it is gender neutral; in other words, it assumes that resources in the hands of a man or woman give equal bargaining power. However, as Katz (1991) pointed out, there are gender bias es not captured by these models. For example, what can be bargained a bout is often gendered ; b ecause of gender norms, women may not be able to participate in certain decisions. Notwithstanding these limitations, t he bargaining power framework is used to inform and address the research questions presented in each of the fol lowing chapters Nash bargaining models of the household start with the fact that household members have different preferences and thus utility functions. Generally, two person households are analyzed. These two people, typically the husband and wife, are in charge of most of the decisions. The spouses have two main alternatives, they can cooperate within the household or they can choose not to cooperate and exit the household. A main 3 Throughout the dissertation the terms spouse and partner are used interchangeably to refer to either the husband or wife or partners in a consensual union.

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17 assumption is that a person will stay in the household unless leaving th e household gives her/him more utility. (Another assumption is that leaving the household is a feasible option, this is discussed in more detail below.) The utility achieved outside the household is considered the fallback utility or fallback position. 4 S upposing that they decide to remain in the household, then the question becomes how they make decisions. It is important to remember that the non cooperative outcome (i.e. exiting the household) determines the cooperative outcome (i.e. bargaining and decis ion making ). After obtaining the non cooperative outcome, household models then predict the cooperative outcomes based on these. In essence, it is assumed that there is complete information such that each member of the couple knows the fallback position of the other and makes their decisions based on this information. Then the couple makes decisions to maximize their joint utility functions. Typically this is expressed as follows. In this expression we see that there are weights functions (U 1 and U 2 ). The weights are interpreted as the balance of power in the household or in other words the bargaining power that each partner has These weights are generally assumed to be between 0 and 1 and to sum to 1. Expressing the weights in this manner impl ies that increasing the power of one partner will necessarily decrease the power of the other. 4 The explanation of the bar gaining power framework draws on work from several authors including Marilyn Manser and Murray Brown 1980, Marjorie McElroy and Mary Jean Horney 1981, Siwan Anderson and Mukesh Eswaran 2009, Quisumbing 2010, among others.

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18 achieved in th e non cooperative outcome. It is a function of the fallback position s; expressed mathematically where and are the utilities achieved in the non cooperative scenario T hey can be thought of as the fallback positions of the wife and term and fallback position ( ) implies an increase in her bargaining power while an increase in her h ) will decrease her bargaining power. Thus, her ( ) and that of her husband ( ) Therefore, the relative fallback positions are important. This can also be s his bargaining power (1 From this expression we can also see that all else equal owned assets, which we assume increase utility, will have a positive impact alone owns them and a negative impact when her husband alone owns them (the impact of jointly owned assets is unclear and would depend on their starting points) Bargaining Power and Marital Regimes As mention ed above, an important assumption of these models is that exiting the household is a feasible alternative. However, this is not always the case. T wo possible exit strategies are discussed in the literature : 1) exiting the household by separation or divorce; or 2) remaining in the household but reverting to separate spheres ( Shelly Lundberg and Robert Pollack, 199 3, Katz 1997, Michael Carter and Elizabeth Katz 1997, and Siwan Anderson and Mukesh Eswaran 2009, among others )

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19 In the separate spheres sce nario, separation/divorce is not feasible ( either legally prohibited or prohibited by cultural norms) and therefore, each member of the couple retreats into her/his traditional gender roles ( e.g. a woman taking up traditional domestic labor but not helping her husband in his domain and vice versa ). It is important to know about the relevant exit options available to the couple since these strategies can greatly impact the outcomes of the bargaining model. As explained in Anderson and Eswaran (2009), if di income (measured as the value of inherited or gifted assets) will unequivocally improve her fallback position since she does not have to forego any leisure time whereas earning hi gher income implies a decline in leisure time However, if retreating into separate spheres is the effective exit strategy, then earned income (income earned in unearned incom e ; this is the case that Anderson and Eswaran (2009) found in Bangladesh If physically exiting the household is feasible, the marital regime that regulates property rights between spouses becomes especially relevant. In Ecuador, the marital regime is th at of partial community property. As such, any property acquired while married is considered joint property while property obtained while single and all divorces, any indi vidual property will go to the individual while joint property will be split equally between the partners. Thus, the relevant fallback positions of each spouse is based (at least in part) in the amount of property and/or wealth that would accrue to that

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20 pe rson in case of divorce. This also assumes that divorce is feasible and that the marital regime regulating property rights is enforced upon divorce. en denied Naila Kabeer 1999: 435). Kabeer (1999) discusses the importance and interconnectedness of resources, agency, and achievements to the process of empowerment (see F igure 1 1) Thi s framework is similar to the bargaining power framework in terms of these three concepts. In the bargaining power framework, access to resources changes outcomes/achievements through the process of bargaining to make household decisions. One of the big d ifferences in the empowerment and the bargaining power literature s is in terms of the treatment of power. In her investigation of empowerment, Jo Rowlands (1997), describes three types of power: power over, power to, power with, and power from within (see also Janet Gabriel Townsend Pilar Alberti, Marta Mercado, Jo Rowlands, and Emma Zapata 1999) In the bargaining power framework, an bargaining power; this is an example of power over Power to Power with is each one of us and makes us truly human. Its basis is self acceptance and self respect

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21 which extend, in turn, to respect Williams et al. 1994: 233 quoted in Townsend et al. 1999: 30). Although power over is a zero sum game the other types of power are positive necessarily imply a of power over and a s such it dismisses the possibility of any positive and additive type of power such as power for power with or power within Many ec onomic studies using the household bargaining power framework focus intermediate link: how access to resources impacts decision making ( see review in Carmen Diana Deere and Magdalena Le n 2001: 15, Elizabeth Katz and Juan Sebastian Chamorro 2003, Quisumbing and Maluccio 2003, Quisumbing 2010, among others ) Furthermore, many of these past studies have used income (labor and non labor market income) as the predominant measure fallback position is determined by such income without also considering her assets and wealth. These studies have found tha income has a positive impact on other deve lopment goals such as nutrition, educatio n, and the budget share spent on various types of consumption goods fallback position also includes the assets and wealth that are owned and that one would keep in case the household dissolved due to separation, d ivorce, or the death of a spouse. Bargaining Power and the Importance of Perceptions Previous authors have expounded on the importance of perceptions in a bargaining framework; often critiquing the Nash bargaining model because it does not

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22 address such pe rceptions (see Amartya Sen 1990 and Katz 1991, 1997). Perceptions are important not only in terms of both the perceived contributions of household members (Sen 1990) and thus their bargaining power but also in terms of what they deem worthy of bargaining important for how well the threat point can be utilized in the bargaining process. In ptions of her assets (or other contributions) are only valid for bargaining power if her husband has similar perceptions. If they have different perceptions about her resources/assets/contributions then the bargaining process and thus outcomes will reflect these differences and perhaps how their perceptions have changed as a result of the bargaining process. Thus, it is important to take into account the different perceptions of men and women in the bargaining power model of household decision making Inter viewing only one of the partners will likely give different results/estimates than if responses were collected from the other partner. As explained in more detail below we have collected information from both partners and can thus test whether there is a systematic difference in their responses and thus in the results of the various models presented in the next chapters. Gaps in the Literature Four main gaps in the literature were identified. First, resources are linked to welfare outcomes ( household bud get shares, health, nutrition, and/or education) without considering the decision making processes within households that lead to such outcomes. Second, the resources considered are typically limited to income and less so to land rights (access or ownershi p), but all physical and financial assets are likely to

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23 ing a home or piece of land or other asset could provide a livelihood in case the household dissolved and as such impacts the relative bargaining positions of the spouses. Third, wife. As discussed above, their relative positions that determine b argaining positions within the relationship. And fourth, the few studies that do focus on the direct link between resources and decision making decision making or occasionally her participation in decisions without real ly considering other forms of decision making what they indicate in terms of bargaining power). The main contribution of this dissertation is that the intra household distributi on of assets and wealth is used as an indicator of resources and is link ed this directly to various forms of decision making within households. This is done in three essays. The first essay (C hapter 2) focuses on housing, which is arguably the most importa nt asset to own in Ecuador. Results of this essay indicate that there is little to no gender differences in the likelihood of homeownership or in housing wealth but that there are gender differences in the factors explaining homeownership and housing wealt h. Then the second and third essays (C hapters 3 and 4) focus on the relationship between decision making and the intra household distribution of assets and wealth. Chapter 3 examines how couples make the decisions about working and spending income. Chapter 4 focuses on how rural smallholders make agricultural decisions.

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24 Hypotheses and Findings My principal hypothesis is that decision making within households is associated s access to resources, particularly their ownership of physical assets and the intra household distribution of wealth wealth) ownership of major assets such as the primary residence, land, and other real estate is associated with a stronger fallback position and hence greater bargaining power within households than women who do not own major assets. And, w bargaining power sh ould be reflected in the way couples make decisions; we expect that women who own real estate will be more likely to participate in household decision making than those who do not. inant of couple wealth is between 0 and 1, and is calculated as follows. bargaining power within the household and this will be related to her greater participation in household decision making More specific hypotheses are listed in each chapter. In general, the results indicate that the intra household distribution of assets and wealth is indeed related to household deci sion making. Both spouses owning real estate is correlated to egalitarian decision making while only the wife owning real estate

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25 decision making Furthermore, a more equal division of wealth is related to egalitarian dec ision making but negatively related to decision making follow the same pattern when it comes to agricultural decision making which may articipate and ultimately choosing something besides agriculture. However, t he ownership of agricultural equipment is a strong predictor of how agricultural decisions are made; women are more likely to make a joint decision about what to cultivate when bot h partners own agricultural equipment and more likely to make an autonomous decision when only they own agricultural equipment. Thus in general we find, as expected, that a fairly equal distribution of assets and wealth within households is related to egal itarian decision making autonomous decision making Setting Ecuador provides an interesting case study to explore these hypotheses. A t 41% Ecuador has one of the highest rates of joint homeownership by couples in Latin America and therefore one of the highest rates of homeownership by women in Latin America at 44% ( Carmen Diana Deere, Gina Alvarado, and Jennifer Twyman 2012). Moreover, according to the results of the 2010 Ecuador Household Assets Survey, also analyzed herein, women own 52 .2 % of the gross household physical and financial wealth, a share approximately equal to their share of the population ( Carmen Diana Deere and Jacqueline Contreras 2011). The high rate of joint as set ownership and thus the near gender equality of wealth in Ecuador is likely related to the marital regime regulating property rights by couples.

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26 As noted earlier, given legally any property purchased during marriage is considered joint property of the couple, while property acquired while single as well as inherited property remain individual property during marriage Furthermore, the marital regime applies to both marriages and consensual unions. Th e inheritance regime in Ecuador, like other South American countries, applies to both men and women equally; all children inherit equally from their parents. H inheriting from their dece ased spouses. In most South American countries a widow(er) retains her/his half of the community property and inh erits from the deceased spouse; but, in Ecuador the widow(er) receive s only her/his half of the community property and does not inherit from t children (Deere and Contreras 2011, Deere and Len 2001). The one source of gender inequality under the law is that even though either or both spouses can administer the community property, if noth ing is declared at the time of marriage, the husband becomes the administrator by default in contrast to many other Latin American countries which recognize the dual headed household and as such both partners administer the marital property Furthermore, as described by Carmen Diana Deere, Jacqueline Contreras, and Jennifer Twyman (2010), the marital regime seems to be widely known and enforced sign the paperwork when selli ng real estate, vehicles, and stocks. Even so, at times gender equality in practice can be elusive. Historically property rights have favored men; in Ecuador potestad marital gave

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27 husbands many rights over their wives. For example, until 1970 married women did not have legal capacity and had to be represented by their husbands in court; women could not administer their own property until 1949 (Deere and Len 2001: T able 2.1 ). Although the laws have chang ed over time, the idea that men are household heads and the owners and managers of property persists. Also, even though marriages and consensual unions are treated equally under the law, they are socially construed as s is still considered single while in a consensual union and to acquire the same rights as a marriage the consensual union must meet certain requirements (a two year monogamous relationship). For these reasons, it is more difficult to enforce the communit y property rights of consensual union s (Deere, Contreras, and Twyman 2010). Survey Design and Data Collection Fieldwork was conducted in Ecuador from June 2009 to August 2010 in two stages. First, qualitative fieldwork consisting of focus group discussio ns and key informant interviews was carried out in three provinces (Pichincha, Manab, and Azuay) which were chosen to represent the two main regions in Ecuador the coast and the highlands and to highlight various processes through which wealth may be acc umulated. Pinchincha, a highlands province was chosen because of the prevalence of the flower industry in rural areas. Manab on the coast was chosen for its fishing and tourism industry, and Azuay in the highlands was chosen because of the high rates of

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28 i nternational migration in the area (see the case study reports: Jacqueline Contreras 2010, Deere 2010a, 2010b, and Jennifer Twyman 2010) 5 A total of 40 focus groups were conducted; most of the groups were organized e were comprised only of women However, we also conducted some mixed sex groups and in each province there was at least one all male group; these were typically organized in collaboration with micro credit organizations or peasant organizations. In each province we also held one focus group with professional and businesswomen. The focus groups focused on four themes: the accumulation of assets over the life cycle; the importance of assets; the market for assets; and household decision making over asset acquisition and use. Besides the focus groups, we also carried out a total of 58 interviews with key informants, including lawyers, judges, notary publics, real estate agents, leaders of grassroots movements, NGO representatives, and academics. Second, a nationally representative house hold survey was conducted with the collaboration of the survey company HABITUS. 6 A stratified random sample was used. T he primary sampling units were the (updated) 2001 national census blocks which were characterized by socio economic level based on an in dex of the proportion of household basic needs satisfied according to the 2001 census data. The household was the secondary sampling unit and these were drawn with equal probability within 5 More information can be found at the Ecuador project website: http://www.flacsoandes.org/web/cms2.php?c=1409 and for the international project website: http://genderassetgap.iimb.ernet.in/ 6 Although HABITUS was hired to conduct the survey, the research team was actively involved throughout the process. We participated in training enumerators, supervising a pilot survey of about 100 households, making modifications, and supervising the administration of the survey and data verification processes. We had less influence in the data entry process.

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29 each selected census block. Twelve households were interviewed pe r census block and replaced if there was a rejection or no one in the household could be located after three attempts. 7 The sample is representative of rural and urban areas and the two major regional geographic and population groupings of the country, th e Sierra (highlands) and Coast. 8 The survey instrument included two questionnaires. First, a household questionnaire was designed to be answered by the couple together or if both were not available, then one of the two could answer these questions. Then, an individual questionnaire was administered separately to the two principal adults. It included questions about decision making, savings, loans, and other information that we thought to be of a private nature and that we would get more truthful responses if the individual answered these questions alone. Furthermore, if the individual was not present during the first part of the questionnaire, then they were asked some of the questions that the spouse/partner had already answered in the household question naire regarding asset ownership and values. In this way we hoped to get the best information possible; the logic was that if the couple was together they could discuss and come to an agreement about the best response, especially in terms of the value of a ssets. 9 If the couple was 7 The original sample size contemplated was 3,000 households. As is typical in large scale living standar d surveys (James Davies, Susana Sandstrom, Anthony Shorricks, and Edward Wolff 2008) we faced an extremely high rejection rate among the highest socio economic group and the sample is thus truncated, not being representative of the wealthiest households. The final sample of 2,892 households has a survey margin error of 1.8% nationally, 2.2% for urban areas and 3.2% for rural areas. See Deere and Contreras (2011) for further details. 8 The Amazon region and the Galapagos Islands, which hold less than 5% of households nationally, were excluded from the sample due to budget constraints. 9 There is a considerable debate in the family studies literature in the United States about whether it is preferable to interview a couple together or separately (Gill Vale ntine 1999). In Ecuador men and women tended to have different knowledge regarding the markets for assets. Moreover, men and women often have access to different kinds of information regarding assets. For example, urban women often had a

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30 not available to answer the questionnaire together, then we wanted to be able to compare their responses. The results of this survey are used for the data analyse s in this dissertation and the qualitative fieldwork helps enhanc e the interpretation of the findings. The survey, known as the UF FLACSO 2010 Ecuador Household Asset Survey (EAFF, Encuesta de Activos Florida FLACSO), includes 2,892 households (Deere and Contreras 2011). A little over two thirds o f the se households ( 68 .5 % ) are dual headed and 31.5 % have a non partnered h ead (24.8 % female headed and 6.7 % male head ed ) (Deere and Contreras 2011: 19). The couple was interviewed together in about half of the dual headed households. In 189 dual headed households (6.9% of the total) the second member of the couple was not interviewed due to one of several reasons: they were temporarily away, an appointment could not be arranged after three attempts, or they refused to be interviewed. Outline and Objectives Housing is a key asset in the wealth portfolio and as such is likely an especially the home. Therefore, the focus of C hapter 2 is on gender differences in homeownership. This chapter first examines the differences in the likelihood of homeownership for men and women and then examines whether there are gender differences in housing wealt h. Then, C hapters 3 and 4 in turn focus on whether asset ownership and the relative wealth positions of husbands and wives is important in terms of decision making as is suggested by the bargaining power framework. Chapter 3 focuses on whether couples better idea of sa les prices of dwellings recently sold in their neighborhood than did men; whereas in rural areas, men tended to have a better idea of land prices than did women.

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31 mak e egalitarian decisions about whether to work outside the home and how to s pend agricultural decisions within landowning households. It is expected that the analyses presented in t he following three chapters will provide insight into the intra household distribution of wealth and how it impacts household decision making As such it is hoped that we will gain a better understanding of the economic agents and activities within the bla ck box known as the household.

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32 Figure 1 1 Empowerment framework (adapted from Kabeer 1999). Access to Resources Agency (Decision Making) Achievements/ Outcomes

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33 CHAPTER 2 IS THERE A GENDER GA P IN HOUSING? MARITA L PROPERTY RIGHTS IN ECUADOR Housing is an important asset; across the globe it is the most commonly owned asset of value and as such is an important component of the household wea lth portfolio ( Robert Dietz and Donald Haurin 2003 Asena Caner and Edward Wolff 2004 Florencia Torche and Seymour Spilerman 2008 Eva Sierminska, J oachim Fri ck, and Markus Grabka 2010 ). In Ecuador, 60% of households own their home and on average housing accounts f or th portfolios (see F igure 2 1). By sex, we find are in housing (Deere and Contreras 2011). Moreover, homeownership often distinguishes the poor (or extremely poor) from the non poor ; this is illustrated in F igure 2 1 where we see that the lowest wealth quintiles have the least invested in housing at only 4% and the richest two quintiles have the highest value invested in housing at 67% Thus housing is an important asset to consider when exploring gender inequalities Ecuador provides an interesting case study to explore gender differences in homeownership. Like oth of partial community property. Interestingly, even though all the South American countries have the same marital regime, there are varying patterns of homeownership among the countries as shown in T able 2 1 (Deere, Alvarado, and Twyman 2012). 1 1 The cited study used data from the 2005/2006 Ecuador Condiciones de Vida (Life Conditions) Survey, which only included titled homes and also used pre coded responses such as household head, spouse, and others. As such this did not allow for all potential owners to be identified. The measures presented in this dissertation use the reported owner regardless of whether they held a title and the owners question was open ended so that the respondent could report any and all owners (with space in the questionnaire for up to three owners plus options for all household members or all children).

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34 Ecuador has one of the highest rates of joint home ownership in Latin America as well as a fairly equal gender distribution of homeowners. In this chapter, we use individual level data to examine the exten t of gender equality of homeownership in Ecuador. Specifically, the following questions are addressed: 1) what is the likelihood of homeownership for men and women; and 2) are there gender differences in the housing wealth owned by men and women? The next sec t ion reviews the literature regarding homeownership. The n, we explain the data and methods. For the analysis we first compare the factors that predict the likelihood of homeownership for men and women. And s econd, since focusing only on the likelihood of homeownership does not account for potential quality differences, we also examine the gender differences in housing wealth which should give an indication of differences in housing wealth assuming that housing with higher quality will be valued higher than lesser quality housing Literature Review Although homeownership can limit mobility and thus limit wage employment opportunities, there are several benefits to homeownership. Alan Gilbert (1999) identifies the benefits of homeownership to the poor in an informal (or self help) settlement in Bogot Colombia. T he residents see homeownership as a good investment in terms of safety/security, having something to leave to their children, a safeguard in old age, and not having to pay rent. He also di scusses how an owned home can be a source of income; either by renting out rooms or as a place for income generating activities (home based businesses). Similarly, Marianne Fay and Caterina Ruggeri Laderchi (2005) discuss the benefits of homeownership in L atin America.

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35 Besides the benefits listed above, they also mention that housing can be used as collateral for obtaining a loan. Owning a home is especially important for women. It provides economic indep endence and security as well as contributing to phys ical and emotional well being. In couple headed households, 2 homeownership may improve position and thus her bargaining power within the home. This is because if th e household dissolves, a woman who is the sole homeowner will st ill ha ve a place to reside and raise her children. There is a debate in the literature about whether individual or joint ownership is best for women in terms of empowerment and/or bargaining power within the home ; much of this debate is centered around land and the issue of titling Agarwal (1994) argues for independent land rights for women in South Asia On the other hand, Deere and L e n (2001) stress the importance of either individual or joint titles in Latin America; they argue that given the legal mari tal regimes in Latin America that upon divorce half of the marital property belongs to the woman and as such even joint titles will be empowering. In one of the few studies regarding housing, Namita Datta (2006) found that joint titles had positive effects in an informal settlement in India; their participation in decision making increased and they had an increased sense of security and self esteem among other benefits Despite the importance of housing few studies have conducted ge nder analyses of homeownership and thus little is known about the gender inequalities of homeownership M ost of the literature focuses on racial differences in homeownership 2 During refers to an adult male except in households where there is not one. Instead the survey focuses on interviewing the two principal adults. Households in which an

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36 in the U.S. (see Donald Haurin, Christopher Herbert, and Stuart Rosenthal 2007 fo r a review) with few studies focus ed on gender differences ( Stanley Sedo and Sherrie Koussoudji 2 004 is an exception). And, there is even less on gender and homeownership in Latin America. This is at least partially due to a lack of data. D eere, Alvarado, and Twyman (2012 ) examined 167 household surveys for 23 Latin American countries and found that only 9 countries had data regarding home ownership at the individual level, which is needed for a gender analysis The few studies that look at gend er inequality in housing typically focus on the barriers to homeow nership by women. Housing is a relatively expensive asset, which may prohibit women, especially poor, single mothers from obtaining ownership. Also gender wage gaps may prevent some women from generating the savings needed to purchas e a home. During fieldwork in Ecuador, we found that homes in the popular sector are usually built rather than purchased and that they are typically built brick by brick as small amounts of money can be put tog ether to buy materials. Construction is often carried out by household members, family, and friends. Poor, single women may lack the time, skills, and social capital that are necessary for home construction as Faranak Miraftab ( 2001 ) found in Mexico; they may also be less likely to own a lot on which to construct a home. Other barriers to female homeownership include discriminatory housing policies and mortgage lending practices. Deere and Len (2001) explain how titling policies may impact female property ownership in Latin America. They explain that titles are often issued to men as heads of households even when women participate in land invasions and contribute their earnings and savings towards home construction. Although the

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37 marital regime in Ecuador and other South American countries is such that any property acquired while married is legally joint property women may have difficulty proving their property rights if the household dissolves due to separation, divo rce, or death Deere and Len (2001) argue that joint titling would reinforce the legal marital regime and help overcome this type of discrimination towards women. Mortgage lending discrimination is another barrier to homeownership by women. Although no studies were found regarding this in Latin America (perhaps because mortgages are still un common), in the U S Judith Robinson (2002) study indicated that discrimination in mortgage lending varies by household composition, gender, and race. She found that single mothers of all racial groups fared worse in the mortgage market than single fathers. Her analysis suggests that mortgage lending to dual headed households depends on race and the employment status of women; white households are at a disadvantage when the woman works while African American households do better in the mortgage market when the woman works. Furthermore, even studies that include gender typically use the sex of the head of the household instead of the sex of the owner(s ). One argument for using the household as the unit of analysis, is that housing is a resource used by all household members and therefore cannot easily be disaggregated ( Faranak Miraftab 1998). This argument seems most relevant when analyzing access to housing, but less so for issues of ownership. Another reason households are used as the unit of analysis is simply because there is a lack of individual level data on owners (Nstor Gandelman 2008).

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38 There are several limitations of using household level data to analyze the gender gap in homeownership. First, households do not own things, people within them do. This is important because household composition change s over time. Household members come and go; children grow up and form households of their own and households may dissolve due to death, separation, or divorce. In such instances there are implications for asset owners and non owners. Another limitation to using the household as the unit of analysis in gender analyses is that households do n ot have a sex. In order to overcome this, these analyses typically use the sex of the household head. However, this results in an analysis more of household type/structure than of gender. Furthermore, Gandelman (2008) argues that such analyses face an e ndogeneity problem; not only does the sex of the head influence homeownership but also homeownership may influence the sex of the head of household. This is especially true of female headed households which are typically defined by the absence of a male b readwinner; in such cases women may choose to head their own households when they own a home but may not when they do not own a home, choosing instead to live with relatives In such cases, they become household surveys since they do not fit the definition of a separate household, which is defined as those who live under the same roof and share meals Donald Haurin and Stuart Rosenthal (2007) address the problem of how household formation impacts homeo wnership rates and thus propose a model that simultaneously predicts headship (or household formation) and the housing tenure question. In doing this they use individual level data and find that lower headshi p rates corresponds to lower homeownership rates Similarly, Maria

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39 Concetta Chiuri and Tullio Jappelli (2003) stress the importance of using individual level data on homeownership when it exists since explanatory variables (such as age and gender) are measured at the individual level. As explained by H aurin, Herbert, and Rosenthal (2007) homeownership studies typically use one of four conceptual approaches. Two of these focus on the demand side of homeownership, using either the user cost approach or the investment and consumption dema nd approach. The other two focus on the supply side, using either the availability of housing approach or the availability of credit approach. The main idea of the user cost framework is that an individual will be a homeowner when the benefits of ownership outweigh the co sts. Many studies in the US compare owner costs to rental costs ; however, there are other tenure choices in Ecuador that are as relevant as renting; T able 2 2 shows that while 60% of households own their home, 21% rent and 20 % have an other tenure status such as borrowed or received for services 3 The investment and consumption approach is another demand side approach that is used to distinguish between investment and consumption reasons for purchasing a home. In this approach it is assumed that if inves tment demand is large relative to consumption demand, then the household will own their home; whereas if consumption demand is large compared to investment demand, then the household will be less likely to own (Haurin, Herbert, and Rosenthal 2007). As sho wn in T able 2 3 only 2 3 % of homes in Ecuador are purchased; most (65 %) are constructed. Moreover, there is not always a strong market for selling homes. For these reasons, this approach may not be 3 provided by an employer, an arrangement frequent among rural workers and manual employees in

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40 appropriate in the case of Ecuador. Furthermore, investme nt demand is typically modeled using tax costs, transaction costs, maintenance costs, depreciation rates, and appreciation rates, which are not available for the current analysis of Ecuador. The supply side approach implicitly assumes that access to credit is necessary for homeownership; it specifically focuses on access to credit and potential discrimination in the mortgage market I n Ecuador mortgages are uncommon ; a s shown in T able 2 2 60% of homes are owned but less than 4% are currently mortg aged. Fu rthermore as shown in T able 2 4 only 24% of homes were acquired with some kind of formal loan ( from IESS -the Ecuadorian Institute of Social Security -a private institution, direct financing, or an employer loan). This approach also requires data on the housing market, such as the number of houses for sale and their prices which we did not obtain for Ecuador. 4 All of these approaches implicitly assume that the household is a static unit that will either own or rent a home. However the number of house holds in a society changes over time and may be influenced by the supply and price of housing as well as by career changes, marriage, separation, divorce, and death. Thus, household formation and dissolution is also an important consideration for homeowne rship studies (Haurin and Rosenthal 2007) This seems to be a very important consideration in Ecuador where many young people continue to live with parents even after getting married or forming a consensual union (at least until they can acquire a home of their own) Furthermore, as mentioned above, a household level analysis generally assume s that the number of households in society is fixed and that the supply and demand 4 We discussed the availability of the data with various real estate agents and property registrars while d oing fieldwork, but obtaining the data was infeasible due to financial and time constraints.

