• TABLE OF CONTENTS
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 Front Cover
 Title Page
 Table of Contents
 Introduction
 Fertility patterns and family planning...
 An economic model of demand for...
 Empirical findings
 Conclusion
 Appendix
 Bibliography
 Advertising






Group Title: Latin American monographs; 2d ser., 18
Title: Family planning and family size determination
Publisher: University Press of Florida
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 Material Information
Title: Family planning and family size determination the evidence from seven Latin American cities
Series Title: Latin American monographs (Gainesville, Fla.)
Physical Description: 96 p. : ; 24 cm.
Language: English
Creator: Carvajal, Manuel J., 1946-
Geithman, David T., 1938- ( joint author )
Publisher: University Presses of Florida
Place of Publication: Gainesville
Publication Date: 1976
 Subjects
Subject: Birth control -- Statistics -- Latin America   ( lcsh )
Family size -- Mathematical models   ( lcsh )
Fertility, Human -- Mathematical models   ( lcsh )
Genre: bibliography   ( marcgt )
statistics   ( marcgt )
non-fiction   ( marcgt )
 Notes
Statement of Responsibility: M. J. Carvajal, David T. Geithman.
Bibliography: Bibliography : p. 93-96.
General Note: "A University of Florida book."
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Holding Location: University Press of Florida
Rights Management: Copyright 1976 by the Board of Regents of the State of Florida. This work is licensed under a modified Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/. You are free to electronically copy, distribute, and transmit this work if you attribute authorship. However, all printing rights are reserved by the University Press of Florida (http://www.upf.com). Please contact UPF for information about how to obtain copies of the work for print distribution. You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). For any reuse or distribution, you must make clear to others the license terms of this work. Any of the above conditions can be waived if you get permission from the University Press of Florida. Nothing in this license impairs or restricts the author's moral rights.
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Table of Contents
    Front Cover
        Front Cover
    Title Page
        Title Page 1
        Title Page 2
        Title Page 3
    Table of Contents
        Table of Contents
    Introduction
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
    Fertility patterns and family planning correlates
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
        Page 12
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
        Page 25
        Page 26
        Page 27
        Page 28
        Page 29
        Page 30
        Page 31
    An economic model of demand for children
        Page 32
        Page 33
        Page 34
        Page 35
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
        Page 42
        Page 43
        Page 44
    Empirical findings
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
        Page 51
        Page 52
        Page 53
        Page 54
        Page 55
        Page 56
        Page 57
        Page 58
        Page 59
        Page 60
        Page 61
        Page 62
        Page 63
        Page 64
        Page 65
        Page 66
        Page 67
        Page 68
    Conclusion
        Page 69
        Page 70
        Page 71
        Page 72
    Appendix
        Page 73
        Page 74
        Levels of statistically significant differences among family planning groups for tables 2.3 through 2.17
            Page 75
        Levels of statistically significant differences among family planning groups for tables 4.1 through 4.24
            Page 76
        Survey questionnaire
            Page 77
            Page 78
            Page 79
            Page 80
            Page 81
            Page 82
            Page 83
            Page 84
            Page 85
            Page 86
            Page 87
            Page 88
            Page 89
            Page 90
            Page 91
            Page 92
    Bibliography
        Page 93
        Page 94
        Page 95
        Page 96
    Advertising
        Page 97
        Page 98
Full Text















ami 1y nng nd Fml0
S ize etermnatio






Latin American Monographs


7 Second Series





Family Planning and Family
Size Determination


The Evidence from Seven Latin American Cities




18









Center for Latin American Studies
University of Florida







Family Planning and Family
Size Determination


The Evidence from Seven Latin American Cities










M. J. Carvajal
David T. Geithman













A University of Florida Book
The University Presses of Florida
Gainesville-1976









This contribution to Latin American population studies has been
funded by a grant from the Tinker Foundation.


Latin American Monographs-Second Series

Committee on Publications

W. W. McPherson, Chairman Paul L. Doughty
Graduate Research Professor Professor of Anthropology
of Agricultural Economics

R. W. Bradbury Lyle N. McAlister
Professor of Economics Professor of History

Raymond E. Crist Felicity M. Trueblood
Graduate Research Professor Assistant Professor
of Geography Latin American
Studies and History



A University of Florida Book
sponsored by the
Center for Latin American Studies

Copyright 1976 by the Board of Regents
of the State of Florida

All rights reserved

Printed by
Storter Printing Company, Incorporated
Gainesville, Florida



Library of Congress Cataloging in Publication Data

Carvajal, Manuel J 1946-
Family planning and family size determination.

(Latin American monographs: 2d ser., 18)
"A University of Florida book."
Includes bibliographical references.
1. Birth control-Latin America-Statistics.
2. Family size-Mathematical models. 3. Fertility,
Human-Mathematical models. I. Geithman, David T.,
1938- joint author. II. Title. III. Series:
Florida. University, Gainesville. Center for Latin
American Studies. Latin American monographs; 2d ser.,
18.
HQ766.5.L3C35 301.32'1 75-37700
ISBN 0-8130-0526-4























Contents


1. Introduction / 1

2. Fertility Patterns and Family
Planning Correlates / 7

3. An Economic Model of Demand
for Children / 32

4. Empirical Findings / 45

5. Conclusions / 69

Appendixes / 73

Bibliography / 93





















1. Introduction


AT ONE TIME popular in economic analysis, the Malthusian
population doctrine depicted human population growth as
essentially self-regulating by virtue of family size adjusting to the
economic conditions of human life. In its starkest and least sophisti-
cated version, the Malthusian theory of population posits a per-
fectly elastic long-run supply of labor at a real wage equal to a
technologically determined constant cost of producing human
beings. The level of this real wage (or cost of production) would
generally be so low as to imply the minimum standard of living
consistent with preservation of human life. But the historical expe-
rience of today's developed nations, which among other things
entailed a dramatic rise in real wages over the past 150 years, stood
in flat contradiction to the Malthusian oversimplification. Up to the
present time, the Malthusian model seems entirely irrelevant to
these developed nations. Furthermore, it is apparently true that no-
where in the world has a population growth induced by rising
income been sufficient by itself to halt the income rise.'
The unmitigated predictive failure of the Malthusian theory of
1. E. E. Hagen, "Population and Economic Growth," American Economic
Review 49 (June, 1959):310-27.








2 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
population ultimately led to the doctrine's complete rejection by
economists. Unhappily, it also resulted in the exclusion for many
decades of population theory from economics and of economics from
population theory. More recently, economists have expressed re-
newed interest in population theory and its reintegration with
economic analysis.2
Probably the most important reason behind the economists' re-
newed interest in population theory is the need to properly formu-
late population policy and develop efficacious guidelines for such
policy. Many contemporary attempts at identifying and under-
standing the determinants of human fertility and the causes of
fertility differentials among populations lack properly formulated
microtheoretical foundations. These efforts have focused on popula-
tion pyramids and past statistical trends, or on differential exposure
to the technology of contraception and differential usage of con-
traceptive techniques rather than on rationalizing the funda-
mental reasons that underlie parental desires to have and raise
children. One example of the phenomenon is the theory of demo-
graphic transition, which repeatedly has failed to fit both the
historical data of today's developed nations and the contemporary
data of the less-developed countries.3 With respect to past trends in
human fertility, the theory of demographic transition seeks to as-
certain only when birth rates began declining in different countries
and the pattern of this decline, but attempts no explanation of why
they fell. Accordingly, as regards future fertility trends in less-
developed countries, the theory cannot be expected to indicate when
birth rates will begin declining or the fundamental reasons why they
should fall.4
Moreover, the provision of family planning clinics and the distri-
bution of birth control devices are not sufficient conditions for fertil-
ity reduction. If the demand for children is inelastic, couples will be
insensitive to the availability of birth control devices no matter how
effective these devices may be and how wide a propaganda cam-
paign the family planning program may launch.5 Quite aside from
any issues surrounding the morality of the problem,

2. Milton Friedman, Price Theory, A Provisional Text (Chicago: Aldine
Publishing Co., 1962), pp. 207-8.
3. Riad B. Tabbarah, "Journal of Theory of Demographic Development,"
Economic Development and Cultural Change 19 (January, 1971):257-76 (see
especially p. 258).
4. Ibid., p. 258.
5. T. Paul Schultz, "A Preliminary Survey of Economic Analyses of Fer-
tility," American Economic Review 63 (May, 1973):71-78 (see especially p. 77).








Introduction 3
little in recent past experience has proven to be more futile
than to attempt to distribute contraceptives among people who
do not wish to use them and who have no felt need to adopt
their use. Parents must want to reduce family size, and only if
they feel themselves better off in some sense by having smaller
families can they reasonably be expected to do so. Modern
family planning and birth control measures simply make it
easier for couples to accomplish this end. Clearly, there is
nothing in this view that denies the usefulness of either re-
ducing couples' ignorance about birth control techniques or
providing contraceptives to those who desire to use them. But
if economic considerations strongly impinge on family-size
decisions, then policy measures designed to lower fertility rates
can anticipate a high degree of success only when they strike
directly at parents' basic economic motives for having chil-
dren.6

The present study rests on the basic premise that changes in fer-
tility are rational ways in which a population invests in its human
element as a response to its perception of changing economic oppor-
tunities. The theoretical framework employed is based on the prin-
ciple of long-term household utility maximization; thus, it implies
that people decide to have and raise children, or to refrain from
having and raising children, because they believe that by doing so
they and their families will be better off. In the theory of household
choice, the fundamental reasons for having and raising children are
expressed in terms of their associated costs and benefits. Costs are
expressed in terms of scarce resources that must be devoted to
having and raising children rather than to other activities, and in
terms of the psychic, nonpecuniary costs incurred by the household
in having and raising children. On the other hand, benefits that re-
sult from fertility decision-making increase the household's long-term
utility over what it would have been if the decision had not been
taken. These benefits accrue to the household either by an increase
in its long-term income stream because of an increase in productiv-
ity or by an increase in the consumer satisfaction of its members.
According to this formulation, the higher the expected benefits rela-
tive to the expected costs associated with having and raising chil-
dren, other things being equal, the higher will be the couple's level
of fertility.

6. David T. Geithman and M. J. Carvajal, "Population and the Economist:
The New Economic Approach to Fertility," Social Science 50 (Autumn,
1975):204-12.








4 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
This approach to explaining the occurrence of changes in fertility
through economic theory can be contrasted with the more traditional
demographic approach, which essentially describes data by histor-
ical or other associations. The traditional demographic approach
maintains that an analysis of past trends is sufficient for predicting
future phenomena. Of course, both approaches employ models to
statistically describe relationships among variables.
The economists' theory of household choice recognizes that all
factors influencing fertility decision-making cannot be reduced to
immediate economic necessity. Perhaps the most serious criticism of
the theory of household choice in identifying the ultimate factors
conducive to fertility decision-making is that, although in principle
it allows for consideration of both economic and noneconomic fac-
tors, in the theoretical structure thus far developed and in empirical
tests, noneconomic variables are inadequately dealt with, especially
as they affect the origins of tastes and preferences that enter the
utility function.7 Moreover, fertility patterns that arose because of
past necessity may continue after the original necessity has ceased
to exist, even when the population is faced with an apparent incon-
sistency between its fertility and its present needs.8 An example of
this phenomenon seems to be the failure of birth rates in some less-
developed countries to fall in response to increasing life expectancy,
despite the fact that high fertility patterns, which in the past may
have been imperative for the survival of the society, are no longer
so. The theory of household choice does contend, however, that
many of the ultimate forces influencing fertility decision-making are
economic in nature and that given sufficient time for adjustment or
sufficient intensity of economic inducement, population patterns will
respond in an economically rational way.
Most economists agree that at the aggregate level of analysis,
fertility rates are likely to have powerful repercussions on key eco-
nomic variables for development and growth, although at present
differences of opinion exist on the direction of this impact. The evi-
dent majority position contends that a high fertility rate presents an
obstacle to economic growth, especially in less-developed countries,9

7. Richard A. Easterlin, "Towards a Socioeconomic Theory of Fertility:
Survey of Recent Research on Economic Factors in American Fertility," in
Fertility and Family Planning: A World View, ed. S. J. Behrman et al. (Ann
Arbor: The University of Michigan Press, 1969), pp. 127-56.
8. Sydney H. Coontz, Population Theories and the Economic Interpretation
(London: Routledge & Kegan Paul Ltd., 1957), pp. 13-21.
9. For some arguments, see Frank Lorimer, "Issues of Production Policy,"
in The Population Dilemma, ed. Phillip M. Hauser (Englewood Cliffs: Prentice-








Introduction 5


while other economists argue that higher fertility actually can stim-
ulate growth.'o Perhaps the primary argument of the majority group
is that high birth rates, by their contribution to high dependency
ratios, can be a major determinant in lowering aggregate saving
rates and thus the potential growth rate. A number of prominent
economists have long maintained that an inverse relationship should
theoretically exist between a society's birth rate and its saving po-
tential," while more recently Leff has suggested that a central
variable in explaining the large discrepancy in aggregate saving
rates between higher- and lower-income countries is the occurrence
of high birth rates and dependency ratios characteristic of less-
developed countries.12
The determinants of fertility can be classified as demand variables
and other variables. Demand variables are those that determine a
couple's desired family size and their motivation to control fertility
based on (1) the price of goods and services complementary to and
competitive with having and raising children, (2) income and time
considerations, and (3) uncertainty. The other types of variables are
related to age, the availability and diffusion of alternative contra-
ceptive techniques, and other biological-medical considerations.
The purposes of this study are to estimate past fertility patterns
experienced by a large sample of Latin American women; to analyze
the correlates of their family planning activities; to formulate an

Hall, 1969), pp. 168-202; and Arthur McCormack, The Population Problem
(New York: Thomas Y. Crowell, 1970), p. 136.
10. For some arguments, see David M. Heer, Society and Population (Engle-
wood Cliffs: Prentice-Hall, 1968), p. 91; Albert O. Hirschman, The Strategy of
Economic Development (New Haven: Yale University Press, 1958); Simon
Kuznets, "Population Change and Aggregate Output," in Demographic and
Economic Change in Developed Countries, National Bureau of Economic Re-
search (Princeton: Princeton University Press, 1960), pp. 324-40; and Joseph J.
Spengler, "Population as a Factor in Economic Development," in Population
and World Politics, ed. Phillip Hauser (Glencoe: The Free Press, 1964), pp.
162-89 (see especially p. 172).
11. Milton Friedman, A Theory of the Consumption Function (Princeton:
Princeton University Press, 1957), p. 123; Hans W. Singer, "Population and
Economic Development," in International Development: Growth and Change
(New York: 1954 World Population Conference, 1964), pp. 80-81; and Joseph
J. Spengler, "The Population Obstacle to Economic Betterment," American
Economic Review 41 (May, 1951):343-54.
12. Nathaniel H. Leff, "Dependency Rates and Savings Rates," American
Economic Review 59 (December, 1969): 886-96, and "Dependency Rates and
Savings Rates: Reply," American Economic Review 61 (June, 1971):476-80.
Leff's conclusions are sharply challenged by Nassau A. Adams, "Dependency
Rates and Savings Rates: Comment," American Economic Review 61 (June,
1971):472-75; and Kanhaya L. Gupta, "Dependency Rates and Savings Rates:
Comment," American Economic Review 61 (June, 1971):469-71.








6 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
economic model for parental demand for children; and, on the
premise that parents' preferences for children have some measurable
impact on observed family size, to empirically test the demand-for-
children model after controlling for the effects of age on child-
bearing. The methodology analyzes simultaneously three samples of
a given population residing in a common geographical area. One of
the sample groups has been exposed to sophisticated family plan-
ning techniques characterized by relatively low failure rates, such as
sterilization, oral contraception, and the diaphragm. A second group
has been exposed to cruder and less reliable forms of contraception
such as the condom, jellies, the douche, the rhythm method, and
coitus interruptus. The third sample group of women has not been
exposed to family planning practices. The study attempts to explore
statistically significant differences in fertility among the estimates of
the parameters of the variables making up the children-demand
equations.
The data used for estimating the equations are obtained from the
Urban Fertility Surveys sponsored by the United Nations Center for
Latin American Demography (CELADE) in seven major Latin
American cities for which homogeneous data were collected be-
tween 1961 and 1965. These cities are Buenos Aires, Rio de Janeiro,
BogotA, San Jos6, Mexico, Panama, and Caracas. They constitute
the capital cities'1 of countries comprising 75 per cent of the area
and 72 per cent of the population of Latin America.
13. At the time the survey in Brazil was taken, Brasilia was the capital.
Since it had not become the capital until 1960, however, Rio de Janeiro pre-
sented more features characteristic of a capital city than Brasilia.





