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41 variables do not influence the number of households, otherwise there would be an endogeneity problem in the model (as di scussed by Haurin and Rosenthal 2007 and Gandelman 2008). However, by using the individual as the unit of analysis, the endogeneity problem is eliminated. This is because the number of individuals in society is not directly influenced by the supply and demand of housing. Unlike household level analyses, an individual level analysis will not hide any potential homeowners. For example, a single mother may either live with relatives or create her own household by livi ng independently; a household level analysis would ignore the woman living with relatives but consider her if she lived independently. On the other hand, the individual level analysis would take her into account in either situation. Data and Methods This study uses data regarding homeowners, housing values, and household and individual characteristics collected in the UF FLACSO 2010 Ecuador Household Asset Survey. The sub sample used in this paper is limited to the 7,432 adults (those of 18 years of age o r older) in the sample of 2,892 households 5 In order t o address the question of gender differences in homeownership first binary dependent variable regression model s are used to examine if there are differences in the variables that predict the likelihoo d that men and women are homeowners. The dependent variable for this set of models is whether the individual is a homeowner or not. 6 The second set 5 There is missing information about the past migration status of one adult, who is therefore not included in the sample for the regression analysis, making the sa mple size 7,431 6 Couples were asked about who owned the principal dwelling together when feasible; otherwise each partner reported on who the homeowners were. In the case of disagreements, we have first checked whether there is a title to the home reported and if so, whos e name is listed on the title (as reported by the first respondent). If there was no title, then we took all listed owners as reported by either respondent.

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42 ordinary least squares reg ression. wealth, which is calculated by dividing the total housing value, as reported in response the total number o f owners. 7 The following paragraphs describe the explanatory variables included in the model s A list of the variables and their definitions are given in T able 2 5 In the U.S. many studies have assumed that the costs, benefits, and affordability of homes vary by race; that is they assume that the weight of the explanatory variables and the overall outcome may differ by race due to discrimination. Sex is another v ariable that can be used for discrimination analysis, but is not often emphasized in these studies (exceptions do exist; see for example Sedo and Kossoudji 2004). For the independent variables, we draw on the few gender studies as well as the race studies. Typical variables used to predict homeownership include: income, race, gender, age, housing characteristics, marital status, family size, and location (see Haurin, Herbert, and Rosenthal 2007). It is expected that the relative costs and benefits of home ownership will change over the course of the life cycle. For this reason, age, household size and composition (in terms of the number of children and adults in the household) and marital status may impact homeownership. In Ecuador marital status likely impact s how the home is owned, that is whether it is owned as individual or joint property since property purchased during marriage is considered joint property ; this will also impact who is or is not a homeowner The qualitative fieldwork indicated that h omes were typically acquired 7 If there was a disagreement between the owners about the housing value, then the values were adj

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43 during marriage or consensual unions and that few homes (unlike land) were inherited. Given the partial community marital regime, we would thus expect that most couples own their homes jointly and that both would therefore be o wners. Data on income is not available in the dataset; however, there are several variables related to socio economic status. Human capital in terms of education which is generally associated with income levels, is likely an important factor affecting hom eownership. T here is also data about ; for the analyses in this chapter, we use non housing wealth. It is expected that non housing wealth will be associated with both the likelihood of homeownership and housing wealth. Furthermore information about whether someone in the household receives a governmen t subsidy or transfer payment ( bono in Spanish) is available This should be a good i ndicator of low described by Veronica Argudo ( 2012 ) leakage means that many non poor household s receive the bono in Ecuador. Finally, a n indicator of earnings is whether the person is employed in a remunerated activity. Unfortunately, it is not feasible to determine if such employment opportunities are formal or informal or to otherwise group them in meaningful ways to capture differences in the level of potential earnings. 8 Location is another variable that will impact the costs and benefits of homeownership. For example, in Ecuador there is little to no housing rental market in rural areas, 9 which limits tenure options. Therefore, a dummy variable is included to 8 Various employment categories were considered; however, none of them were found to distinguish between different potential earnings. 9 This fact was often mentioned in focus group discussions durin g fieldwork.

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44 indicate rural/urban areas. A lso included is a regional variable for Sierra/Coast to control for other potential regional differences M igration and remittances can aid in the construction of a home ; therefore a variable that identifies past international migrants is included in the model As explained by Krystal Anderson (2012) ther e are a variety of estimates of the number of Ecuadorians living overseas varying from 7% reported by FLACSO UNFPA (2008) to 10 to 15% is likely a better estimate since the FLACSO UNFPA data only considers migrants who left between 1999 and 2007. During focus group discussions and interviews, women mentioned that migration was a strategy for acquiring homes ; we could also see the evidence in terms of newly constructed hom es in several areas where international migration rates were high ( Carmen Diana Deere 2010 a ) Since homeownership is widely distributed in Latin America and thus a good indicator of inequality in Latin America (Torche and Spilerman 2008). However, housing quality and hence the value of homes owned varies widely; therefore, housing wealth, which gives an indication of the quality of homes owned by men and women, will provide more information about inequality than a study of homeownership alone. Few studies have examined the question of the determinants of housing wealth A few exceptions include studies by James Long and Steven Caudill (1992), Samuel Myers and Chanjin Chung (1996), and Chenoa Flippen (2001) all of which examined the racial gaps in housing va lues and/or equity in the US. Each of them used similar va riables to those mentioned above

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45 Even though housing wealth is likely a better indicator of inequality than income levels (Torche and Spilerman 2008) some question whether there are markets for homes, especially those in the many informal settlements of Latin America. Latin America is characterized by high rates of urbanization that has led to numerous informa l settlements. In Latin America, Torche and Spilerman (2008) report three fourths of the population live in urban areas. In Ecuador the rate is not quite that high but it is still predominately urban with about 63% of the population living in urban areas. 10 Our analysis of invasions indicates that less than 1% of homes are acquired through inv asions and another 1% by governmental re location programs. However, when we consider how the housing lot was acquired, the proportion of invasions increases to to 5%. As explained by Torche and Sp ilerman (2008 ) these rates of invasion are likely underestimated for a couple of reasons; first respondents may not want to admit that invasion was the form of acquisition, and second they may consider it as having been inherited if the home or land has been in the family for more than one generation. Gil bert (1999) suggests that many homes in informal settlements are not sold precisely because they are informal (Gilbert 1999) and the owners do not hold titles. During our survey, some respondents were reluctant to give a value ; their initial response was t hat they had no desire to sell their home. We persisted in asking the question in the hypothetical and usually got an answer. If the respondent still insisted that their home could not be sold, we reported that there was no housing market in the area this typically occurred in rural areas Overall, in o nly 1.6% of households was no housing market reported and another 1.3% reported that they did not know the value of 10 Fasccula Nacional: Resultados del Censo 2010 de poplacin y vivienda en el Ecuador. INEC. http://www.inec.gob.ec/cpv/descargables/fasciculo_nacional_final. pdf

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46 their home indicating that at most 2.9% of respondents could not give an estimate of their However, as indicated by Gilbert (1999) and others it may in fact be difficult to sell homes in such areas and as such our estimates may overestimate housing wealth in terms of the market value; on the other hand, as indicated by these same authors, homes are still valuable to the owners and as such the estimated values at least give us an idea of their valuations. Besides the variables already discussed, the housing wealth model also includes t he number of other owners. Since total housing v alue is divided among all homeowners one may expect that the value belonging to each individual will decrease with the number of owners; however, it could also indicate greater housing wealth since people can afford more together than separately. Some p ast studies indicate that couples own higher valued homes than single owners ( Flippen, 2001). Similarly others have found that in the U.S. married individuals have more than twice the wealth (measured as net worth) as single people (Lucie Schmidt and Purvi Se vak 2006 and Alexis Yamokoshi and Lisa Keister 2006); so we might expect their housing wealth to follow a similar pattern. Results Descriptive statistics are presented in T ables 2 6, 2 7, and 2 8. Homeownership seems to be distributed fairly equally by gen der in Ecuador ; as shown in T able 2 6 36% of women and 34% of men are homeowners This is likely due to the partial community property marital regime, which implies that assets purchased during marriage are legally joint property. Considering all homeowners both individual and joint owners 46% are men and 54% are women (see T able 2 6 ), which is similar to the sex ratio of adults in the sample (47% men and 53% women ) At nearly 41%, Ecuador has one of the

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47 highest rat es of joint o wnership in Latin America (see T able 2 1), which seems to suggest that the marital regime is being enforced. Of owned homes, 16% are owned by an individual man, 30% by an individual woman, 41% are jointly owned by a couple and 13% have anothe r type of joint ownership ( see F igure 2 2 and Deere and Contreras 2011). Overall 35% of adult s are homeowners. Marital status is an important variable; qualitative fieldwork indicated that housing is typically acquired after marriage or forming a consensu al union. Furthermore, given the marital regime it is expected that married couples will be more likely than those in a consensual union to own a home jointly (although if the marital regime were enforced, then we would expect no difference). 11 Thirty eigh t percent of the sample are married and 22% are in conse nsual unions; 24% are single, 2 % divorced 8% separated and 6% widowed. Past migration, conditional cash transfer payment, employment, years of schooling, and non household wealth are included as ex planatory variables; since income data was not collected in the survey, these variables give an idea about poverty and potential earnings A bout 3 % of our sample are returned migrants; meaning that they migrated outside of the country for work and returned to Ecuador. Twelve percent receive a conditional cash transfer payment. Although we did not collect income data, we did ask about employment status. Here we measure employment as whether the 11 Consensual unions and marriages have the same marital regime regarding property rights when the couple has been in a monogamous relationship for at least two years.

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48 p erson is employed in a remunerated activ ity ; 12 68% of the sampl e are employed; 81% of men and 56% of women. On average, the adults in the sample have completed nine years of schooling. The mean average non housing wealth is $3,697 but the median is only $410 indicating a skewed distribution The average age was 40, w ith a range from 18 to 99. Mestizos 13 are the largest ethnic group, comprising 89% of the sample. Indigenous people account for 5% of the sample and other ethnicities, including afro Ecuadorians, for 7%. On average there are four people per household, tw o children and three adults. Thirty two percent of the sample lives in rural areas ; and, 53% live in the coastal region, with the other 47% living in the highlands (known as the sierra). As shown in T able 2 8, t he mean reported sales value of owned home s is $25,675 and the median $15,000; there are 2 owners per owned home on average. The mean housing wealth for an owner is $16,601 with a median of $10,000 (T able 2 7) ; which is slightly higher than half of the reported value per home (roughly $12,800 for the mean and $7,500 for the median) Comparing Owners and Non Owners The desc riptive statistics reported in T ables 2 6, 2 7, and 2 8 are presented by sex and by owners and non owners to get an initial idea of differences between the groups. There is no n oted difference among homeownership status for the different ethnic groups. There are some differences by marital status. More married men and women are likely to be owners than non owners; however lower percentages of single people 12 The person is considered employed if they reported that they had worked in the pa st 12 months except if they were an unpaid family worker. 13 This category includes those people who classify themselves as either mestizo or white since they are culturally and socially similar in Ecuador.

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49 and those in a consensu al union are homeowners than non owners. Widowed women may be slightly more likely to be homeowners than non owners but there does not seem to be much difference for men. Furthermore, there does not seem to be a difference for those who are separated or di vorced. Not much difference is noted for past migrants. There is a slightly higher percentage of women receiving the government transfer payment who are owners than non owners (27% compared to 16%) but not much difference for men (6% for owners and 2% for non owners) There does not seem to be much difference between those who are employed and those who are not. A greater percentage of rural residents are owners than non owners; but little difference in terms of ownership for coastal and highland residents As shown in T able 2 7 on average men and women in the sample are about the same age (40) and have similar levels of education (about 9 years). Men have $4,347 of non housing wealth on average while women have $3,128. Comparing owners, the data suggests that owners are older (about 50) than non owners (about 35) on average. Owners tend to have less schooling, 7.6 years on average compared to non owners, who have 9.6 on average. This could be because in general older people have less education than younger people and we saw that owners are older than non owners Finally owners have more non housing wealth at $6,197 on average compared to non owners with $2,336. Multivariate Analysis Although the comparison of owners and non owners discussed above, provides some insight into differences between these groups, it does not provide a complete picture. In order to more fully understand these difference s, multivariate analysis in the

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50 form of regressions is warranted. First, the regression results for the pooled sa mple, which includes both men and women is presented and then to further examine gender differences, the models for the samples of men and women are presented separately. In each case, t he coefficients are reported in the results tables; the odds ratios ca n be T able 2 9 reports the estimated coefficients for a logit model of the likelihood of homeownership for adults in Ecuador (the pooled sample) In this model there is a weakly statistically s ignificant difference between the likelihood that men and women are homeowners. 14 If anything, women are slightly more likely than men to own homes in Ecuador, holding all else equal (women have 1.1 times the odds of men of being a homeowner) There is a non linear relationship between age and homeownership as expected. There is no difference in the probability of homeownership among the ethnic groups considered. Single people, those in consensual unions, the widowed, and the divorced and separa ted are all less likely than those who are married to own a home. Those receiving the conditional cash transfer payment are more likely to own a home than those who do not receive it. Non s likelihood of homeownership. Employ ment and t he number of children do not impact homeownership but as the number of adults increase s the likelihood of homeownership decreases. Furthermore, r ural and coastal residents are more likely than urban or highland residents to own a dwelling 14 The female dummy variable is nearly significant with a p value of 0.103.

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51 Al though this pooled dataset, which includes both men and women shows no statistically significant difference in the likelihood or probability that men and women own homes, there may be different factors associated with homeownership by men and women. In or der to examine whether there are such gender differences, separate models are used to gener ate results for men and women (T able 2 10 ). The results for men are similar to the overall model; age has a positive but non linear relationship, there are no diffe rences between ethnic groups, married men are more likely than others to be homeowners, higher non ownership, and rural and coastal residents are more likely to own than urban and highland residents. In c ontras t with the overall model, receiving a conditional cash transfer payment do es The results for w omen are also quite similar to the overall model; age, marriage, receiving the government conditional cash transfe r, non housing wealth, self employment in a professional career, number of adults and rural and coastal residents are all correlated with greater likelihood of being a homeowner. However, past migration is also associated with a greater likelihood of hom eownership for women. The last column of T able 2 10 shows the Wald chi square test for differences between the models for men and women. This test indicates that being in a consensual union, receiving a conditional cash transfer payment, and living in a rural area have gender differences. While both men and women in consensual unions are less likely than those who are married to be a homeowner, the difference for men is even greater than that for women. While men in a consensual union have only 0.4 time s the odds as married men of being a homeowner, for women it is 0.6 times the odds. Similarly there

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52 is no statistically significant difference between men who do and do not receive the conditional cash transfer payment; however, for women it is a positive predictor of homeownership. And, although rural positively predicts homeownership for both men and women, men in rural areas have greater odds (2.3 times the odds as urban residents) than women (1.7 times the odds). In order to control for potential unobserved household effects influencing the model, a conditional logit was also used. The biggest drawback to using this type of model is that it cannot include individuals living in households where there is no variation in the dependent variable; thus, households in which al l or none of the adults are owners cannot be included when estimating the model. (Also, none of the household level explanatory variables can be included.) The results are shown in T able 2 11 and are similar to those reported above. This model also indicates that there is no statistically significant homeownership. However, in this model being employed is a positive predictor of homeownership In or der to understand gender differences using this model, we included t w o gender variables. The first is a dummy variable that takes the value of 1 if the person is female and 0 if male. The second variable is an interaction term between the female dummy and the number of male adults. This variable gives information about household composition since the household variables of number of children and number of adults (both household level variables) cannot be included as explained above If there are no adult me n in the household then this variable will take the value of 0 and therefore the coefficient estimate drops out. However, if there are adult men in the household then

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53 the coefficient estimate for being female changes since both coefficients must be taken i nto account. The coefficient estimates imply that while women living with no men in the household, would have 1.1 times the odds of a man of owning a home, the odds increase to (exp(0.120+0.084)) 1.2 times for women living with a man. This suggests that ho usehold composition is an important predictor of homeownership; it may support previous research which suggests that women often acquire housing through their relationship with men; however, the limitation of the model implies that single women (living wit h no other adults in the home) are excluded from the analysis and as such limits what we can conclude about women homeowners. Table 2 1 2 presents the results of the OLS model of housing wealth for homeowners. Again, there is no statistical ly significant difference between the housing wealth owned by men and women. Age and ethnicity do not impact housing wealth. There is no difference between the housing wealth of homeowners who are in a consensual union and those who are married ; however, widows and wi dowers have about $10, 580 more housing wealth than married homeowners. This could be because widows and widowers assume that they inherit the home from their deceased spouse even though this is not legally the case (unless there are no children or if the children are underage, in which case the living spouse has usufruct rights until the children come of age). Thus, this could indicate that widow(er)s could have reported that they alone own the home but legally the home belongs to the widow(er) and her/his children. Alternatively, husbands could have will ed the house to their wives before death. Surprisingly divorced and separated homeowners also have greater housing wealth than those who are married by about $6,588 for those who are divorced and $4,604 for

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54 those who are separated This is likely because one of the partners will acquire the full value of the home upon separation or divorce by buying out the other whereas when they are together they each own half of the value. Each extra year of schooling increases housing wealth by about $1300. Returned migrants have approximately $ 7,312 more housing wealth than non migrants. Receiving the conditional cash transfer payment decreases housing wealth by about $5, 45 0, which makes sense given that it is a means tested program, implying that those receiving this payment should be below the poverty line or have a disability. Non housing wealth is statistically significant; a thousand dollar increase in no n housi ng wealth correlates with a $8 0 increase in housing wealth. Suprisingly, homeowners who are currently employed have $2,245 less in housing wealth than those who are not employed. For every additional owner, housing wealth decreases by $3,9 00. Rural homeowners have about $8, 2 00 less housing wealth than urban homeowners. And co astal homeowners have about $8,4 00 less housing wealth than highland homeowners. Table 2 13 gives the OLS results for housing wealth by the sex of the homeowner 15 As shown th e statistically significant variables are similar for both men and women although some differences that stand out. Age marital status, education, and past migration receiving the transfer payment, and non housing wealth have different correlations to hou sing wealth for men and women. A ge is positively 15 Similar to the conditional logit, a fixed effects model was also used to control for household level effects in housing wealth (see T able 2 14 ). This model could not be run using only home owners since there is not enough variation within households to run such a model; so it includes all adults. If they are not homeowners, then they have zero housing wealth. This fixed effects model is then comparable to an OLS model with all adults included but not directly to the OLS model presente d in T able 2 12 which considers only owners. Although the results of the OLS model with all adults are not presented here, the fixed effects model has similar results as that model (results available upon request).

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55 associated with housing wealth and it is statistically significant for women but not for men W idowed men (widowers) have $1 7,100 more housing wealth than married men ; widowed women own only $ 9 ,300 more than married women. Furthermore, divorced and separated men are predicted to have greater housing wealth than married men; $10,000 more for separated men and $12,500 more for divorced men. However, there is no statistically significant difference between married women and either those who are separated or divorced. In terms of education, e ach additional year of schooling about $1,521 but only $1,080 for women. Female returned migrants have about $11,400 more housi ng wealth than those who have not housing wealth. Finally, there are statistically significant differences in terms of the relationship between non housing and housing wealth. For men, every one thousand dollar increase in non housing wealth is associated with only a $61 increase in housing wealth, while for women it is $127. Discussion and Concluding Thoughts This is one of the first gender analyses of homeownership a nd housing wealth in Latin America. As discussed above, Ecuador has a high rate of joint homeownership and a fairly equal gender distribution of homeownership. The regression analyses in this chapter suggest similar probabilities of homeownership and simil ar levels of housing wealth for both men and women in Ecuador; likely due at least in part to the near legal importance of partial community property in terms of joint owner ship. However, key gender differences in the predictors of homeownership and housing wealth were

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56 identified. Th ese differences may indicate differences in the processes of accumulation for men and women. Past migration is important for women; it increases their probability of homeownership and the amount of housing wealth owned. However, past migration This is likely related to the fact that women, especially single mothers, use mig ration as a strategy for acquiring homes, a point that was brought up during qualitative fieldwork time and again. Also, given that they leave children behind when they migrate, they likely have more incentive than many male migrants to return to Ecuador. More research is needed to more thoroughly test this hypothesis since there may be some latent variable coming into play; it takes a certain personality and/or set of circumstances for women to seek work through migration, which may also impact their proba bility of homeownership. homeownership. Women who receive this payment are 1.4 times more likely than women who do not receive it to be a homeowner. We must be careful with ca usality here; this relationship could indicate one of two things (or a combination of both). First, it could be that women who receive the payment can better afford to acquire a home; perhaps the additional income enables them to purchase construction mate rials in order to build their homes slowly over time. Second, it could indicate that homeowners are more likely to receive the payment ; p erhaps there is some underlying issue with how the payment is distributed that favors homeowners For example having a more permanent

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57 residence may facilitate payment receipts More research to disentangle the causality is warranted. Marital status is also an important explanatory variable. Although a person in a consensual union is less likely than a married person to ow n a home, they own similar amounts of housing wealth (there is no statistically significant difference). Widows and widowers own more housing wealth than married individuals but this effect is also gendered While widowers have about $17,000 more in housin g wealth than married men, widows only have about $9,300 more than married women. Furthermore, while divorced and separated women have about the same has wealth as married women, divorced and separated men have $10,000 to $12,500 more than married men. Thi s implies that men gain housing wealth by divorcing or separating whereas women do not. Perhaps the men keep the house and thus gain the full value of the house that was shared before (and women will tend to acquire a similar amount of housing wealth as th ey had while married) or perhaps men move up in socio economic status by buying a more valuable home while women do not. A limitation to these generalizations is that men who lose housing during divorce or separation are not included in the regression anal ysis of housing wealth since they are not owners; therefore men who are still homeowners (either keeping the marital home or purchasing a new home after the separation/divorce) are likely to own more in housing wealth than married men. But, ng here is that there is no statistically significant difference for divorced or separated women compared to married women. More education implies greater housing wealth for both men and women However, for men each additional year of schooling correlates to an additional $1,521 in

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58 housing wealth; while for women it correlates to an additional $1,080. In terms of housing wealth, it seems that education does not have the same return on investment for men and women (assuming that increased housing wealth is caused by more education). Further research is needed to clarify the impact of employment and job category on both homeownership and housing wealth. Additional research on the form of acquisition and processes of accumulation may also lead to interestin g gender differences. Finally, more work is warranted to determine the impacts of homeownership and/or housing wealth; for example how does homeownership or housing wealth within the home, community and/or state in terms of decision making and bargaining power ? This is addressed in more detail in the following two chapters. Although this study helps explain the situation in Ecuador, similar studies in other South American countries would be particularly useful in explaining t he wide range of ownership patterns identified in previous studies. regime partial community property and the fact that is known and enforced through on of homeownership and housing wealth. However, research in other countries would help verify this by addressing the following questions. Do other countries with the partial community property marital regime also have similar rates of homeownership and ho using wealth for men and women? If so, this could indicate that the marital regime is promoting gender equality. If not, perhaps there are monitoring and enforcement issues that need to be addressed and these should be compared across countries. For

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59 exampl mechanisms that make people aware of their rights as well as enforcing them? Addressing these questions in various countries would go a long way in determining the impact of the marital regime and enforcement mechanisms in promoting gender equality in property rights. Furthermore, the results presented in this chapter indicate several gender differences in terms of the predictors of homeownership and housing wealth. Similar stud ies in other countries could also compare these results and what that indicates for gender equality. Perhaps patterns would reveal gender differences in terms of how dwellings are acquired and quality differences.

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60 Figure 2 1. Wealth portfolios by wealth quintile and overall Ecuador 2010. Percent of wealth in each asset category. Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 2 1. The household distribution of homeownership by sex (of owner occupie d homes) Country & Survey Year Women Men Joint Total N Argentina 2001 21.7 37.7 40.7 100% 4.8 million Chile 2003 40.5 56.1 3.4 100% 2.7 million Ecuador 2005 21.4 37.3 41.3 100% 1.1 million Guatemala 2000 24.8 72.7 2.5 100% 1.1 million Honduras 2004 38.0 59.0 3.0 100% 0.5 million Mexico 2004 33.9 62.8 3.3 100% 18.1 million Nicaragua 2005 46.1 47.4 6.3 100% 0.8 million Panama 2003 41.9 42.3 15.9 100% 0.3 million Paraguay 2000 32.5 64.1 3.5 100% 0.4 million Source: D eere, Alvarado, and Twyman (2012 ) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Financial Assets Consumer Durables Businesses Agricultural Equipment Livestock Other Real Estate Agriculutral Land Housing

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61 Table 2 2. Distribution of dwelling tenure by household in Ecuador, 2010 Owned & Paid Owned & Mortgaged Sub Total Owned Rented Other Total No. obs. (n ) Sierra 50.5 5.0 55.5 % 25.8 18.7 100 % 1,391 Costa 62.5 1.6 64.1 % 15.8 20.1 100 % 1,501 Total 56.7 3.2 59.9 % 20.6 19.5 100 % 2,89 2 Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 2 3. Form of dwelling acquisition by rural and urban households in Ecuador, 2010 Form of acquisition Urban (n = 1045) Rural (n = 682) Total (n = 1 727) Purchase 30 14 23 Construction 59 75 65 Gift/Donation /Inheritance 10 10 10 Other 1 2 2 Total 100 % 100% 100% Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 2 4. Type of financing for p urchased or constructed homes (n = 1,528) Type of financing n % Savings 1,266 82.9% Remittances 14 0.9% MIDUVI 140 9.2% IESS loan 93 6.1% Loan from private institution 239 15.6% Informal loan 47 3.1% Direct financing 8 0.5% Work loan 21 1.4% Other 47 3.1% Source: UF FLACSO 2010 Ecuador Household Asset Survey Note: Does not sum to 100% because households could finance with multiple sources.

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62 Table 2 5. List of variables and their definitions. Variable Name Operational Definition Owner Binary dependent variable; 1 if individual is an owners, 0 otherwise Housing Wealth Dependent variable; sales value of home divided by number of owners Female Dummy variable; 1 if individual is a female, 0 otherwise Age Age in years Age 2 Age squared Ethnicity Dummy variables of self reported ethnicity Mestizo 1 if Mestizo or white, 0 otherwise (base category) Indigenous 1 if Indigenous, 0 otherwise Other 1 if reported another ethnicity: Afro Ecuadorian, Arab, Mulato, or any other et hnicity listed, 0 otherwise Marital Status Dummy variables of current marital status Married 1 if currently married, 0 otherwise (base category) Single 1 if single and never married or in consensual union, 0 otherwise Consensual Union 1 if currently in a consensual union, 0 otherwise Widowed 1 if widowed, 0 otherwise Divorced 1 if divorced, 0 otherwise Separated 1 if separated, 0 otherwise Years of schooling Number of years of formal schooling completed; pre school is not included, adult education and literacy classes are included such that every 2 years are counted as one year. Returned migrant Dummy variable; 1 if person ever migrated to another country for work, 0 otherwise Receives transfer payment Dummy variable; 1 if person receives the "bono", 0 otherwise Non housing wealth Sales value of all physical and financial assets except housing owned by the person; the value of asets owned by more than one peson is divided equally among all the owners Employed (not employed) Dummy variable; 1 if the person reported that s/he was currently employed and remunerated (unpaid family labourers are not included); 0 otherwise Number of children (<18) Number of children under 18 years of age in the household Number of adults Number of adults aged 18 or over in the household Rural Dummy variable; 1 if household is in a rural area (with less than 5,000 residents), 0 otherwise/urban Coast Dummy variable; 1 if household is in a coastal province (Esmeraldas, Guayas, Los Rios, Manabi, El Oro, Santa Elena, or Santo Domingo), 0 if household is in a highland/sierra province (Azuay, Bolivar, Canar, Carchi, Cotopaxi, Chimborazo, Imbabura, Loja, Pinchincha, Tungurahua) Number of owners Number of homeowners of an owned home

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63 Source: Deere and Contreras, 2011 Figure 2 2 Form of homeownership, Ecuador 2011 Individual man 16% Individual woman 30% Joint by couple 41% Other joint 13%

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64 Table 2 6 Descriptive statistics for categorical variables, composition (percent) of adult sample in Ecuador 2010 Total Sample (n=7,431) Homeo wners (n = 2,621) Non Homeo wners (n = 4,810) Women Men Total Women Men Total Women Men Total (n=3,959) (n=3,472) (n=7,431) (n=1,428) (n=1 ,193) (n=2,621) (n=2,531) (n =2,279) (n =4,810) Owners 36% 34% 35% 100% 100% 100% 0% 0% 0% Sex Women 100% 0% 53% 100% 0% 54% 100% 0% 53% Men 0% 100% 47% 0% 100% 46% 0% 100% 47% Total 100% 100% 100% 100% 100% 100% 100% 100% 100% Ethnicity Mestizos 89% 88% 89% 88% 87% 88% 89% 89% 89% Indigenous 5% 5% 5% 5% 5% 5% 5% 4% 4% Other Ethnicity 7% 7% 7% 7% 8% 7% 6% 7% 7% Total 100% 100% 100% 100% 100% 100% 100% 100% 100% Marital Status Married 36% 41% 38% 50% 64% 56% 28% 29% 29% Single 21% 28% 24% 6% 6% 6% 29% 39% 34% Consensual Union 20% 23% 22% 17% 20% 18% 22% 25% 23% Widowed 9% 3% 6% 14% 4% 9% 6% 2% 4% Divorced 3% 1% 2% 2% 1% 2% 3% 1% 2% Separated 11% 4% 8% 12% 5% 8% 12% 4% 8% Total 100% 100% 100% 100% 100% 100% 100% 100% 100% Past migrant 2% 3% 3% 3% 4% 3% 2% 3% 2% Receives transfer payment 20% 4% 12% 27% 6% 18% 16% 2% 9% Remunerated Employment Employed 56% 81% 68% 58% 84% 70% 55% 80% 67% Not employed 44% 19% 32% 42% 16% 30% 45% 20% 33% Total 100% 100% 100% 100% 100% 100% 100% 100% 100% Lives in Rural household 32% 33% 32% 40% 42% 41% 28% 28% 28% Lives in Coastal household 51% 54% 53% 53% 55% 54% 50% 54% 52% Source: UF FLACSO 2010 Ecuador Household Asset Survey

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65 Table 2 7 Descriptive statistics for continuous variables of adult sample in Ecuador, 2010 n M inimum Maximum Mean Std. dev. Median Adult Sample (n = 7,431) Age 7,431 18 99 40.400 17.162 37 .00 Yrs of schooling 7 ,431 0 21 8.932 4.690 9 .00 Non housing wealth 7,431 0 596 3.697 15.548 0.41 Adult Men ( n = 3,472) Age 3,472 18 99 40.302 17.361 36.5 Yrs of schooling 3,472 0 20 9.118 4.548 9 Non housing wealth 3,472 0 596 4.347 19.305 0.395 Adult Women ( n = 3,959) Age 3,959 18 99 40.485 16.988 37 Yrs of schooling 3,959 0 21 8.768 4.805 9 Non housing wealth 3,959 0 284 3.128 11.237 0.435 Owners (n = 2,621) Housing wealth 2,621 0.033 400 16.601 22.782 10 Age 2,621 18 95 50.393 15.492 50 Yrs of schooling 2,621 0 20 7.632 4.716 6 Non housing wealth 2,621 0 596 6.197 22.833 0.854 Non Owners ( n = 4,810) Age 4,810 18 99 34.955 15.500 30 Yrs of schooling 4,810 0 21 9.640 4.521 10 Non housing wealth 4,810 0 207 2.336 9.177 0.266 Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 2 8 Descriptive statistics for continuous variables of household sample in Ecuador, 2010 N Minimum Maximum Mean Std. dev. Median Household Characteristics All Households (n = 2,891) Number of household members 2,891 1 15 4.171 1.897 4 Number of children 2,891 0 8 1.601 1.448 1 Number of adults 2,891 1 9 2.570 1.202 2 Number of adult men 2,891 0 6 1.201 0.823 1 Number of adult women 2,891 0 7 1.369 0.772 1 Owned homes (n = 1,734) Number of homeowners per owned home 1,734 1 10 1.667 0.874 2 Market value of owned homes 1,734 0.088 400 25.675 30.919 15 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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66 Table 2 9 Logistic regression results for model of homeownership in Ecuador, 2010 Std. Err. Intercept 5.205 *** 0.277 Individual Characteristics Female 0.107 0.066 Age 0.188 *** 0.010 Age 2 0.001 *** 0.000 Ethnicity (Mestizo) Indigenous 0.010 0.147 Other 0.043 0.114 Marital Status (Married) Single 1.351 *** 0.106 Consensual Union 0.726 *** 0.080 Widowed 0.657 *** 0.125 Divorced 1.348 *** 0.206 Separated 0.839 *** 0.106 Years of schooling 0.010 0.007 Returned migrant 0.160 0.163 Receives transfer payment 0.270 *** 0.091 Non housing wealth a 0.011 *** 0.003 Employed (not employed) 0.079 0.072 Household Characteristics Number of children (<18) 0.005 0.022 Number of adults 0.167 *** 0.023 Rural 0.671 *** 0.066 Coast 0.345 *** 0.064 Number of cases (n ) 7431 Likelihood ratio chi square (df) 2349.21 (19)*** Psuedo R 2 0.244 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0.05, and ***p < 0.01 a) Non housing wealth is in thousands of dollars (USD, which is the currency in Ecuador)

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67 Table 2 10 Logistic regression results for models of homeownership in Ecuador, 2010 Model II -Men Model III -Women Std. Err. Std. Err. Chi square for difference Intercept 4.957 *** 0.420 5.272 *** 0.369 0.318 Individual Characteristics Age 0.180 *** 0.016 0.197 *** 0.014 0.712 Age 2 0.001 *** 0.000 0.002 *** 0.000 1.447 Ethnicity (Mestizo) Indigenous 0.134 0.222 0.092 0.197 0.579 Other 0.076 0.167 0.015 0.156 0.072 Marital Status (Married) Single 1.485 *** 0.161 1.216 *** 0.145 1.541 Consensual Union 0.910 *** 0.114 0.554 *** 0.112 4.953 ** Widowed 0.778 *** 0.249 0.509 *** 0.149 0.855 Divorced 1.552 *** 0.476 1.284 *** 0.231 0.257 Separated 0.860 *** 0.199 0.784 *** 0.127 0.105 Years of schooling 0.012 0.011 0.010 0.010 0.010 Returned migrant 0.043 0.219 0.454 0.249 2.250 Receives transfer payment 0.098 0.225 0.368 *** 0.104 3.530 Non housing wealth a 0.010 *** 0.003 0.013 *** 0.004 0.399 Employed (not employed) 0.051 0.150 0.117 0.084 0.961 Household Characteristics Number of children (<18) 0.029 0.032 0.039 0.030 2.344 Number of adults 0.188 *** 0.034 0.152 *** 0.031 0.635 Rural 0.818 *** 0.099 0.546 *** 0.090 4.121 ** Coast 0.386 *** 0.097 0.315 *** 0.087 0.294 Number of cases (n ) 3472 3959 Likelihood ratio chi square (df) 1224.89 (18)*** 1146.46 (18)*** Psuedo R 2 0.274 0.222 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0.05, and *** p < 0.01

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68 Table 2 11 Conditional logit regression results for model of homeownership in Ecuador, 2010 Model I -All obs. Std. Err. Personal Characteristics Female 0.120 0.219 Female*number of male adults 0.084 0.109 Age 0.241 *** 0.020 Age 2 0.002 *** 0.000 Ethnicity (Mestizo/white) Indigenous 2.151 1.434 Other 0.097 0.448 Marital Status (Married) Single 1.528 *** 0.238 Consensual Union 0.677 ** 0.311 Widowed 1.284 *** 0.268 Divorced 2.167 *** 0.437 Separated 1.061 *** 0.272 Years of schooling 0.010 0.019 Past migrant 0.309 0.368 Receives transfer payment 0.334 ** 0.167 Non housing wealth a 0.050 *** 0.011 Employed (not employed) 0.315 ** 0.135 Number of cases (n ) 3739 Likelihood ratio chi square (df) 1707.39 (16)*** Psuedo R 2 0.603 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0.05, and ***p < 0.01

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69 Table 2 12 Ordinary least squares regression of housing wealth (in thousands of USD) of homeowners in Ecuador, 2010 Model I -All obs. Coef. Std. Err. Intercept 7.977 4.348 Personal Characteristics Female 0.380 0.859 Age 0.217 0.149 Age 2 0.001 0.001 Ethnicity (Mestizo) Indigenous 1.856 1.845 Other 0.068 1.473 Marital Status (Married) Single 3.217 1.732 Consensual Union 0.060 1.111 Widowed 10.580 *** 1.477 Divorced 6.588 ** 3.091 Separated 4.604 *** 1.455 Years of schooling 1.310 *** 0.095 Returned migrant 7.312 *** 2.074 Receives transfer payment 5.453 *** 1.127 Non housing wealth 0.080 *** 0.017 Employed (not employed) 2.245 ** 0.918 Household Characteristics Number of children (<18) 0.137 0.284 Number of adults 0.384 0.315 Number of owners 3.891 *** 0.399 Rural 8.186 *** 0.843 Coast 8.370 *** 0.860 Number of cases (n ) 2621 F statistic (df) 56.82 (20)*** Adjusted R 2 0.30 Source: UF FLACSO 2010 Ecuador Household Asset Survey N otes: Reference categories given in parentheses *p < 0.1 **p < 0.05, and ***p < 0.01

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70 Table 2 13 Ordinary least squares regression of housing wealth (in thousands of USD) by sex of homeowners in Ecuador, 2010 Model II -Men Model III -Women Chi square Coef. Std. Err. Coef. Std. Err. Intercept 10.907 0.241 5.017 5.467 1.158 Personal Characteristics Age 0.064 0.002 0.430 ** 0.190 5.074 ** Age 2 0.003 2.848 0.002 0.002 0.000 Ethnicity (Mestizo) Indigenous 0.904 2.848 3.035 2.385 0.329 Other 1.778 2.316 1.361 1.877 1.109 Marital Status (Married) Single 4.174 2.933 2.809 2.147 0.141 Consensual Union 0.832 1.699 0.631 1.457 0.428 Widowed 17.112 *** 3.088 9.280 *** 1.668 4.979 ** Divorced 12.496 *** 7.565 4.945 3.217 0.844 Separated 10.096 *** 2.899 2.688 1.650 4.933 ** Years of schooling 1.521 *** 0.148 1.080 *** 0.123 5.224 ** Returned migrant 2.874 3.076 11.36 *** 2.805 4.154 ** Receives transfer payment 8.867 *** 2.720 5.297 *** 1.260 1.418 Non housing wealth 0.061 *** 0.021 0.127 *** 0.033 2.857 Employed (not employed) 3.939 ** 1.918 1.088 1.016 1.725 Household Characteristics Number of children (<18) 0.649 0.440 0.152 0.372 1.937 Number of adults 0.148 0.498 0.466 0.400 0.247 Number of owners 4.563 *** 0.608 3.365 *** 0.525 2.225 Rural 8.424 *** 1.321 7.881 *** 1.082 0.101 Coast 7.559 *** 1.369 8.795 *** 1.101 0.495 Number of cases (n ) 1193 1428.000 F statistic (df) 28.02 (19)*** 34.81 (19)*** Adjusted R 2 0.30 0.310 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0.05, and *** p < 0.01

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71 Table 2 14 Ordinary least squares regression of housing wealth (in thousands of USD) of homeowners in Ecuador, 2010 (with fixed effects) Model I -All obs. Coef. Std. Err. Intercept 7.063 *** 1.865 Personal Characteristics Female 0.374 0.385 Age 0.375 *** 0.069 Age 2 0.001 0.001 Ethnicity (Mestizo) Indigenous 4.801 4.415 Other 0.645 1.830 Marital Status (Married) Single 3.483 *** 0.776 Consensual Union 2.622 *** 0.962 Widowed 4.280 *** 1.092 Divorced 7.485 *** 1.707 Separated 0.548 0.966 Years of schooling 0.128 ** 0.065 Past migrant 1.247 1.374 Receives transfer payment 2.107 *** 0.678 Non housing wealth 0.114 *** 0.017 Employed (not employed) 0.122 0.462 Number of cases ( n ) 7431 Number of groups 2892 F statistic (df) 59.48 (15)*** Within group R 2 0.16 Between group R 2 0.10 Overall R 2 0.14 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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72 CHAPTER 3 ASSET OWNERSHIP AND DECISION MAKING IN DUAL HEADED HOUSEHOLDS IN ECUADOR 1 As explained in Chapter 1, many studies about s such as changes in household budget shares, increased nutrition, health, and /or educational attainment of children. Although these studies provide evidence that are related to these welfare outcomes, they limit the type of decision making processes that lead to such outcomes. In order to overcome these l imitations, in this chapter, we focus on the intra household distribution of wealth and how it is related to how decisions are made within the household As discussed by Sunita Kishor and Lekha in household decision m aking Furthermore, i t is widely recognized that the empowerment of women requires an [their] goals and act upon T h is aspect of empowerment is often measured in terms of n in household decision making As explained by Kishor and Subaiya (2008) m any studies autonomous decision making but others measure it as whet her or not women participate in decisions at all, either alone or jointly. However, as they state, decisionmaking is not one undifferentiated variable. For any decision, making the An earlier version o f this paper was presented at the Allied Social Sciences Association (ASSA) annual conference in Chicago in January 2012 and will be published in the Review of Radical Political Economy proceedings (Carmen Diana Deere and Jennifer Twyman, 2012).

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73 decision alone making it jointly with a husband or someone else, or participating at all in the decision ( alone or jointly ), constitute unique vari ables with different correlates (Kishor and Subaiya 2008: 41). Thus, it matters for quantitative analysis whether the focus is on women maki ng decisions alone or jointly. The implications of this finding is that in the analysis of decision making together as a dependent variable on whether women participate at all; rather, each type of decision making needs to be examined on its own. 1 It is often d ifficult to determine what form of decision making (joint or alone) is more empowering for women and it depends on the starting point. It is often (implicitly) assumed that men make the household decisions autonomously (see for example empowering. However, if women are traditionally making the decision autonomo usly then her making that decision alone would not indicate empowerment. In such cases male involvement or a move from autonomous to joint decision making may indicate a change in gender roles and could be a more empowering experience. 2 For example, it i s conceivable that growing male involvement in what had been a female domain, such as a tendency towards joint decision making regarding the household food budget, could be more gender progressive than female autonomy if it signals a change in the traditio nal division of labor, with men now more involved in domestic labor. Conversely, 1 Of cour se in contexts where women rarely participate in household decisions at all it may be appropriate making, as Anderson and Eswaran (2009) do in a study of a region in Bangladesh. 2 The caveat to this a ssumption is that sometimes men begin to take over what has been traditionally female roles; such as in the cases of improved varieties of crops that go from subsistence crops and thus in the female domain to cash crops that are in the male domain.

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74 a change from joint decision making to autonomous decisions over income control, even if by both husband and wife, could signal a break down in cooperation in which women are not necessarily better off, particularly if there are significant gender disparities in the amount of income each controls. Most decision making indicators of empowerment such as those included in the DHS examined by Kishor and Subaiya (2008) include o nly questions regarding decision making probably because m not likely to be measured by their participation in household decision making (even if margi nalized groups of men warrant study of empowerment, it is not likely that their lack of empowerment is at the household level it is more likely in empowerment. decision making seems to be the norm in most studies, we start by analyzing w decision making regarding the decision about whether to work and how to spend her own income. We contribute to the decision making by examining perceptions of their own decision making bu t also autonomous decision making since as discussed previously in Chapter 1, perceptions decision mak ing we also examine the correlates of when the spouses agree about her autonomous decision making This

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75 step allows us to understand the conditions under which the couple agrees about her autonomy However, since autonomous decision making may not be the best indicator of decision making by couples in Drawing on the framework developed by Diane Coleman and Murray Strauss (1990) regarding marital decision making power, egalitarian households are defined as those in which the couple makes decisions together, 3 as opposed to being male dominated (where most of the decisions are made by the man), female dominated (where most of the de cisions are made by the woman) or characterized by divided power (where the man makes some decisions, and the woman makes others). We define egalitarian decision making in a strict way; it implies that both spouses report making their own decision jointly and they report that their spouse does the decision making Furthermore, as explained in Carmen Diana Deere and Jennifer in the case of dual headed households (those constituted by a husband and wife), is autonomy the appropriate measure of agency? Or is it when women ar e able to negotiate as equals with their partners, to reach truly joint decisions as a couple? In our analysis, for egalitarian decision making within households to prevail both husbands and wives must report that they each make decisions jointly; moreov er, we impose an even more restrictive condition -that they agree that the other does in fact 3 As me ntioned above, such joint decision making is defined restrictively in the sense that both spouses report that they themselves and their spouses make joint decisions.

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76 make decisions jointly. This allows us to differentiate truly egalitarian households, from those where the couple disagrees on whether joint decision making is the prevailing practice, along with those that report that decisions are taken autonomously by either the man or woman. measured by her participation in household decisio n making in several ways. First, it uses the intra household distribution of assets and wealth as a key explanatory variable decision making decision making This has methodological perceptions will impact bargaining power (Sen 1990 Katz 1991 ). T his application will help us better understand the differences in perceptions by comparing the correlates of decision making as reported by men and women Methodologically it is important to understand how collecting data from only one individual (the man or woman) may impact results. Third, we identify the correl ates to men and women agreeing that the wife makes autonomous decisions. This allows us to understand under what conditions men and women have similar perceptions of the n household decision making By examining both autonomous and egalitarian decision making we can identify any important differences that arise and hope to add to the debate in the literature about how best to capture decision making as an indicator of wom

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77 Context One of th e main objective s of this study is to explore the relationship between asset ownership and decision making Ecuador is a particularly appropriate case to study this relationship because joint ownership of major assets am ong couples is quite common. Moreover, according to the results of the 2010 Ecuador Household Asset Survey, women own 52.2 % of the gross physical and financial household wealth, a share approximately equal to their share of the population (Deere and Contre ras 2011). Furthermore, Ecuador is typically characterized by high levels of joint decision making During the qualitative fieldwork, nearly all responses to how household discussion in which both spouses participated Further evidence of joint decision making Demographic and Maternal and Infant Health Survey (ENDE MAIN) for 2004 which included six questions about how household decisions were made. As shown in T able 3 1, the majority of partnered women responded that the decisions were made jointly by the couple. The highest rate of joint decision making was regarding the decision to visit family at 79% and the lowest was regarding whether to work outside the home or study at 53%. Women were most likely to make the decision about when to take a child to a physician alone (29%) alone, followed by whether t o work outside the home or study (24%). In terms of decision making Ecuador differs from many of the countries analyzed by Kishor and Subayia (2008); unlike most of the countries included in the DHS surveys, relatively few women in Ecuador report that the ir spouses make any of these six decisions alone, with the

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78 highest reported share (22 % ) also being the decision on whether or not the wife works outside the home or studies. Data The subsequent analysis is based on 1,776 households with couples ( where both partners responded to the decision making questions), which corresponds to 3,552 adult men and women, age 18 and over. The household decision making module included the following four questions regarding the participa tion of each person: Do (or did) you m ake the decision on whether or not to work? If you earn or receive income do you make the decision on how to spend this money? Do you make the decision to access health services for yourself? Do (or did) you make the decision on whether or not to use contr aceptives or some form of family planning? In the case of the first two decisions, regarding the decision to work and to spend made this decision ; thus the wording in The potential responses included: Yes, alone 4 (ID or relational code solicited) Not applicable 4 The ID is the unique identifier of a household member, whereas the relational code refer s to a non household member. We collected the latter information in order to be able to capture extra household economic relations with extended family members, including permanent migrants. The latter were defined as those who had lived outside the hou sehold for six months or longer, but during the past ten years contributed to the household economically with either remittances or gifts in kind.

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79 The decision on spending income contained one additional option, where the person could respond that they made the decision alone regarding a portion of their own income, but decided jointly over the other portion. This option was included since it is a fairly common practice in Ecuador for men to decide how much of their income to keep as their own discretionary income, and how much to turn over to his gas to ). Table 3 2 presents the basic descriptive data on the four household decisions with about their own decision. Men reported that they alone made the decision on whether or not to work much more frequently than did women, 52 % versus 32 % In contrast, the great majority of women reported that they made the decision on whether or not to work jointly with their partners (which might include an additional third person, as explained below). It was also more frequent for women than men to report that they asked permission or that the decision on whether or not they worked was made by their partner or another person; overall, however, these responses (including not applicable) characterized only 5 % of the women. Our results differ from the ENDEMAIN 2004 survey in this regard, since in that survey 22 % of the women reported that the decision on whether or not to work or to study was made by their partners ( T able 3 1). We can only speculate whether this relatively higher share who reported that their partners make this decision is due to the inclusion of the decision to study in this earlier survey question. With respect to the decision on how to spend the income that one earns or receives (such as wage income, the conditional cash transfer or other non labor income), a much higher share of women, 29 % reported that they alone make this

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80 decision as compared t o men, 19 % But, as expected, men more frequently than women reported that they made the decision alone over a portion of their income and jointly over another portion, 15 % vs. 10 % Seven percent of the women as compared to only 1 % of men reported that th is decision was not applicable because they did not earn or receive any income. 5 In the majority of households, these decisions were made jointly. Our question differed from the one included in the ENDEMAIN 2004 survey, since in that survey the question e licited information on the broader decision over spending of majority of women (69 % ) reported making this decision jointly with their partners. A higher share of women did con sider this decision to be made by their partner alone (19 % ) than by themselves alone (12 % ). With respect to health care, in the 2010 survey a slightly higher share of women than men (43 % vs. 39 % ) reported that they themselves alone made the decision on whether to seek health care for themselves; the majority of both men and women reported making this decision jointly. 6 Also, the great majority of both men and women reported that they made the decision on whether or not to use family planning or contrac eptives jointly, although women more frequently reported that they made this 5 A relatively high share of these partnered women do not currently work, 46%, as compared to only 5.5% of m en. This suggests that a large number are receiving some form of non labor income, since such relatively few women considered the question as not applicable. 6 The response to this question with respect to women can be compared with the results of the DHS surveys for Bolivia and Nicaragua. In both countries a higher share of women reported that they made the decision regarding their own health care autonomously (53 and 47%, respectively) than do so in Ecuador, and in these countries the share responding t hat they made the decision alone exceeded those making the decision jointly with their partner. On the other hand, in both countries around 10% that repres ented less than 1% of the total in Ecuador (Kishor and Subaiya 2008: 18).

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81 decision alone (24 % ) than did men (13 % ). Our findings on this latter question parallel thos e of the ENDEMAIN 2004 survey ( T able 3 1). The responses to the four decision making q uestions in the 2010 survey lend support to the proposition that joint decision making appears to be the norm in Ecuador. These data also suggest that women in Ecuador are more likely than their male partners to make decisions on their own, exceeding them in the share of autonomous decision making for three of the four decisions. But do the partners in a couple make these decisions in a similar fashion ( i e. is there symmetry in decision making within the household? ). Before addressing this questio n, the statistics presented in T able 3 3 give an decision making and a first look at the differences in perception of men and women. As shown, 32% of women report the decision alone. The difference is even greater for the spending de cision; 43% of women report making the decision alone compared to only 25% of men. The last column shows the percent of couple who agree that the wife makes the decision alone; only 13% agree about the decision to work and 18% about the spending decision. Now, turning to the question of whether the partners both make decisions in a si milar fashion (symmetrically), T able 3 4 presents the data on the distribution of responses of joint decision making by men and women In 22 % of households each partner report s making their own decision on whether or not to work by themselves. The decision to seek health care is the only other decision where both partners report making the decision autonomously in a good share of households, 23 % There is much

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82 greater symmetr y in decision making with respect to joint decision making, being highest with respect to the use of contraception (69 % income (41 % ), seeking health care (39 % ) and the decision to work (35 % ). Where men and women differ mos t in how they each make decisions regarding themselves is on spending the income that they earn. The category of joint decision making employed thus far includes situations where the joint decision is made by the couple alone, by the couple plus someone else, and where the decision is made jointly by the respondent with some one besides their partner. As T able 3 5 shows in one percent or less of households the joint decision is made with someone besides the partner. A somewhat higher share of joint decis ions is made by the couple along with an additional household member (such as a parent or child), but for no decision does this exceed three percent. 7 In the subsequent analysis of egalitarian decision making we exclude those cases of joint decision makin g with someone other than a partner, but retain in the definition of the dependent variable joint decision making which includes the spouse plus an additional household member. 8 We now turn to the degree of agreement among couples on how each spouse make s the decision. This is the variable that has been used in recent analyses of household decision decisions and whether her husband concurs or not with her perceptions. We gathered this more deta iled information for only two decisions, the decision to work and to spend 7 In the questionnaire respondents could indicate up to three people with whom they made each decision. 8 Thus, if one spouse indicated making the decision jointly with his/her spous e and someone else while the other spouse indicated making the decision jointly only with his/her spouse, this was considered symmetric (i.e. that they both agreed that the decision was made jointly with the spouse).