2. Fertility Patterns and Family
Planning Correlates









IN ATTEMPTING to assess the determinants, or some of the deter-
minants, of fertility behavior and family size, this chapter first
classifies the women included in the study by family planning status.
It then estimates the patterns of past fertility experienced by these
women according to two fertility criteria and by family planning
status. Finally, to analyze the correlates of various family planning
activities, this chapter tests for statistically significant differentials
among the individual members of the sample, grouped by family
planning status, for several key variables that are postulated to be
important to the individual's decision to employ birth control tech-
niques and to have and raise children. These variables are tradition-
alism, exposure to media, pattern of household authority, extent of
urban influence, marital status, age, income, female participation in
the work force, formal education of the woman, aspirations of socio-
economic upward mobility and past occupational mobility, and
parental expectations of a high probability of infant or child mor-
tality. In subsequent chapters an empirical model of fertility be-
havior will be developed and estimated for the women in the sample,
grouped by family planning status, in order to infer the responsive-








8 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
ness of household fertility to systematic changes in the environment
of the women and their households.


FAMILY PLANNING AND FERTILITY PATTERNS
In the seven major Latin American cities covered by the Urban
Fertility Surveys, which constitute the data base of this study, a
total of 12,663 married or previously married women were inter-
viewed in regard to family planning activities and usage of contra-
ceptive techniques. The number of married or previously married
women interviewed in each city was approximately the same, rang-
ing from 1,605 in San Jos6 to 2,031 in Rio de Janeiro. Single women
were not questioned about their usage of contraceptive measures,
and, therefore, they were specifically excluded from the sample em-
ployed in this study. From the married or previously married women
interviewed it was learned whether or not at the time of the survey
they were using or had ever used the following means of contracep-
tion: sterilization, oral contraception, the diaphragm, the condom,
chemical jellies, the douche, the rhythm method, or coitus inter-
ruptus. These techniques can be viewed as either sophisticated or
unsophisticated according to their expected failure rates.1 While the
failure rates of sterilization and oral contraception are negligible,
and that of the diaphragm is as low as 4 pregnancies per 100 women-
years, the failure rates of the other contraceptive techniques sur-
veyed are considerably higher: as high as 28 pregnancies per 100
women-years for the condom, 43 for chemical jellies, 41 for the
douche, 38 for the rhythm method, and 38 for coitus interruptus.2
Based on these widely different failure rates, the women contained
in our sample are classifiable by family planning status according to
contraceptive techniques employed. For the purposes of this study,
women who had been sterilized prior to the time of the interview, or
1. The basis for calculating the failure rate was developed by R. Pearl in a
1982 article in "Human Biology," and is known as Pearl's formula. It is equal
to total accidental pregnancies divided by total number of months of exposure,
the whole ratio multiplied by 1,200.
2. John Peel and Malcolm Potts, Textbook of Contraceptive Practice (Cam-
bridge, Great Britain: Cambridge University Press, 1969), p. 47; Gregory
Pincus, The Control of Fertility (New York: Academic Press, 1965), p. 226;
Anna L. Southam, "Contraceptive Methods: Use, Safety, and Effectiveness," in
Family Planning and Population Programs, Planning Committee for the Con-
ference on Family Planning Programs (Chicago: The University of Chicago,
1966), pp. 375-86 (see especially p. 386); and Christopher Tietze, "Modem
Methods of Birth Control: An Evaluation," in Family Planning Programs, ed.
Bernard Berelson (New York: Basic Books, Inc., 1969), pp. 183-91 (see es-
pecially p. 185).








Fertility Patterns and Family Planning 9
who were using or had used in the past oral contraception or the
diaphragm, are classified as sophisticated family planners. Unsophis-
ticated family planners are women who, at the time of the interview,
were using the condom, jellies, or the douche as a means of contra-
ception, or who had made use of one of these techniques in the past
but had never been sterilized or employed oral contraception or the
diaphragm. Women who had never used any of the forms of contra-
ception in the above two categories are classified as nonplanners.
Unfortunately, the data available do not include frequency or dura-
tion of use of contraceptive techniques. A woman using the pill once
is classified as a sophisticated planner and considered equivalent to
a person using the diaphragm regularly. With this limitation, the
number of women in each city falling within each family planning
category and the percentage distribution of the sample by family
planning status are presented in Table 2.1.
In all cities except Buenos Aires and San Jos6, the percentage of
nonplanners exceeds the total percentage of sophisticated and un-
sophisticated family planners, and in all cities but PanamA the per-
centage of unsophisticated planners is considerably larger than the
percentage of sophisticated planners. With the exception of PanamA
and Rio de Janeiro, sophisticated family planners in every city con-
stitute less than 10 per cent of the total sample.
When all cities are taken together, the most widely used method
of contraception is the condom, followed closely by the douche, the
rhythm method, and coitus interruptus, in that order. As can be ob-
served in Table 2.2, relative preferential use of the various means of
contraception is not distributed homogeneously among all cities. In
Buenos Aires, San Jose, and Caracas the condom is the most popular
contraceptive technique, while the douche is most widely used in
Rio de Janeiro and PanamA, and the rhythm method is the technique
most often practiced in BogotA and M6xico.
Two alternative measures of fertility are used throughout this
study. These are: (1) the total number of pregnancies the woman
has experienced, whether or not they resulted in live births, and (2)
the number of surviving sons and daughters at the time of the inter-
view. For each of the three family planning categories, the average
number of pregnancies per woman and the average number of sur-
viving children per woman are shown in Tables 2.3 and 2.4, respec-
tively. Perhaps it would be expected a priori that the fertility of non-
planners would exceed that of unsophisticated family planners, and
that the fertility of unsophisticated planners in turn would exceed
the fertility of sophisticated planners because of the letters' better


















TABLE 2.1. Classification of Women by City and Family Planning Status


Family planning status
Sophisticated Unsophisticated
planners planners Nonplanners Total
City Number Per cent Number Per cent Number Per cent Number Per cent

Buenos Aires 53 3.1 1,187 69.0 479 27.9 1,719 100.00
Rio de Janeiro 243 12.0 680 33.5 1,108 54.5 2,031 100.00
Bogota 78 4.3 527 28.9 1,221 66.8 1,826 100.00
San Jos6 154 9.6 717 44.7 734 45.7 1,605 100.00
Mexico 186 9.8 421 22.3 1,284 67.9 1,891 100.00
Panami 442 24.0 427 23.2 970 52.8 1,839 100.00
Caracas 148 8.4 668 38.1 936 53.5 1,752 100.00
Total for all cities 1,304 10.3 4,627 36.5 6,732 53.2 12,663 100.00











TABLE 2.2. Classification of Women by City and Use of Alternative Contraceptive Methods, in Per cent



Means of contraception
City Sterilization Oral Diaphragm Condom Jelly Douche Rhythm Coitus interruptus

Buenos Aires 0.3 1.0 1.7 41.9 8.6 16.8 18.1 36.1
Rio de Janeiro 5.3 3.6 3.5 10.9 5.1 20.3 14.4 4.9
Bogota 0.9 2.0 1.8 8.9 5.6 10.5 15.7 14.0
San Jose 5.0 1.7 3.5 30.6 4.1 14.7 17.7 19.9
Mexico 1.7 5.3 3.6 8.2 3.8 12.8 13.2 6.4
Panama 16.6 3.4 5.8 13.9 4.4 21.3 13.1 8.4
Caracas 4.5 0.9 3.4 24.0 1.7 19.1 14.3 17.3
Total for all cities 5.0 2.6 3.4 19.2 4.7 16.5 15.1 14.8









12 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

ability to control the number of their progeny. However, the empiri-
cal findings show exactly the opposite. The average number of preg-
nancies and living children among sophisticated and unsophisticated
planners is consistently larger than the average number of preg-
nancies and living children among nonplanners. These facts stand in
stark contradiction to the often-repeated platitude that the major
force keeping families relatively small is contraception.3


TABLE 2.3. Average Number of Pregnancies per Woman, by Family
Planning Status*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 2.63h 2.32dj 2.12c
(1.97) (1.53) (1.84)

Rio de Janeiro 3.21n 3.26mo 3.22n
(1.91) (2.04) (2.45)

Bogota 4.62nj 4.74mi 3.97be
(2.13) (2.33) (2.52)

San Jose 4.83fi 4.35bi 3.91a
(2.34) (2.22) (2.68)

Mexico 4.83 4.89mi 4.29ae
(2.22) (2.31) (2.62)

Panam~ 4.30i 3.87a 3.31ae
(1.99) (2.15) (2.37)

Caracas 4.26nj 4.06mi 3.71be
(2.37) (2.43) (2.73)


See Appendix I for levels
differences.


of statistically significant


At least two explanations can be attempted for this phenomenon.
The first, and most superficial, is that the higher level of fertility
among family planners is due to their adopting birth prevention
techniques after the size of their family is larger than average.4 In

3. See, for example, Ronald Freedman, Pascal K. Whelpton, and Arthur A.
Campbell, Family Planning, Sterility, and Population Growth (New York:
McGraw-Hill Book Co., 1959), p. 55.
4. Donald J. Bogue, Principles of Demography (New York: John Wiley and
Sons, Inc., 1969), p. 723.









Fertility Patterns and Family Planning 13

other words, the use of contraception techniques is seen as a conse-
quence of higher fertility and not as a cause of lower fertility. Al-
though this explanation may be true of a certain portion of every
population, it hardly seems capable of explaining the broad statisti-
cal trends reported in Tables 2.3 and 2.4. A more plausible explana-
tion for the higher fertility of family planners relative to nonplan-
ners is that the comparisons presented in Tables 2.3 and 2.4 do not

TABLE 2.4. Average Number of Surviving Children per Woman,
by Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 1.79no 1.84mi 1.55me
(1.04) (1.17) (1.58)
Rio de Janeiro 2.49no 2.57mj 2.38mf
(1.54) (1.71) (2.03)
Bogotg 3.71n1 3.96mi 3.27d
(1.96) (2.10) (2.35)
San Jose 3.98f 3.62bi 3.14a
(2.15) (2.05) (2.51)
Mexico 3.83ni 3.95mi 3.34ae
(2.07) (2.23) (2.39)
Panama 3.73ei 3.15a 2.72a
(1.88) (2.01) (2.19)
Caracas 3.60nj 3.41mi 3.03b
(2.27) (2.22) (2.55)


See Appendix I for levels of statistically significant
differences.

control for differentials in other aspects of individual and family life
beyond the single dimension of usage of birth control techniques.
For example, one factor contributing to the higher fertility found
among family planners may be the higher percentage of female par-
ticipation in the labor force, or employment outside the household,
among nonplanners. Another factor may be the higher level of in-
come received by families that plan their number of offspring. In
short, a comprehensive understanding of fertility differentials must
go beyond a simple comparison of fertility levels by use or lack of








14 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
use of contraceptive techniques and include an analysis of the con-
ditions surrounding differential use of contraception as well as the
woman's and/or parents' motivation to control family size.

SOME CORRELATES OF FAMILY PLANNING

Traditional Values
The widespread usage of contraceptive methods in the United States
and Western Europe is indicative of the extent of attitudinal change
and modernization of outlook that has pervaded these societies.
Birth control is now integrated into these countries' life styles. But
in less-developed countries such as those embraced by this study,
traditionalism plays a more important role in shaping people's de-
cisions in almost every aspect of life, and the adoption of some form
of contraception is likely to conflict with deeply held traditional
values. As a general rule, high fertility levels have been upheld and
glorified traditionally and religiously, in part because until only re-
cently high fertility rates were essential to the preservation of
society as compensation for very high mortality rates. The internal-
ization of high fertility values is reflected particularly in the teach-
ings of the Roman Catholic Church, which in the past has main-
tained an unequivocal attitude toward contraception, viz., the aim of
marriage is the procreation of children, and any artificial inter-
ference with this natural process is contrary to the laws of God.
Thus, an inverse empirical variation is expected to exist between
the strength of traditionalism and the use of contraception. A nine-
point scale of traditionalism has been developed by the United Na-
tions Center for Latin American Demography (CELADE) as part
of the Urban Fertility Surveys. Lower scores in this scale represent
a lesser regard for traditional values by the respondent, while higher
scores are indicative of more traditionally oriented respondents.
Average values in the scale of traditionalism by family planning
category for the seven cities are shown in Table 2.5. As expected,
the scores on traditionalism of sophisticated planners are generally
significantly lower than the scores of unsophisticated planners, and
the scores of unsophisticated planners are lower than the scores of
nonplanners.
The diffusion of modernizing ideas through the mass media tends
to undermine the role of traditionalism in life by making people
aware of alternative life styles. In particular regard to fertility be-
havior, exposure to mass media is conducive to greater use of con-
traception by increasing the public's knowledge about the existence









Fertility Patterns and Family Planning 15

and availability of alternative means of contraception as well as
about their respective advantages and drawbacks.5 Furthermore,
exposure to mass media has the additional economic impact of help-
ing to create a demand for goods and services that are competitive
with having and raising children, such as travel, entertainment, con-
sumption durables, etc., thus motivating the individual to reduce


TABLE 2.5. Average Values in the Scale of Traditionalism, by
City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 2.83ei 4.07ai 4.43ae
(2.12) (2.48) (2.46)

Rio de Janeiro 4.67fi 5.12bi 5.64ae
(2.42) (2.43) (2.35)

Bogota 4.62e 5.71a 6.21ae
(2.32) (2.06) (1.93)

San Jose 5.01ei 5.53a 5.81af
(2.26) (2.19) (2.08)
M6xico 4.60ei 5.12ai 5.65ae
(2.26) (2.21) (2.21)

Panami 4.57"1 4.42mj 4.75df
(2.27) (2.31) (2.22)

Caracas 4.91fi 5.41bi 5.87ae
(2.53) (2.37) (2.25)


See Appendix I
differences.


for levels of statistically significant


desired family size. Therefore, it is expected that exposure to mass
media and use of contraceptive techniques are directly related.
Tables 2.6 and 2.7 present the percentages of women who are
regularly exposed to the written media, by family planning status.
An analysis of these differentials conforms to expectations. When-
ever the differences are statistically significant, sophisticated plan-
ners are generally more exposed to the written media than un-
sophisticated planners, and the latter are in turn more exposed to

5. Arthur McCormack, The Population Problem (New York: Thomas Y.
Crowell, 1970), p. 171.









16 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

the written media than nonplanners, tending to confirm the hypoth-
esis that greater exposure to modernizing influences through mass
communication is conducive to adoption of contraceptive practices.
Another aspect of traditionalism is the pattern of authority within
the family, which also can be hypothesized to significantly affect
fertility decision-making. Since the woman exclusively bears the
biological burdens of childrearing, it may be expected that she
would be more motivated to use contraception than the husband.

TABLE 2.6. Percentage of Women Reading Newspapers Regularly,
by City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 0.849no 0.863m 0.850"
(0.361) (0.344) (0.358)
Rio de Janeiro 0.782ni 0.789mi 0.644ae
(0.414) (0.408) (0.479)
Bogota 0.948fi 0.860bi 0.692ae
(0.222) (0.348) (0.462)
San Jose 0.974ei 0.888ai 0.837ae
(0.160) (0.315) (0.370)

Mexico 0.860ni 0.841mi 0.649ae
(0.348) (0.366) (0.478)
Panam 0.946ho 0.965dj 0.938mf
(0.227) (0.184) (0.241)
Caracas 0.845ni 0.847mi 0.629ae
(0.364) (0.360) (0.483)


See Appendix I
differences.


for levels of statistically significant


Thus, all other things constant, increased sharing in decision-making
between husband and wife is likely to result in greater usage of
contraceptive methods.
The authority structure in the family is measured in the Urban
Fertility Surveys with a dummy variable that records whether or not
the husband alone makes the most important decisions in the house-
hold. Since a higher degree of male authority over the woman in the
household or, in other words, a more unilateral pattern of household
decision-making is expected to lead to less use of contraception, the









Fertility Patterns and Family Planning 17

percentage of households in which the husband alone makes the
most important decisions is hypothesized to be smaller among fam-
ily planners than among nonplanners. A comparison of these per-
centages by family planning status in Table 2.8, however, reveals
exactly the opposite relationship, namely that whenever the differ-
ences are statistically significant, the percentage of households in
which the husband alone makes the most important decisions is gen-

TABLE 2.7. Percentage of Women Reading Magazines Regularly,
by City and Family Planning Status


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 0.717no 0.748mi 0.672me
(0.455) (0.434) (0.470)

Rio de Janeiro 0.745ni 0.721mi 0.570ae
(0.437) (0.449) (0.495)
Bogot$ 0.859ei 0.567a 0.354a
(0.350) (0.496) (0.478)
San Jos 0.708e 0.550ai 0.448a
(0.456) (0.498) (0.498)
Mgxico 0.747ni 0.732mi 0.543ae
(0.436) (0.444) (0.498)
Panama 0.781hk 0.822di 0.740e
(0.414) (0.383) (0.439)
Caracas 0.797ni 0.769mi 0.580ae
(0.403) (0.422) (0.494)


See Appendix I for levels of statistically significant
differences.

erally larger among family planners than among nonplanners. On
the other hand, the expected pattern of male dominance in decision-
making being linked with higher fertility levels is present when
comparing sophisticated and unsophisticated planners in BogotA
and Panama, the only two cities in which the differences between
sophisticated and unsophisticated planners are statistically signifi-
cant: in these two cities the percentage of households in which the
husband alone makes the most important decisions is greater among
unsophisticated planners than among sophisticated planners.