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83 As T able 3 6 shows with respect to the decision on whether or not to work, the degree of disagreement among couples is similar, 35 % whether considering the decision. The greatest degree of disagreement is with respect to the decision regarding In 57 % of households husbands had a different perception than their wives. In contrast to what has been found in the literature, wives claim greater autonomy for themselves in the decision to spend their own income than perceived by their husbands. There was spending their own income, with only 34 % of couples disagreeing. Many of the disagreements seem to stem from a discrepancy over whether or not women have any of their own money to spend. About 29 % of (520 out of 1776) women reported that they make the decision to spend their own income alone, while only 15 % (275 out of 1776) husbands report that their wives alone made such a decision. Many of the husbands of wives report ing that they alone made the decision (165 out of the 520 or 32 % ) reported that this decision was not applicable for their wives presumably because the husbands did not know their wives had any money of their own to spend. A further analysis of the disagre ements shows that while only 127 women considered the question not to be applicable because they did not earn or received any income to spend, 747 men reported that this question did not pertain to their wives. Men could be forgetting about the conditiona

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84 question was not applicable. Whe reas only 18 men (1 % ) reported that they did not earn or receive any income, 95 women (5 % ) reported this answer for their husbands Finally, in Table 3 7 we present the results on egalitarian decision making, those that meet the condition of both symmetry and agreement with respect to joint decision making in the decisions to work and spend. In terms of the decision to work, in 78 % of households characterized by joint decision making, both partners report that the decision is made jointly both wit h respect to themselves and their partner. The decision on how income is spent is much more contentious, with only 42 % of couples who both make the decision jointly also being in agreement with respect to their partner. Conceptual Framework Household deci sion making processes are likely to vary by household and type of decision. I n Ecuador own income, we assume a bargaining process within the household; and as such we expect the intra household distribution of assets and wealth to impact how these decisions are made. However, other factors are also likely to impact household decision making processes; these are discussed in more detail below. Socio economic status and the i ntra household distri bution of assets and wealth. In most analyses of household decision making, some measure of household socio different points in the wealth or income distribution. In the DHS su rveys, household wealth was constructed as an index of household ownership of selected assets and/or certain amenities. Kishor and Subaiya (2008) found that in the majority of countries and autonomous decision making. With respect to joint decision making, the index is positive and

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85 significant in only a handful of countries, but only for certain decisions. In Bolivia, for example, wealth is positively associated with joint decision making in terms of visits to care and large household purchases. These surveys only included information about household level assets; however, t he EAFF 2012 has the benefit o f having been able to collect individual level data on asset ownership and wealth Thus we can estimate both individual and household in households were only women own asset s (as compared to those were neither own assets) women will be more likely to make autonomous decisions and that households in which both own real estate will be more likely to make egalitarian decision s Ownership of the principal dwelling, agricultural l and and/or other real estate should fallback position), and strengthen her bargaining power in the marriage. We would expect the strength of elated to household decision making in a similar fashion to how a strong fallback position might deter intimate partner violence, as Pradeep Panda and Bina Agarwal (2005) have shown for Kerala, India. Alternatively, it might not be just ownership of key assets per se, that influences Since this should be directly related to her relative fallback position, we expect more equal shares of couple (or household) wealth to be positively associated with egalitarian decision making.

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86 Relative positions of spouses. W ducation, their relative earnings and whether both spouses are of the same ethnicity in order to capture possible differences in factors that affect the bargaining process between spouses. Differences between spouses may affect their threat points and thus bargaining power within the home. particular when she is beyond child bearing age. Thus to the extent that household decision making processes are negotiated, we might expect wom decision making and couples egalitarian decision making to increase as women grow older. Kishor and Subaiya (2008:21) found, in their regression analyses of the DHS surveys for 23 countries, that the age of the woman was the covariate mos t consistently own health care, large household purchases, purchases for daily needs, visits to family or friends) in the majority of countries. However, the net effect of age on joint decision making was found to be less consistent. Countering this tendency, particularly in cross sectional data, may be a cohort effect, with different norms governing gender relations within households among younger and older couples. Youn ger couples may be more open to alternative gender roles (R.S. Oropesa 1997). In Ecuador we thus expect the age variable to be indeterminate. It may not be just the absolute age of the woman that is important in influencing decision making, but rather th e difference in the age between the husband and wife.

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87 age is a resource which can affect the perception of strength when power and Nonetheless, they find that in the majority of countries that they analyze for most decisions, spousal age difference did not have a significant net effect on either autonomous or joint decision making. Nonethe less, in the case of Ecuador, we hypothesize that the more equal in age are husband and wife, the more likely they are to be characterized by egalitarian decision making. And conversely, the older the wife compared to the husband, the more likely she will be to make autonomous decisions. empowerment and participation in household decision making, Kishor and Subaiya (2008) found that this relationship is more nuanced. T hey f ound that the share of women who participate in decision making increases with the level of education, but varies depending on the particular decision and whether considering joint or autonomous decision making. Summarizing both their bivariate and multiv ariate analyses, they found that the level of education tends to be positively associated with women making decisions alone regarding their own health care and daily household purchases. With frequently positive and significant in terms of decisions regarding large household purchases and making visits to family and friends. We expect that the likelihood of decision making will increase with her education Stan Becker, Fannie Foseca Becker, and Catherine Schenck Yglesias (2006)

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88 women having some say in their index of household decision making. We would also oling to be positively related to egalitarian decision making since years of education may be associated with a greater willingness (or tolerance) to consider alternative points of view. Nonetheless, if the level or years of education of one partner signi with the greater degree of education to dominate in household decision making. Thus we would also expect that the more equal the level of schooling attained by husband and wife, the more likely th ey are to be characterized by egalitarian decision making. to their status cross culturally. Various studies have reported that women working for pay or earning an income to be p ositively associated with their participation in decision making (Becker Fonseca Becker, and Schenck Yglesias 2006, Shireen Jejeebhoy 2002). In their analysis of the DHS surveys, Kishor and Subaiya (2008) found that, holding other factors constant, women working for cash remuneration was positively associated with making decisions alone in the majority of countries. This covariate was associated with making decisions jointly in roughly half of the countries studied. Similarly, Anderson and Eswaran We expect that the labor force participation of women, as well as by both members of the couple, to be positively associated with egalitarian decision making. But it may be that it is not just whether or not women are employed, or how much they earn, but rather how much they earn in relation to their partners that influences their participation in decision making, and particularly, joint decis ion making. We expect that the more

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89 equal the earnings of the partner, the greater the likelihood that the couple is characterized by egalitarian decision making. Although we do not have data on the amount or level of income, we did ask both partners who made the most income. 9 We expect that in households where the wife earns the most, she will be more likely to make autonomous decisions and where the couple earns about the same they will be more likely to make egalitarian decisions. In terms of ethnicit y, indigenous couples have traditionally had relatively egalitarian relationships; however indigenous women traditionally administer the Sarah Hamilton 1998) T hus for the spending decision we expect that indigenous women to be more like ly to make decisions autonomously. However, the relationship for the work decision may be more egalitarian. Other ethnic differences may also be relevant so a categorical variable was creat ed to identify any differences; therefore c ouples were classified i nto one of th e following ethnic categories: b oth mestizo, both indigenous, both other ethnicity, or different ethnicities. 10 It is expected that if both spouses are indigenous, then the wife may be more likely to make the spending decisions autonomously but that the couple will make the work decision in an egalitarian fashion. If they have different ethnicities, then they may be less likely to make egalitarian decisions. Current and previous relationship status. We consider whether couples are formally marri ed versus in consensual unions, since consensual unions in Latin America are common, and usually considered to be less stable than marriages (Dallan Flake and 9 This variable may be reflecting socia l norms of equality and as such may give an omitted variable effect of underlying norms and not necessarily an effect of income inequality. 10 For the different ethnicity category, men and women were first classified into mestizo, indigenous, or other. If

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90 Renata Forste 2006). The effect of this variable likely depends on whether one is focusing on au tonomous versus joint decision making. Consensual unions might be associated with greater economic autonomy for women if they feel less constrained in marriage may signi fy a greater degree of commitment by each partner to each other, and thus, willingness to compromise and reach decisions by consensus. We thus expect marriage as opposed to consensual unions to be positively associated with egalitarian decision making and consensual unions with autonomous decision making. Whether a person (or both partners ) is in a second marriage or union may also influence their willingness to negotiate, compromise and make decisions jointly; especially if the break up of their previous relationship was associated with unequal gender relations within the household. Separ ated and divorced women may be particularly motivated to avoid a repetition of situations of domination (Deere, Contreras, Twyman 2010). We thus expect the wife or both members being in a second relationship to be positively associated with joint decision making. Household characteristics. In Ecuador most households are comprised of nuclear families but the presence of in laws may be related to decision making. in law has a negative e It is unclear if this is just a South Asian phenomenon since it seems to be in this region that mothers in law seem to have a particularly strong influence on their daughter in laws. In Ecuador it is speculated that

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91 extended f amily members 11 decision members reside may be less likely to make autonomous or joint decisions while if her family members reside i n the household she may be more empowered to make autonomous decisions. On the other hand, the presence of such family members may mean that women and/or couples are more likely to make decisions with these other family members than making them alone. Household location in terms of region (Coast/Sierra) and/or area (rural/urban) may also impact the bargaining positions of spouses. Rural to urban migration is sometimes associated with a breakdown in traditional norms, and particularly non egalitarian po wer relations within households, particularly in Latin America (Oropesa 1997). Such is related both to the greater exposure to information and alternative life styles in urban areas and the greater flexibility in gender roles that is sometimes required by differential labor market opportunities for men and women. But the impact of this variable probably depends on the extent to which households in rural areas are male dominated. The ethnographic literature for Ecuador suggests that at least in the highla nds, gender relations in rural indigenous households are relatively egalitarian (Hamilton 1998). We thus expect the effect of locale to be indeterminate with respect to joint decision making. Methods We use b inary dependent variable logistic regression models to identify the key decision making (as reported by women 11 not be determined if that person was a relative of the husband or wife and was therefore not included. Furthermore, children, stepchildren, and grandchildren were not included.

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92 decision making 12 The decisions regarding whether to wo For the models of autonomous decision making the dependent variable takes the value of 1 when the wife (husband) reports that she makes the decision alone and 0 otherwise. Similarly, for the models of egalitarian decision making the dependent variable takes a value of 1 when the couple makes egalitarian decisions and 0 otherwise. As explained in more detail above, egalitarian decision making implies that both spouses report that they both make a joint decision. The dependent variables and their frequenc ies are shown in T able 3 8. First, decision making is defined as the wife making the decision alone for the work decision and that she makes the spending decision completely or partially alone. Separate models a autonomous decision making as reported by women themselves and by their husbands. As shown in T able 3 8, the model of autonomous decision making as reported by the women themselves for the work decision includes 1757 women ( 19 wom en who not applicable ) and of these, 32 % reported that they made the decisi on alone. Only 25 % of men report that their wives make the decision alone. The sample size for the spending decision is 1649 women and about 43 % of these reported that they made the decision alone while only 25 % of husbands reported that their wives made this decision alone. Next, we expand on the traditional female autonomy model by adding the restriction that the husband agrees with his wife that she makes the decision 12 In all models, those individuals who report that the decision is not applicable to them are dropped from the sample for the logistic regressions.

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93 autonomously. The sample for this model is the same as the first two: 1757 women for the work decision and 1649 for the spending decision. Twenty five percent of couples agree that the wife mak es the work de cision autonomously while only 1 8 % agree that she wives make the spending decision autonomously Finally, since relative autonomy (being able to negotiate and make joint decisions) may be more important than making decisions alone, egalitarian decision m aking defined as both spouses making the decision jointly and reporting that their spouse does as well, is analyzed. In terms of the decision to work the sample size for this model is 1756 couples, 13 of these 488 or 28 % reported that the decision was egal itarian. Egalitarian spending decisions included only those reporting joint decisions; the partially joint, partially alone category was not included. T he sample size is 1635 couples 14 and of these 309 or 19 % are classified as egalitarian. Results D escript ive statistics of the independent variables are presented in T ables 3 9 and 3 10. As shown in T able 3 9 only about 35% of couples reside in a rural area; most (65%) are urban. About 53% of couples live in the Coast and the other 47% in the Sierra. Wives have extended family members present in 4.5% of households and husbands extended family members a re present in 4.1% of households. Only one household included extended family members of both the husband and wife. The majority of couples are both mestizo; 4.9% of partners are both indigenous, 5.6% are both of another ethnicity, and 3.4% have different ethnicities. 13 As reported above 19 women and 1 man reported that this decision was not applicable reducing the sample siz e by 20 from 1776. 14 Of the 1776 couples in the sample, 141 of them reported that the decision was not applicable for at least one of the partners.

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94 About 35 % of couples are in consensual unions and 65 % are married. A total of 23 % of couples in the sample were in a previous relationship; in 7 % of the couples, only the wife had been in a previous relationship, in 9 % only the husband had, an d in 8 % both the husband and wife had been previously married or in a consensual union. The employment variable is defined as anyone who is economically active; it is included % of coup les, both partners work; in 4 % only the wife works and in 45 % only the husband works (and in 4 % neither work). 15 Seventy four percent of couples agreed that the husband earned the most income. Only 7 % of couples reported that the wife made the most income and in 10 % they reported earning the same amount. In the other 10 % partners disagreed about who made more. We also explore whether it matters whether only the husband or wife owns a major asset versus both of them owning assets, either individually or jo intly. In 8 % of households only the wife owns real estate, in 12 % only the husband owns, in 46 % both own and in 34 % neither own. 16 Table 3 10 shows that on average, women ho ld 46 % of We also control for socio economic status by 15 Employment was det ermined by one who reported working but was not classified as an unpaid family laborer. For the work decision, we found 142 men (out of the 1776 in this sample) were unemployed but only one of these reported that the work decision was not applicable. In th e case of women, 823 were unemployed but only 19 reported the work decision was not applicable. These differences in unemployment and the work decision being not applicable are likely due to the fact that the work question decision not to work. 16 In some households, spouses reported different owners of such assets. In these cases, a reconciliation process, we first checked whether or not there was a title and if so the owners reported as being on the title were considered the owners. If there was no he analysis.

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95 17 to see whether the wealth level makes a difference in how decisions are made The mean wealth of couples is US$23,310 but with a wide range from $9 to $619,400 and a median of just over $8,000. The average age of women in the sample is 41; while the average age of men is 45. The average age difference between husbands and wives in the sample is four years (in other words, men are on average four years older than their wives). B oth men and women have about 8 years of schooling on average. The average difference in years of schooling is 0.4; so men have only slightly more education o n average. The results of the various logistic regression models are presented in T ables 3 11 through 3 1 8 and are discussed below model by model. The coefficients are reported in the results tables; the odds ratios can be calculated by taking the exponen t of the since it does not include the variables on asset ownership or intra household distribution of wealth. Then model II includes whether the wife, husband, bo th or neither are asset owners. Finally, model III includes the Autonomous Decision making as Reported by Women T hemselves Work decision Table 3 11 Model I shows that both partners having been in a previous relationship, and women earning the most are decision making A s women age, they are more 17 poverty; however, many non poor households receive the bono (Argudo, 2012), thus the wealth of a couple is likely a better indicator of their s ocio economic status.

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96 likely to make the decision about work alone 18 Women livi ng in r ural households are less likely than women in urban households to make the decision to work alone ; specifically the odds ratio can be calculated as exp( 0.512), which is 0.6. Thus, women in urban households are 1.7 (1/0.6) times more likely to make the decision alone than women in rural households Women in households in which both partners had been in a previous relationship are more likely to m ake an autonomous decision than when neither partner had been in a previous relationship (1.5 times the odds) (This is only statistically significant in the baseline model; in the others it is no longer significant at the 0.10 level.) Women i n households in which the wife earn s the most are more likely to make the decision alone than in households in which the man earns the most (they have 2 times the odds) Also, if the couple disagree s about who earns the most women are more likely (they have 1.6 times the odds) to make an autonomous decision than in households in which the man earn s the most. Models II and III give similar results The differences are that the previous relationship variable is no longer statistically significant and the coast (compare d to the highland) variable is now significant; women in households located in the coastal region are less likely than women in highland households to make the decision alone In Model II, we find that women in households in which only the wife owns real estate (housing, land, or other real estate) are more likely than women in household s in which n either partner own s real estate to make the decision alone. If both partners own real estate women are less likely to make the decision to work autonomously. 18 calculation: Also a test of joint significance found that the age variables are jointly statistically significant at the 0.01 level (p = 0.000 < 0.01).

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97 Model III shows that likely to make the decision alone. 19 We can use the coefficients on the female share and female share squared variables to calculate the share at which women are least likely to make the decision autonomously This calculation reveals that women are least likely to make the decision about whether or not to work alone when % At amounts less than and greater than 38 % they are more likely to make the decision alone. Spending decision Table 3 12 shows the results for women making the decision about spending their own money autonomously. In the baseline model (Model I) the following variables are signifi extended family members in the household, ethnicity, employment, and earnings. Older women are more likely to make the decision on how to spend their own money autonomously. 20 Women in rural hous eholds are less likely to make the decision alone than women in urban households; and, women in coastal households are more likely than women in highland households to make the decision alone. Women who have extended family members (parents or siblings) l iving in their households are more likely than women without extended family members present in their households to make the decision alone. This may indicate that extended family members make women feel they have greater bargaining power (or are more empo wered). Women in households in Ecuadorian being the greatest proportion of these) are less likely to make the decision alone than women in 19 A test of joint significance also reveals that the two variables (female share and femal e share squared) are jointly significant with a p value of 0.000. 20 value of 0.025.

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98 households in which both partners are mestizo ; however there is no statistically significant difference between mestizo and indigenous couples Women in households in which the wife only or both partners are employed are more likely to make the decision alone than women in households in which only the husban d is employed ; but, there is no statistically significant difference between women in households in which neither are employed and those in which only the husband is employed Women in households in which both partners earn about the same are less likely to make the decision alone than women in households in which the man earns the most ; they are likely making joint decisions Women in households in which the partners disagree about who earns the most are more likely to make the decision alone than women in households in which the man earns the most. Models II and III have similar results to those reported above for model I except that the consensual union variable is not statistica lly significant in either model II or III, the wife only being employed i s not statistically significant in Model III, and the earning the same variable is not statistically significant in Model II. Model II adds the asset ownership variables and we find that women in households in which the wife only owns real estate are more likely to make the decision alone than women in households in which neither own real estate. Also, women in households in which both partners own real estate are less likely to make the decision alone than women in households in which neither own real es tate. There is no statistically significant difference between households in which only men own and those in which neither own.

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99 alone. Women are least likely to make the decision alone when they own about 33 % of cou likely to make the decision alone. Comparison of the Work and Spending Decision Models (as Reported by Women) Comparing the work and spending decision models as reported by women (see Tables 3 11 and 3 12), we find some similarities and some differences. First, the models are similar in terms of the sign and significance of the variables related to l estate not depend on the decision being considered. So, for both decisions, as women get older they are more likely to make the decisions alone. Rural women are less likely than urban women to make the decision alone perhaps supporting the ethnographic research that indicates rural highland households being relatively egalitarian (Hamilton 1998). The correlates for the decisions differ in terms of the following variab les: coast, consensual union, wife has extended family members, both other ethnicity, both have been in a previous relationship, and woman earns the most. For the decision to work, the coastal variable was significant for models II and III. Women living in the coastal region were less likely to make the work decision alone but more likely to make the spending decision alone than women in the highlands. There was no difference between women in consensual unions and married women for the work decision; but women in consensual unions were more likely to make the spending decision alone than married women (this variable was only significant in the baseline model for the spending decision). The wife having extended family members present was negatively assoc iated with women making the work decision alone but was not statistically

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100 significant; however, in the spending decision this variable was positive and significant. Women who live with extended family members (parents and/or siblings) are more likely to m ake the decision about how to spend their own money alone compared to those women who do not live with extended family members. Although women in households spendin g decision alone than women in households in which both partners were classified as mestizo, there was no statistical significance for the work decision. When both partners had been in a previous relationship, women were more likely to make the decision to work alone (for the baseline model) but there was no statistically significant difference in terms of the spending decision. Also, women in households in which the wife earned the most were more likely to make the work decision alone than women in househo lds in which the husband earned the most but there was no significant difference for the spending decision. Autonomous Decision making as Reported by M en Work decision As shown in Table 3 13 which gives the results for the models of decision making as reported by their husbands, the following Similar to the more likely to make the decision to work alone. Women in rural households are less likely to make the decision alone than women in urban households. And, women in households in which the wife earns the most are more likely than women in households in whic h the husband earns the most to make the decision to work alone. Model II includes the real estate ownership variables, which are not statistically significant. Also in this model, rural is no longer statistically different than urban. Model III includes

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101 decision alone until reaching 68 % (the point at which women are least likely to make the decision alone). Spending decision The results for women making autonomous decision about spending their own money as re ported by men are presented in T able 3 14. In these ethnicity, and employment are s tatistically significant variables related to women making the spending decision alone. Again, as women get older they are more likely to make the decision alone. Women in rural households are less likely than those in urban households to make the decisio n alone but women in coastal households are more likely than women in highland households to make the decision alone. Women who have extended family members residing in their households are less likely to make the decision alone than women who do not have extended family members living with them. Women in households in which both partners are classified as other ethnicity are less likely than those in households in which both partners are classified as mestizo to make the decision alone. Women in househo lds in which the wife only works, both work, or neither work are more likely than women in households in which only the husband works to make the decision alone. Models II and III give similar result as those reported above but in model II we also find t hat women in households in which the wife only owns real estate are more likely than women in households in which the husband only owns real estate to make the not statistically significant.

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102 Comparison of the Work and Spending Decision Models (as Reported by Men) Comparing the work and spending decision models for women as reported by men (see Tables 3 13 and 3 14) we find many more significant variables for the spending decision than the work decision. The only variables that are significant in both models with women making the decisions alone and women in rural households are less likely than women in urban households to make the decisions alone. The following variables differed in terms of significance and/or sign for the two decisions: coast, wife has extended family members in the household, both other ethnicity, and woman earns the most. Women in coastal households were more likely than women in highland households to make the decision about spending autonomously whereas there was no difference for th e work decision. Women in households with extended family members of the wife present are less likely to make the decision about spending autonomously than women in households without extended family members of the wife present; but there is no statistica lly significant difference for the work decision. Women in households in which both partners are classified as other ethnicity are less likely than women in households in which both partners are mestizo/blanco to make the decision to spend autonomously; b ut, there is no difference for the work decision. Finally women in households in which the wife earns the most are more likely than women in households in which the husband earns the most to make the work decision alone. This variables was not statistical ly significant for the spending decision; although the spending decision models included employment variables which were significant women in households in which the wife only, both, or neither partner

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103 worked were more likely than women in households in wh ich the husband only worked to make the spending decision autonomously. Decision making Work decision Comparing Tables 3 11 and 3 ecision can be identified. The effect of the household in both the men and women ; however, the magnitude is greater in model than in mode l. Furthermore, women who live in the coastal region are less likely than women living in the highlands to make the decision alone; however in the men there is no difference between living on the coast or in the highlands. h partners having been in a previous marriage or consensual union is related to a greater likelihood of her making the decision alone; but, been in a previous relationsh over the amount of earnings is correlated to a greater likelihood of making the decision and the men earning the most. W omen only owning as compared to neither owning real estate implies a greater likelihood of women making the decision alone; and both owning implies a lower likelihood of women making th e decision alone. However, in variables are not significant. This seems to indicate that women with assets are

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104 does not seem to impact men And, while the of 69%. This may indicate that men view joint decision making to occur at these higher autonomous decision, then they would be more likely to make a joint decision at that point. So, while women may perceive joint decision making to occur most often when she owns 38%, men do not think joint decision making occurs until she owns 69% of wealth. This may relate to the number of disagreements about how decisions are made as well. Spending decision s models of the spending decision can be compared by examining Tables 3 12 and 3 with extended family in the household are more likely to make an autonomous decision than women without extended family members present. In th opposite result is found; women with extended family members present in the household are less likely to make an autonomous decision; perhaps he views her as making decisions with her family members. ouseholds in which either the woman alone or both partners are employed the women are more likely to make autonomous decisions than in households in which only the husband is employed. This supports loyment for her bargaining both partners, or neither partner works implies that the woman is more likely to make

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105 ortance of women working; all categories in which women work are significantly different than just the man working; that is if the man works, the wife is less likely to make th e decision alone only category); although when they both work she is more likely than when only he works to make the decision autonomously. both earn about the same amount, then women are less likely to make the decision alone (in the baseline model). If they disagree about who earns the most, women are more likely to make the decision alone. Thus, disagreement about who earns the most may be an indicator of separate spheres None of these el it is not % share of couples wealth at which she is least likely to make the decision alone is 56 % ; however, it is not statistically significant. What does such imply for household bargaining power? If women are perceiving that their share does influence decision making (even if they do not consciously acknowledge this) but men do not, do they really have the bargaining power given that bargaining power depends on the rel ative positions of men and women?

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106 Husband and Wife Agree that She Makes the Decision A utonomously Work decision Table 3 15 presents the results for the decision making about whether to work when both spouses agree that she makes the dec ision autonomously most are statistically significant variables. As women get older the couple is more likely to agree that she makes the decision alone Couples are less likely to agree about he r autonomous decision making in rural households than in urban households. In households in which both partners are indigenous couples are more likely to agree that the wife makes the decision autonomously than in households in which both partners are mes tizo Also, couples which agree that the woman earns the most are more likely to agree that she makes the decision autonomously. Models II and III have similar results. Model II adds the variables about real estate ownership, none of which are statistica lly significant. Model III adds the variables about increases, the couple is less likely to agree that she makes the d ecision autonomously up until the woman owns 56 % of t they both report that she makes an autonomous decision begins to increase again. Spending decision The results for the couples agreeing that women make the spending decision autonomously are reported in Table 3 ethnicity, and employment are statistically significant variables. Couples are more likely to report that the wife make s the decision autonomously the older the woman is. Couples in rural households are less lik ely than those in urban households to report that the wife makes an autonomous decision. Also, c ouples in coastal regions are more likely than those in the highlands to report that the wife makes an autonomous decision.

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107 Couples of other ethnicities are le ss likely than mestizo couples to report that the wife makes the decision autonomously. And, c ouples in households in which the wife only, both partners, or neither partner is employed are less likely to report that the wife makes an autonomous decision than couples in households in which only the husband works. Models II and III find similar resu lts as those in Model I. In Model II we find that couples in households in which only the wife owns real estate are more likely to report that the wife makes autonomous decisions than couples in households in which only the husband works. Model III prese Comparison of the Work and Spending Decision Models Agree Autonomous Comparing T ables 3 15 and 3 16 we find a few similarities and several diffe decisions autonomously. Also, couples living in rural areas are less likely to agree t hat the wife makes an autonomous decision than couples living in urban areas. Although couples on the coast are more likely than those in the highlands to agree that the wife makes the decision alone, there is no difference between coastal and highland couples in terms of the work decision. When both partners are indigenous the wif e is more likely to make an autonomous decision about work (and her husband agreeing) than when both partners are mestizo; but, there is no difference in terms of the spending decision. However, for the spending decision, couples in which both partners ar e classified as other ethnicity are less likely to agree that the wife makes an autonomous decision about spending than mestizos but there is no difference for the work decision. Couples in which the woman earns the most are more likely to report the

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108 wife making an autonomous decision about work than couples in which the husband earns the most. The earnings variables are not significant for the spending decision. However, the spending decision models include employment variables, which are all significant Finally, the asset ownership and wealth variables are different for the two decisions. Couples in which only the wife owns real estate are more likely to report an autonomous decision for spending than when the husband only owns real estate but there i decision. Reporting Work decision Comparing T ables 3 11 and 3 15 we can identify the differences between women reporting autonomous decision making with regards to the work age, rura l, woman earns the most, and female share of wealth are significant variables in both models. So, older women are both more likely to report that they make the decision alone and that their husbands agree that they do so. Also, women in rural households ar e less likely to report that they make the decision alone and that their husbands also report this. Women in households in which the woman earns the most are both more likely to make the decision alone and for their husbands to agree that they do so. As wo make the decision alone and for husband to agree. The difference with this variable is the estimated share at which the wife is least likely to make the decision alone. In the s model we found that women are least likely to make the decision alone when

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109 she owns about 38 % makes the decision alone are least likely to occur when the wife owns 56 % of the This indicates that women must own more of the wealth for their husbands to recognize and agree that their wives are making the decision autonomously. Comparing T ables 3 13 and 3 decision making and couples agreeing about her autonomous decision making in regards to the decision about whether to work. W e again find that as women get older they are more likely to make the decision autonomously and for the husband to agree. Also, women in ru ral households are less likely than those in urban households to make the decision alone and for their husbands to agree. Women in households in which the woman earns the most are more likely than women in households in which the man earns the most to make the decision alone and for her % likely to make the decision alone whereas in the agreem ent model, women owning model is real estate ownership significant. Although both being indigenous is positive and significant in the agreement model it is not statistical couples are more likely to agree about the way decisions are made than are mestizo couples. This is explored more below in the results about egalitarian decision making

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110 Spending deci sion We compare T ables 3 12 and 3 16 to identify the differences decision making and couples agreement decision making coast, both other ethnicity, wif e only employed, both employed, and wife only owns real estate are statistically significant variables and have the same sign in both models. The following variables are different between the two models: consensual union, wife has extended family members in household, neither being employed, earning the wealth. Although women in consensual unions are more likely to report that they make the decision autonomously than married w omen, there is no difference in terms of couples agreeing about the wife making the decision autonomously. Women in likely to report making the decision autonomously; how ever, in these same households couples are less likely to agree that she makes the decision autonomously (although the variable is not significant in the agreement model). Women do not perceive that they are more likely to make the decision autonomously wh en neither work (as compared to when only the husband works) but for agreement neither working is significantly different than the husband only working. Both owning assets is associated with a lower likelihood of women making the decision alone but not st atistically different for agreement that she makes it alone. Also, while women reported that they were less was not significant for the agreement model.

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111 We can also decision making to couples agreeing that the wife makes the decision autonomously by looking at Tables 3 14 and 3 16. These two models are more alike than the models of agreement and elves. The only difference b etween the results reported in T ables 3 14 and 3 16 is with regards to wife having extended family members present. significant, it is not signi ficant in the agreement model (but it does have the same sign). Egalitarian Decision making The results for the models of egalitarian decision making ( for the decision to work (or not) and for the decision about spending the income one earns or receives ) are reported in T ables 3 17 and 3 18 21 The classification of egalitarian decision making is quite restrictive in that it requires both spouses/partners to report that they each make the decision jointly and that their spouse concurs that they do so (bot h symmetry and agreement). Work decision In Table 3 17 rural, coast, both spouses being indigenous and both spouses earning the same are statistically significant predictors of the likelihood of making the decision to work in an egalitarian that this variable is also part of age difference, the impact is nearly zero. 22 Rural households h ave 1.4 times the odds (exp(0.31 9)) of making the decision to work in an 21 We also ran the model with the dependent variable being only the wife making the decision jointly (when her husband was in agreement) and got similar results as those presented for the egalitarian decision making model even though the sample size is considerably larger with this less restrictive condition. 22 Remember that a one must use the formula from the first derivatives:

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112 egalitarian fashion as their urban counterparts. Couples in coastal regions have 1.2 times the odds of making an egalitarian decision than do couples in the sierra. Also, households in which both partners earn the same ha ve 1.7 times the odds of making an egalitarian decision as do households in which the husband earns the most. Model II adds variables for whether the wife, husband, or both own real estate. In this model we find similar results as in Model I. Furthermo re, we find that couples in which only the wife is an owner of real estate are less likely to make the decision to work in an egalitarian fashion than in couples in which neither partner owns real estate As expected, this is opposite of what we found in t decision making Again Model III has similar results as that of Model I. It considers the intra egalitaria n decision up to a share of 0.41 ; it then declines This means that the greatest likelihood of egalitarian decision making for the decision to work is when wo men own 41 Spending decision Table 3 18 reports the results for the model regarding the wn income. 23 Note that the pseudo R square is higher for the spending model (at 0.16) than the work model. In model I, we find similar results as with the decision to work with a few additional variables becoming significant. The 23 It should be noted that there is a potential endogeneity problem with models II and III since deciding wife. We reviewed potential instrumental variables, argument could be made that our dependent variable is defined so restrictively in terms of both symm etry and agreement in the decision to spend that such a level of agreement would be unlikely to

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113 correlated with the likelihood of an egalitarian decision making older women are more likely to make the decision alone (as indicated by the previous regression results) or that there is more disagreement between the spouses about how the decision is made. Rural couples have 1.6 times the odds of making the decision in an egalitarian fashion as urban women. When the couple lives on the Coast, the wife is less likely to mak e the decisi on jointly with her husband (0.6 times the odds) than those living in the highlands. In Model I couples in consensual unions are less likely than married couples to make an egalitarian decision; however, this variable is not significant in Mod els II or III. In households in which the wife has extended family members the couple is less likely to make an egalitarian decision. Also, w hen both partners are indigenous, the couple is less likely to make an egalitarian decision. However, if only the wife is employed or both spouses are employed, then they are more likely to make egalitarian decisions about spending than if only the husband is employed. If only the wife is employed, they have 2.4 times the odds of making egalitarian decisions as when only the husband is employed. If they are both employed, then they have 5.9 times the odds. Also, if the couple earns about the same amount, then t hey have 2.5 times the odds of making egalitarian spending decisions as when the husband makes the most in come. Model II shows the impact of asset ownership on the likelihood of egalitarian spending decisions. In this case we have the same variables significant as before with similar magnitudes (in terms of the odds ratio). We also find that when only the wi fe owns real estate they are less likely to make egalitarian spending decisions (with 0.56

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114 times the odds) as compared to when the wife does not own real estate but this variable is not statistically significant at the 0.10 level In these cases it is lik ely that the wife makes the decision alone or that they disagree as indicated in the previous regression results. If both spouses own real estate (either jointly or individually) then there is a greater likelihood that the couple makes an egalitarian decis ion ( 1.5 times the odds) compared to when neither owns real estate wealth is associated with egalitarian decision making about spendi ng Again, the same variables are sig nificant as before with similar magnitudes. The likelihood of egalitarian decision 48 % at which point the likelihood begins to decrease. Comparison of the Work and Spending Decision Models Egalitarian Comparing Tables 3 17 and 3 18 we can identify differences in terms of egalitarian decision making for the work and spending decisions. The two decisions are similar in terms of the following share of wealth. They are different in several key ways. First, for the spending decision women having extended family members in the household is associated with couples being less likely tha n those without the wife having extended family members in the household to make an egalitarian decision; however this variable is not statistically significant for the work decision. In terms of ethnicity, couples in which both partners are indigenous are more likely to make the work decision in an egalitarian fashion but less likely to make the spending decision in an egalitarian fashion. This seems to support the ethnographic research that suggests indigenous households in the highlands of Ecuador are re latively egalitarian and that women have traditionally managed the

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115 household budget (Hamilton 1998). Also, when both partners are classified as other ethnicity, they are more likely than mestizo couples to make an egalitarian decision with regards to spen ding but there is no difference between mestizo and other ethnicity couples in terms of the work decision. Furthermore, couples in which the wife only owns real estate are less likely than couples in which neither own real estate to make an egalitarian de cision in regards to the work decision but there is no statistically significant difference in terms of the spending decision. Whereas both owning real estate is a statistically significant predictor of an egalitarian spending decision (as compared to neit her owning), it is not statistically significant for the work decision. similar pattern for both egalitarian work and spending decisions; it increases and then decreases at a point somewhat near equal wealth leve ls. For the work decision, couples are most likely to make an egalitarian decision when the wife owns about 41% of couple wealth; whereas for an egalitarian spending decision the greatest likelihood is when the wife owns 48% of couple wealth. Discussion an d Concluding Thoug h ts Similar to the literature discussed above, the results indicate different predictors of household decision making processes depending on the decision, whether the focus is on women making the decision autonomously or the spouses makin g the decision in an responses about their wives. There were some consistently different results when comparing models of autonomous decision making with egalitarian decisio n making positively correlated to her autonomous decision making (in all specifications of

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116 autonomous) it is negatively correlated to egalitarian decision making This implies that as women get older they are more likely to make deci sions alone and less likely to make egalitarian decisions. In rural households women are less likely to make autonomous decisions and couples are more likely to make egalitarian decisions. I n households in which only women own real estate it is more likely that women make autonomous decisions and less likely that the couple makes egalitarian decision making Also, the female share of household wealth is negatively correlated with decision making to a point where the wife owns between 33 % and 68 % decision making to a point where the wife owns between 41 % and 48 % For the work decision, a woman earning the most is correlated with a greater likelihood of her making an autonomous decision (as compared to when the man earns the most). However, egalitarian decisions are correlated with the couple earning about the same. For the spending decision, women on the coast are more likely to make an autonomous decision, and couples are less likely to make an egalitarian decision. Also, autonomous decision and couples are more likely to make an egalitarian decision. decision in terms of both egalitarian and agreement that women make the decision autonomous decision making This may indicate tha t indigenous couples are more likely

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117 to agree about how the decision is made (either by the woman alone or by the couple jointly). headed households is strongly associated with how couples make decision s We found that in households where only the wife owns real estate, she is more likely to make autonomous decisions regarding whether to work and how to spend her own income. Moreover, households where both husband and wife own re al estate, either jointly or individually are positively and significantly associated with the likelihood of egalitarian decision making among couples Furthermore, the female share of couple wealth was positively related to egalitarian decision making an d negatively correlated to autonomous decision making by women, indicating that the more wealth equality in the household, the more likely decisions are to be made in an egalitarian fashion, while inequality that favors women is more likely to lead to her making autonomous decisions. The level of earnings of each spouse, specifically, where this is roughly equal, and employment in the case of the spending decision, are also important indicators of egalitarian decision making. A lthough this study suffers from limitations similar to other studies that look at household decision making especially that of potential endogeneity, we have demonstrated the usefulness of approaching household decision making from a gender they themselves as well as their spouses make decisions. Also, we have contributed t o the previous literature in several ways. First, we found that the intra household distribution of assets and wealth are

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118 important correlates of both autonomous and egalitarian decision making Future work shoul d consider including measures of assets and wealth as well as income when decision making were compared. As suggested by Sen ( 1990 ) and Ka tz ( 1991 ), men and women have different perceptions about how much their contributions (herein measured as their assets and wealth) impact bargaining power. We found that men and women do perceive different levels of autonomy depending on who owns real est ciated autonomous decisions with only the wife owning real estate (compared to neither owning real estate); the real estate ownership as contributing to her autonomous decision making (except in the case of the spending decision, where it is slightly significant at the 0.1 level). Also, women associated both owning real estate to a lower likelihood of autonomous power in terms of autonomous decision making Third, we also looked at what explains husbands and wives agreement about her autonomous decision making which is described in detail above. In terms of the asset and wealth variables, only the wife owning real estate is positively associated with the couple agreeing th at she makes an autonomous decision regarding spending her own money; however there is no such relationship for the work decision. For the work decision, the female share of couple wealth follows a similar pattern, in that the

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1 19 omous decision is higher at low share s and decreases until reaching 56 is not significant for the spending decision. s decision making decision making but is at least weakly associated with egalitarian decision making On the other hand, both owning real estate is weakly related to a greater likelihood of egalitarian decision making wealth for autonomous and egalitarian decision making ; these results sug gest that couples are most likely to make egalitarian decisions when wealth is distributed fairly equally, whereas women are more likely to make autonomous decisions when the wealth is not distributed equally, especially if she owns most of the wealth. Ega litarian decisions were defined in a restrictive manner that considered both s ymmetry and agreement; nonetheless, they capture well the content of egalitarian gender relations within dual headed households. In the context of Ecuador, both spouses participa decisions is likely to indicate fairly equal bargaining power and could thus be empowering for women, since they are able to negotiate as equals with their husbands not only in terms of the ir own employment and spending decisions but also in terms of

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120 Table 3 1 Decision Her alone Spouse alone Couple jointly Other No response Total To visit family 10.1 10.2 79 .0 0.2 0.4 100% When a child needs to see a physician 28.6 5.4 61.3 0.7 4.1 100% How to discipline children 19.2 7.6 68.1 0.7 4.4 100% Use of contraception 16.0 5.7 69.6 1.3 7.4 100% How to spend household income 12.0 19.2 68.6 0.1 0.2 100% Whether to work or study 23.7 21.6 53.3 0.2 1.2 100% Source: ENDEMAIN 2004 N = 6256 married women or those in consensual unions, age 15 to 49.

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121 Table 3 2 How each spouse reports making their respective decision, Ecuador 2010 a) Whether or not to work b) If earn or receive income, how to spend c) To seek health care for themselves d) Whether or not to use contraception Man % Woman % Man % Woman % Man % Woman % Man % Wom an % Alone 926 52 565 32 330 19 520 29 700 39 755 43 238 13 422 24 Part alone and part jointly 264 15 182 10 Joint 840 47 1120 63 1154 65 941 53 1048 59 987 56 1455 82 1337 75 Asks permission 8 0.5 55 3.1 10 0.6 22 1.2 16 0.9 8 0.5 Someone else makes decision 1 17 1 10 0.6 6 0.3 17 1 11 0.6 66 3.7 8 0.5 Not applicable 1 19 1.1 18 1 127 7.2 Total 1776 100 1776 100 1776 10 0 1776 10 0 1775 100 1775 100 1775 100 1775 100 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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122 Table 3 decision making as reported by her and her h usband, Ecuador 2010 Decision Wife Reports Autonomous % Husband Reports that Wife Makes Autonomous Decision % Spouses Agree that Wife Makes Autonomous Decision % To work (n = 1,757) 565 32 437 25 236 13 To spend (n = 1,649) 702 40 404 25 296 18 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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123 Table 3 4 Symmetry in decision making Whether both members of the couple make the decision regarding themselves in a similar fashion, Ecuador 2010 a) Whether or not to work b) If earn or receive income, how to spend c) To seek health care for themselves d) Whether or not use contraception Each alone 386 21.7 159 9 .0 408 23 .0 146 8.2 Each partly alone & partly jointly 96 5.4 Each makes jointly 627 35.3 736 41.4 699 39.4 1221 68.8 Each asks permission or someone else 1 0.1 4 0.2 1 0.1 1 0.1 Differ 762 42.9 781 44 .0 667 37.6 407 22.9 Total 1776 100 .0 1776 100 .0 1775 100.0 1775 100 .0 Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 3 5 The distribution of joint decision making, Ecuador 2010 Decision Couple only % Couple plus someone else % With someone besides partner* % Total To work 622 99.2 3 0.4 2 0.3 627 To spend 723 98.2 10 1.4 3 0.4 736 To access health services 674 96.4 16 2.3 9 1.3 699 To use contraception 1218 99.8 3 0.2 1221 Source: UF FLACSO 2010 Ecuador Household Asset Survey *In the majority of these cases only one spouse reports making the decision jointly with someone else while the partner reports making the decision jointly with only the spouse.

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124 Table 3 6 Degree of agreement by spouses on how partner makes the decision, Ecuador 2010 a) Decision on whether or not to work b) perception of decision % perception of decision % perception of decision % perception of decision % Agree that spouse makes decision alone 236 13.2 506 28.5 171 9.6 149 8.4 Agree partly alone & partly jointly 62 3.5 117 6.6 Agree that joint decision 893 50.3 648 36.5 423 23.8 889 50 Agree that asks permission 14 0.8 Agree that someone else makes decision 3 0.2 3 0.2 Agree that N/A 103 5.8 14 0.8 Disagree 630 35.5 622 35 .0 1017 57.3 604 34 .0 Total 1776 100 .0 1776 100 .0 1776 100 .0 1776 100 .0 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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125 Table 3 7 Symmetry and agreement: egalitarian decision making, Ecuador 2010 Decision Each partner says joint* (symmetry) % Partners agree that the other makes decision jointly (agreement) % Partners disagree that the other makes decision jointly % To work 625 100 488 77.9 138 21.9 To spend 733 100 309 42.2 424 57.8 Source: UF FLACSO 2010 Ecuador Household Asset Survey Note: *May include others in addition to spouse; see Table 3 4. Table 3 8. Descriptive statistics of the binary dependent variables, Ecuador 2010 Decision to work Decision to spend Model -Dependent Variable Sample size (n) % of sample Sample size (n) % of sample Autonomous -Her reporting 1757 32.2% 1649 42.6 % Autonomous -His reporting (about her) 1757 25.2% 1649 24.5 % Husband and wife agree that she makes an autonomous decision 1757 13.4% 1649 18.0% Egalitarian -Both make joint decisions and report spouse does also 1756 27.8% 1635 18.9% Source: UF FLACSO 2010 Ecuador Household Asset Survey

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126 Table 3 9. Descriptive statistics for categorical variables, composition (percent) of sample of couples, Ecuador 2010 (n = 1,776) Percent of sample Rural Household 35.1% Coastal Household 52.9% Couple in consensual union 35.3% Wife has extended family members in household 4.5% Husband has extended family members in household 4.1% Ethnicity Both spouses mestizo/white 86.1% Both spouses indigenous 4.9% Both spouses another ethnicity 5.6% Spouses are different ethnicities 3.4% Total 100.0% Previous relationship Wife only 6.5% Husband only 9.3% Both 7.6% Neither 76.6% Total 100.0% Who is employed? Wife only 4.2% Husband only 44.9% Both 46.6% Neither 4.4% Total 100.0% Who earns the most? Wife 6.6% Husband 73.7% They earn the same 9.6% They disagree 10.0% Total 100.0% Real Estate Ownership Wife only owns real estate 8.0% Husband only owns real estate 12.1% Both own real estate 45.9% Neither own real estate 34.0% Total 100.0% Source: UF FLACSO 2010 Ecuador Household Asset Survey

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127 Table 3 10. Descriptive statistics for continuous variables of sample of couples, Ecuador 2010 n M inimum Maximum Mean Std. dev. Median Wife's age 1 ,776 1 8 90 41.3 14.20 39 Husband's age 1,776 18 93 45.33 15.2 8 43 Age Difference 1,776 23 42 4.0 6 6.30 3 Wife's years of schooling 1,776 0 20 8.0 6 4.58 7 Husband's years of schooling 1,776 0 20 8.4 4 4.48 7 Difference in years of schooling 1,776 11 14 0.38 3.50 0 of USD) 1,776 0.009 619.4 23.3 0 43.3 8.2 W ife's share of couple's wealth 1,776 0 1 0.462 0.246 0.497 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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128 Table 3 11. Logistic regression results for models of autonomous decision making for the decision to work; Ecuador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 1.640 *** 0.307 1.639 *** 0.308 1.389 *** 0.346 Woman's age 0.021 *** 0.005 0.023 *** 0.005 0.021 *** 0.005 Age difference (man's age woman's age) 0.002 0.009 0.001 0.009 0.002 0.009 Woman's years of schooling 0.006 0.016 0.004 0.016 0.007 0.016 Schooling difference (man woman) 0.012 0.017 0.014 0.017 0.013 0.017 Rural (Urban) 0.512 *** 0.122 0.440 *** 0.124 0.481 *** 0.124 Coast (Highlands) 0.185 0.117 0.203 0.119 0.225 0.119 Consensual Union (Married) 0.156 0.139 0.078 0.140 0.079 0.141 Couple's wealth (in thousands of USD) 0.001 0.001 0.002 0.001 0.001 0.001 Wife has extended family in hh 0.043 0.256 0.131 0.265 0.219 0.270 Husband has extended family in hh 0.026 0.260 0.014 0.260 0.003 0.263 Ethnicity (Both mestizo/blanco) Both indigenous 0.029 0.264 0.020 0.261 0.020 0.267 Both other ethnicity 0.045 0.234 0.067 0.236 0.037 0.238 Different ethnicities 0.269 0.289 0.185 0.294 0.227 0.296 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.322 0.210 0.274 0.211 0.262 0.211 Man only has been in a previous relationship 0.162 0.186 0.152 0.187 0.169 0.188 Both have been in a previous relationship 0.391 0.209 0.310 0.208 0.261 0.214 Who earns more (Man earns the most) Woman earns the most 0.692 *** 0.205 0.685 *** 0.206 0.708 *** 0.206

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129 Table 3 11. Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Earn the same 0.027 0.184 0.017 0.186 0.010 0.187 Disagree about earnings 0.480 *** 0.166 0.520 *** 0.168 0.507 *** 0.166 Assets & Wealth (Neither own real estate) Wife only owns real estate 0.627 *** 0.196 Husband only owns real estate 0.064 0.187 Both own real estate 0.368 ** 0.145 Woman's share of wealth 2.414 *** 0.630 Woman's share of wealth squared 3.175 *** 0.619 Number of cases (n ) 1757 1757 1757 Likelihood ratio chi square (df) 82.37 (19)*** 107.06 (22)*** 114.10 (21)*** Pseudo R 2 0.0392 0.051 0.055 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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130 Table 3 12. Logistic regression results for models of autonomous decision making for the decision to spend; Ecuador, 2010 (Baseline) Model I Model II Model III Coeff. Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 1.108 *** 0.306 1.116 *** 0.307 1.049 *** 0.336 Woman's age 0.013 *** 0.005 0.014 *** 0.005 0.013 *** 0.005 Age difference (man's age woman's age) 0.004 0.009 0.005 0.009 0.004 0.009 Woman's years of schooling 0.005 0.015 0.006 0.015 0.004 0.015 Schooling difference (man woman) 0.007 0.017 0.008 0.017 0.006 0.017 Rural (Urban) 0.737 *** 0.118 0.689 *** 0.121 0.720 *** 0.119 Coast (Highlands) 0.320 *** 0.116 0.311 *** 0.117 0.304 *** 0.117 Consensual Union (Married) 0.254 0.135 0.202 0.136 0.222 0.136 Couple's wealth (in thousands of USD) 0.001 0.001 0.001 0.001 0.001 0.001 Wife has extended family in hh 0.665 *** 0.255 0.624 ** 0.255 0.578 ** 0.255 Husband has extended family in hh 0.031 0.267 0.034 0.269 0.048 0.267 Ethnicity (Both mestizo/blanco) Both indigenous 0.056 0.247 0.055 0.246 0.048 0.249 Both other ethnicity 0.409 0.235 0.426 0.234 0.403 0.234 Different ethnicities 0.222 0.286 0.176 0.292 0.203 0.290 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.117 0.217 0.076 0.217 0.091 0.217 Man only has been in a previous relationship 0.077 0.193 0.065 0.191 0.088 0.193 Both have been in a previous relationship 0.158 0.213 0.103 0.213 0.105 0.216 Who is employed? (Husband only)

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131 Table 3 12 Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Wife only 0.534 0.318 0.540 0.321 0.483 0.321 Both 0.494 *** 0.121 0.498 *** 0.122 0.482 *** 0.122 Neither 0.363 0.291 0.350 0.291 0.352 0.292 Who earns more (Man earns the most) Woman earns the most 0.154 0.248 0.142 0.249 0.171 0.249 Earn the same 0.320 0.185 0.285 0.186 0.316 0.186 Disagree about earnings 0.317 0.175 0.349 ** 0.176 0.329 0.174 Assets & Wealth (Neither own real estate) Wife only owns real estate 0.430 ** 0.209 Husband only owns real estate 0.122 0.182 Both own real estate 0.234 0.141 Woman's share of wealth 0.847 ** 0.617 Woman's share of wealth squared 1.277 *** 0.616 Number of cases ( n ) 1649 1649 1649 Likelihood ratio chi square (df) 117.96 (22)*** 128.34 (25)*** 123.28 (24)*** Pseudo R 2 0.056 0.062 0.060 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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132 Table 3 13. Logistic regression results for models of women's autonomous decision making for the decision to work as perceived by husbands; Ecu ador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 1.836 *** 0.320 1.811 *** 0.320 1.497 *** 0.350 Woman's age 0.015 *** 0.005 0.016 *** 0.005 0.015 *** 0.005 Age difference (man's age woman's age) 0.011 0.010 0.011 0.010 0.010 0.010 Woman's years of schooling 0.012 0.017 0.010 0.017 0.013 0.017 Schooling difference (man woman) 0.011 0.018 0.014 0.018 0.012 0.018 Rural (Urban) 0.228 0.129 0.195 0.132 0.229 0.130 Coast (Highlands) 0.180 0.128 0.175 0.129 0.180 0.128 Consensual Union (Married) 0.107 0.151 0.062 0.152 0.094 0.151 Couple's wealth (in thousands of USD) 0.000 0.001 0.001 0.001 0.000 0.001 Wife has extended family in hh 0.027 0.274 0.031 0.275 0.070 0.276 Husband has extended family in hh 0.048 0.288 0.051 0.291 0.066 0.288 Ethnicity (Both mestizo/blanco) Both indigenous 0.350 0.258 0.342 0.260 0.328 0.260 Both other ethnicity 0.253 0.242 0.229 0.243 0.239 0.245 Different ethnicities 0.420 0.302 0.400 0.301 0.432 0.301 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.096 0.235 0.073 0.238 0.077 0.236 Man only has been in a previous relationship 0.005 0.203 0.023 0.202 0.017 0.202 Both have been in a previous relationship 0.072 0.229 0.049 0.229 0.035 0.232 Who earns more (Man earns the most) Woman earns the most 0.419 0.214 0.418 0.217 0.449 ** 0.216 Earn the same 0.225 0.185 0.260 0.186 0.269 0.185

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133 Table 3 13 Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Disagree about earnings 0.055 0.189 0.022 0.189 0.028 0.189 Assets & Wealth (Neither own real estate) Wife only owns real estate 0.003 0.223 Husband only owns real estate 0.214 0.191 Both own real estate 0.221 0.153 Woman's share of wealth 1.353 ** 0.648 Woman's share of wealth squared 0.994 0.660 Number of cases ( n ) 1757 1757 1757 Likelihood ratio chi square (df) 29.59 (19)* 34.89 (22)** 34.42 (21)** Pseudo R 2 0.015 0.018 0.018 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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134 Table 3 14. Logistic regression results for models of autonomous decision making for the decision to spend as reported by men; Ecuador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 3.385 *** 0.397 3.427 *** 0.400 3.303 *** 0.425 Woman's age 0.018 *** 0.006 0.019 *** 0.006 0.018 *** 0.006 Age difference (man's age woman's age) 0.004 0.010 0.005 0.010 0.004 0.010 Woman's years of schooling 0.009 0.018 0.009 0.018 0.009 0.018 Schooling difference (man woman) 0.029 0.020 0.029 0.020 0.029 0.020 Rural (Urban) 0.561 *** 0.149 0.525 *** 0.151 0.556 *** 0.149 Coast (Highlands) 0.458 *** 0.139 0.444 *** 0.140 0.459 *** 0.140 Consensual Union (Married) 0.177 0.160 0.154 0.162 0.171 0.161 Couple's wealth (in thousands of USD) 0.000 0.001 0.000 0.001 0.000 0.001 Wife has extended family in hh 0.674 ** 0.313 0.712 ** 0.318 0.668 ** 0.317 Husband has extended family in hh 0.291 0.326 0.300 0.326 0.289 0.326 Ethnicity (Both mestizo/blanco) Both indigenous 0.212 0.320 0.208 0.323 0.217 0.320 Both other ethnicity 0.876 *** 0.307 0.891 *** 0.306 0.875 *** 0.307 Different ethnicities 0.435 0.309 0.390 0.315 0.433 0.309 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.175 0.259 0.196 0.258 0.177 0.258 Man only has been in a previous relationship 0.009 0.223 0.002 0.222 0.013 0.224 Both have been in a previous relationship 0.044 0.234 0.004 0.233 0.033 0.236 Who is employed? (Husband only) Wife only 1.526 *** 0.350 1.523 *** 0.354 1.528 *** 0.351