18 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

Another factor influencing the individual's adherence to and re-
spect for traditional values is his or her place of birth. Other things
being equal, the values of women born and raised in larger cities are
likely to be less traditional than the values of women living in large
cities but born and raised in smaller towns or rural areas. As Freed-
man and Slesinger point out, attitudes toward contraception and
fertility among rural immigrants in an urban population are "af-


TABLE 2.8. Percentage of Households in Which the Husband Alone Makes
Most Important Decisions, by City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 0.113no 0.129mi 0.081me
(0.319) (0.336) (0.274)
Rio de Janeiro 0.173no 0.182ml 0.153mh
(0.379) (0.386) (0.361)
Bogota 0.051gk 0.121co 0.114cn
(0.222) (0.327) (0.318)
San Jose 0.117no 0.139mo 0.119m
(0.322) (0.347) (0.323)
Mexico 0.113no 0.135m 0.130m
(0.317) (0.343) (0.336)
Panam~ 0.088fo 0.138bi 0.085me
(0.284) (0.345) (0.278)
Caracas 0.196nk 0.198mi 0.138c
(0.398) (0.399) (0.345)


See Appendix
differences.


I for levels of statistically significant


fected by both the cultural patterns of their farm origins and [those]
at their urban destinations";6 the extent of usage of contraception is
expected to change by modification of rural values under the impact
of urban living and urban attitudes.
Table 2.9 presents the percentage of women by family planning
status who were born and raised in the capital city where the sur-

6. Ronald Freedman and Doris P. Slesinger, "Fertility Differentials for the
Indigenous Non-Farm Population of the United States," Population Studies 15
(November, 1961):161-73 (see especially p. 161).









Fertility Patterns and Family Planning 19
vey was conducted. Although in many cases there are no statistically
significant differences among the three family planning categories,
the trend in those cases in which significant differences are recorded
conforms to expectations: the percentage of women born and raised


TABLE 2.9. Percentage of Women Born and Raised in the Capital City,
by City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 0.566nj 0.519mi 0.415be
(0.500) (0.500) (0.493)
Rio de Janeiro 0.535ni 0.509mi 0.418ae
(0.500) (0.500) (0.493)
Bogotg 0.282n1 0.275mi 0.208de
(0.453) (0.447) (0.406)
San Jose 0.4871n 0.533mi 0.426de
(0.501) (0.499) (0.495)
Mexico 0.554ei 0.409ao 0.407an
(0.498) (0.492) (0.491)
Panama 0.416no 0.419mo 0.400'm
(0.493) (0.494) (0.490)
Caracas 0.223no 0.258mk 0.220mg
(0.418) (0.438) (0.415)


*
See Appendix
differences.


I for levels of statistically significant


in the capital city is greater among family planners than among non-
planners.

Marital Status
Another important variable in explaining the differential use of con-
traceptive techniques pertains to prevailing sexual institutions in a
society, as reflected in the marital structure of its population. Sexual
intercourse is not an isolated phenomenon but rather is deeply im-
bedded in a complex set of social and cultural norms and institu-
tions. Almost every society possesses its own set of such norms,
which establishes the pattern of accepted sexual behavior and cen-








20 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
sures deviations from it.7 It is expected that the nature of such pat-
terns of sexual behavior, the extent to which they are enforced, and
the possible consequences of deviant behavior play an important
role in determining the use of contraception.
The type of social response that follows nonmarital sex or the
establishment of consensual union may be an important factor in de-
termining the use of contraception. If social norms are such that
marriage is forced after nonmarital sex that results in pregnancy, the
deviation from the established pattern of childbearing within the
family is self-corrective. But if the prospective consequence of non-
marital sex is illegitimacy for the child and if strong sanctions
against illegitimacy exist, a greater motivation to avoid pregnancy
is likely to exist, which may translate into the use of contraception.
The incidence of consensual union by family planning category is
summarized in Table 2.10. An analysis of this table reveals that,
although most of the comparisons are not statistically significant, the
differences that are, with the exception of those for PanamA, show
that the incidence of consensual union among family planners is
higher than among nonplanners, which lends support to the hypoth-
esis that negative sanctions on illegitimacy act as an incentive to pre-
vent children through the use of contraception.

Fecundity
The fecund years of a woman are bounded by menarche at the lower
age limit and by menopause at the upper end. Fecundity cannot be
measured accurately because it refers to childbearing potential and
not to an actual condition. As Petersen points out, the only proof of
fecundity is conception of a child; once conception occurs, however,
the event is no longer potential but actual, changing the definition
from fecundity to fertility.8 Additional complications in estimating
fecundity arise out of the use of contraceptive techniques by most
cultures, even in ancient times. For example, contraception is found
in the Old Testament by coitus interruptus, in ancient Egypt by
blocking the cervix with leaves and cloth, and in ancient Greece by
homosexuality and infanticide.9 Nevertheless, Sauvy estimates that
for a hypothetical population, "if a couple comes together at puberty,
stays together until the woman's menopause and has no recourse to
7. Moni Nag, "Family Type and Fertility," World Population Conference
2 (New York: United Nations, 1967):160-63 (see especially p. 161).
8. W. Petersen, Population (London: The MacMillan Co., Ltd., 1965), p.
538.
9. Paul R. Ehrlich and Anne H. Ehrlich, Population, Resources, Environ-
ment (San Francisco: W. H. Freeman and Company, 1970), pp. 210-12.









Fertility Patterns and Family Planning 21

contraception, its average number of children will be about ten. In
a population living in the best possible conditions this would prob-
ably increase to twelve. The dispersal around this mean would be
large: some couples are sterile, others can have twenty to twenty-five
children."10 Thus, the fecundity distribution of a population, i.e.,
the mutually exclusive and exhaustive list of the fecundity of all
women of that population, is likely to have a large variance.

TABLE 2.10. Percentage of Women Consensually Married, by City and
Family Planning Status


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 0.019n 0.008ml 0.017mh
(0.137) (0.091) (0.128)

Rio de Janeiro 0.082go 0.049cj 0.077mf
(0.275) (0.215) (0.266)

Bogota 0.013hk 0.047do 0.061cn
(0.113) (0.213) (0.240)

San Jose 0.091no 0.109mo 0.091mn
(0.288) (0.312) (0.288)
Mexico 0.065n1 0.086mo 0.100dn
(0.246) (0.280) (0.301)
Panama 0.312f 0.391bi 0.297me
(0.464) (0.489) (0.457)
Caracas 0.162"n 0.175mo 0.185"
(0.370) (0.380) (0.388)


See Appendix I for levels
differences.


of statistically significant


The age of the woman is one central and objective biological de-
terminant of her fecundity. Fecundity seems to reach a peak be-
tween the ages of 20 and 34 and decreases markedly after age 35
until it disappears entirely with the advent of menopause." The

10. Alfred Sauvy, General Theory of Population (New York: Basic Books,
Inc., 1969), p. 349.
11. Louis Henry, "Some Data on Natural Fertility," Eugenics Quarterly
8 (March, 1961):81-91; and Edward G. Stockwell, Population and People
(Chicago: Quadrangle Books, 1968), p. 104.








22 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
percentage of women who are sterile increases with the age bracket,
and by the time a woman reaches 50 years of age she is likely to be
unable to bear children.12 Between menarche and age 20 and again
between age 35 and menopause the woman undergoes periods of
subfecundity in which the chances of conception, given a fixed
amount of exposure, are less than they were between ages 20 and
34.13 The periods of adolescent and senescent subfecundity also in-
volve greater dangers associated with pregnancy. The incidence of
foetal death is higher among very young and older mothers than
among women of other ages, reaching its lowest level among mothers
in their middle or late twenties.14 Coale and Tye contend that preg-
nancies occurring shortly after menarche may damage fecundity at
subsequent ages.15 Age can exert opposite effects on the differential
use of contraception. On the one hand, it could be expected that
older women are more motivated than younger women to control
fertility through the use of contraception because, other things be-
ing equal, older women are more likely to have attained their de-
sired family size while younger women are more likely to have
fewer children than they desire in their lifetime. On the other hand,
younger women may be more actively engaged in the labor force
(work outside the home), and thus may have more of an economic
interest in avoiding pregnancy due to the greater amount of lost
work time and earnings than women not engaged in outside em-
ployment. Moreover, older women may tend to be more traditionally
oriented, and thus have recourse to contraception less often than
younger women. Table 2.11 presents the average age of the women
in the three family planning categories. The results lend support to
the hypothesis that younger women generally use contraception
more often than older women.

Income
As noted by many researchers, contraception seems to be used more
often by higher-income people than by lower-income families.'1

12. Henry, op. cit., p. 83.
13. Petersen, op. cit., p. 176; and Stockwell, op. cit., p. 195.
14. Ronald Freedman, Lolagene C. Coombs, and Judith Friedman, "Social
Correlates of Fetal Mortality," Milbank Memorial Fund Quarterly 44 (July,
1966):327-44 (see especially p. 827).
15. A. J. Coale and C. Y. Tye, "The Significance of Age-Patterns of Fertility
in High Fertility Populations," Milbank Memorial Fund Quarterly 39 (October,
1961): 631-46.
16. Carmen A. Mir6 and Ferdinand Rath, "Preliminary Findings of Com-
parative Fertility Surveys in Three Latin American Cities," Milbank Memorial
Fund Quarterly 48 (January, 1965):36-62; S. Mitra, "Occupation and Fertility









Fertility Patterns and Family Planning 23

This is often adduced as stemming from a lack of knowledge of and
accessibility to contraceptive techniques, from an insufficiency of
funds to pay for these techniques even when available, and from
a lack of awareness of the benefits involved in controlling fertility
among the lower income brackets of the population.17 Not only does
the use of contraception tend to increase with the level of income,
but also adoption of more sophisticated contraceptive techniques is

TABLE 2.11. Average Age of the Women in the Sample, by Family
Planning Status


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 34.75gi 36.63ci 38.19ae
(8.69) (7.49) (8.37)
Rio de Janeiro 33.84ni 33.79mi 35.87ae
(7.42) (7.94) (9.26)

Bogota 33.64n" 32.58m' 32.94'
(6.81) (7.02) (8.43)
San Jose 35.92eo 32.31ai 35.31me
(7.36) (7.37) (8.80)
Mexico 33.04 34.38bi 36.56ae
(7.27) (7.51) (8.84)
Panama 34.63ei 31.88aj 33.14af
(7.77) (7.88) (9.01)

Caracas 34.41e 31.50ai 34.30me
(7.52) (7.49) (9.36)


See Appendix I for levels
differences.


of statistically significant


more likely to occur among higher-income couples. The expected
relationship between income and fertility is discussed more fully and
in a more rigorous economic context in Chapter 3.

in the United States," Eugenics Quarterly 13 (June, 1966):141-46 (see
especially p. 141); and Pascal K. Whelpton, A. A. Campbell, and J. E. Patter-
son, Fertility and Family Planning in the United States (Princeton: Princeton
University Press, 1966), p. 177.
17. Catherine S. Chilman, "Fertility and Poverty in the United States:
Some Implications for Family-Planning Programs, Evaluation, and Research,"
Journal of Marriage and the Family 30 (May, 1968):207-27 (see especially
p. 217).









24 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

The level of income of the household is approximated in this study
by a discrete variable measuring household expenditure. This vari-
able consists of a 0-9 discrete scale and is used for standardization
purposes, since the currency unit varies from country to country. In
order to obtain values for the income scale, households are distrib-
uted in deciles ranking from lowest to highest tenth. Households in
the lowest decile are then assigned an income value of zero, those

TABLE 2.12. Average Scores for Income, by City and Family
Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 5.66ei 4.55ai 3.76ae
(3.01) (2.48) (2.70)

Rio de Janeiro 4.91fi 4.49bi 3.45ae
(2.63) (2.44) (2.39)

Bogota 7.18e 5.48al 3.97ae
(1.84) (2.19) (2.17)
San Jose 5.31ei 4.28ai 3.34ae
(2.07) (1.99) (1.97)
Mexico 6.50 6.04bi 4.32ae
(2.26) (2.40) (2.39)

Panama 5.58gi 5.26c0 4.25ae
(2.44) (2.58) (2.40)

Caracas 6.37f 5.92bi 4.78ae
(2.58) (2.22) (2.37)


See Appendix
differences.


I for levels of statistically significant


in the next-to-lowest decile are assigned a value of one, and so forth;
households in the highest-income decile are assigned a value of
nine.
Table 2.12 presents the average values in terms of the income
scale for the three family planning groups. A comparison of these
groups shows that sophisticated planners have a significantly higher
level of income than unsophisticated planners, and that unsophisti-
cated planners have a significantly higher level than nonplanners.








Fertility Patterns and Family Planning 25
Thus, use of contraception appears to be strongly and negatively
associated with income.

Female Employment
Participation of women in the labor force tends to decrease norms
of traditionalism in individual behavior. To the extent that having
and raising children is incompatible with other values and interests
such as female employment outside the home,18 women who are
employed might be expected to be more motivated to utilize family
planning techniques than women who are not employed outside the
home. Moreover, female participation in the labor force tends to
increase the degree of authority exercised by the woman in family
decision-making, including matters of childbearing.1" Since the
woman must bear the biological burden of childbearing, she might
be more motivated to use contraception than the husband, all other
things being equal. Thus, female labor force participation could
lead to a differentially high rate of family planning. The anticipated
association between fertility and female employment in the labor
force is discussed in a more rigorous economic framework in
Chapter 3.
An analysis of female participation in the labor force by family
planning status is presented in Table 2.13, where a dummy variable
records whether or not the woman is employed outside the home.
The values of Table 2.13, however, seem to contradict the preceding
arguments: the percentage of working women is higher in the non-
planning group than in the two family planning groups. A more de-
tailed and economic analysis of the empirical fertility-employment
relationship is postponed to Chapter 4.

Female Education
Two proxies will be subsequently used to test the quality-of-child
argument in the economic model of the demand for children de-
veloped in Chapter 3. The first of these proxies is the woman's level
of formal education. Stycos, among others, has found a positive asso-
ciation between use of contraception and the woman's level of for-

18. Richard A. Easterlin, "Towards a Socioeconomic Theory of Fertility:
Survey of Recent Research on Economic Factors in American Fertility," in
Fertility and Family Planning: A World View, ed. S. J. Behrman et al. (Ann
Arbor: The University of Michigan Press, 1969), p. 132.
19. Robert H. Weller, "The Employment of Wives, Dominance, and Fer-
tility," Journal of Marriage and the Family 30 (August, 1968):437-42 (see es-
pecially p. 441).








26 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

mal education.20 More education presumably enhances a woman's
awareness of the benefits involved in controlling fertility through
the use of contraception. A more educated woman is also likely to
more accurately evaluate the advantages and shortcomings of alter-
native contraceptive techniques and to use contraceptive methods
more effectively.21 As can be observed in Table 2.14, a comparison
of the levels of formal education by family planning status consist-

TABLE 2.13. Percentage of Female Participation in the Labor
Force, by City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 0.339ho 0.257di 0.370me
(0.478) (0.437) (0.483)

Rio de Janeiro 0.198ni 0.218mi 0.282ae
(0.399) (0.413) (0.450)
Bogota 0.397fo 0.266bj 0.327mf
(0.493) (0.442) (0.469)
San Jos6 0.305go 0.237c0 0.353me
(0.462) (0.426) (0.478)
Mexico 0.194ni 0.188mi 0.291ae
(0.396) (0.391) (0.455)

Panama 0.283ni 0.318mj 0.381af
(0.451) (0.466) (0.486)

Caracas 0.203ni 0.211mi 0.317ae
(0.403) (0.408) (0.466)


See Appendix I for levels of statistically significant
differences.


ently confirms the expectation of a positive relationship: the aver-
age level of education among family planners is higher than among
nonplanners, and among family planners the average level of edu-
cation among sophisticated planners is higher than among un-
sophisticated planners.