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135 Table 3 14 Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Both 1.982 *** 0.173 1.986 *** 0.175 1.986 *** 0.173 Neither 1.019 *** 0.344 1.015 *** 0.342 1.019 *** 0.344 Who earns more (Man earns the most) Woman earns the most 0.231 0.249 0.228 0.247 0.235 0.249 Earn the same 0.128 0.208 0.105 0.209 0.120 0.208 Disagree about earnings 0.154 0.193 0.170 0.194 0.160 0.193 Assets & Wealth (Neither own real estate) Wife only owns asset(s) 0.388 0.227 Husband only owns asset(s) 0.056 0.221 Both own asset(s) 0.114 0.170 Woman's share of wealth 0.398 0.751 Woman's share of wealth squared 0.337 0.741 Number of cases ( n ) 1649 1649 1649 Likelihood ratio chi square (df) 196.94 (22)*** 197.08 (25)*** 197.84 (24)*** Pseudo R 2 0.143 0.146 0.144 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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136 Table 3 15. Logistic regression results for models of women reporting autonomous decision making for the decision to work and men agree; Ecuador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Coeff. Robust Std. Err. Intercept 3.015 *** 0.402 2.999 *** 0.403 2.544 *** 0.448 Woman's age 0.024 *** 0.006 0.026 *** 0.006 0.025 *** 0.006 Age difference (man's age woman's age) 0.004 0.012 0.005 0.012 0.003 0.012 Woman's years of schooling 0.011 0.022 0.008 0.022 0.012 0.022 Schooling difference (man woman) 0.013 0.024 0.016 0.024 0.015 0.025 Rural (Urban) 0.609 *** 0.175 0.556 *** 0.177 0.600 *** 0.176 Coast (Highlands) 0.208 0.163 0.213 0.164 0.215 0.164 Consensual Union (Married) 0.312 0.193 0.240 0.194 0.277 0.192 Couple's wealth (in thousands of USD) 0.000 0.002 0.001 0.002 0.000 0.002 Wife has extended family in hh 0.088 0.354 0.098 0.357 0.071 0.360 Husband has extended family in hh 0.049 0.362 0.068 0.364 0.041 0.362 Ethnicity (Both mestizo/blanco) Both indigenous 0.706 ** 0.320 0.703 ** 0.322 0.685 ** 0.325 Both other ethnicity 0.002 0.328 0.043 0.329 0.020 0.333 Different ethnicities 0.264 0.385 0.215 0.388 0.262 0.388 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.198 0.295 0.161 0.298 0.168 0.295 Man only has been in a previous relationship 0.245 0.245 0.215 0.244 0.220 0.245 Both have been in a previous relationship 0.167 0.282 0.121 0.281 0.090 0.287 Who earns more (Man earns the most) Woman earns the most 0.772 *** 0.250 0.764 *** 0.255 0.807 *** 0.253

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137 Table 3 15 Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Earn the same 0.178 0.241 0.236 0.243 0.240 0.242 Disagree about earnings 0.146 0.228 0.194 0.228 0.187 0.228 Assets & Wealth (Neither own real estate) Wife only owns real estate 0.247 0.266 Husband only owns real estate 0.309 0.236 Both own real estate 0.313 0.195 Woman's share of wealth 2.275 *** 0.804 Woman's share of wealth squared 2.031 ** 0.818 Number of cases ( n ) 1757 1757 1757 Likelihood ratio chi square (df) 55.33 (19)*** 63.12 (22)*** 63.81 (21)*** Pseudo R 2 0.038 0.045 0.044 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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138 Table 3 16. Logistic regression results for models of women reporting autonomous decision making for the decision to spend and men agree; Ecuador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 4.098 *** 0.455 4.163 *** 0.463 4.071 *** 0.487 Woman's age 0.019 *** 0.006 0.021 *** 0.007 0.020 *** 0.006 Age difference (man's age woman's age) 0.013 0.011 0.015 0.011 0.014 0.011 Woman's years of schooling 0.012 0.020 0.012 0.020 0.012 0.020 Schooling difference (man woman) 0.021 0.023 0.021 0.022 0.021 0.023 Rural (Urban) 0.728 *** 0.175 0.684 *** 0.176 0.716 *** 0.176 Coast (Highlands) 0.585 *** 0.154 0.565 *** 0.154 0.578 *** 0.155 Consensual Union (Married) 0.156 0.180 0.129 0.182 0.141 0.181 Couple's wealth (in thousands of USD) 0.001 0.002 0.001 0.002 0.001 0.002 Wife has extended family in hh 0.493 0.335 0.527 0.340 0.524 0.337 Husband has extended family in hh 0.387 0.346 0.405 0.345 0.395 0.346 Ethnicity (Both mestizo/blanco) Both indigenous 0.263 0.384 0.259 0.387 0.260 0.385 Both other ethnicity 0.555 0.325 0.581 0.323 0.551 0.324 Different ethnicities 0.149 0.369 0.082 0.376 0.138 0.370 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.046 0.276 0.074 0.276 0.053 0.275 Man only has been in a previous relationship 0.128 0.243 0.118 0.240 0.123 0.244 Both have been in a previous relationship 0.206 0.257 0.144 0.255 0.179 0.259 Who is employed? (Husband only) Wife only 1.961 *** 0.379 1.961 *** 0.385 1.938 *** 0.379

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139 Table 3 16 Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Both 2.093 *** 0.209 2.098 *** 0.210 2.089 *** 0.208 Neither 1.244 *** 0.386 1.246 *** 0.384 1.241 *** 0.385 Who earns more (Man earns the most) Woman earns the most 0.147 0.264 0.144 0.264 0.155 0.265 Earn the same 0.188 0.233 0.152 0.234 0.186 0.234 Disagree about earnings 0.254 0.202 0.279 0.203 0.258 0.202 Assets & Wealth (Neither own real estate) Wife only owns real estate 0.472 0.244 Husband only owns real estate 0.143 0.245 Both own real estate 0.137 0.187 Woman's share of wealth 0.411 0.847 Woman's share of wealth squared 0.576 0.820 Number of cases ( n ) 1649 1649 1649 Likelihood ratio chi square (df) 173.33 (22)*** 173.83 (25)*** 173.39 (24)*** Pseudo R 2 0.152 0.156 0.152 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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140 Table 3 17. Logistic regression results for models of egalitarian decision making for the decision to work; Ecuador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 0.906 *** 0.311 0.911 *** 0.312 1.147 *** 0.342 Woman's age 0.009 0.005 0.011 ** 0.005 0.009 0.005 Age difference (man's age woman's age) 0.011 0.009 0.012 0.009 0.011 0.009 Woman's years of schooling 0.025 0.016 0.026 0.016 0.025 0.016 Schooling difference (man woman) 0.020 0.018 0.021 0.018 0.020 0.018 Rural (Urban) 0.319 *** 0.123 0.267 ** 0.126 0.299 ** 0.123 Coast (Highlands) 0.206 0.120 0.210 0.122 0.223 0.121 Consensual Union (Married) 0.190 0.138 0.144 0.140 0.147 0.139 Couple's wealth (in thousands of USD) 0.001 0.001 0.002 0.001 0.001 0.001 Wife has extended family in hh 0.213 0.274 0.155 0.280 0.124 0.280 Husband has extended family in hh 0.071 0.268 0.068 0.269 0.073 0.269 Ethnicity (Both mestizo/blanco) Both indigenous 0.494 ** 0.249 0.489 ** 0.249 0.500 ** 0.250 Both other ethnicity 0.053 0.241 0.055 0.242 0.055 0.242 Different ethnicities 0.178 0.329 0.119 0.335 0.146 0.333 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.191 0.235 0.162 0.236 0.147 0.237 Man only has been in a previous relationship 0.239 0.207 0.232 0.207 0.243 0.206 Both have been in a previous relationship 0.269 0.238 0.213 0.238 0.181 0.240 Who earns more (Man earns the most) Woman earns the most 0.098 0.225 0.110 0.226 0.091 0.225 Earn the same 0.522 *** 0.176 0.500 *** 0.177 0.503 *** 0.177 Disagree about earnings 0.116 0.194 0.135 0.195 0.128 0.194

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141 Table 3 17. Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Assets & Wealth (Neither own real estate) Wife only owns real estate 0.432 0.247 Husband only owns real estate 0.003 0.193 Both own real estate 0.233 0.145 Woman's share of wealth 1.754 *** 0.681 Woman's share of wealth squared 2.162 *** 0.692 Number of cases ( n ) 1756 1756 1756 Likelihood ratio chi square (df) 36.69 (19)*** 45.54 (22)*** 48.22 (21)*** Pseudo R 2 0.019 0.023 0.024 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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142 Table 3 18. Logistic regression results for models egalitarian decision making for the decision to spend and; Ecuador, 2010 (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 2.117 *** 0.423 2.083 *** 0.426 2.562 *** 0.451 Woman's age 0.018 *** 0.007 0.022 *** 0.007 0.019 *** 0.007 Age difference (man's age woman's age) 0.010 0.012 0.011 0.013 0.009 0.012 Woman's years of schooling 0.028 0.020 0.030 0.020 0.027 0.020 Schooling difference (man woman) 0.032 0.022 0.035 0.022 0.032 0.022 Rural (Urban) 0.451 *** 0.157 0.352 ** 0.162 0.419 *** 0.158 Coast (Highlands) 0.443 *** 0.153 0.456 *** 0.160 0.437 *** 0.154 Consensual Union (Married) 0.326 0.186 0.252 0.191 0.276 0.188 Couple's wealth (in thousands of USD) 0.000 0.002 0.001 0.002 0.000 0.002 Wife has extended family in hh 0.691 0.380 0.646 0.385 0.636 0.386 Husband has extended family in hh 0.052 0.358 0.087 0.351 0.058 0.358 Ethnicity (Both mestizo/blanco) Both indigenous 0.751 ** 0.319 0.751 ** 0.319 0.720 ** 0.319 Both other ethnicity 0.571 0.293 0.585 0.305 0.560 0.298 Different ethnicities 0.353 0.442 0.280 0.451 0.362 0.448 Previous Relationships (Neither in a previous relationship) Woman only has been in a previous relationship 0.001 0.274 0.074 0.277 0.055 0.274 Man only has been in a previous relationship 0.026 0.255 0.001 0.257 0.045 0.259 Both have been in a previous relationship 0.126 0.342 0.045 0.340 0.006 0.347 Who is employed? (Husband only) Wife only 0.884 0.499 0.931 0.495 0.934 0.494

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143 Table 3 18. Continued (Baseline) Model I Model II Model III Robust Std. Err. Robust Std. Err. Robust Std. Err. Both 1.775 *** 0.192 1.779 *** 0.194 1.785 *** 0.192 Neither 0.703 0.463 0.748 0.466 0.707 0.467 Who earns more (Man earns the most) Woman earns the most 0.174 0.310 0.176 0.311 0.128 0.309 Earn the same 0.925 *** 0.207 0.881 *** 0.209 0.889 *** 0.209 Disagree about earnings 0.228 0.209 0.176 0.213 0.193 0.211 Assets & Wealth (Neither own real estate) Wife only owns real estate 0.580 0.354 Husband only owns real estate 0.233 0.264 Both own real estate 0.428 ** 0.187 Woman's share of wealth 2.539 *** 0.933 Woman's share of wealth squared 2.633 *** 0.947 Number of cases ( n ) 1635 1635 1635 Likelihood ratio chi square (df) 193.43 (22)*** 208.74 (25)*** 197.54 Pseudo R 2 0.153 0.163 0.158 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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144 CHAPTER 4 LAND OWNERSHIP AND A GRICULTURAL DECISION MAKING other agricultural related assets are associated with their participation in agricultural decis ion making. This may primarily be due to the way data is collected in large household surveys. Even when the data is collected (typically in smal l surveys), m ost gender a nalyses of land and agriculture focus on gender differences in productivity and/or eff iciency but ignore the intra hous ehold decision making processes (which includes both how decisions are made within households and by whom ) that may regarding these issues differ. This chapter uses bargaining power theory to explore the relationship between agricultural decision making and agricultural asset ownership by women. Bargaining power models of household decision making suggest that asset own ership impacts bargai ning power within the household. T hus this chapter s pecifically focuses on the relationship between three measures of asset ownership form of land ownership (individual or joint), agricultural equipment couple wealth and agricultural decision making within landowning households in which the wife is a landowner Gender and Agricultur e Little is known about the relationship between land ownership and agricultural decision making by gender largely because of the lack of appropriate individual level data on these variables. National agricultural censuses only collect data on the operated farms the principal farmer is the

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145 owner. While most of the Living Standard Measurement Studies (LSMS) surveys collect data on land tenure at the parcel level, these rarely ask who specifically in the household owns the plot. Moreover, information on farming practices in the LSMS surveys is gathered from only one person, the pers on who is considered to be the most knowledgeable or who reportedly makes the agricultural decisions, and at the farm rather than the plot level. It is thus difficult to establish if the landowner is, in fact, the person who manages the land parcel and who makes the majority of decisions regarding farm production. Further more e xisting data sets rarely take into account that a land parcel might be jointly owned by a couple, that farm management might involve more than one person in the household, or that d ecision making might vary according to the specific activity. decision making had largely gone unexamined. Deere, Alvarado and Twyman (2012) explored this relationship with the LSMS datasets for Latin America and found these to be deficient for this task. Only two of the 167 questionnaires reviewed, for Honduras and Nicaragua, ha d collected data on both land ownership and farm management by sex. While data on land ownership was available at the parcel level, the information on the agricultural decision maker was only gathered at the household level; moreover, detailed sex disaggre gated data was not gathered on any of the specific decisions that make up farm management. They found that women are a much lower share of the reported farm managers than of the parcel owners in both countries. Given the inappropriate way that data w as g athered on decision making it cannot be concluded

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146 that female landowners do not always manage their own farms or are not involved in decision making. Although s everal studies have shown that land o wnership empowers rural women, there are still several unanswered questions about the relationship between land who have been denied the ability to make strategic life choices acquire such an abilit (Kabeer 1999: 437). In her framework, Kabeer (1999) states that such choices require three inter related and indivisible dimensions: resources, agency, and achievements. However, empowerment is often measured in terms of some outcomes (achievements) or agency which (Kabeer 1999: 483) and is thus typically measured as participating in household decisions (either having the final say or participating in some way). For example, some s and outcomes. Typically the outcome of interest is the change in household expenditure patterns. John Hoddinott and Lawrence household income increased, the household budget share on food increased while that of alcohol and cigarettes decreased. a variety of outcomes. Land has often been the key asset of consideration since, as Aga women have been denied land rights so that granting such rights gives them the ability South east Asia, this line of reasoning has been used in other contexts/ studies and it is

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147 now a widely held belief that land is an important asset for empowering women. In Ghana, Cheryl Doss ( 200 5) found that wom e expenditure increases, household food budgets also increase. In an econometric study of rural households in Nicaragua, Katz and Chamorro (2003) found that, holding other factors constant, female landown ers administer a much larger share of household agricultural income than in farming households w h ere women do not own land. Also Panda and Agarwal (2005) found that women who own land or housing are less likely to e xperience domestic violence than women wh o do not own such property. In Nepal, Keera Allendorf (2007) found that the children of women landowners are less likely to be severely underweight than the children of mothers who do not own land. And, in Brazil, Marrilee Mardon (2005 ) found that the chil dren of lone mothers with land rights had higher levels of education than those without land rights. decision making When this link is made, it is typically about general household (or personal decisions) such as those typically asked in the DHS surveys: 1) their own healthcare, 2) large household purchases, 3) purchases for daily needs, and 4) visits to family and frien ds. For example, Allendorf (2007) found that wo men who own land in Nepal are more likely to have the final say in household decisions using these four decisions as an indicator. However, there are even fewer studies that directly examine the link between asset ownership and decision making related to the assets owned The empowerment

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148 say in household decisions but it does not tell us whether ownership will favor certain typ es of decisions over others. 1 It might be assumed that ownership of agricultural assets, such as land and agricultural equipment, would imply more say in agricultural decisions than in other areas; however neither the bargaining power n or the empowerment frameworks makes this connection. Furthermore there is a debate about whether joint or individual ownership is best This primarily comes out of the literature regarding land tilting programs. While Agarwal (1994 ) argues s independent land rights, Deere and Len (2001) contend that mandatory joint titling which would reinforce the legal marital regime in many Latin American countries, could reduce inequalities in property ownership. Further support of joint title s is seen in Datta (2006) study, which found that joint titling of homes empowered women in an urban setting of India. She claims increased their security, access to knowledge, an d self esteem all of which taken together indicate empowerment Also Wiig (2012 ) finds that in Peru women in communities in which joint titling programs have occurred are more likely to participate in household decisions than women in communities with communal property. By examining how the form of ownership (either individual or joint) is related to th e form of agricultural decision making our study will contrib ute to this debate Land and Development Access to land has been shown to improve household welfare but the studies that find this typically ignore intra household allocation issues and therefor e fail to provide 1 In an economic framework, the bargaining power theory may suggest that the types of de cisions impacted by asset ownership will be determined by preferences (and utility maximization).

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149 insight on how these intra household relations are impacted by land ownership Frederico Finan, Elisabeth Sadoulet, and Alain de Janvry (2005) found that access to land significantly increases household earnings in rural Mexico. Furtherm ore, Agarwal (1994) citing Amartya incidence of absolute poverty and land access (owned or operated) has been noted in several studies; and landless laborers are found to be worse off than the nea r landless ell being through its productive capacity (it can provide food) and indirectly because it facilitates access to credit, can be sold or mortgaged during crises, and ownership of land (as well as other assets/wealth) strengthens support from family members. Another major finding of Finan, Sadoulet, and de Janvry (2005) is that the welfare outcomes of access to land are likely dependent on access to complementary resources such as such as education and access to roads. The idea of complementary resources is quite compelling and could be expanded to include other resources such as key inputs (i.e. seeds, fertilizer, etc.), credit and agricultural equipment Although Finan, Sadoulet, and de Janvry (2005) use the house hold as the unit of analysis and thus ignore gender others have considered gendered aspe c ts of complementary resources. Ruth Meinzen Dick et al. ( 2011 ) in their gender, assets, and agricultural programs (GAAP) framework stress the importance of recognizing not only what resources women (and men) have access to and control over but also in which markets and other institutions they participate. Using this framework it is easy to identify that even women with land may not have the same access to input markets credit or agricultural equipment as do their male counterparts. This may explain the gender

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150 differences in agricultural productivity that have been identified ( discussed in more detail below). In general, th e liter ature on land and development ignores intra household allocation issues and therefore does little to inform a gender analysis of land ownership and agricultural decision making. The main question left unanswered is: Whose welfare within the household is im proved by land ownership and how does it impact intra household inequalities? Following the bargaining power framework, we argue that this on their relative wealth and asset ownership. This study will further explore this issue by agricultural equipment, and their share of wealth impacts agricultural decision making Although this does not directly answer the welfare question, it could be assumed that women who participate more in decisions will have greater welfare than those that do not since their preferences will be taken into account during the decision making process. Gender and Productivity Mu ch literature focuses on gender differences in agricultural productivity and efficiency, but typically ignores the intra household decision making processes that are likely to influence such ge nder differences Women are often found to be less productive t han men. For example, Stein Holden, Klaus Deininger, and Hosaena Ghebru (201 1) found that female headed households were less productive than male headed households in Ethiopia. Amber Peterman, Agnes Quisumbing, Julia Behrman, and Ephraim Nkonya (2011) found lower productivity on female owned plots and in

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151 female headed households (than male owned plots and male headed households) in Nigeria and Uganda. However, these productivity differences are often attributed to gender differences in access t o complementary resources such as irrigation, seed, chemical fertilizer, pesticides, extension services, etc. Hassan Aly and Michael Shields (2010) attributed Robert Gilbert Webster S akala, and Todd Benson (2002) found that in Malawi when inputs were supplied to both men and women there were no productivity differences. In Zimbabwe, Sara Horrell and Pramila Krishnan (2007) found gender differences in productivity for cotton but not for maize or groundnuts once they controlled for input use. And, Addis Tiruneh Teklu Tesfaye, Wilfred Mwangi, and Hugo Verkujl (2001) found that female headed households in Ethiopia had less gross output than male headed households and attributed the differe nce to limited input access by female headed households. Similarly Cheryl Doss and Michael Morris (2001) found that men and women adopt improve d maize varieties and fertilizer at different rates due to differences in access to complementary resources such as land, labor, and extension services. Many studies have shown perhaps because the y account for input differences ( Peter Moock 1976 Akinwumi Adesina and Kouakou Djato 199 7 Awoyemi Timothy and Adetola Adeoti 2006 and Arega Arl en e Victor Manyon, Gospel Omanya, Hodeba Mignouna, Mpoko Bokanga, and George Odhiambo 2008 ). A few studies have found evidence of allocative inefficiencies within households (see Quisumbing 1996 for a review and Christopher

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152 productive if they were farmed more intensively or in other words if more inputs (labor, in formation about how resources are allocated within households. Objectives This chapter provides a first step in filling the gaps in the literature identified above. It examines the relationship between land ownership and farm management decisions. The ma in question of interest is: Is land ownership by women in dual headed households associated with their participation in agricultural decision making ? More specifically, the following questions will be addressed: 1) how likely are female land owners to be engaged in agricultural decision making on their own plots; 2) is ownership of agricultural equipment associated with a greater likelihood of agricultural decision making ; 3 ) is the form of land and/or agricultural equipment ownership ( either individual or joint) related to the likelihood that the woman will make the decisions alone or jointly; 4 ) what other factors (such as non farm employment) are associated with ; and 5 ) do men and agricultural decision making differ? Data Data for the analyses presented in this chapter come from t he EAFF 2012 individual questionnaire which ation in major household and farm decisions, on their financial assets, and information related to marital and inheritance regimes. 2 The agricultural module included four questions 2 In the case one of the partners had not been present for the household questionnaire, they were also asked in the individual questionnaire about the ownersh ip and valuation of all of the assets which appeared in the household inventory as well as about any additional assets owned by someone in the

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153 regarding decision making for each owned land parcel, referring to the prev ious 12 months: who in the household made the decision on what to plant; who made the decision on what inputs to use; if some of the harvest was sold, who made the decision on how much to sell; and who decided on how to spend the money generated from the sale. 3 provided for up to two people to be listed among those who made the decision. We also asked who in the household provided labor on the plot and who actually made the market sal e. % of households nationally reported that someone residing in the household owned land. Overall respondents provided information on a total of 513 owned land parcels. Of these, 29 % were owned i ndividually by men, 28.1 % individually by women, 34.3 % jointly by the principal couple, 2.0 % jointly by other or all household members, and 6.6 % were owned jointly by a household member with a non household member. 4 Since the bargaining power between spo uses motivates the research, t he subsequent analysis is restricted to those owned parcels whose owners are either married or in a consensual union. In such cases, w e collected information on decision making from both husbands and wives who were landowners T he re are responses making from the individual questionnaire are used but the agricultural equipment ownership variable and 3 We also asked if anyone in the household had made an investment in land improv ement in the past five years, and if so, who participated in this decision. Unfortunately, few such investments had been made. Only 15.7% of partnered men and 9.5% of partnered women reported having made any land improvements. Therefore, the responses to t his question are not analyzed here. 4 These percentages are weighted, reflecting the sample expansion factors.

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154 f rom landowning wives regarding 270 parcels. 5 Of these, 85.9 % were cultivated by someone in the household during the previous twelve months and thus decision making information was collected. The final sample size for partnered women consists of decision making on 228 owned parcels. 6 Partnered men considered themselves owners of 295 parcels, of which 89.2 % were reported as being cultivated by someone with in the household in the last twelve months, giving a sample size of 261 parcels for partnered men. 7 Then, considering whether both spouses reported agricultural decision making on the same parcel the sample is reduced to 180 parcels. We call this the paired sample since it includes the parcels reported on by the pair, both the husband and the wife, and as such is directly comparable. Table 4 1 presents a cross tabulation of the descriptive statistics of the data of interest as reported by the wife First, n ote that while information on the decision on what to cultivate is provided for 228 agricultural plots, the number of observations then decreases for other decisions. I nputs were not used on o ver one quarter of the plots reported on b y women owners, and t herefore they did not answer the question regarding who makes decisions on what inputs to use. 8 Moreover, for half the parcels, 5 Responses to the agricultural decision making module were restricted to those who answered that they were a landowner, owning land either indiv idually or jointly with their spouse or another person. Wives and husbands did not always agree on the form of ownership of the parcel, thus comparable information on decision making is not available for those spouses who did not consider themselves to be a landowner; hence, male and female responses are not strictly comparable. 6 The final sample size was reduced from 232 to 228 due to non responses on some of the decision making questions and 2 plots that are reported as jointly owned by the woman and so meone besides her spouse. 7 The final sample size was reduced from 263 to 261 due to non response of some of the questions. 8 Unfortunately, it appears this question was interpreted as whether they used purchased inputs only, such as improved seed or inorg anic fertilizer.

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155 the decision on how much to sell was reported as not applicable, since none of the harvest of the previous year from that parce l was sold. Considering the four decisions, irrespective of the type of plot ownership, partnered women landowners were least likely to participate in the decision regarding the use of the inputs (women had no say regarding 28.6 % of the plots), and were most likely to participate in the decision about spending the income from crop sales from the plots which they owned (only 5.9 % were not involved). The data presented in T able 4 1 show considerable variation, as expected, by type of decision and the form of ownership of the parcel. On plots owned by partnered women, all four decisions were more likely to be made by women alone when women owned these parcels individually than when these were owned jointly with their partners, particularly the decisions reg arding how much to sell and over the use of the proceeds from a sale. On the other hand, plots owned by women jointly with their partners were much more likely to be characterized by joint decision making than those plots with sole female owners. Model s The responses to the agricultural decision making questions can be used to This is done by creating an index variable that takes into account each agricultural decision in which the household participates for each parcel. F our agricultural decisions were included in this index : what to plant/cultivate, what inputs to use, how muc h to sell, and how to spend the proceeds. she is considered not to participate. Participation in a decision gives a score of one and non participation a score of zero The denominator is determined by the number of

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156 decisions in which the household is reported as making (and is at least one because all households report making the cultivation decision). So, if a woma n participate s in the cultivation decision and selling decision but not the input use and spending decision she would get a score of 0.5 (two divided by four). If however, the household did not sell any of their harvest, they would only report on the cultivation and input use decision; in th is example she wou ld still get a score of 0.5 (one divided by two). Table 4 2 reports th e frequency of the index scores, which range from zero (no participation the wife does not participate in any of the agricultural decisions ) to one (full participation the wife is involv ed in every agricultural decision). 9 Sub s amples and Dependent Variables Note that three sub samples are included in T able 4 2 : 1) couples where both partners responded to the decision making questions 2) partnered women who responded, and 3) partnered men who responded. The person must have responded to the agricultural decision making questions to be included in at least one of the sub samples. So, they must have considered themselves an owner of the parcel and that someone in their household worked on the parcel in question. The design of the questionnaire had all others ( i.e. non land owning spouses) skip the agricultural decision making questions. This limitation of the survey design is also the reason why only the paired sample is directly comparabl e; these are the only parcels on which both spouses reported how agricultural decisions were made (and as such both spouses consider themselves an owner even if they do not agree on who the owners are) 9 Note that the unit of analysis is the parcel; however, for clarity of prose the parcel level language is often excluded.

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157 Women tend to report higher rates of participation for themselves than the men do is lower at 0.69 in the paired sam ple. Similarly, 61% of women report full participation (an index score of one, meaning that they are participating in each decision that the household makes) while only 52 % of men report that their wives fully participate (in the paired sample). In this sa mple, slightly more men report that their wives do not participate at all; 13% compared to 11% of the women. A chi square test indicates that there are statistically In the sample s of all partnered men and women, the difference is even greater with 63 % of women reporting full participation and only 44 % participation. Only 12 % of partnered women report no participation but 25 % of men report that their wi ves do not participate at all. However, this comparison comes with a caveat; most of these men and women are reporting about different parcels and the by the women, w she considers herself an owner. We ran two sets of index models; each set includes a model using the responses given by women and the other with responses given by men. First, the pair ed sample, which includes the parcels that both partners respond about agricultural decision making is used giving comparable results by gender Second, a nother set of index models was run using all of the partnered men and women in separate models; these are not directly comparable since it refers to different parcels in the women the

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158 s These same samples of all partnered men and women were used in the Indep endent Variables and Hypotheses The key variables of interest are the form of land ownership agricultural equipment ownership participates in field work on the plot, and whether either of them is employed off farm. We would expect women who own land individually rather than jointly to be more involved in the decisions regardin g their plots, if individual ownership is associated with a stronger fallback position and corresponding bargaining power within the household. We also include a variable indicating who within the household owns agricultural equipment; this includes every thing from small agricultural tools like hoes and machetes to large equipment such as tractors and installations like barns or irrigation systems. While ownership of large a gricultural equipment would imply a stronger fallback position ; all types of agricu ltural equipment are complementary input s for agricultural production and owners of any such equipment are likely to be participating in agricultural production. T hus it is hypothesized that women who own agricultural equipment are more likely to participa te in agricultural decision making As with land ownership the form of agricultural equipment ownership, either joint or individual, may also be associated with how agricultural decisions are made. positions are important for determining bargaining power, we also include the female share of couple wealth as a variable to measure their relative wealth positions. This alth divided by the W

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159 of couple wealth to be positively associated with their participation in decision making. However, bargaining power theory does not indicate which dec isions will be impacted so it is unclear how female share of couple wealth will be associated with agricultural decision making As suggested in the literature culture in Latin America (see Deere and Len 1982 and Brenda Kl eysen and Fabiola Campillo 1996), we expect to find a positive association between wome field work on their plot s and their participation in decision making. We also expect making to be positively participation in off farm work, and negatively related to their p articipation in off farm work. 10 We also control for whether annual crops (vs. perennials, forage, or fruit trees) are grown on the parcel cation, marital status, number of adults besides the principal couple in the household, ethnicity, included as an indicator of their socio economic status. Age and education variables as other indicators of potential differences in their relative bargaining positions Although the samples only include partners, a marital status variable that indicates whether the c ouple is married or in a consensual union is included to control for any possible differences that this might imply. The number of adults in the household besides the principal couple is included since if other adults are 10 Although we did not directly ask if the person was working off farm, we assumed this to be the case if they report ed working during the last year, did not report that they were an unpaid family laborer, and did not report working in an agricultural related occupation.

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160 participating in agricultural deci sions, the wife may be less likely to do so. We also control for ethnicity by including a dummy variable for whether the wife considers herself indigenous. Finally locational variables for rural/urban and Coast/Sierra are also included. The summary statist ics all independent variables are presented in T ables 4 3 through 4 6 by the sub sample considered. Results Tables 4 3 through 4 6 give the descriptive statistics. The average age of the partnered women in the sample s is 51 5 3 and the average age difference between husbands and wives is about 4 years. O n average w omen have about 4 or 5 years of schooling (with a median of 6) and men have about 1 year more of schooling than their wives. There is about 1 other adult in the hous ehold besides the principal couple. On average couple wealth ranges from $46,000 $52 ,000 with a median of around $18,000. Wives own about 41 % to 50 % ; men report a lower share of wealth owned by women at 41%. This is likely because the wives are typically not considered land owners but the husbands are while in the range for all samples considered is from about 0 to nearly 100 % Table 4 6 p resents the summary statistics for the categorical variables. In the paired sample, women report owning nearly 95 % of the parcels jointly while 5 % report individual ownership The husbands in this sample report that their wives own 85 % of the parcels jointly and the other 15 % of the parcels are owned by the men alone. Considering all partnered women, 85 % of the parcels are reported as jointly owned and 15 % owned individually by women. And, considering all partnered men, 65 % of the

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161 parcels are owned joi ntly by the spouses while the other 35 % are owned individually by the men (therefore husbands do not consider their wives owners of these plots) In the paired sample, husbands report that crops are grown on 83% of their parcels while on the other 17% of p arcels forages, perennials, or trees are grown. Similarly wives report that crops are grown on about 84% of their parcels. These percentages are slightly lower for the all partnered men and women samples; women report crops grown on 81.4% of their parcels while men report crops grown on 78% of their parcels. Only one percent of parcels owned by those in the paired sample are owned by someone in a consensual union; 99% are owned by someone who is married. About 8 % of the parcels are reported on by women in c onsensual unions when considering all partnered women. While 16 % of parcels reported on by partnered men are owned by men in consensual unions. About 82 % to 86 % of parcels are reported on by rural residents; while about 14 % to 18 % of the parcels were owned by urban residents. Between 15 % and 17 % of the parcels are owned by co astal residents and the other 69 % to 85 % a re owned by highland residents, which seems to indicate that there are more men than women who consider themselves land owners on the coast. Some 17 % to 21 % of the parcels were owned by indigenous women, while most were owned by those of other ethnicities (white, mestizo or AfroEcuadorian). A bout 9 % to 12 % of parcels are owned in households in which only the wife worked off farm; while in many households (27 % to 30 % ) only husbands worked off farm, in 21 % to 22 % both worked off farm, and in 39 % to 43 % neither worked off farm.

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162 In the paired sample, husbands and wives report similar levels of fieldwork participation. Women report that only the hus band participates in fieldwork on about 28 % of the parcels while men report that only they work on about 29 % Wives report that they alone participate in fieldwork on about 9 % of the parcels while their husbands report that only the wife does fieldwork on about 6 % Husbands report a higher level of both doing fieldwork (65 % ) than do wives (63 % ). However, when looking at all partnered men and women we find more differences. The partnered women report that only the husband works on about 26 % of the parcels, only the wives do fieldwork on 12 % they both work on about 60 % and neither work on about 2 % All partnered men report that only husbands work on 40 % of the parcels, only wives on 6 % of the parcels, both on 53 % of the parcels, and neither on about 1 % of pa rcels. In the paired sample only the husband owns agricultural equipment on about 29 % of parcels only the wife owns agricultural equipment on 5 % of the parcels, both own agricultural equipment on about 52 % of the parcels, and on 14 % of parcels neither own agricultural equipment. 11 In the all partnered women sample, only husbands own agricultural equipment on 27 % of the parcels only wives on 7 % of parcels, both on 52 % of parcels, and neither on 13 % of parcels. In the all partnered men sample, only husbands own agricultural equipment on 42 % of parcels, only wives on 4 % of parcels, both on 39 % of parcels and neither on 14 % of parcels. 11 The reconciled/final agricultural equipment owners are used in this analysis; when there were disa greements about who the owners were, any owners reported by either spouse are considered owners.

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163 Regression Results of the Paired Sample Tables 4 7 through 4 11 participation in agricultural decision making Each table presents 4 models; Model I is the baseline model which does not include any of the asset or wealth variables. Model II includes agricultural equipment ownership; Model III includes the female share of couple wealth; and finally Model IV includes both agricultural equipment ownership and female share of couple wealth. All four models are presented to illustrate that the results are stable; they do not ch ange much with the different specifications and they illustrate the importance of including the asset and wealth variables Table 4 7 shows the ordinary least squares regression results of the index of decision making as reported by partnered women paired sample). 12 In Model I we find that women participate less in the decision making when they are in a consensual union than when they are married (0.2 points less). Parcels on which only the wife participates in decision making as compared to those parcels on which only the husband works. And, parcels on which both the husband and wife work have 0.5 participation as compared to those parcels on which only the husband works. None of the other variables are statistically significant at the 0.1 level. Model II has similar results with the additional variab le of the both owning agricultural equipment also being statistically significant. As in Model I women in 12 These models include the joint land ownership variable. Alternative models that did not include this variable were also run and yielded similar results as th ose presented. (We included the joint land ownership variable because over 5% were still owned individually; and the variable is nearly significant with a p value of about 0.15 (varies slightly by model).) Also, models of all partnered men and women were r un with similar results as those presented.

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164 consensual unions decrease participation by 0.2 points compared to married women. O nly the wife participating in fieldwork is associated with an addit ional 0.63 points and compared to those parcels on which only husbands do fieldwork. Also, in this model we find that when both spouses own agricultural equipment, women are more likely to participate in agriculture decision making (with a 0.1 point increase over those parcels on which only the husband owns agricultural equipment). Model III, which includes the female share of couple wealth again has similar results. Wome n in consensua l unions have an index score about 0.3 points lower than married wo men. T he wife only participating in fieldwork is associated with a 0 .6 point increase in the index, while both participating is associated with a 0.5 point increase over only the husband participating. The female share variable is negatively related to decision making increases, her participation decreases Model IV includes both the agricultural equipment and f emale share variables. This model has similar results as those already discussed. Women in households in which both partners own agricultural equipment have a score of 0.1 points higher than those in households in which only the husband owns agricultural e quipment, and the parti cipation Table 4 8 reports the results decision making as reported by men in the paired sample ; therefore, this table is directly compar able to the previous one. Model I results indicate that the following variables are

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165 decision making : schooling differenc e, coast, neither working off farm, wife only and both participating in fieldwork. As reported by men, a year increase in the difference is associated with a 0.01 point decrease in her index score. Also, wome n living in the coastal region have a score 0.14 points lower than those in the highlands. When neither partner works of f farm the wife has a score 0.13 points less than when only the husband works off farm. Only the wife doing fieldwork is associated with a score 0. 6 points higher than when only the husband does fieldwork. And, both doing fieldwork is associated with 0.4 points more than only the husband doing fieldwork. Model II gives similar results with the additional statistically significant variable of both owning agricultural equipment W omen in households in which both partners own agricultural equipment have an additional 0.1 points compared to women in households in which only the husband owns agricultural equipment. Models III and IV have simila r results as those in Models I and II share of couple wealth is negatively associated with her participation in agricultural decision making it is not statistically signif Comparing Table s 4 7 and 4 8 we can see important similarities and differences in the results for the samples of paired men and women. Both suggest that women in households in which only the wife does fieldwork participate in agricultural decision making more than in hou seholds in which only the husband does the fieldwork; and, that both doing fieldwork is associated with a higher index score than those where only

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166 both partners owning agricu ltural equipment is associated with a higher index score of about 0.1 points. This may suggest that both the husband and wife owning agricultural equipment is an indicator of the true farm family that makes egalitarian decision s following variables: consensual union, coast, neither working off farm, and the female share of couple wealth. consensual unions parti cipate less in agricultural decision making than do married women ; in the s there were no statistically significant difference s between women in consensual unions and marriages. Also, i s women on the coast had lower index score s than women in the highlands while no statistically significant s Furthermore s suggest that women have lower index scores if neither partner worked off farm as compared to when only the husband wor ked off farm while this variable was not statistically significant for s s suggest that the higher the share of couple wealth agricultural decisi on making model s This implies that women view their wealth share to impact their say in agricultural decisions but men do not. Overall, t he d ifferences suggest that men and women have differen decision making Next, the cultivation decision is examined in more detail in order to more fully ion in a specific agricultural decision. The cultivation decision is examined because this is a decision made by all landowners in the sample

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167 and it may be the most important decision the family farm makes especially in regards to a risk y decision ( Kleysen and Campillo 1996 ) T ables 4 9, 4 10 and 4 11 present the se results ; T able 4 9 gives the results of the participation in the decision about what to cultivate as reported by women landowners. Table 4 10 presents the r cultivation decision, this is done to see if there are differences between women making the decision alone or jointly (which are both considered participation in the logistic regression) Finally the binary logistic regression results reported by all partnered their wives participation in agricultural decision making (T able 4 11). As shown in T able 4 9 we find that joint land ownership and who participates in the for the sample Women who are joint owners are more likely than women who report individual ownership to participate in t he cultivation decision. The multinomial logistic regression results in Table 4 10 show that joint landowners are more likely to make a joint decision than not participate in the decision making process and that join t landowners are less likely to make th e decision alone as compared to jointly. In other words, joint landowners are more likely to make a joint decision than to make the decision alone (and individual land owners are more likely to make the decision alone) Furthermore, similarly to the inde x models, in the logit model we find that when the wife participates in fieldwork she is more likely to participate in the cultivation decision and when her husband participates in fieldwork she is less likely to participate in the

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168 cultivation decision. 13 The multinomial results further disentangle these differences When the wife does fieldwork she is more likely to make the decision alone or jointly as compared to not participating; but, there is no difference between her making the decision alone or joi ntly. Furthermore, the husband doing fieldwork is associated with women being less likely to make the decision alone than not participating and with her making the decision alone as compared to jointly. However, there is no statistically significant differ ence for women making the decision jointly or not participating when considering men doing fieldwork or not. When only the wife owns agricultural equipment she is more likely to participate in the cultivation decision than when only the husband owns agricu ltural equipment. The multinomial results also indicate that women are more likely to make the decision either alone or jointly than not to participate; and, they are more likely to make the decision alone than jointly when they alone own agricultural equi pment as compared to when their husbands alone own agricultural equipment. Next, we present the cultivation decision. The results of the reported in T able 4 11 sugges decision: joint land ownership, consensual union, number of adults besides the principal couple in the household, neither working off farm, wife and husband doing fieldwork, an d both owning agricultural equipment. T indicates that women who 13 Notice that in the index models mutually exclusive household variables were used: only husband, only wife, both, and neither. However, in the logistic models of the cultivation decision, the wife only doing fie ldwork perfectly predicted her participation in the cultivation decision and as such the model could not be estimated (by STATA). Therefore for the logistic regression models, these variables were reduced to two dummy variables; either the wife does fieldw ork or not, and either the husband does fieldwork or not.

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169 are joint owners are less likely than those who are not owners to participate. 14 This is an unexpected result since we would expect that women landowners to be more likely to pa rticipate in agricultural decision making ; however, these results do not include all non landowning women and therefore we cannot conclude that all women joint owners are less likely than all non own ing women to participate. Women in consensual unions are less likely to participate in the cultivation decision than married women. 15 Also, the number of adults in the household besides the principal couple is associated with lower likelihood of men reporting that their wives participate in the cultivation decis ion. This result was expected but it is interesting that it s that men perceive other adult household members to be making the cultivation decision while women do not. In terms of the asset and wealth variables, M odel s II and IV suggest that when both own agricultural equipment the wife is more likely to participate in the cultivation decision than when only men own agricultural equipment This result is similar to the index mode cultivation decis ion (as compared to when only men own agricultural equipment). The 14 This variable is included differently in the two models because of the survey design; men and women were asked if they considered themselves an owner and only then did they precede to answer the a gricultural decision making questions. Thus if the man reported that the wife was the only owner he did not answer who made the agricultural decisions. 15 Although this variable is not statistically significant at the 0.1 level in Models III and IV, it is still weakly significant with a p value of about 0.12 in each of these models.

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170 Model III indicates that indigenous women are more likely than non indigenous women to participat e in the cultivation decision. Neither spouse working off farm is associated with women being less likely to participate in the cultivation decision than when only the husband works off farm. And, like the the cultivation d also suggests that women who do fieldwork fieldwork indicates a lower likelihood of women participat ion in the cultivation decision. Discuss ion and Concluding Thoughts As shown in Table 4 1 most women landowners are involved in agricultural decision making in Ecuador. Furthermore, t here is a correlation between joint land ownership and joint decision making as seen in the multinomial regressio n results for the decision about what to cultivate. However, in terms of the index of participation in agricultural decision making there was no difference between joint and individual land owners. their wives participation in the cultivation decision suggests that women who are joint landowners are less likely than non owners to participate in the cultivation decision, this does not compare all non landowning women to all landowning women. A limita tion of this study is that the agricultural decision making questions were not asked of non land owners, which would be needed to fully address the question of whether land ownership impacts how agricultural decisions are made. In all models, a gricultural equipment ownership (either by only the wife or by both spouses) decision making In the index model, a w oma n who own s equipment along with her husband is more likely to participate in agricultural decision making than a wom a n whose husband alone own s

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171 agricultural equipment. Furthermore, for the cultivation decision a wi f e who alone own s agricultural equipment is more likely than a woma n whose husband alone own s agricultur al equipment to make the decision either alone or jointly than not to participate She is also more likely to make the decision alone than jointly. These results indicate the importan ce of complementary asset ownership. In fact, it may be that agricultural equipment ownership in some way defines who farmers are and thus who is making the agricultural decisions. Another important correlate to female participation in agricultural decisio n making is her participation in fieldwork. Women who do fieldwork are highly likely to be making agricultural decisions. Interestingly, share of couple wealth was either not negatively decision making model). As discussed in C hapter 3, this variable was statistically significant and positively associated with egalitarian decision making for the work and spen ding decisions. The negative relationship decision making may indicate that women may prefer to use any additional bargaining power in other ways More research is needed to f urther explore this issue. Land is an important resource and land ownership has been linked to development and poverty alleviation. However, past studies largely ignore d the intra household and gender aspects of land and agricultural decision making Agr icultural related studies that do focus on gender tend to examine the gender differences in productivity and

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172 efficiency but do not focus on who is making the decision so the underlying processes that lead to such differences are ignored. This paper used a bargaining power framework to explore the gendered relationship between form of land ownership and form of agricultural decision making in order to directly address the question of whether who owns land is important to decision making The results presented in this chapter indicate that while the form of land ownership (joint or individual) generally did not impact decision making it did make a difference in terms of how women participated in the cultivation de cision; women who were joint owners were more likely to make the cultivation decision jointly while women who owned land individually were more likely to make the decision alone. One important contribution of the research presented in this chapter, is tha t it uses individual level data about both land ownership and agricultural decision making to explore the relationship between asset ownership (land and agricultural equipment) and farm management. This chapter highlights the importan ce of recognizing t hat owners and decision makers are not always the same A s shown in this chapter although there is a correlation between ownership and decision making it is not a perfect correlation ; some non owners participat e in decision making and some owners do not. Fur decision making vary depending on who reported th e information men or women This is an important result in terms of perceptions; as explai ned in Chapter 1 important factors in determining bargaining power. Interestingly, it seems that they have

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173 decision making More research is needed in this area to examine how differences in decision making

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174 Table 4 1 The participation of partnered female landowners in agricultural decisions by type of ownership and level of participation in decision making as reported by partnered landowning women Form of Ownership Individual Owner Joint Owner Total Wife's participation in cultivation decision Alone 47.4% 12.1% 17.7% Joint 25.8% 66.4% 60.0% No participation 26.8% 21.5% 22.3% Total 100.0% 100.0% 100.0% n = 35 193 228 Wife's participation in input use decision Alone 45.1% 18.3% 23.0% Joint 24.5% 53.5% 48.4% No participation 30.4% 28.2% 28.6% Total 100.0% 100.0% 100.0% n = 27 137 164 Wife's participation in selling decision Alone 58.7% 7.8% 14.7% Joint 22.6% 67.4% 61.3% No participation 18.7% 24.8% 24.0% Total 100.0% 100.0% 100.0% n = 15 100 115 Wife's participation in spending decision Alone 66.9% 16.2% 23.1% Joint 26.1% 78.1% 71.0% No participation 7.0% 5.7% 5.9% Total 100.0% 100.0% 100.0% n = 15 100 115 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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175 Table 4 2. Composition (percent) of sample of partnered women and men in each level of the index of women's participation in agricultural decision making Ecuador 2010 Paired sample: b oth spouses report agricultural decision making n = 180 All self reported landowners Partnered women Partnered men Partnered women, n = 231 Partnered men, n = 261 No participation 0.0 10.6 12.8 12.1 24.5 0.3 6.7 8.9 6.5 9.2 0.3 1.7 2.8 1.3 2.7 0.5 12.2 13.9 10.8 11.9 0.7 3.3 1.1 2.6 0.8 0.8 4.4 8.3 3.5 6.9 Full participation 1.0 61.1 52.2 63.2 44.1 Total 100% 100% 100% 100% Pearson Chi Square 171.8*** Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 4 3. Descriptive statistics for continuous variables of paired sample, Ecuador 2010 n Minimum Maximum Mean Std. dev. Median Wife's age 180 23 82 52.68 12.524 53 Husband's age 180 23 90 57.07 12.725 58.5 Age Difference 180 7 29 4.39 5.479 3 Wife's Years of schooling 180 0 18 4.47 3.624 5 Husband's years of schooling 180 0 18 5.69 3.973 6 Difference in years of schooling 180 9 12 1.22 3.364 0 Number of adults in household (besides principal couple) 180 0 6 1.039 1.266 1 Couple's wealth (thousands USD) 180 0.369 619 52.09 93.641 18.05 Wife's share of couple's wealth 180 0.014 1 0.478 0.152 0.499 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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176 Table 4 4. Descriptive statistics for continuous variables of sample of parcels reported on by partnered women who report on agricultural decision making, Ecuador 2010 n Minimum Maximum Mean Std. dev. Median Wife's age 231 23 82 51.91 12.701 53 Husband's age 231 23 90 56.24 12.880 56 Age Difference 231 7 29 4.32 5.415 3 Wife's Years of schooling 231 0 18 4.78 3.977 6 Husband's years of schooling 231 0 19 5.77 4.051 6 Difference in years of schooling 231 12 12 1.00 3.350 0 Number of adults in household (besides principal couple) 231 0 6 1.11 1.267 1 Couple's wealth (thousands USD) 231 0.3595 619 46.19 84.608 17.34 Wife's share of couple's wealth 227 0.014 1 0.502 0.180 0.499 Source: UF FLACSO 2010 Ecuador Household Asset Survey Table 4 5. Descriptive statistics for continuous variables of sample of parcels reported on by partnered men who report agricultural decision making, Ecuador 2010 n Minimum Maximum Mean Std. dev. Median Wife's age 261 18 82 51.35 13.241 52 Husband's age 261 19 90 55.95 13.988 57 Age Difference 261 10 29 4.60 5.683 4 Wife's Years of schooling 261 0 18 4.90 3.851 6 Husband's years of schooling 261 0 18 5.74 4.036 6 Difference in years of schooling 261 9 12 0.84 3.480 0 Number of adults in household (besides principal couple) 261 0 6 0.96 1.212 1 Couple's wealth (thousands USD) 259 0.369 619 49.74 92.422 18.395 Wife's share of couple's wealth 261 0 1 0.41 0.214 0.493 Source: UF FLACSO 2010 Ecuador Household Asset Survey

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177 Table 4 6. Descriptive statistics for categorical variables, composition (percent) of samples, Ecuador 2010 Paired sample (n = 180) Partnered Women (n = 231) Partnered Men (n = 261) Wife is joint owner (individual owner) -reported by women 94.4% 84.7% Wife is joint owner (not an owner) -reported by men 85.0% 64.8% Crop grown on parcel (as compared to perennials, forage, or trees) reported by women 83.9% 81.4% Crop grown on parcel (as compared to perennials, forage, or trees) reported by men 83.3% 78.2% Consensual Union (marriage) 1.1% 8.2% 16.1% Rural (Urban) 86.1% 84.9% 82.4% Coast (Sierra) 15.0% 16.5% 30.7% Wife is indigenous (Wife not indigenous) 20.6% 18.6% 16.9% Off farm Employment Husband only 26.7% 29.9% 27.2% Wife only 9.4% 8.7% 12.3% Both 20.6% 22.1% 19.2% Neither 43.3% 39.4% 41.4% Total 100.0% 100.0% 100.0% Who participates in fieldwork -reported by women Husband only 28.3% 26.4% Wife only 8.9% 11.7% Both 62.8% 60.2% Neither 0.0% 1.7% Total 100.0% 100.0% Who participates in fieldwork -reported by men Husband only 28.9% 39.9% Wife only 6.1% 6.1% Both 65.0% 53.3% Neither 0.0% 0.8% Total 100.0% 100.0% Who owns agricultural equipment? Husband only 29.4% 27.3% 42.2% Wife only 5.0% 7.4% 4.2% Both 51.7% 52.0% 39.1% Neither 13.9% 13.4% 14.6% Total 100.0% 100.0% 100.0% Source: UF FLACSO 2010 Ecuador Household Asset Survey

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178 Table 4 7. Ordinary least squares regression results for models of the index of women's participation in agricultural decision making (as reported by women in the paired sample); Ecuador, 2010 (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 0.325 0.203 0.341 0.207 0.460 ** 0.216 0.490 ** 0.218 Wife is joint land owner (individual owner) 0.135 0.105 0.147 0.117 0.128 0.106 0.137 0.119 Annual crop (perennial/forage/fruit trees) 0.019 0.056 0.002 0.055 0.009 0.056 0.013 0.055 Couple's wealth (in thousands of USD) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Wife's age 0.002 0.002 0.003 0.002 0.002 0.002 0.003 0.002 Age Difference (husband wife) 0.000 0.003 0.001 0.003 0.000 0.003 0.001 0.003 Wife's years of schooling 0.004 0.006 0.006 0.006 0.003 0.006 0.005 0.006 Schooling difference (husband wife) 0.001 0.007 0.004 0.007 0.001 0.007 0.004 0.006 Consensual union (marriage) 0.199 0.117 0.214 0.111 0.255 *** 0.089 0.275 *** 0.085 Number of adults (besides principal couple) in the household 0.006 0.015 0.006 0.015 0.007 0.014 0.007 0.015 Rural (Urban) 0.051 0.073 0.062 0.075 0.048 0.074 0.057 0.077 Coast (Sierra) 0.066 0.067 0.072 0.065 0.076 0.064 0.086 0.061 Wife is indigenous (not indigenous) 0.027 0.041 0.021 0.042 0.018 0.041 0.009 0.042 Off farm employment (Husband only) Wife only 0.091 0.070 0.107 0.074 0.091 0.071 0.110 0.075 Both 0.015 0.053 0.052 0.056 0.028 0.054 0.068 0.059 Neither 0.041 0.046 0.028 0.046 0.026 0.047 0.008 0.048 Participates in fieldwork (Husband only) Wife only 0.622 *** 0.064 0.630 *** 0.064 0.640 *** 0.063 0.650 *** 0.064 Both 0.523 *** 0.060 0.504 *** 0.061 0.536 *** 0.059 0.515 *** 0.059