20. J. Mayone Stycos, "Education and Fertility in Puerto Rico," in Social
Demography, ed. Thomas R. Ford and Gordon F. DeJong (Englewood Cliffs:
Prentice-Hall, Inc., 1970), pp. 453-59 (see especially p. 458).
21. Southam, op. cit., p. 385.








Fertility Patterns and Family Planning 27

Aspirations of Socioeconomic Mobility

The second proxy which will subsequently be used to test the
quality-of-child argument is an index designed to measure the
parents' aspirations of socioeconomic mobility for the eldest son.
The values of this index range from 3, which represents an expec-
tation of future downward mobility, to +3, which represents the
highest possible expectations for the eldest son's upward mobility

TABLE 2.14. Average Level of Formal Education Completed by Women,
by City and Family Planning Status



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 9.17ei 7.29aj 6.90a
(3.97) (2.99) (3.42)
Rio de Jaieiro 7.44gi 6.95ci 5.00
(3.82) (3.82) (3.77)
Bogota 9.14ei 6.95ai 4.69ae
(4.05) (3.44) (3.52)

San Josg 7.77ei 6.88ai 5.28ae
(3.75) (3.59) (3.47)
Mexico 7.85e 7.00a1 4.66ae
(3.63) (3.69) (3.70)
Panama 8.38n" 8.65mi 7.56a
(3.31) (3.50) (3.41)
Caracas 6.60hi 6.13di 4.03ae
(3.89) (3.48) (3.56)


See Appendix
differences.


I for levels of statistically significant


relative to the father's occupational category. The average values
for this index are presented in Table 2.15. The average expectations
of socioeconomic upward mobility are generally higher for family
planners than for nonplanners, which seems to suggest that the
woman with relatively high expectations for her children believes
that the conditions conducive to their escalating the socioeconomic
ladder are to some extent inconsistent with a large family size; con-
sequently she makes use of contraceptive techniques more often
than a woman lacking such high aspirations for her offspring.









28 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

One important determinant of a couple's mobility expectations for
its offspring might in part be the husband's own occupational
mobility at the time of his marriage relative to his father's occupa.
tional category. A scale similar to the index of expectations of socio-
economic mobility for the eldest son has been developed to com-
pare the husband's occupational category at the time of his marriage
with his father's occupation. This scale also ranges from -3 for

TABLE 2.15. Average Values for Index of Expectations of Socioeconomic
Mobility, by City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 0.69fo 1.11bi 0.64me
(1.22) (1.34) (1.13)
Rio de Janeiro 1.26ni 1.16mi 0.79ae
(1.32) (1.31) (1.23)
Bogota 1.48eo 1.90ai 1.50me
(1.31) (1.34) (1.41)
San Jose 1.45ei 1.78ai 1.07ae
(1.37) (1.28) (1.37)
Mexico 1.66ho 1.82di 1.59me
(1.30) (1.30) (1.40)
Panam~ 1.84ni 1.79m 1.22a
(1.38) (1.39) (1.41)
Caracas 1.82f 2.07bi 1.20ae
(1.23) (1.22) (1.41)


See Appendix I
differences.


for levels of statistically significant


maximum downward mobility to +3 for highest upward mobility
attainment. A value of zero is indicative of no intergenerational
occupational mobility.
A comparison of the mean values in the scale of intergenerational
occupational mobility in Table 2.16 reveals that, whenever the dif-
ferences are statistically significant, family planners score generally
higher than nonplanners. This seems to suggest that upwardly
mobile parents are relatively more aware of the tradeoff involved
between controlling family size on the one hand and escalating the









Fertility Patterns and Family Planning 29

socioeconomic ladder on the other. People achieving upward occu-
pational mobility before or at the time of marriage are likely to
have higher aspirations for their children, reacting by more careful
planning of the size of their family.

Uncertainty
The proxy used in this study to determine the effects of uncertainty
in the process of family formation is a dummy variable measuring

TABLE 2.16. Average Values for Husband's Occupational Mobility
at Time of Marriage, by City and Family Planning Status*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 0.23no 0.24mk 0.15m
(0.85) (0.95) (0.82)
Rio de Janeiro 0.02no 0.05m 0.04mn
(0.69) (0.60) (0.48)
Bogota 0.26f 0.02bo -0.Olan
(1.14) (0.97) (0.70)
San Jos 0.21nj 0.23mi 0.07be
(0.98) (0.99) (0.65)
Mexico -0.15n1 -0.10.m -0.05d
(1.36) (1.27) (0.92)
Panam 0.02no 0.01ml -0.06m
(1.17) (1.10) (0.86)
Caracas 0.14nl 0.19mi 0.05de
(1.04) (1.06) (0.65)


See Appendix I
differences.


for levels of statistically significant


whether or not the household members believe that the probability
of foetal or child mortality is high. According to Schultz's family
planning hypothesis, parents can be expected to compensate for the
loss of children through death with additional births in order to
achieve a desired number of surviving children.22 A higher prob-

22. T. Paul Schultz, "An Economic Analysis of Family Planning and Fertil-
ity," The Journal of Political Economy 77 (March-April, 1969):153-79 (see
especially pp. 160-61).









30 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

ability of infant or child mortality would be expected to result in less
motivation to employ contraception because a greater number of
pregnancies would be required to attain any given desired family
size. This expectation is confirmed by Table 2.17, which shows per-
centages of households fearing a high probability of death for their
children classified by family planning category. Only one statistically
significant difference between sophisticated and unsophisticated

TABLE 2.17. Percentage of Households Characterized by Expectation
of a High Probability of Death for Their Children,
by City and Family Planning Status


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners
Buenos Aires 0.226no 0.257mj 0.307nf
(0.423) (0.437) (0.462)
Rio de Janeiro 0.453nj 0.468mi 0.534be
(0.499) (0.499) (0.499)
Bogota 0.410e1 0.574ai 0.716a
(0.495) (0.495) (0.451)
San Jose 0.234ni 0.272mi 0.433ae
(0.425) (0.445) (0.496)
Mexico 0.188ni 0.216'i 0.396ae
(0.391) (0.412) (0.498)
Panama 0.287ni 0.274mi 0.390ae
(0.453) (0.447) (0.488)
Caracas 0.270nj 0.271mi 0.362be
(0.446) (0.445) (0.481)


See Appendix I for levels of
differences.


statistically significant


planners appears, but the fear of infant or child death among non-
planners generally does exceed that of family planners, which is
the anticipated relationship.

Intercity Comparisons
With the exceptions of Buenos Aires and San Jos6, over 50 per cent
of the women sampled in each city have never used any form of
contraception. M6xico generally records the highest fertility levels








Fertility Patterns and Family Planning 31
in all three family planning groups, in terms of both average num-
ber of pregnancies and average number of surviving children per
woman. Sophisticated planners in San Jos6 and unsophisticated
planners and nonplanners in Bogota also have relatively high levels
of fertility, while the lowest fertility levels are consistently recorded
in Buenos Aires and Rio de Janeiro.
There seems to be an intercity pattern of associations among indi-
cators of traditionalism, although some inconsistencies are obvious.
For example, in San Jos6 the percentage of women who read news-
papers regularly is relatively high but the percentage who read mag-
azines regularly is very low. The opposite occurs in Caracas, where
the percentage of exposure to newspapers is among the lowest while
the percentage of exposure to magazines is high relative to the other
cities. In general, however, Caracas and Bogota seem to be the most
traditional, whereas Buenos Aires and Panama show the lowest in-
dexes of traditionalism. Migration patterns are similar to patterns
of traditionalism; Caracas and Bogota report the highest percentages
of women born and raised in the capital city, whereas Buenos Aires
and San Jos6 have the highest in-migration rates.
Finally, little is apparent in the way of a consistent overall inter-
city pattern among the various characteristics. Buenos Aires presents
relatively high levels of education, low values for expectation of
socioeconomic mobility, high values for husband's occupational mo-
bility at time of marriage, and low expectation of child death. Rio
de Janeiro shows relatively low income, little female participation in
the labor force, low expectation of socioeconomic mobility, and a
high fear of child death. BogotA experiences a relatively high inci-
dence of women participating in the labor force, high expectation
of socioeconomic mobility, and fear of a high probability of child
death. San Jos6 records relatively low income and high values for
husband's occupational mobility at time of marriage. M6xico shows
a relatively high level of income, low female participation in the
labor force, low scores for husband's occupational mobility at time
of marriage, and little fear of death. PanamA presents a relatively
high percentage of female labor force participation, high educa-
tional attainment, and low levels of husband's occupational mobility
at time of marriage, while Caracas records relatively high levels of
income, little female participation in the labor force, low educa-
tional attainment, and high scores for expectation of child death.























3. An Economic Model of Demand for Children









T HIS CHAPTER attempts to develop a model of demand for chil-
dren in order to subsequently empirically test the direction of
impact, magnitude, and statistical significance of the effects on fer-
tility of demand-for-children considerations. Demand-for-children
variables are those determining, or helping to determine, a house-
hold's demand to have and raise children, or in other words, the
household's desired family size. The demand-for-children hypothesis
implies that the environment of individual households helps deter-
mine parents' preferences to have children, and that these prefer-
ences exert a measurable impact on observed family size.1 The
microeconomic theory of fertility to be presented in this chapter is
associated with the prior work of Becker2 and Mincer.3 Essentially,
1. M. J. Carvajal and David T. Geithman, "Some Economic Determinants
of Fertility: The Evidence from Costa Rica," mimeo, p. 14; and M. J. Carvajal
and David T. Geithman, "An Econometric Model of Fertility Differentials:
Costa Rica, A Case in Point," paper delivered at Southern Economic Associa-
tion annual meetings, Washington, D. C., November, 1972.
2. Gary S. Becker, "An Economic Analysis of Fertility," in Demographic
and Economic Change in Developed Countries, National Bureau of Economic
Research (Princeton: Princeton University Press, 1960), pp. 209-31; also Gary
S. Becker, Human Capital (New York: Columbia University Press, 1964), and
"A Theory of the Allocation of Time," The Economic Journal 75 (September,
1965):493-517.
3. Jacob Mincer, "Market Prices, Opportunity Costs, and Income Effects,"








An Economic Model of Demand for Children 33
it is an elaboration of the concept of human capital and the exten-
sion of microtheory to deal with the allocation of time. A model
arises in which the fundamental reasons for having children and the
substance of the parent-child relationship are expressed in terms of
their associated costs and benefits.


DEMAND CONSIDERATIONS
A theoretical economic treatment of household demand for children
begins with the postulate that households seek to maximize some
utility function in which children, or "children services," and child-
raising activities, plus other goods, services, and activities, appear as
arguments, with utility maximization subject to price effects plus
time and income constraints.4
Parents derive utility from having and raising children by enjoy-
ing them as consumption goods, some findings even indicating that
children are the primary source of satisfaction in the marriages of
many couples.5 For example, Blake views children as "the instru-
mentalities for achieving virtually prescribed social statuses
('mother' and 'father'), the almost exclusive avenues for feminine
creativity and achievement, and the least common denominator for
community participation."6
Children, however, can also increase long-term household utility
by adding to the stream of potential household earnings. This view
treats children virtually as economic agents of production. The in-
crease in household earnings may accrue to the family unit during
the offspring's childhood or in the future after the child has reached
adulthood. Increased family earnings that occur during the off-
spring's childhood might result from all forms of child labor, per-
formed in the market or at home, as well as from subsidies, exemp-
tions, and other economic gains from children that parents may
realize. Future economic benefits arise if the parents secure a source
of economic support from the child when they can no longer furnish
in Carl F. Christ et al., Measurement in Economics: Studies in Mathematical
Economics and Econometrics in Memory of Yehuda Grunfeld (Stanford: Stan-
ford University Press, 1963), pp. 67-82.
4. M. J. Carvajal and David T. Geithman, "An Economic Model of the
Determinants of Fertility," mimeo, pp. 1-18.
5. Eleanore B. Luckey and Joyce K. Bain, "Children: A Factor in Marital
Satisfaction," Journal of Marriage and the Family 32 (February, 1970):43-44.
6. Judith Blake, "Demographic Science and the Redirection of Population
Policy," in Social Demography, ed. Thomas R. Ford and Gordon F. DeJong
(Englewood Cliffs: Prentice-Hall, Inc., 1970), pp. 326-47 (see especially pp.
340-41).:








34 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
their own means of support, i.e., the child is viewed as a form of
social security.
Although the economic benefits derived from children as agents
of production were at one time substantial in the West, their rela-
tive importance with respect to other investment goods has declined
in modern times. As Kamerschen points out, "the value marginal
product of children has fallen relative to the value marginal product
of substitute capital goods."7 In the less-developed countries, how-
ever, this change has not yet occurred, or at least has not occurred
to the same degree as in more-developed countries.
Goods and services, other than children, from whose consumption
the household derives utility can be broken down into two cate-
gories: goods and services complementary to having and raising
children and goods and services competitive with having and raising
children. Complementary goods and services are either those whose
rate of consumption is augmented by having children or those for
which increases in the rate of consumption tend to increase the re-
production and rearing of children.8 This set of goods and services
includes maternity and pediatric services, toys, baby food, child
care, child education, and other goods and services required to meet
the needs of the child. All other commodities can be broadly de-
scribed as competitive, since they compete with having and raising
children for a fixed budget of income and available time. This cate-
gory includes commodities such as adult food, entertainment, and
travel.
Significant increases in the price of complementary goods and
services relative to competitive goods and services would discourage
parental fertility, that is, reduce parental demand for children or
shift the demand curve for children to the left. Okun contends that
in the economic development of the West, the desired size of the
family declined over time as a result, among other things, of price
increases: "the relative cost per child increased, inducing families to
substitute commodities for children."9 In other words, economic de-
velopment can move families away from having and raising children
and consuming child-complementary goods and services, and toward

7. David R. Kamerschen, "Socio-economic Determinants of Fertility Pat-
terns," Population Review 11 (January, 1967):24-29 (see especially p. 26).
8. Joseph J. Spengler, "Some Economic Aspects of the Subsidization by the
State of the Formation of Human Capital," Kyklos 4 (1950):316-43 (see es-
pecially p. 320).
9. Bernard Okun, Trends in Birth Rates in the United States Since 1870
(Baltimore: The Johns Hopkins Press, 1958), pp. 179-80.








An Economic Model of Demand for Children 35
consuming goods and services competitive with having and raising
children.
If income acts as a constraint in the maximization of the house-
hold's utility function, fertility would be expected to vary positively
with income, because a family with a higher income can afford to
have and raise additional children without being forced to give up
the consumption of as many other goods and services as a lower-
income family would. This relationship is noted by Thomlinson;10
Freedman;11 and Kiser, Grabill, and Campbell.12 On the other hand,
families with a higher level of income can afford a wider variety of
goods and services than lower-income families, some of which may
be goods and services whose consumption is competitive with having
and raising children. Thus, two effects of income on fertility can be
identified: a positive income effect, which tends to increase house-
hold demand for children as income increases, and a negative sub-
stitution effect, which tends to reduce household demand for chil-
dren as income rises. The overall nature of the resulting net income-
fertility relationship depends upon which of these two opposing
forces is stronger than the other. If the income effect is stronger
than the substitution effect, the relationship between income and
fertility will tend to be positive; if the opposite is true, the relation-
ship will tend to be negative.
As noted above, time is the second constraint under which the
household utility function is maximized. The total time available to
parents during a given period is a constraint having four compon-
ents: time allotted to working, time allotted to the consumption of
children, time allotted to the consumption of goods and services
complementary to having and raising children, and time allotted to
the consumption of goods and services competitive with having and
raising children. With the inclusion of the time constraint, the model
recognizes explicitly the opportunity cost of childbearing and child-
rearing. This opportunity cost can be viewed as the income and/or
utility that may be derived from activities that compete with having
and raising children for the parents' fixed time resources.

10. Ralph Thomlinson, Population Dynamics (New York: Random House,
Inc., 1965), p. 172.
11. Ronald Freedman, "American Studies of Family Planning and Fertility:
A Review of Major Trends and Issues," in Research in Family Planning, ed.
Clyde V. Kiser (Princeton: Princeton University Press, 1962), pp. 211-27.
12. Clyde V. Kiser, W. H. Grabill, and A. A. Campbell, Trends and Vari-
ations in Fertility in the United States (Cambridge: Harvard University Press,
1968), pp. 289-40.