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179 Table 4 7. Continued (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Assets & Wealth (Husband only owns ag ricultural equipment) Wife only owns ag ricultural equipment 0.047 0.066 0.020 0.068 Both own agricultural equipment 0.096 ** 0.045 0.109 ** 0.046 Neither own agricultural equipment 0.068 0.075 0.074 0.073 Woman's share of wealth 0.609 0.326 0.681 ** 0.328 Woman's share of wealth squared 0.486 0.315 0.536 0.324 Number of cases ( n ) 180 180 180 180 F Statistic (df) 18.80 (17)*** 18.42 (20)*** 33.59 (19)*** 110.27 (22)*** Adjusted R 2 0.5956 0.610 0.605 0.621 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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180 Table 4 8. Ordinary least squares regression results for models of the index of women's participation in agricultural decision making (as reported by men in the paired sample); Ecuador, 2010 (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 0.453 ** 0.185 0.515 *** 0.177 0.389 0.198 0.456 ** 0.190 Wife is joint land owner (not an owner) 0.021 0.046 0.036 0.048 0.046 0.051 0.059 0.053 Annual crop (perennial/forage/fruit trees) 0.018 0.062 0.009 0.060 0.025 0.061 0.002 0.059 Couple's wealth (in thousands of USD) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Wife's age 0.000 0.002 0.001 0.002 0.000 0.002 0.001 0.002 Age Difference (husband wife) 0.003 0.004 0.000 0.004 0.003 0.004 0.001 0.004 Wife's years of schooling 0.008 0.008 0.010 0.008 0.008 0.008 0.011 0.008 Schooling difference (husband wife) 0.013 0.007 0.016 ** 0.007 0.013 0.007 0.015 ** 0.007 Consensual union (marriage) 0.185 0.152 0.177 0.110 0.126 0.177 0.123 0.131 Number of adults (besides principal couple) in the household 0.009 0.018 0.017 0.019 0.008 0.018 0.015 0.019 Rural (Urban) 0.003 0.065 0.021 0.062 0.005 0.065 0.013 0.063 Coast (Sierra) 0.141 0.082 0.154 ** 0.082 0.157 0.083 0.169 ** 0.083 Wife is indigenous (not indigenous) 0.067 0.051 0.049 0.051 0.079 0.052 0.061 0.052 Off farm employment (Husband only) Wife only 0.089 0.078 0.095 0.075 0.083 0.080 0.089 0.077 Both 0.021 0.062 0.065 0.061 0.018 0.061 0.062 0.060 Neither 0.132 ** 0.059 0.118 0.060 0.134 ** 0.058 0.120 ** 0.060 Participates in fieldwork (Husband only) Wife only 0.603 *** 0.063 0.652 *** 0.069 0.605 *** 0.064 0.652 *** 0.070 Both 0.439 *** 0.060 0.425 *** 0.060 0.426 *** 0.062 0.414 *** 0.062

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181 Table 4 8. Continued (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Assets & Wealth (Husband only owns ag ricultural equipment) Wife only owns ag ricultural equipment 0.073 0.095 0.073 0.100 Both own ag ricultural equipment 0.115 ** 0.055 0.112 ** 0.055 Neither own agricultural equipment 0.020 0.080 0.019 0.080 Woman's share of wealth 0.206 0.407 0.180 0.427 Woman's share of wealth squared 0.049 0.357 0.059 0.379 Number of cases ( n ) 180 180 180 180 F Statistic (df) 15.02 (17)*** 16.38 (20)*** 13.15 (19)*** 14.04 (22)*** Adjusted R 2 0.482 0.507 0.491 0.514 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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182 Table 4 9. Logistic regression results for models of women's participation in the decision about what to cultivate (as reported by women -sample of all partnered women); Ecuador, 2010 (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 1.014 1.793 0.145 1.907 1.778 2.151 1.135 2.182 Wife is jo int land owner (individual owner) 0.978 ** 0.487 0.894 0.497 0.993 0.550 0.917 0.574 Annual crop (perennial/forage/fruit trees) 0.058 0.548 0.265 0.563 0.024 0.559 0.184 0.581 Couple's wealth (in thousands of USD) 0.002 0.002 0.001 0.002 0.002 0.002 0.001 0.002 Wife's age 0.012 0.023 0.013 0.025 0.008 0.023 0.009 0.025 Age Difference (husband wife) 0.033 0.040 0.022 0.042 0.032 0.041 0.020 0.044 Wife's years of schooling 0.013 0.076 0.013 0.080 0.015 0.076 0.017 0.078 Schooling difference (husband wife) 0.008 0.093 0.023 0.094 0.013 0.090 0.029 0.091 Consensual union (marriage) 1.385 1.026 1.452 1.203 1.293 1.096 1.273 1.273 Number of adults (besides principal couple) in the household 0.032 0.163 0.052 0.161 0.053 0.168 0.071 0.162 Rural (Urban) 0.640 0.767 0.716 0.867 0.711 0.823 0.797 0.939 Coast (Sierra) 0.720 0.703 0.853 0.787 0.740 0.675 0.924 0.750 Wife is indigenous (not indigenous) 0.977 0.892 0.716 0.832 0.871 0.863 0.553 0.802 Off farm employment (Husband only) Wife only 0.262 0.750 0.658 0.771 0.318 0.763 0.780 0.757 Both 0.316 0.772 0.146 0.837 0.157 0.803 0.076 0.874 Neither 0.509 0.575 0.162 0.617 0.366 0.586 0.026 0.592 Participates in fieldwork Wife (not wife) 3.658 *** 0.506 3.681 *** 0.562 3.729 *** 0.488 3.807 *** 0.546 Husband (not husband) 1.814 *** 0.658 1.667 ** 0.667 1.797 *** 0.644 1.614 ** 0.636

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183 Table 4 9. Continued (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Assets & Wealth (Husband only owns ag ricultural equipment) Wife only owns ag ricultural equipment 2.019 ** 0.927 2.125 ** 1.048 Both own ag ricultural equipment 0.671 0.526 0.748 0.538 Neither own ag ricultural equipment 1.084 0.765 1.227 0.781 Woman's share of wealth 3.605 4.664 5.292 4.765 Woman's share of wealth squared 2.776 4.088 4.358 4.309 Number of cases ( n ) 228 228 225 225 Likelihood ratio chi square (df) 90.47 (17)*** 104.47 (20)*** 97.92 (19)*** 106.06 (22)*** Pseudo R 2 0.4693 0.483 0.470 0.486 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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184 Table 4 10. Multinomial logistic regression results for models of women's participation in the decision about what to cultivate (as reported by women -sample of all partnered women); Ecuador, 2010 Model IV Alone (None) Joint (None) Alone (Joint) Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 7.698 ** 3.642 0.146 2.184 7.552 ** 3.515 Wife is joint land owner (individual owner) 1.295 0.779 1.169 0.627 2.464 *** 0.639 Annual crop (perennial/forage/fruit trees) 1.265 0.796 0.305 0.558 1.570 ** 0.687 Couple's wealth (in thousands of USD) 0.005 0.004 0.001 0.002 0.004 0.004 Wife's age 0.014 0.038 0.008 0.025 0.006 0.033 Age Difference (husband wife) 0.084 0.081 0.012 0.045 0.072 0.075 Wife's years of schooling 0.055 0.117 0.020 0.077 0.075 0.107 Schooling difference (husband wife) 0.094 0.183 0.037 0.091 0.131 0.169 Consensual union (marriage) 2.336 1.556 1.147 1.350 1.190 1.360 Number of adults (besides principal couple) in the household 0.005 0.298 0.118 0.158 0.124 0.286 Rural (Urban) 1.743 1.532 0.666 0.967 1.077 1.247 Coast (Sierra) 5.170 *** 1.638 0.613 0.768 4.557 *** 1.538 Wife is indigenous (not indigenous) 0.606 1.124 0.638 0.800 1.244 0.901 Off farm employment Wife (not wife) 0.530 1.116 0.491 0.517 1.021 0.987 Husband (not husband) 0.329 0.799 0.335 0.448 0.664 0.731 Participates in fieldwork Wife (not wife) 4.243 *** 1.457 3.689 *** 0.549 0.553 1.412 Husband (not husband) 4.790 *** 1.016 1.181 0.721 3.609 *** 0.956 Assets & Wealth (Husband only owns ag ricultural equipment) Wife only owns ag ricultural equipment 4.544 *** 1.680 1.466 1.028 3.078 ** 1.214 Both own agricultural equipment 0.024 0.970 0.812 0.552 0.836 0.834 Neither own agricultural equipment 0.083 1.411 1.370 0.762 1.287 1.259

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185 Table 4 10. Continued Model IV Alone (None) Joint (None) Alone (Joint) Robust Std. Err. Robust Std. Err. Robust Std. Err. Woman's share of wealth 10.898 9.667 5.188 4.626 5.710 8.717 Woman's share of wealth squared 8.489 7.738 4.165 4.318 4.324 6.791 Number of cases ( n ) 225 Wald chi square (df) 156.82 (42)*** Pseudo R 2 0.4876 Source: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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186 Table 4 11. Logistic regression results for models women's participation in the decision about what to cultivate (as reported by men -sample of all partnered men); Ecuador, 2010 (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Intercept 2.024 1.972 3.273 2.329 1.574 1.998 2.892 2.328 Wife is jo int land owner (not owner) 0.601 0.466 1.065 ** 0.469 1.109 ** 0.552 1.480 *** 0.553 Annual crop (perennial/forage/fruit trees) 0.066 0.476 0.241 0.522 0.075 0.504 0.293 0.555 Couple's wealth (in thousands of USD) 0.001 0.002 0.002 0.002 0.001 0.002 0.001 0.002 Wife's age 0.006 0.023 0.009 0.023 0.006 0.023 0.009 0.024 Age Difference (husband wife) 0.012 0.044 0.009 0.049 0.024 0.043 0.025 0.049 Wife's years of schooling 0.043 0.085 0.087 0.092 0.051 0.090 0.091 0.098 Schooling difference (husband wife) 0.008 0.073 0.057 0.075 0.014 0.079 0.056 0.081 Consensual union (marriage) 1.414 0.773 1.546 0.864 1.218 0.774 1.363 0.875 Number of adults (besides principal couple) in the household 0.335 ** 0.149 0.359 ** 0.159 0.311 ** 0.151 0.327 ** 0.157 Rural (Urban) 0.407 0.484 0.306 0.503 0.315 0.478 0.176 0.513 Coast (Sierra) 0.515 0.567 0.465 0.541 0.574 0.606 0.547 0.570 Wife is indigenous (not indigenous) 1.114 0.761 0.769 0.676 1.462 0.834 1.091 0.740 Off farm employment (Husband only) Wife only 0.195 0.564 0.032 0.584 0.228 0.608 0.027 0.623 Both 0.310 0.531 0.076 0.545 0.406 0.540 0.043 0.565 Neither 1.391 *** 0.466 1.120 ** 0.523 1.546 *** 0.462 1.264 ** 0.520

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187 Tabl e 4 11. Continued (Baseline) Model I Model II Model III Model IV Robust Std. Err. Robust Std. Err. Robust Std. Err. Robust Std. Err. Participates in fieldwork Wife (not wife) 3.236 *** 0.451 3.301 *** 0.508 3.376 *** 0.470 3.467 *** 0.513 Husband (not husband) 2.484 ** 0.988 2.954 ** 1.185 2.628 ** 1.081 3.091 ** 1.264 Assets & Wealth (Husband only owns ag ricultural equipment) Wife only owns ag ricultural equipment 0.693 0.764 0.832 0.730 Both own ag ricultural equipment 1.662 *** 0.501 1.697 *** 0.518 Neither own ag ricultural equipment 0.551 0.789 0.625 0.768 Woman's share of wealth 1.485 2.897 0.319 2.988 Woman's share of wealth squared 1.525 3.062 2.856 3.174 Number of cases ( n ) 259 259 259 259 Likelihood ratio chi square (df) 97.93 (17)*** 93.90 (20)*** 96.17 (19)*** 93.52 (22)*** Pseudo R 2 0.466 0.501 0.487 0.521 S ource: UF FLACSO 2010 Ecuador Household Asset Survey Notes: Reference categories given in parentheses *p < 0.1, **p < 0 .05, and ***p < 0.01

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188 CHAPTER 5 CONCLUSION This dissertation has examine d the intra household distribution of asset ownership and wealth as well as its relationship to how decisions are made within households. It does so by using individual level sex disaggregated data, which u p until now has not been widely available, particu larly nationally representative data The main objectives of this dissertation have been to address the four gaps identified in the literature regarding the Introduction, the first gap was that many past studies linked resources to welfare outcomes without considering the decision making processes that were assumed to precede such changes in welfare outcomes. Second, resources oftentimes were measured as income or occasionally as either access to or ownership of land. Third, the resources considered resources within the household even though the bargaining power model suggests tant. And fourth, even studies that directly examined the link between resources and decision making typically focus only on decision making or their participation without considering other ways in which household decisions may be made. The main contribution of this dissertation has been linking the intra household distribution of assets and wealth to various decisions and the ways in which they are made within the household By doing so we have been able to address each of the four gaps discussed above. First, the direct link between resources (assets and wealth) has been examined instead of focusing on welfare outcomes. Second, we have used asset ownership and wealth instead of income as the main resources of interest. Third, by

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189 focusin g on the intra household distribution of assets and wealth we have focused on And finally, we have considered various decisions regarding the household and farm, and forms of decision making (either individually or jointly), as well as the perceptions of both men and women. These issues have been explored in t hree essays. The first essay foc used on the gender distribution of housing, an important asset in the composition of wealth in Latin America. It analyzed the factors that explain homeownership and housing wealth by gender It showed that although there is gender equality in terms of homeownership and housing wealth in Ecuador there are gendered differences in terms of the factors associated with the likelihood of homeownership and the factors associated with the amount of housing wealth. Overall it seems that strategies differ. Oft entimes it is assumed that women accumulate assets, and particularly housing, through their relationships with men. Our results do not negate th is assumption but they suggest that women may use other strategies for housing acquisition as well. For example, the results indicate that women are more likely to use international migration as a strategy for acquiring a home than men Other key differences between t he factors associated with likelihood of homeo wner s h ip and amount of housing wealth includes whether the person receives the conditional cash transfer ( bono ) which is associated with an increased probability of homeownership for women bu t not for men and is associated with lower housing wealth for both men and women. Education is related to greater

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190 housing wealt h for both men and women but has Marital status also seems to be an import ant indicator of ho meownership and housing wealth; while those in a consensual union are less likely to be homeowners they have similar amounts of housing wealth as those who are married. Those who are single, widowed, divorced, or separated are all less l ikely to be homeowners than married people These results indicate the importance of marriage in acquiring a home. They also suggest the importance of the marital regime since many of these homeowners are joint owners with their spouse. On the other hand m arried people tend to have less housing wealth than people of all other marital statuses. For homeowners, household dissolution seems to be increasing their housing wealth. However, taking the homeownership and housing wealth results together, we speculate that one spouse is gaining from household dissolution (due to separation or divorce) and the other is losing out. One spouse is likely to acquire the entire home and housing wealth while the other is no longer a homeowner (and thus not considered in the h ousing wealth models presented in C hapter 2 ). T he second essay examined how the intra household distribution of assets and wealth were re lated to how decisions were made Two key decisions were examined: the decision of whether or not to work and the deci money. Similar to previous research ( see Kishor and Subaiya 2008 ) participation in decision making we found that the predictors of decision making varied by the decision being considered, by the form of decision making autonomous decision making decision making ), and by the

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191 perceptions of men and women. Older women are more likely to make autonomous decisions and less likely to make egalitarian decisions. Women in rural ar eas are less likely than their urban counterparts to make autonomous decisions and couples residing in rural areas are more likely to make egalitarian decision s Only the wife owning real estate is associated with her autonomous decision making and both o wning real estate is associated with egalitarian decision making Similarly, women are more likely to make an autonomous decision when she earn s more than her husband and couples who earn about the same are more likely to make egalitarian decisions than co uples where the husband earn s the most. Furthermore, while egalitarian decisions are most likely when the wife owns just under half the decision making by women are least likely at th is level. Overall, the results of this essay support the hypotheses that the intra household distribution of assets and wealth is associated with household decision making ; the wife only owning assets is related to her autonomous decision making and a fairly equal distribution of wealth is associated with egalitarian decision making processes. The third essay investigated the relationship between the intra household distribution of assets and wealth and agricultural decision making This chapter specifically dealt with women participation in agricultural decision making measured in terms of an index based on four agricultural decisions participation was examined in more detail by focusing on the decision about what to cultivate the main decision carried out by landowning households Both of these measures were modeled separately according to

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192 the responses given by men and women and thus give an idea of their differences in perceptions In this chapter we discovered that the form of or joint) is not related to the index of decision making but is related to how the cultivation decision is made; women who owned land jointly are more likely to make the decision join tly while women who own land individually are more likely to make the decision individually. Both owning agricultural making More specifically, when only women owned agricultural equipment, they were more likely to make the agricultural decision about what to cultivate alone while when both partners owned agricultural equipment women were more likely to make the decision jointly. One of the other main results from this chapter is that if a woman is engaged in fieldwork on her own land parcel then she is highly likely to also be making the decisions regarding that parcel. Furthermore, we found some differences between the on the gender of the respondent Such differences indicate the usefulness of collecting individual, sex disaggregated data from both men and women. In both Chapters 2 and 3 we found that the intra household distribution of assets, in terms of who owns as sets (real estate and agricultural equipment), is an important explanatory factor in how couples make decisions regarding who works, how income is spent, and agricultural production We found that the wife only owning real estate was s autonomous decision making regarding work and spending

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193 both owning real estate was associated with egalitarian decision making and participation in agricultural decision ma king Furthermore Chapters 2 and 3 explored the importance of the relative wealth positions of husbands and wives. In Chapter 2 w wealth is associated with egalitarian decision making The highest probability of egal itarian decision making was found to be when women own approximately 41 % to 48% all else constant). Also, as expected women are least likely to make autonomous decisions whe n the y own 33% to 6 8 % of couple wealth a range that includes the range of female share where the couple is most likely to make an egalitarian decision. These results indicate that households in which the woma n own s more of the wealth, she is likely to make the decisions alone and in households in which wealth is distributed fairly equally, the couple will likely make egalitarian decisions. This supports the idea that relative positions of men and women are important in the bargaining power model of household decision making The results of the agricultural decision making chapter (Chapter 3) are not so clear cut. The most confounding results are 1) that according to male landowners in a couple, wives who are not als o owners are more likely than women who are joint owners to wealth is not strongly correlated with agricultural decision making and if anything there is a negative relatio nship, which suggests that as share increases, the likelihood of her participation in making the decision declines. These results may

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194 suggest that women without property rights (the non owners) feel a need to exercise a claim over their husbands of that parcel. On the other hand, women may be expressing a choice about which household decisions they participate in; and agriculture may not be the preferred are n a of decision making However more research is needed to further test these hypotheses; first by collecting agricultural decision making data from all men and women in land owning households regardless of whether they own the parcel, and second by specifically asking women and men about the household decisions in which they most want or do not want to participate. The equal distribution of housing within Ecuador (as shown in Chapter 1 ) and the commu nity property regime and its enforcement are generating gender equality in terms of property rights in Ecuador. The partial community property marital regime is being supported by policies that enforce this marital regime. For example, the double signature policy in Ecuador helps ensure that property (housing, land, other real estate, and stocks) is considered joint property when it is sold. Further research is warranted in other countries with the partial community pr operty marital regime to see what proc esses are contributing to the gender differences in property ownership and/or the different patterns of the form of ownership. As explained by Deere, Alvarado, and Twyman (2012), South American countries with t he same marital regime exhibit a large range o f joint homeownership rates by couples More research is neede d to assess what makes Ecuador and Argentina (see Table 2 1) unique in terms of joint homeownership; is it that these countries have mechanisms in

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195 place to enforce the marital regime (such as th e double signature) that other countries lack. Or, perhaps homes are more likely to be inherited or acquired while single in other countries while in Ecuador they are more likely to be acquired during marriage or in a consensual union. The main limitation faced throughout this dissertation was that of potential endogeneity. Since asset ownership and wealth are likely to impact and be impacted by decision making it is difficult to determine the direction of causality. Does intra househol d distribution of assets and wealth impact how decisions are made or does how decisions are made impact the intra household distribution of assets and wealth? We acknowledge that it likely works both ways and because of this we cannot assess the impact of the intra household distribution of assets and wealth on household decision making processes. The most we are able to say is that there is a relationship or association between these variables. Further research is needed in this area; first to find suffici ent instruments or other methods for determining the impacts and second to measure those impacts. Overall, we have shown the importance of collecting individual, sex disaggregated data about asset ownership and wealth The results of this dissertation have shown that the intra household distribution of assets and wealth are important indicators of how household decisions are made. It has also shown that it matters who you ask about how household decisions are made since the estimated coefficients in the mod els differ disaggregated data about decision making and the intra household distribution of assets and wealth,

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196 we have been able to directly examine the relationships between how couples make decisions and how assets and wealth are distributed between them.

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197 LIST OF REFERENCES Agricultural Economics 16: 47 53. Agarwal, Bina. 1994. Ca mbridge: Cambridge University Press. Feminist Economics 3(1): 1 51. World Development 35(11): 1975 1988. The Journal of Developing Areas 43(2): 111 124. Making and the Bienvenid@s a Casa American Studies, University of Florida: Gainesville. termines Female Autonomy? Journal of Development Economics 90: 179 191. Argudo, Veronica. 2012. The Contribution of Growth and Declining Inequality to Poverty Reduction in Ecuador Department of Economics, Tul ane University: New Orleans. Arlen e Arega, Victor Manyong, Gospel Omanya, Hodeba Mignouna, Mpoko Bokanga, World Devel opment 36(7): 1247 1260. Becker, Stan, Fannie Fonseca Becker, and Catherine Schenck Yglesias. 2006. making Power in Western Social Science and Medicine 62: 2313 2326. 99: Review of Income and Wealth 50(4): 493 518. Contract: Understanding the Impact of Gender In L. Haddad, J. Hoddinott, and H. Alderman (eds.), Intrahousehold Resource

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198 Allocation in Developing Countries: Methods, Models, and Policies Baltimore, MD: John Hopkins University Press, pp. 95 111. CEPAR (Centro de Estudios de Poblacin y Desarrollo Social). 2005. Encuesta Demogrfica y de Salud Materna e Infantl 2004 (ENDEMAIN 2004). Quito: CEPAR. Chiuri, European Economic Review 47: 857 875. in a Nationall Straus and Richard J. Gelles (eds.), Physical Violence in American Families New Brunswick, NJ: Transaction Publishers, pp. 287 304. Vida: Apuntes sobre la FLACSO Ecudor. http://www.flacsoandes.org/web/imagesFTP/14121 .Ciclo_vida_Clase_media_Co ntreras.pdf Accessed on July 10, 2012. A Win Win Policy? Gender and Property Rights in Feminist Economics 12 (1 2): 271 298. Deere, Carmen Diana. 2010 a Mujeres, Activos y el Ciclo de Vida: Apuntes sobre Tres Program. Quito: FLACSO Ecuador. http://www.flacsoandes.org/web/imagesFTP/14136.PICHINCHA_CicloVida_versi on_19_de _septiembre.pdf Accessed July 10, 2012. and Culture Program. Quito: FLACSO Ecuador. http://www.flacsoandes.org/web/imagesFTP/14124.Ciclo_vida_Clase_media_De ere.pdf Accessed July 10, 2012. Feminist Economics 12(1 2): 1 50. Deere, Carmen Diana and Jackeline Contreras. 2011. Acumulacion de activos: una apuesta por la equidad. FLACSO, Quito, pp. 46. Deere, Carmen Diana and Magdalena Len. 1982 Women in Andean Agriculture: Peasant Production and Rural Wage Employment in Colombia and Peru. Geneva: International Labour Office.

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199 Deere, Carmen Diana and Magdalena Len. 2001. Empowering Women: Land and Property Rights in Latin America. Pittsburg PA: University of Pittsburg Press. Decision making in Dual Review of Radical Political Economics 44 (3). Forthcoming. Deere, Carmen Diana, Gina Alvarado, and Jennifer Twyman. 20 12. "Gender Inequality in Asset Ownership in Latin America: Female Owners versus Household Heads" Development and Change 43(2): 505 530. Deere, Carmen Diana, Jacqueline Contreras, and Jennifer Twyman f Assets Over the Life Cycle: Patrimonial ALASRU (Asociacin Latinoamericana de Sociologa Rural). Anlisis latinoamericano del medio rural. Nueva poca 5: 135 176. Micro Level Journal of Urban Economics 54: 401 450. Journal of African Economies 15(1): 149 180. Agricultural Economics 25: 27 39. Ellis, Frank. 1988. Peasant Economics: Farm Households and Agrarian Development Cambridge: Cambridge University Press. The Urban Poor in Latin America Washington D.C.: World Bank. Finan, Frederic Journal of Development Economics 77: 27 51. FLACSO UNFPA ( Facultad Latinoamericana de Ciencias Sociales United Nations Population Fund ) 2008. Ecuador: La Migracin Internacional en Cifras. Quito: FLACSO. Journal of Family Violence 2 1 (1): 19 29.

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203 Discussion Paper. Institute for teh Study of Labor (IZA), Bonn, Germany, pp. 38. Sen, Amartya. 1981. Poverty and Famines: An Essay on Entitlement and Deprivation Oxford: Clarendon Press. Irene Tinker, ed. Persistent Inequal ities pp. 123 149. New York: Oxford University Press. Oxford Economic Papers 62: 669 690. nomic Efficiency: New Evidence from Cassava Based Farm Holdings in Rural South African Development Review 18(3): 428 443. Tiruneh, Addis, Teklu Tesfaye, Wilfred Mwangi, and Hugo Verkuijl. 2001. Gender Differentials in Agricultural Production and Decision Making Among Smallholders in Ada, Lume, and Gimbichu Woredas of the Central Highlands of Ethiopia Mexico, D.F.: International Maize and Wheat Improvement Center (CIMMYT) and Ethiopian Agricultural Research Organization (EARO). Tor Personal wealth from a global perspective. Oxford University Press, New York. Townsend, Janet, Pilar Alberti, Marta Mercado, Jo Rowlands, and Emma Zapata. 1999. Women and Power: Fighting Patriarchies and Poverty London: Zed. Cantones de la Provincia Culture Program. Quito: FLACSO Ecuador. http://www.flacsoandes.org/web/imagesFTP/14840.Jennifer_Twyman.pdf Accessed July 1 0, 2012. The Journal of Political Economy 104(5): 1010 1046. Area 31 (1): 67 74. Wiig Henrik. 2012. International Congress, San Francisco, CA, May 23 26, 2012.

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20 4 Yamokoshi, Al and Parenthood in the Asset Accumulation of Young Baby Boomers in the United Feminist Economics 12(1 2): 167 194.

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205 BIOGRAPHICAL SKETCH Jennifer Twyman received her Bachelor of Science an d Master of Science degrees in agricultural e conomics from the University of Missouri Columbia in 2002 and 2005 respectively. During her undergraduate career she mi nored in Spanish and international a griculture while also taking classwork focusing on environmental issues. Midwest (Missouri and Iowa). She also conducted research on the adoption of integrated natural resour ce management technologies in western Kenya. After spending a year working for the Missouri State Auditor doing economic evaluations of state programs, she pursued a PhD in the Food and Resource Economics d epartment at the University of Florida wh ere she specialized in international development and natural resource and environmental economics. She also obtained certificates in Latin American studies and tropical conservation and d evelopment. s dissertation analyzes the intra household dist ribution of assets and wealth in Ecuador. As part of her doctoral program, she spent the 2009 2010 academic year as a visiting scholar at FLACSO Ecuador assisting in the fieldwork and data collection for the Povert y Assets, and Gender Inequality project.