36 FAMILY PLANNING AND FAMILY SIZE DETERMINATION

The nature of the income-fertility relationship is complicated by
the cost and allocation of parental time. According to Becker's
theory of allocation of time,18 a rise in time-based income (i.e.,
higher income that is premised upon and requires a greater devotion
of parental time) implies a rise in the cost of parental time relative
to goods and services. Therefore, this type of income increase would
induce a substitution away from competing time-intensive activities
and toward other kinds of activities that are not as intensive in their
demands on parental time. Of course, having and raising children
is a notably time-intensive activity. Thus, it would be expected that
the higher the level of time-based income rises, the more time-
intensive is the process of having and raising children, and the
stronger will be the substitution away from having and raising
children toward consuming other, less time-intensive goods and
services.
Numerous empirical studies have found a negative association
between female participation in the labor force and fertility.14 At
least two explanations are offered for this association. First, female
participation in the labor force may delay marriage and conse-
quently reduce fertility. A job may also demand commitments that
are incompatible with, and to a certain extent alternative to, mar-
riage. Moreover, employment can be viewed by the working wife
not only as a source of additional income but also as an avenue to-
ward achieving a higher status and self-fulfillment or as an escape
from the boredom of the house.15
A second and more economics-based explanation for a negative

13. Becker, "A Theory of the Allocation of Time," op. cit., pp. 512-15.
14. Carvajal and Geithman, "Some Economic Determinants of Fertility," op.
cit., pp. 9-10; Freedman, "American Studies of Family Planning and Fertility,"
op. cit., p. 223; Ronald Freedman, Pascal K. Whelpton, and A. A. Campbell,
Family Planning, Sterility, and Population Growth (New York: McGraw-Hill
Book Co., 1959), p. 137; David M. Heer, "Fertility Differences Between Indian
and Spanish-Speaking Parts of Andean Countries," Population Studies 18 (July,
1964):71-84; Gwendolyn Z. Johnson, "Differential Fertility in European Coun-
tries," in Demographic and Economic Change in Developed Countries, Na-
tional Bureau of Economic Research (Princeton: Princeton University Press,
1960), pp. 36-72 (see especially p. 61); Kiser, Grabill, and Campbell, op. cit.,
p. 220; Edward Pohlman, The Psychology of Birth Planning (Cambridge:
Schenkman Publishing Company, Inc., 1969), pp. 136ff.; Jeanne C. Ridley,
Mindel C. Sheps, Joan W. Linguer, and Jane A. Menken, "On the Apparent
Subfecundity of Non-Family Planners," Social Biology 16 (March, 1969):24-28;
Robert H. Weller, "The Employment of Wives, Dominance, and Fertility,"
Journal of Marriage and the Family 30 (August, 1968):437-42 (see especially
p. 437); and Pascal K. Whelpton, A. A. Campbell, and J. E. Patterson, op. cit.,
p. 107.
15. Pohlman, op. cit., pp. 128ff.








An Economic Model of Demand for Children 37
association between the woman's participation in the labor force
and her fertility is that her income would be forgone, at least tem-
porarily, with the advent of a child. In other words, the opportunity
cost of having and raising children is higher for working wives than
for nonworking wives. The employment opportunities forgone by
the woman during pregnancy and early childrearing have the same
direction of impact on fertility as do increases in the prices of child-
complementary goods and services. As women's earnings continue
to rise because of the availability of more and better job opportun-
ities outside the home, the "price" increase tends to act as a restrain-
ing force on fertility.
The woman's opportunity cost of bearing and rearing children
seems to vary with the level of national economic development. The
expected behavior of the woman in most less-developed countries is
to assume the role of caring for the house and raising the children,
and she is likely to find great discrimination in the labor market.
Moreover, most working women in less-developed countries are en-
gaged in lower-status and lower-income occupations. On the other
hand, in more-developed countries the work status and income of
the woman tend to be higher and job discrimination occurs less
often. Becker suggests, therefore, that one of the factors contrib-
uting to the secular decline of fertility in the West has been a steady
rise of the woman's status and pay in society as evidenced by a con-
tinuous decrease in job discrimination.16
Family structure is another important determinant of the shape of
the household's utility function as well as the allocation of its time.
In the extended-household system typical of less-developed coun-
tries, the family is the basic institution around which life revolves
to a much greater degree than in more-developed countries. Conse-
quently, the full costs of having a child-rather than being borne
almost entirely by the parents, as is characteristic of the nuclear-
family structure typical of the more-developed countries-can be
distributed among members of the extended-family group. The
greater the amount of assistance parents receive from their kinship
system in bearing these costs, the weaker will be the incentive to
prevent or postpone pregnancy.17 This point is particularly appli-
cable to child care which may be available, for example, because

16. Becker, "An Economic Analysis of Fertility," op. cit., p. 228.
17. David Goldberg, "Some Recent Developments in American Fertility
Research," in Demographic and Economic Change in Developed Countries,
National Bureau of Economic Research (Princeton: Princeton University Press,
1960), pp. 137-51.








38 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
of the presence of older relatives in the household. The opportunity
cost to the parents of the woman's time in bearing and rearing a
child is reduced, and the incompatibility between higher fertility
and greater female participation in the labor force-which is the
tradeoff typical of the nuclear household-occurs to a lesser degree
in the extended-household structure. The importance of such a
tradeoff between higher fertility and greater female opportunity
cost would be additionally decreased by the existence of a sharp
differentiation between the roles of men and women that would tend
to confine females to household activities.18
Although there are numerous nonchild goods and services that
compete with having and raising children, none of them is a close
substitute for children. The only true close substitute for having
children is having children of a different "quality," where the term
"quality" is used here in Becker's sense. Becker considers "high-
quality" children those from whom parents derive higher utility be-
cause of additional voluntary expenditures per child.19 Given a
fixed budget of income and time, parents may be faced with the
need to make a choice between more quantity or higher quality in
their decisions on desired size of family. Moreover, parents in dif-
ferent income strata would be expected to encounter different pres-
sures to rear "quality" children. For this reason, Leibenstein con-
tends that the cost of having and rearing children increases as the
level of household income increases.20 Thus, children can be re-
garded as consumer goods purchased in more expensive varieties by
higher-income groups rather than merely in larger numbers.21
The parents' level of education is an important variable in inter-
preting variations in quality of children desired by parents. It is
reasonable to expect that the higher the completed educational level
of the parents, the higher would be their educational aspirations for
their children, i.e., the higher would be the expected value of the
"quality" of the family's children. Assuming the existence of an in-
come constraint, this would imply fewer children desired by par-
ents. Less-educated parents presumably would tend to place a lower
value on education than would more-educated parents, perhaps

18. Edward G. Stockwell, Population and People (Chicago: Quadrangle
Books, 1968), pp. 81-82.
19. Becker, "An Economic Analysis of Fertility," op. cit., p. 211.
20. Harvey Leibenstein, Economic Backwardness and Economic Growth
(New York: John Wiley and Sons, Inc., 1957), p. 163.
21. Ronald Freedman and Doris P. Slesinger, "Fertility Differentials for
the Indigenous Non-Farm Population of the United States," Population Studies
15 (November, 1961):161-73 (see especially p. 168).








An Economic Model of Demand for Children 39
putting their children to work at an earlier age. Thus, a higher level
of parents' formal education, all other things being equal, is ex-
pected to have a negative effect on family size.
Another way in which the quality-of-child argument helps to
interpret desired family size is in regard to the parents' aspirations
for their children in terms of socioeconomic or occupational mobil-
ity. Desired family size would be expected to vary inversely with
the magnitude or degree of such aspirations by parents for their
children. As Friedlander and Silver point out, "where opportunities
for social mobility exist, parents will be inclined to have higher
expenditures per child ... in order for the child to maintain or sur-
pass the social and economic status of his parents."22 In addition, it
is hypothesized that upwardly mobile households tend to allocate
their financial and time resources toward working longer hours, sav-
ing a higher percentage of their income, attaining a better education,
and other activities not compatible with childbearing and child-
rearing, all of which would result in lower fertility in these house-
holds.
Higher levels of infant and child mortality involve significant
uncertainties in the process of family formation, particularly if a
minimum number of children is desired or needed as a guarantee of
security in old age. It may be that, to cope with survival uncertain-
ties, parents tend to be risk averters and to err on the safe side,
having more children than the number they expect will be necessary
to insure their desired number of surviving progeny. Thus, a lower
anticipated level of infant and child mortality would result in a
lower fertility rate because fewer births would be required to
achieve any given desired family size.

DEFINITION OF THE MODEL
The empirical model of household demand for children that is tested
in this study (within the limitations of the data provided by the
Urban Fertility Surveys) interprets the level of household fertility
as a nonlinear function of five independent variables. Each of these
fertility determinants has been discussed in the preceding section of
this chapter: household income, female participation in the labor
force, number of years of formal education completed by the


22. Stanley Friedlander and Morris Silver, "A Quantitative Study of the
Determinants of Fertility Behavior," Demography 4 (1967):30-70 (see especially
p. 40).








40 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
woman, parental expectations for eldest son's socioeconomic mobil-
ity, and mother's uncertainty of child survival. That is,

Pojj/ (Aijk -15) = aoj + aijYijk
+ a2jjLjjk + as3jEijk
+ a4jjSiC + a5ijDijqk + Uijk
Cjjk/ (Aij 15) = Poy + fPlYui
+ #2 ,L j~ + p33EiEj
+ /#41Sije + # ijDij + Vfilk
where
Pij = number of pregnancies experienced by the kth woman of
the jth family planning category in the ith city, whether or
not these pregnancies terminated in a live birth;
Cijk = number of surviving children at the time of the interview
with the kth woman of the ith family planning group in the
ith city;
Ajk = age of the kth woman of the ith family planning category in
the ith city;
Yok = a 0-9 discrete income scale as approximated by household
expenditure for the kth household of the ith family plan-
ning category in the ith city(households in the lowest ex-
penditure decile are assigned a value of zero, households in
the next-to-lowest-expenditure decile are assigned a value of
one, and so on; households in the highest-expenditure decile
are assigned a value of nine);
Lik = a dummy variable for female participation in the labor
force, assigned a value of one if the kth woman in the ith
family planning category in the ith city is a member of the
labor force, a value of zero otherwise;
Ey, = number of years of formal education completed by the kth
woman of the ith family planning category in the ith city;
Sjk = a -3 through +3 discrete scale representing parents' ex-
pectations for the eldest son's socioeconomic mobility rela-
tive to the father's occupational category in the kth house-
hold of the ith family planning category in the ith city (a
negative sign for this index implies a downward mobility
expectation, a positive sign implies an upward mobility ex-
pectation, and a value of zero implies no social mobility ex-
pectation);
Dijk = a dummy variable for infant or child survival uncertainty,
assigned a value of one if the kth woman of the ith family








An Economic Model of Demand for Children 41
planning category in the ith city believes that the proba-
bility of foetal or child mortality is high, a value of zero
otherwise;
Uijk and Vi = normally, independently distributed stochastic dis-
turbance terms for the kth household of the jth
family planning category in the ith city; and
aoyt, .., a5j and
fl0o, 8 ., 5sj = the regression coefficients to be estimated for the fth
family planning category in the ith city;

and where

k= 1, ., Kj, where Ky is the sample size of the ith family plan-
ning category in the ith city;
j= 1, 2, 3, for the three family planning categories of sophisti-
cated planners, unsophisticated planners, and non-
planners; and
i= 1, ., 7 for the seven cities in the survey: Buenos Aires, Rio
de Janeiro, BogotA, San Jos6, M6xico, PanamA, and
Caracas.
This study seeks to (1) uncover the degree to which desired fam-
ily size responds to various economic and socioeconomic develop-
ments that systematically affect the potential costs and benefits of
having children, and (2) measure whether or not differences in fer-
tility patterns exist among sophisticated and unsophisticated family
planners and nonplanners. As noted in Chapter 2, all women in the
sample are classified into one of these three mutually exclusive fam-
ily planning categories. Sophisticated planners are defined to in-
clude sterilized women or women who at the time of the interview
were using or had used in the past oral contraception or the dia-
phragm. Unsophisticated planners are defined to include women
who at the time of the interview were using or had used in the past
the condom, jellies, the douche, the rhythm method, or coitus inter-
ruptus but who had not been sterilized and had never used oral
contraception or the diaphragm. Nonplanners are defined to include
women who had never used any of the forms of contraception listed
above.
Note that two distinct fertility indicators are employed: the total
number of pregnancies experienced by the woman, whether or not
they terminated in live births, and the number of children surviving
and recorded at the time of the survey. However, as shown in
Tables 2.3, 2.4, and 2.11, the values of these fertility indicators are








42 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
heavily determined by the age of the mother. Consequently, the
number of pregnancies and the number of surviving children must
be standardized or controlled for the woman's age. In order to con-
trol for age, it is assumed that the woman becomes fecund at age 15
and thus 15 is subtracted from her attained age to obtain her num-
ber of childbearing years. This number of years is then divided into
the number of pregnancies or the number of surviving children re-
ported to obtain the average number of pregnancies or the average
number of live children per years of fecundity or exposure to preg-
nancy.
The method of estimation used in this study is ordinary least-
squares. Fertility is expressed as a function of the five considerations
posited to affect the family's demand for children. The stochastic
nature of the model implies that for each set of values of the inde-
pendent variables there exists a whole probability distribution of
values of the dependent variable. It is assumed in the model that
(1) all elements of the stochastic disturbance are normally distrib-
uted with a 0 mean and a constant variance for all observations, (2)
there is no contemporaneous correlation, and (3) the independent
variables are not highly correlated among themselves. Finally, it also
is assumed by the model that all the independent variables in the
model are predetermined; that is, the values of the coefficients in the
regressions do not depend upon the level of fertility. Empirical test-
ing is conducted using t ratios, coefficients of multiple determination,
and F ratios.
Due to the nature of the variables used, the assumption that no
contemporaneous correlation occurs might appear questionable. This
assumption implies that the regressors are not correlated with the
disturbance. As Goldberger points out, "if a regressor is correlated
with the disturbance, then least-squares estimation-which attempts
to give as much credit to regressors and as little to disturbance as
possible-will give a misleading estimate of variations in the re-
gressor or variations in the regressand."23 Specifically, if the woman's
age and any of the independent variables contained in the model are
significantly correlated, the least-squares estimators will be neither
consistent nor unbiased. To be sure, this does not mean that the
estimates would be wrong, but rather that there would be no way of
determining how close or far they are from the population param-
eters, which would subtract a good deal from the reliability of the
results of this study.
23. Arthur S. Goldberger, Econometric Theory (New York: John Wiley and
Sons, Inc., 1964), p. 282.








An Economic Model of Demand for Children 43
To test for the presence of contemporaneous correlation, least-
square estimates are obtained for the following preliminary equa-
tion:

1/ (At 15) = 80j + 81,Yijk + 82SijLij
+ 8,ajEIjk + 84.jSijk + 85,Dijk + Wije

We = a normally, independently distributed stochastic dis-
turbance for the kth household of the ith family
planning category in the ith city; and
o80,, ., 85s = the regression coefficients to be estimated in the pre-
liminary equations for the ith family planning cate-
gory in the ith city.
The other variables remain as defined previously. A total of 105
coefficients are estimated in the preliminary equation. If a large
number of these coefficients are statistically significant, it could be
concluded that contemporaneous correlation exists, thereby bringing
into question the reliability of the empirical results of the fertility
equations.
According to the law of probabilities, approximately one statisti-
cally significant coefficient at the 0.01 level, five at the 0.05 level,
ten at the 0.10 level, and twenty-one at the 0.20 level can be attrib-
uted to chance. The empirical evidence from the preliminary equa-
tion indicates that none of the coefficients is statistically significant
at the 0.01 level, only two are significant at the 0.05 level, eight are
significant at the 0.10 level (including the two at 0.05), and twenty-
two are significant at the 0.20 level (including the eight at 0.10).
These results imply that the statistical associations are indeed chance
events. Furthermore, the statistical significance are not systemati-
cally confined to any one variable but are dispersed rather evenly
among the five independent variables. Therefore, it can be reason-
ably concluded that no evidence of contemporaneous correlation
exists and the estimates of the fertility equations are both unbiased
and consistent.
Another assumption in this study that might be questioned per-
tains to the absence of correlation among the independent variables,
or the absence of multicollinearity. Multicollinearity is a matter of
degree and not of kind. As Kmenta points out, "the meaningful dis-
tinction is not between the presence and the absence of multi-
collinearity, but between its various degrees."24 Even if a high de-

24. Jan Kmenta, Elements of Econometrics (New York: The Macmillan
Company, 1971), p. 380.








44 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
gree of multicollinearity existed, the least-squares estimators are
both unbiased and consistent, although their standard errors would
tend to be high relative to the coefficient size. The empirical results
presented in Chapter 4, however, strongly suggest that multicollin-
earity poses no serious problem in this study.





















4. Empirical Findings











T HE PURPOSE of this chapter is to present and discuss least-
squares estimates of the extent to which household fertility be-
havior is systematically affected by changes in parental environment.
The 12,663 women included in this study are grouped according to
their family planning status-sophisticated, unsophisticated, and
nonplanners-to determine the extent to which systematic variation
in fertility behavior exists among those families practicing or at-
tempting to practice some form of contraception or birth control and
families making no attempt whatsoever to prevent conception. The
analysis concentrates on the effects of variation of income, woman's
opportunity cost of time, desired quality of children, and uncer-
tainty in the family formation process.

INCOME
Estimated values for the coefficients of the income variable, their
standard errors, and their levels of significance are presented in
Table 4.1 for the total number of pregnancies experienced by the
woman and in Table 4.2 for the household's total number of sur-








46 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
viving children.1 With the exception of the coefficients for unsophisti-
cated family planners in Buenos Aires, Rio de Janeiro, and Bogoti,
all regression coefficients are significantly different from zero at
least at the 0.20 level. All statistically significant coefficients for
sophisticated family planners and for unsophisticated planners are
negative, while all coefficients for nonplanners are positive. These
findings are intriguing. They indicate that among nonplanners in-
come acts primarily as a constraint on the family having and raising
children, with the importance of any negative substitution effect be-
ing secondary or at least overpowered by a positive income effect;
that is, as household income increases parents can afford to have
and raise more children without having to give up consumption of
as many other goods and services, and they respond by increasing
their family size. On the other hand, as income increases a negative
substitution effect seems to exist among family planners, so that as
family planners' income increases most of that increase is allotted to
the consumption of goods and services that are competitive with
having and raising children.
Furthermore, a compensated increase in family income that stems
from increased wage or salary earnings due to more hours spent
working results in an increase in the price of time relative to goods.2
This increase suggests, in turn, a shift away from the consumption
of time-intensive goods and services as income from wages and
salaries rises. Thus, in the case of compensated income changes due
to changes in time-based earnings, we would normally anticipate
that the income coefficient of parental demand for children would
be negative if having and rearing children were a time-intensive
activity relative to other parental activities.3 The lack of significance
of the income coefficients for unsophisticated planners in Buenos
Aires, Rio de Janeiro, and BogotA may be the result of the income
effect and the substitution effect canceling each other out. The sta-
tistical results also show that the income coefficients of sophisticated
planners, with the exception of those in San Jos6, are lower than the
coefficients of unsophisticated planners.
Elasticity in general can be defined as the ratio of a percentage
change in the dependent variable to the corresponding percentage
change in the independent variable when the value of the per-
1. All tables appear at the end of the chapter.
2. Gary S. Becker, "A Theory of the Allocation of Time," The Economic
Journal 75 (September, 1965):439-517 (see especially p. 502).
3. T. Paul Schultz, "An Economic Analysis of Family Planning and Fer-
tility," The Journal of Political Economy 77 (March-April, 1969):153-79 (see
especially p. 157).








Empirical Findings 47
centage change in the independent variable approaches zero. Thus,
income elasticity refers to the limit of the ratio of the percentage
change in fecundity or fertility to an infinitesimally small change in
income. These elasticities (computed at the means of the fecundity,
fertility, and income variables) show, for example, that a 10 per cent
increase in income in Buenos Aires decreases fecundity among so-
phisticated planners by 2.3 per cent but increases fecundity among
nonplanners by 0.6 per cent. An analysis of the income elasticities
presented in Tables 4.3 and 4.4 reveals that whenever the coeffi-
cients are statistically significant, the fertility indicators of sophisti-
cated family planners are generally more income-elastic than the
fertility indicators of unsophisticated planners. Even more im-
portant, the absolute values of income elasticity among family plan-
ners generally exceed the absolute values among nonplanners, which
implies that the impact of the (negative) substitution effect among
family planners is more powerful than the impact of the (positive)
income effect among nonplanners.

OPPORTUNITY COST OF TIME
The statistically significant negative signs of the coefficients measur-
ing female participation in the labor force (Luj) support the con-
tention that female work experience outside the home acts as a
strong deterrent to fertility since working women who have and
raise children have higher opportunity costs than women not em-
ployed outside the home. These coefficients are presented in Table
4.5 for the woman's total pregnancies and in Table 4.6 for the house-
hold's total number of surviving children.
The level of statistical significance of the regression coefficients
and the absolute values of the elasticities for female participation in
the labor force (see Tables 4.7 and 4.8) are generally higher among
nonplanners than among family planners. This phenomenon is re-
lated to the findings of Table 2.13 that female participation in the
labor force occurs more often among nonplanners than among fam-
ily planners. The market wage is a correct measure of what the
woman forgoes in devoting her time to her children only when the
woman is working (or plans to work part of her lifetime). Non-
working women presumably have a nonmarket valuation of their
time greater than the market wage. Thus, unlike the case of working
women, no negative association should be expected for nonworking
women between female participation in the labor force and fertility,
due to the negative effects on fertility of a higher opportunity cost of








48 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
time. Other things being equal, the higher the participation rate of
women in the labor force, the higher will be the detrimental effect
of outside employment on fertility and the greater will be the sta-
tistical significance of the coefficient measuring such participation.

DESIRED QUALITY OF CHILDREN
According to the quality-of-child argument, given the allocation of
a certain portion of parental income and time resources to bearing
and rearing children, parents are faced with a tradeoff between the
quantity of children they can rear and the quality standards they can
choose for their children. Since income and time resources devoted
to having and raising children are constrained, a larger family size
would imply lower-quality children (i.e., lower average voluntary
expenditures per child).
One of the variables used in this study to attempt to measure
parental demand for higher-quality children is the mother's level of
completed formal education. Estimated values for the coefficients
of the education variable, their standard errors, and their levels of
significance are presented in Table 4.9 for the woman's total preg-
nancies and in Table 4.10 for the household's total number of sur-
viving children. The statistical estimates of these coefficients con-
form to expectations as all are negative and significantly different
from zero (with the exception of sophisticated planners in BogotA).
These findings lend support to the hypothesis that more-educated
parents place a higher value on education as a means of socio-
economic mobility than do less-educated parents. In other words,
more-educated parents are more prone to invest in upgrading the
quality of their children through education than are less-educated
parents, and in so doing they compensate-given their budget con-
straint-by reducing their family size.
The negative effect of woman's education on both fertility indi-
cators among nonplanners is generally stronger than among unso-
phisticated planners, and that of unsophisticated planners is gen-
erally stronger than it is for sophisticated planners. Furthermore,
the absolute values of the estimated elasticities for nonplanners tend
to exceed those for family planners. The values of the estimated
elasticities are presented in Tables 4.11 and 4.12. This evidence of
elasticities implies that, as the level of the mother's formal education
rises, the negative impact that more education exerts on family size
is greater for nonplanners than for family planners.
The other proxy used to measure parents' demand for higher-








Empirical Findings 49
quality children is the occupational mobility index. This index re-
cords parents' expectations for their eldest son in relation to the
father's occupational category. It is hypothesized that, other things
being equal, the higher parents' aspirations are for their children,
the larger will be the level of expenditure or investment per child
that they are willing to undertake (i.e., the higher will be the qual-
ity of their children) and, given their budget constraint, the lower
will be the number of children they desire. The statistically signifi-
cant and negative estimates of the family planners' coefficients for
the social mobility aspirations index (presented in Tables 4.13 and
4.14) support this hypothesis. The coefficients for this index, how-
ever, are positive and highly statistically significant among non-
planners. The positive sign of the coefficients for nonplanners seems
to indicate that those parents not engaged in family planning tend
to relate upward social mobility and status achievement to having
and rearing a large family. This behavior pattern, the opposite of
that observed for family planners, is perhaps best understood as
reflecting the continuing hold of traditional views, values, and atti-
tudes. Recall from Chapter 2 that nonplanners are notably more tra-
ditional (on CELADE's 9-point scale) than family planners (Table
2.5), they read fewer newspapers and magazines than family plan-
ners (Tables 2.6 and 2.7), and the husband tends to dominate
decision-making more than in families that practice birth control
(Table 2.8).
The negative effect of traditionalism on both fertility indicators is
consistently stronger among sophisticated planners than among un-
sophisticated planners. Moreover, a comparison of elasticities re-
veals that the fertility of sophisticated planners is slightly more elas-
tic in reference to aspirations than is the fertility of unsophisticated
planners. Estimates of these elasticities are presented in Tables 4.15
and 4.16. Further analysis reveals that the absolute value of these
elasticities among family planners generally exceeds the absolute
value of the elasticities among nonplanners. This implies, of course,
that family planners are more likely to adjust their family size in
light of their perceived negative association between upward mo-
bility and fertility than are nonplanners in light of their perceived
positive association between the two variables.

UNCERTAINTY
The effect of uncertainty in the process of family formation is mea-
sured in this study with a dummy variable that records whether or








50 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
not a high probability of infant or child death is anticipated by the
Parent. Estimated values of the coefficients for the expectation of a
high probability of death, their standard errors, and levels of signifi-
cance are presented in Table 4.17 for the woman's total number of
pregnancies and in Table 4.18 for the household's total number of
surviving children. An expectation of a high probability of death is
hypothesized to translate into parental compensation with additional
births for the anticipated or actual loss of children through death in
order to achieve a given desired family size. This implies, of course,
an expected positive regression coefficient. This expectation is con-
firmed by the estimated coefficients obtained for nonplanners. The
coefficients for family planners, however, show a negative sign and
are statistically significant. This result, which is contrary to the find-
ings of others who have related higher prior death rates positively
to fertility levels,4 implies that as the anticipated probability of child
death increases, family planners respond by having and raising
fewer children. The probability of child death can be economically
interpreted as the risk involved in investing in a larger family size.
Other things being equal, normally the higher the risk involved in a
given activity in relation to alternative investment opportunities, the
lower will be the expected level of investment in that activity. The
negative sign of the coefficients for the expectation of a high prob-
ability of death may indicate that, as the risk involved in having and
raising children increases among family planners, there is a substi-
tution effect away from having and raising children and toward
other forms of human capital investment or toward consumption of
goods and services that are alternatives to bearing and rearing
children.
The statistical results show that in general the coefficients for an
expectation of high probability of death among sophisticated plan-
ners are smaller (i.e., higher absolute value) than the coefficients
among unsophisticated planners. Furthermore, as can be observed
in Tables 4.19 and 4.20, the absolute values of the elasticities for an
expectation of a high probability of death are quite small, which im-
plies that in general there is a rather moderate fertility response to
changes in parental uncertainties in the process of family formation.
BogotA and Caracas, however, are exceptions to this generalization
and reveal higher elasticities, especially among sophisticated family
planners.

4. Ibid., pp. 169-76; and Harold B. Newcombe and Philip O. W. Thynas,
"Child Spacing Following Stillbirth and Infant Death," Eugenics Quarterly 9
(March, 1962):25-35.








Empirical Findings 51
INTERCEPT

The intercept values of the equations estimated in this chapter are
presented in Table 4.21 for the woman's total number of pregnancies
and in Table 4.22 for the household's total number of surviving chil-
dren. Two points of comparison can be noted when analyzing the
values of the intercepts. First, the intercept values for sophisticated
and unsophisticated planners are approximately the same and both
are considerably higher than the intercept values for nonplanners.
Second, with the exception of nonplanners in Panama, the intercept
values for the equations measuring number of pregnancies consis-
tently exceed the intercept values for the equations measuring sur-
viving number of children.

F STATISTIC

The F statistic is used to test whether or not the effect on fertility of
an entire set of variables is statistically significantly different from
zero when these variables are taken together. In other words, the F
statistic is used to determine if the empirical model is specified
properly. Tables 4.23 and 4.24 show the values obtained for the F
ratio in the two sets of equations. The high statistical significance of
the F ratios indicates that the variables analyzed in this study do
indeed have an important effect on fertility as measured by both
number of pregnancies and number of surviving children. The
specification of the variables in the model seems to apply best to
nonplanners.

COEFFICIENTS OF MULTIPLE DETERMINATION

The coefficient of multiple determination, or R2, is another indicator
of whether or not the model is correctly specified. It measures the
percentage of the variation in the dependent variable that is ac-
counted for by variations in the independent variables. The coeffi-
cients of multiple determination for the two fertility equations are
presented in Tables 4.25 and 4.26. An analysis of these tables reveals
that the coefficients of multiple determination for nonplanners ex-
ceed those for family planners. Moreover, for family planners the
coefficients for the equations measuring number of pregnancies
generally exceed those for the equations measuring surviving num-
ber of children, but for nonplanners the opposite is true.








52 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
INTERCITY DIFFERENCES

No major consistent intercity patterns are apparent among the esti-
mated elasticity values of the independent variables used in the
demand-for-children model. Buenos Aires records relatively low
elasticities for the index of aspirations of socioeconomic mobility and
for expectations of probability of death. Estimates for Rio de Janeiro
indicate low elasticities for income, women's participation in the
labor force, and index of aspirations of socioeconomic mobility, but
high elasticities for education. Bogota presents relatively high elas-
ticities for the index of aspirations of socioeconomic mobility. San
Jos6 shows relatively low elasticities for education, index of aspira-
tions of socioeconomic mobility, and expectations of probability of
death. M6xico presents relatively low elasticities for female partici-
pation in the labor force and expectations of probability of death.
Panama records relatively high income elasticities but low elasticities
for expectations of probability of death. And estimates for Caracas
indicate relatively high elasticities for expectations of probability of
death.









TABLE 4.1. Estimated Values of the Coefficients for Household
Income (Yijk), Their Standard Errors, and
Levels of Significance



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00572c 0.00115 0.00157b
(0.00341) (0.00101) (0.00072)

Rio de Janeiro -0.00655b -0.00156 0.00136C
(0.00256) (0.00206) (0.00074)

Bogota -0.01087c -0.00248 0.00171c
(0.00597) (0.00330) (0.00097)

San Jose -0.00770c -0.01811a 0.01263a
(0.00430) (0.00334) (0.00335)

Mexico -0.01141b -0.00820b 0.00618a
(0.00516) (0.00346) (0.00221)

Panama -0.01344a -0.01083a 0.00923a
(0.00300) (0.00316) (0.00239)

Caracas -0.00744c -0.00720b 0.00415d
(0.00394) (0.00311) (0.00265)


*


pregnancies per
of statistically


Dependent variable: average number of
year of fecundity. See Appendix II for levels
significant differences.









TABLE 4.2. Estimated Values of the Coefficients for Household
Income (Yijk), Their Standard Errors, and
Levels of Significance



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00437d -0.00179 0.00261b
(0.00339) (0.00178) (0.00125)

Rio de Janeiro -0.00412d -0.00045 0.00202a
(0.00283) (0.00168) (0.00054)

Bogota -0.00863b 0.00250 0.00242a
(0.00421) (0.00269) (0.00093)

San Jos0 -0.00442d -0.01169a 0.00402b
(0.00277) (0.00269) (0.00193)

Mexico -0.00677d -0.00446d 0.00060d
(0.00479) (0.00314) (0.00041)

Panami -0.01157a -0.00673b 0.00518b
(0.00276) (0.00269) (0.00209)

Caracas -0.00545 -0.00406d 0.00160d
(0.00374) (0.00273) (0.00115)


Dependent variable: average number of surviving
children per year of fecundity. See Appendix II for levels of
statistically significant differences.










TABLE 4.3. Income Elasticities Computed at the Means of the
Variables



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.23 -0.05e 0.06

Rio de Janeiro -0.17 -0.36e 0.03

Bogota -0.30 -0.47e 0.03

San Jose -0.16 -0.28 0.19

M6xico -0.26 -0.18 0.10

Panama -0.30 -0.22 0.18

Caracas -0.20 -0.16 0.09


Dependent variable: average number of
year of fecundity. See Appendix II for levels
significant differences.


pregnancies per
of statistically


TABLE 4.4. Income Elasticities Computed at the Means of the
Variables



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.25 0.09e 0.14

Rio de Janeiro -0.13 -0.01e 0.05

Bogota -0.28 0.06e 0.05

San Jose -0.12 -0.22 0.08

Mexico -0.19 -0.12 0.01

Panama -0.30 -0.17 0.13

Caracas -0.17 -0.11 0.04


*
Dependent variable: average number of surviving
children per year of fecundity. See Appendix II for levels of
statistically significant differences.










TABLE 4.5. Estimated Values of the Coefficients for Female
Participation in the Labor Force (Lijk), Their Standard
Errors, and Levels of Significance



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00892b -0.01565a -0.02724a
(0.00347) (0.00547) (0.00909)

Rio de Janeiro -0.02259c -0.01090c -0.02578a
(0.01477) (0.00589) (0.00934)

Bogota -0.05908b -0.01961c -0.05467a
(0.02892) (0.01093) (0.00948)

San Jose -0.04015c -0.04929a -0.07624a
(0.02430) (0.01315) (0.01259)

Mexico -0.02417c -0.01265c -0.05015a
(0.01446) (0.00771) (0.01004)

Panama -0.03398b -0.02855c -0.05817a
(0.01420) (0.01607) (0.01110)

Caracas -0.04695c -0.07082a -0.04206a
(0.02794) (0.01466) (0.01221)


Dependent variable: average number of pregnancies per
year of fecundity. See Appendix II for levels of statistically
significant differences.










TABLE 4.6. Estimated Values of the Coefficients for Female
Participation in the Labor Force (Lijk), Their Standard
Errors, and Levels of Significance



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00362 -0.01712a -0.01724a
(0.02100) (0.00421) (0.00616)

Rio de Janeiro -0.02548b -0.01987b -0.02544a
(0.01047) (0.00888) (0.00744)

Bogota -0.04659b -0.01549c -0.04190a
(0.02271) (0.00836) (0.00809)

San Jose -0.03406b -0.03534a -0.05904a
(0.01642) (0.01062) (0.01100)

Mexico -0.02564b -0.01812c -0.04587a
(0.01274) (0.01006) (0.00872)

Panama -0.03436a -0.02935b -0.04836a
(0.01307) (0.01370) (0.00970)

Caracas -0.05464a -0.06805a -0.02771a
(0.02678) (0.01287) (0.01002)


*


Dependent variable: average
per year of fecundity. See Appendix
cally significant differences.


number of surviving children
II for levels of statisti-











TABLE 4.7. Female Labor Participation Elasticities Computed
at the Means of the Variables*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.02e -0.03 -0.10

Rio de Janeiro -0.02 -0.01 -0.04

Bogota -0.09 -0.02 -0.07

San Jose -0.05 -0.04 -0.12

Mexico -0.02 -0.01 -0.06

Panama -0.04 -0.04 -0.10

Caracas -0.04 -0.06 -0.06


Dependent variable: average number of
year of fecundity. See Appendix II for levels
cally significant differences.


pregnancies per
of statisti-


TABLE 4.8. Female Labor Force Participation Elasticities
Computed at the Means of the Variables*


City

Buenos Aires

Rio de Janeiro

Bogota

San Jos5

Mexico

Panama

Caracas


Family planning status
Sophisticated Unsophisticated
planners planners Nonplanners

-0.01e -0.05 -0.09

-0.03 -0.03 -0.06

-0.08 -0.02 -0.07

-0.05 -0.04 -0.12

-0.02 -0.02 -0.07

-0.04 -0.04 -0.11

-0.05 -0.06 -0.05


Dependent variable: average number of surviving children
per year of fecundity. See Appendix II for levels of statisti-
cally significant differences.










TABLE 4.9. Estimated Values of the Coefficients for Woman's
Education (Eijk), Their Standard Errors, and Levels
of Significance*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00188d -0.00209b -0.00321a
(0.00139) (0.00086) (0.00042)

Rio de Janeiro -0.00345b -0.00797a -0.00963a
(0.00146) (0.00132) (0.00123)

Bogota -0.00001 -0.00685a -0.00862a
(0.00466) (0.00212) (0.00140)

San Jose -0.00286c -0.00342b -0.00597a
(0.00161) (0.00148) (0.00197)

Mexico -0.00562c -0.00904a -0.00510a
(0.00314) (0.00223) (0.00143)

Panama -0.00304c -0.00557b -0.00485a
(0.00167) (0.00238) (0.00172)

Caracas -0.00532b -0.00755a -0.01110a
(0.00260) (0.00200) (0.00177)


Dependent variable: average number of pregnancies per
year of fecundity. See Appendix II for levels of statistically
significant differences.










TABLE 4.10. Estimated Values of the Coefficients for Woman's
Education (Eijk), Their Standard Errors, and Levels
of Significance*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00167d -0.00085d -0.00430a
(0.00088) (0.00066) (0.00112)

Rio de Janeiro -0.00349a -0.00606a -0.00735a
(0.00095) (0.00108) (0.00098)

Bogota -0.00031 -0.00635a -0.00673a
(0.00430) (0.00173) (0.00119)

San Jose -0.00420b -0.00466a -0.00446a
(0.00174) (0.00151) (0.00172)

Mexico -0.00384b -0.00683a -0.00625a
(0.00192) (0.00203) (0.00124)

Panama -0.00293c -0.00611a -0.00724a
(0.00150) (0.00203) (0.00151)

Caracas -0.00617 -0.00733a -0.01118a
(0.00245) (0.00176) (0.00157)


Dependent variable:


average


n


children per year of fecundity. See A
statistically significant differences.


lumber of surviving
*ppendix II for levels of


TABLE 4.11. Education Elasticities Computed at the Means
of the Variables*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.12 -0.13 -0.22

Rio de Janeiro -0.13 -0.29 -0.27

Bogota -0.00e -0.17 -0.16

San Jos5 -0.09 -0.08 -0.15

Mexico -0.15 -0.23 -0.09

Panama -0.10 -0.19 -0.17

Caracas -0.15 -0.17 -0.20


*
Dependent variable: average number of pregnancies per
year of fecundity. See Appendix II for levels of statistically
significant differences.










TABLE 4.12. Education Elasticities Computed at the Means
of the Variables*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.16 -0.07 -0.42

Rio de Janeiro -0.17 -0.28 -0.29

Bogota -0.01e -0.19 -0.16

San Jose -0.16 -0.14 -0.14

Mexico -0.13 -0.22 -0.14

Panamg -0.11 -0.26 -0.07

Caracas -0.20 -0.20 -0.25


Dependent variable: average number of surviving
children per year of fecundity. See Appendix II for levels of
statistically significant differences.

TABLE 4.13. Estimated Values of the Coefficients for Index
of Socioeconomic Mobility Aspirations (Sijk), Their Standard
Errors, and Levels of Significance


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.01890d -0.00325c 0.01024a
(0.01285) (0.00180) (0.00386)

Rio de Janeiro -0.01260b -0.00574c 0.00731a
(0.00633) (0.00344) (0.00240)

Bogota -0.03475a -0.00990b 0.01426a
(0.01265) (0.00471) (0.00315)

San Jose -0.01389c -0.00913b 0.00597a
(0.00830) (0.00432) (0.00133)

Mexico -0.01225c -0.00962c 0.02130a
(0.00711) (0.00566) (0.00328)

Panama -0.01676a -0.00797d 0.01041a
(0.00461) (0.00537) (0.00377)

Caracas -0.01238c -0.01082b 0.01032a
(0.00645) (0.00518) (0.00302)


Dependent variable: average number of pregnancies per
year of fecundity. See Appendix II for levels of statistically
significant differences.










TABLE 4.14. Estimated Values of the Coefficients for Index
of Socioeconomic Mobility Aspirations (Sijk), Their Standard
Errors, and Levels of Significance*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.01607b -0.00283b 0.01169a
(0.00806) (0.00138) (0.00304)

Rio de Janeiro -0.01290b -0.00561b 0.00123a
(0.00502) (0.00280) (0.00041)

Bogota -0.03129a -0.00820b 0.00898a
(0.01153) (0.00384) (0.00269)

San Jose -0.01249b -0.00991a 0.00637a
(0.00629) (0.00348) (0.00228)

MExico -0.01809b -0.00769c 0.01693a
(0.00754) (0.00513) (0.00284)

Panama -0.01669a -0.00671c 0.01688a
(0.00424) (0.00457) (0.00330)

Caracas -0.01409b -0.00835d 0.00701a
(0.00605) (0.00455) (0.00256)


Dependent variable: average number of surviving
children per year of fecundity. See Appendix II for levels of
statistically significant differences.

TABLE 4.15. Elasticities for Socioeconomic Aspirations for
Eldest Son Computed at the Means of the Variables*


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.09 -0.03 0.07

Rio de Janeiro -0.08 -0.03 0.03

Bogota -0.20 -0.07 0.09

San Jose -0.08 -0.06 0.03

Mexico -0.07 -0.06 0.13

Panama -0.12 -0.06 0.06

Caracas -0.09 -0.08 0.06


*
Dependent variable: average number of pregnancies
per year of fecundity.










TABLE 4.16. Elasticities for Socioeconomic Aspirations for
Eldest Son Computed at the Means of the Variables*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.11 -0.03 0.11

Rio de Janeiro -0.10 -0.04 0.01

Bogota -0.21 -0.07 0.07

San Jose -0.09 -0.08 0.04

Mgxico -0.13 -0.06 0.13

Panamg -0.14 -0.06 0.12

Caracas -0.13 -0.08 0.05


Dependent variable: average
children per year of fecundity.


number of surviving


TABLE 4.17. Estimated Values of the Coefficients for the
Expectation of a High Probability of Death (Dijk),
Their Standard Errors, and Levels of Significance


Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.01592d -0.01202b 0.00363c
(0.01191) (0.00556) (0.00189)

Rio de Janeiro -0.00571d 0.00306 0.01550b
(0.00374) (0.00946) (0.00745)

Bogoti -0.04719b -0.01574d 0.01317c
(0.01990) (0.01084) (0.00777)

San Jose -0.03883b -0.01801b 0.01007d
(0.01768) (0.01002) (0.00724)

Mexico -0.03332c -0.02126c 0.01630b
(0.01687) (0.01278) (0.00742)

Panami -0.00932b -0.01524b 0.00713c
(0.00456) (0.00712) (0.00394)

Caracas -0.08782a -0.05826a 0.00341c
(0.01583) (0.01377) (0.00182)


pregnancies per
of statistically


Dependent variable: average number of
year of fecundity. See Appendix II for levels
significant differences.










TABLE 4.18. Estimated Values of the Coefficients for the
Expectation of a High Probability of Death (Dijk)t Their
Standard Errors, and Levels of Significance



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.00590d -0.00789c 0.00589c
(0.00379) (0.00428) (0.00348)

Rio de Janeiro -0.00683c -0.00011 0.00433d
(0.00407) (0.00770) (0.00273)

Bogota -0.04282b -0.01073d 0.01247c
(0.01762) (0.00747) (0.00733)

San Jose -0.03921a -0.01423d 0.00561c
(0.01098) (0.01051) (0.00370)

Mexico -0.01680d -0.02962a 0.01050d
(0.01197) (0.01113) (0.00618)

Panami -0.00534d -0.03203a 0.01036b
(0.00340) (0.00460) (0.00457)

Caracas -0.04863a -0.03995a 0.00115d
(0.01476) (0.01209) (0.00087)


Dependent variable: average number of surviving
children per year of fecundity. See Appendix II for levels
of statistically significant differences.










TABLE 4.19. Elasticities of Expectation of a High Probability
of Death Computed at the Means of the Variables*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.03 -0.03 0.01

Rio de Janeiro -0.01 0.01e 0.05

Bogota -0.07 -0.03 0.04

San Jose -0.04 -0.02 0.02

Mexico -0.02 -0.02 0.02

Panama -0.01 -0.02 0.01

Caracas -0.10 -0.06 0.01


Dependent variable: average number of
year of fecundity. See Appendix II for levels
significant differences.


pregnancies per
of statistically


TABLE 4.20. Elasticities of Expectation of a High Probability
of Death Computed at the Means of the Variables*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires -0.01 -0.02 0.03

Rio de Janeiro -0.02 -0.00e 0.02

Bogotg -0.08 -0.03 0.04

San Jose -0.05 -0.02 0.02

Mexico -0.01 -0.03 0.02

Panama -0.01 -0.04 0.02

Caracas -0.06 -0.05 0.00


Dependent variable: average number of surviving
children per year of fecundity. See Appendix II for levels
of statistically significant differences.










TABLE 4.21. Intercepts for Equations in Which Dependent Variable
Equals Average Number of Pregnancies per Year of Fecundity


City

Buenos Aires

Rio de Janeiro

Bogota

San Jose

Mexico

Panama

Caracas


Family planning status
Sophisticated Unsophisticated
planners planners Nonplanners

0.20217 0.13213 0.11868

0.26337 0.25232 0.21208

0.40648 0.36804 0.26639

0.33996 0.39288 0.22285

0.42446 0.41311 0.23503

0.37635 0.37433 0.16233

0.36315 0.38722 0.24751


TABLE 4.22. Intercepts for Equations in Which Dependent Variable
Equals Average Number of Surviving Children per Year of Fecundity



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 0.14646 0.10971 0.08811

Rio de Janeiro 0.21143 0.19540 0.16154

Bogoti 0.34576 0.28422 0.20906

San Jose 0.28220 0.32318 0.19095

Mexico 0.30450 0.31731 0.21114

Panama 0.33136 0.30980 0.20170

Caracas 0.29300 0.31759 0.21676










TABLE 4.23. F Ratios and Levels of Significance for Equations
in Which Dependent Variable Equals Average Number of
Pregnancies per Year of Fecundity*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 3.15b 4.00a 11.35a

Rio de Janeiro 4.30a 10.63a 28.31a

Bogota 3.86a 6.19a 30.83a

San Jose 3.49a 19.34a 25.03a

Mexico 4.21a 8.09a 39.20a

Panama 8.72a 7.01a 28.51a

Caracas 4.45a 21.52a 30.01a


See Appendix II for
cant differences.


levels of statistically signifi-


TABLE 4.24. F Ratios and Levels of Significance for Equations
in Which Dependent Variable Equals Average Number of Surviving
Children per Year of Fecundity*



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 2.40b 6.10a 13.37a

Rio de Janeiro 3.51a 8.02a 24.88a

Bogota 3.54a 5.40a 27.91a

San Josg 3.70a 17.22a 20.91a

Mexico 3.33a 4.92a 35.65a

Panamg 7.88a 7.13a 25.17a

Caracas 2.92a 19.46a 28.82a


*
See Appendix II for
cant differences.


levels of statistically signifi-









TABLE 4.25. Coefficients of Multiple Determination for Equations
in Which Dependent Variable Equals Average Number of
Pregnancies per Year of Fecundity



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 0.131 0.050 0.291

Rio de Janeiro 0.139 0.219 0.767

Bogota 0.476 0.142 0.789

San Josg 0.143 0.359 0.635

Mgxico 0.246 0.266 0.882

Panama 0.273 0.231 0.730

Caracas 0.325 0.419 0.671




TABLE 4.26. Coefficients of Multiple Determination for Equations
in Which Dependent Variable Equals Average Number of
Surviving Children per Year of Fecundity



Family planning status
Sophisticated Unsophisticated
City planners planners Nonplanners

Buenos Aires 0.087 0.076 0.343

Rio de Janeiro 0.093 0.169 0.632

Bogota 0.449 0.122 0.686

San Jose 0.163 0.324 0.697

Mexico 0.182 0.168 0.912

Panamg 0.248 0.234 0.876

Caracas 0.190 0.384 0.692





















5. Conclusions


A NY COMPREHENSIVE and intellectually satisfying approach to the
study of fertility must recognize and deal with numerous little-
understood relationships among economic, sociological, demo-
graphic, and political variables. Methodological advance must be
deliberate and reflective, with constant reference to the full reality
of a particular context as well as to the search for theoretical ele-
gance and rigor. In addition, the task is hampered by a severe short-
age of reliable data of the kind required for empirical research on
the subject. Thus, any results at this time must be regarded as pre-
liminary in nature.
Despite its many shortcomings, the approach employed in this
study broadly corroborates the view that fertility is a rational phe-
nomenon. That is, people respond to their perception of the environ-
ment and changing economic opportunities by altering their family
size. The empirical results of this study strongly indicate that as
cities become more economically developed (i.e., as the level of
education increases, as women participate more in the labor force,
as the level of income increases, and as the probability of infant and
child deaths declines), the household's demand for children will be
reduced. A decrease in the demand for children, coupled with an








70 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
increase in the supply of contraceptives, will ultimately lead to a
reduction in the level of fertility.
Several bases can be offered for this prediction. One is that as the
benefits of having and raising children decrease relative to the con-
sumption of alternative goods and services, a substitution effect
away from having and raising children and toward goods and serv-
ices competitive with children will take place. Another is that the
economic costs of having and raising children will rise and a larger
expenditure per child will be required from parents, in terms of both
out-of-pocket costs and opportunity costs, because of a growing
preference by parents for higher-quality children (e.g., as parents
become more educated they will desire more education for their
offspring). Also, the process of economic development usually en-
tails more or less rapid urbanization, and children are notably more
expensive to raise in an urban environment than in rural surround-
ings. Children are also far less valuable to their parents as economic
agents or factors of production in an urban setting than in a rural
environment, where farming without a large number of children to
help with the work is often impossible. Finally, as economic develop-
ment proceeds, infant and child mortality usually drops and hence
uncertainties in the family formation process will decrease. There
will consequently be a reduction in the need to compensate for the
loss of children through death with additional births in order to
achieve a desired number of surviving children.
These conclusions place fertility in an economic resource allo-
cation framework and imply the existence of some level of fertility
consistent with optimal national resource allocation. Changes in
fertility, however, do not occur simultaneously with changes that
take place in the independent variables identified throughout this
study. Rather, fertility changes may be subject to a time lag which
can delay fertility responses for a whole generation or even more. A
theoretical framework such as the one discussed here can be a
valuable beginning in providing policy-makers with some insight
into the nature, scope, and elements of an economically rational and
dynamic population policy. With population considerations perform-
ing an important function in facilitating structural changes associ-
ated with the development process, policies could be designed to
increase the flow of information about the costs and benefits in-
volved both in preventing births and in having children. The re-
sponses of individuals to differential benefits and costs cannot be
more economically rational than their awareness of the existence of
such differentials. At this point a critical issue arises: does govern-








Conclusions 71
ment have the responsibility to insure that people are fully informed
about the long-term benefits of family planning? In other words,
should government (all members of society) pay for expenditures
that will directly benefit only one segment of society (those who
plan their family size)? If the benefits of family planning accrued
only to the individuals contemplating such decisions, there would be
little or no rationale for the implementation of public policy in this
area. There exist externalities or spillover effects, however, in the
process of family formation. In fact, as valuable as family planning
might be to the individuals directly involved, the social benefits of
family planning may exceed the private benefits.
Family planning also has an important intergenerational value. If
the quality-of-child argument holds-and the empirical evidence
from this study seems to indicate that it does-at least some of the
household expenditures eliminated because of a reduction in the
level of completed fertility will be channelled into a higher level of
expenditure per child. Thus, each child can enjoy not only better
consumption goods but also a higher level of human capital invest-
ment (in the form, say, of more education and better health), which
in turn will enhance his or her employment opportunities and eco-
nomic productivity in the future.
Thus, society in general also benefits from family planning. More-
over, a society oriented toward economic development must be
committed to change. To the extent that fertility plays a funda-
mental role in implementing an effective program of human-
resource development that raises productivity and speeds social
progress, it may be concluded that the government has a positive re-
sponsibility to promote favorable conditions under which people
may behave rationally in planning their family size. This responsi-
bility becomes even more important in light of the inadequacy of
private markets in financing human capital investment.
Government may extend direct public credit to family planning
programs to help compensate for imperfections in private capital
markets. In addition, public subsidization of family planning pro-
grams can be undertaken through the tax structure. The tax struc-
ture may affect fertility by allowing for preferential treatment of
certain sources of income. For tax purposes, income in the form of
wages, dividends, or capital gains may be treated differently from
other income forms. Income earners receiving income from different
sources may not have the same propensities to bear and rear chil-
dren. For example, wage earners may have a higher propensity to
bear and rear children than do dividend earners. Thus, other things








72 FAMILY PLANNING AND FAMILY SIZE DETERMINATION
being equal, a tax policy that allows preferential treatment of divi-
dend income would tend to promote a lower level of fertility than a
tax policy that allows no such preferential treatment. But perhaps
the most important and reasonable way in which the tax structure
may affect fertility is through exemptions and deductions. An ex-
emption refers to a tax-free amount of income deemed necessary for
subsistence; it is designed to reduce the tax burden as the number
of dependent persons increases. Other things being equal, the lower
the exemption per dependent, the heavier the burden of an addi-
tional dependent. Thus, a tax policy designed to promote low levels
of fertility would be expected to decrease or eliminate the tax-free
amount for each dependent. A deduction refers to preferential treat-
ment of uses of income. In this sense, deductions are equivalent to
governmental subsidies of certain activities. A tax policy is favorable
to higher fertility to the extent that child-related expenditures (such
as maternity fees, child medical care, baby and child food and uten-
sils, etc.) can be deducted from the tax base.
As the importance of human capital investment becomes more
firmly established within the framework of resource allocation for
economic development, the question arises of where its importance
stands relative to alternative growth-inducing investment oppor-
tunities, particularly in light of the less-developed countries' plight
of mass poverty. To be sure, family planning alone does not create
development. It can, however, reduce population pressure on lim-
ited nonhuman resources and can become a valuable complement to
an effective capital-accumulation, full-employment growth policy.
Thus, the economic value of family planning lies in its contribution
to productive potential rather than in its direct contribution to the
economy's success in achieving that potential.














Appendixes
























Appendix I


LEVELS OF STATISTICALLY SIGNIFICANT DIFFERENCES AMONG FAMILY PLANNING
GROUPS FOR TABLES 2.3 THROUGH 2.17

a. Significantly different from the coefficient of sophisticated planners (0.01
level).
b. Significantly different from the coefficient of sophisticated planners (0.05
level).
c. Significantly different from the coefficient of sophisticated planners (0.10
level).
d. Significantly different from the coefficient of sophisticated planners (0.20
level).
e. Significantly different from the coefficient of unsophisticated planners (0.01
level).
f. Significantly different from the coefficient of unsophisticated planners (0.05
level).
g. Significantly different from the coefficient of unsophisticated planners (0.10
level).
h. Significantly different from the coefficient of unsophisticated planners (0.20
level).
i. Significantly different from the coefficient of nonplanners (0.01 level).
j. Significantly different from the coefficient of nonplanners (0.05 level).
k. Significantly different from the coefficient of nonplanners (0.10 level).
1. Significantly different from the coefficient of nonplanners (0.20 level).
m. Not significantly different from the coefficient of sophisticated planners.
n. Not significantly different from the coefficient of unsophisticated planners.
o. Not significantly different from the coefficient of nonplanners.
























Appendix II








LEVELS OF STATISTICALLY SIGNIFICANT DIFFERENCES AMONG FAMILY PLANNING
GROUPS FOR TABLES 4.1 THROUGH 4.24

a. Significantly different from zero at the 0.01 level.
b. Significantly different from zero at the 0.05 level.
c. Significantly different from zero at the 0.10 level.
d. Significantly different from zero at the 0.20 level.
e. Not significantly different from zero at the 0.20 level.


























Appendix III


SURVEY QUESTIONNAIRE


1. What is your opinion about population
changes in (surveyed city)?




2. a) What would be best for the country in
the next 10 years?


b) Why?

3. Do you believe that children today die
than (as) 20 years ago?



4. a) Respondent's month and year of birth.
b) Respondent's age.

5. a) Were you born in (surveyed country)?

b) If answer to 5a is negative, in what
country were you born?


Grows rapidly
Grows slowly
No change
Decreases
No response

Fast population growth
Slow population growth
Unchanged population size
Population decrease
No response


More often
Less often
Same
No response


a) Yes
b) No









78 APPENDIXES

c) If answer to 5a is positive, were you
born in ?



d) If you were not born in (surveyed city),
how old were you when you moved
permanently to this city?


6. a) What is (was) your father's main
occupation?

b) In his occupation, what (is) (was) your
father?



7. How many live-born children did your
mother bear? Please indicate total num-
ber of live-born children, even if born in
different marriages (unions).






8. In your opinion, what is the ideal age for
a woman to get married?










9. a) In your opinion, what is the ideal
number of children a family should
have?


a) Capital city
b) Another city
c) Small town
d) No response

a) 1 year or less
b) More than 1 but less than
2 years
c) Between 2 and 4 years
d) Between 4 and 9 years
e) Between 10 and 14 years
f) 15 years or more
g) No response
h) Not applicable


a) Employer
b) Employee
c) Self-employed
d) No response

a) 1-2
b) 3-4
c) 5-6
d) 7-8
e) 9-10
f) 11-12
g) 13-14
h) 15 or more
i) Does not know

a) 18 years or less
b) 19 years
c) 20 years
d) 21 years
e) 22 years
f) 23 years
g) 24 years
h) 25 years
i) 26-29 years
j) 30 years or more
k) No response

a) None
b) 1
c) 2
d) 3
e) 4
f) 5
g) 6
h) 7
i) 8 or more
j) As many as might come
k) No response











b) Why not more?


c) Why not less?


10. What is the ideal interval between
marriage and birth of first child?


11. What is the ideal age for a woman to
have her last child?

12. a) Do you think that some time should
elapse between consecutive births?


b) If answer to 12a is positive, how long?


Appendixes 79

a) Economic reasons
b) So that children can live
better
c) Health reasons
d) Avoid further problems
e) Other
f) No response
a) Religious and moral reasons
b) Fear of death
c) Likes children
d) Other
e) No response
a) Less than 1 year
b) Between 1 and 2 years
c) Between 2 and 3 years
d) Between 3 and 4 years
e) Between 4 and 5 years
f) 5 years or more
g) No response


a) Yes
b) No
c) No response

a) 1 year
b) 1 years
c) 2 years
d) 2% years
e) 3 years
f) 3V years
g) 4 years
h) 5 years or more
i) No response
j) Not applicable


13. Have you ever had a child or have you a) Yes
ever been pregnant? If answer is nega- b) No
tive please go on to question 19a.


14. a) For each child presently alive, please
give


Name
Age
Month and age of birth


b) Have you included all your living chil- a) Yes
dren, even those not living with you? b) No

15. a) Have you had other children who are a) Yes
dead now? b) No


b) If answer to 15a is positive, please
give


a) Month and year of birth
b) Sex
c) Month and year of death









80 APPENDIXES

16. a) In addition to the births you have al- a) Yes
ready mentioned, have you ever had a b) No
miscarriage, abortion, or child born
dead?

b) If answer to 16a is positive, between
which pregnancies did this happen?
Please specify if pregnancy resulted in
a child born dead, spontaneous
abortion, or provoked abortion.

17. a) If there is an interval of 2 years or a) Yes
more between births or miscarriages, b) No
the interviewer should ask: How come
such a long time elapsed between your
(number) and your (number)
pregnancies? Have you forgotten any
pregnancy?

b) If answer to 17a is positive, record
information here and in question 14a.

18. As a summary please repeat the
following information:
a) How many live births have you had?
b) How many of these children have died?
c) How many children are alive now?
d) How many stillborn children have
you had?
e) How many miscarriages have you had?
f ) Are you pregnant now?
g) How many pregnancies have you had?

19. a) Do you want to have (more) children a) Yes
(than you already have)? b) No

b) If answer to 19a is positive, how a) 1
many? b) 2
c) 3
d) 4
e) 5
f) 6
g) 7
h) 8 or more
i) As many as might come
j) Does not know
k) Not applicable
c) At what age would you like to give
birth to your last child?

20. If you were to start a family now, how a) None
many children would you like to have? b) 1
c) 2
d) 3
e) 4









Appendixes 81

5
6
7
8 or more
As many as might come
Does not know


21. Before this interview, had you ever
thought of the number of children you
would like to have?

22. Do you approve of a married woman
working outside the home?



28. a) What is your religion?


a) Yes
b) No
c) No response


Yes
No
Undecided
No response


a) Catholic
b) Protestant
c) Jewish
d) Other
e) None
f) No response


b) Do you attend religious services?


c) If answer to 23b is positive,
how often?





d) If Catholic, do you receive
communion?

e) If answer to 23d is positive,
how often?


24. What was the last year of formal
education you completed?

25. Besides this, have you taken any other
courses? If so, which?


26. a) Are you presently working in any
activity for which you earn money?


a) Yes
b) No


a) Once or several times a week
b) Once or twice a month
c) Less frequently
d) Never
e) No response
f) Not applicable

a) Yes
b) No

a) Once or several times a week
b) Once or twice a month
c) Several times a year
d) Once a year
e) Less than once a year
f) No response
g) Not applicable


a) Yes
b) No


a) Yes
b) No
c) No response









82 APPENDIXES


b) If answer to 26a is positive, where
do you work?



c) What is your occupation?

d) For those working outside the home,
how many hours per week do you
work at this occupation?





27. a) What level of education would you
like or would you have liked for your
eldest son?


b) What occupation would you like or
would you have liked for your eldest
son?

28. a) How often do you read newspapers?


b) How often do you read magazines?




29. a) What is your view of the world?



b) Should women have the same work
opportunities as men?


c) Which is more important for a parent
to expect from his (her) children?


d) Should women participate in politics?



e) Do you approve of mixed education of
boys and girls?


f) Women should be confined to do
household chores.


a) At home
b) Outside the home
c) No response
d) Not applicable



a) Less than 10 hours
b) 10-19 hours
c) 20-29 hours
d) 30-39 hours
e) 40 hours or more
f) No response
g) Not applicable


Primary
Secondary
University
No response


Does not read newspapers
Once in a while
Daily
No response

Does not read magazines
Once in a while
Weekly
No response

There is progress
Things never change
No response

Yes
No
No response

Obedience
Love
No response

Yes
No
No response

Yes
No
No response

Agree
Disagree
No response









Appendixes 83

80. a) How much money do you usually a) Weekly
spend on your family? This amount b) Monthly
ought to include food, clothing, trans-
portation, and other expenditures ex-
cept rent.

b) How many people are included in this a) Number of persons 10 years
expenditure? old or younger
b) Number of persons 11 years
old or older
c) Total

31. a) How much rent do you pay for your a) Monthly
house? b) Weekly
b) If the house is owned by its occupants,
how much do you estimate you would
have to pay for a house similar to this?

Questions 32 and 88 are applicable only to women with 6 years or less of
formal education.

32. a) What is your present marital status? a) Single
b) Consensually married
c) Legally married
d) Separated from a legal
marriage
e) Separated from a consensual
union
f) Divorced
g) Widow from a legal marriage
h) Widow from a consensual
union

Questions 32b through 32j are applicable only to women who responded d),
e), f), g), or h) in question 82a


b) If respondent has been legally or con-
sensually married, please give month
and year in which (you separated) (he
died) (you got divorced).

c) If respondent has been legally or con-
sensually married, how old were you
when (you separated) (he died) (you
got divorced)?

d) If respondent has been legally or con-
sensually married, please give month
and year in which you (got married)
(began living in concubinage).

e) If respondent has been legally or con-
sensually married, how old were you
when you (got married) (began living
in concubinage)?









84 APPENDIXES

f) If respondent has been legally or con- a) Yes
sensually married, did you have a b) No
previous marital union?

g) If respondent has had more than one
marital union, please give month and
year in which you previously (got
married) (began living in concubinage).

h) If respondent has had more than one
marital union, how old were you when
you previously (got married) (began
living in concubinage)?

i) If respondent has had more than one
marital union, in what month and
year was the previous marriage
terminated?

j) If respondent has had more than one
marital union, how old were you when
the previous marriage terminated?


33. a) If respondent is either legally or con-
sensually married, please give month
and year in which you (got married)
(began living in concubinage).

b) If respondent is either legally or con-
sensually married, how old were you
when you (got married) (began living
in concubinage)?

c) If respondent is either legally or con- a) Yes
sensually married, did you have a b) No
previous marital union?

d) If respondent is either legally or con-
sensually married and has had more
than one marital union, please give
month and year in which you previ-
ously (got married) (began living in
concubinage).

e) If respondent is either legally or con-
sensually married and has had more
than one marital union, how old were
you when you previously (got married)
(began living in concubinage)?

f) If respondent is either legally or con-
sensually married and has had more
than one marital union, in what month
and year was the previous marriage
terminated?








Appendixes 85

g) If respondent is either legally or con-
sensually married and has had more
than one marital union, how old were
you when the previous marriage ter-
minated?
Questions 34 and 35 are applicable only to women with more than 6 years of
formal education.
34. a) What is your present marital status? a) Single
b) Consensually married
c) Legally married
d) Separated from a legal
marriage
e) Separated from a consensual
union
f) Divorced
g) Widow from a legal marriage
h) Widow from a consensual
union
Questions 34b through 34j are applicable only to women who responded d), e),
f), g), or h) in question 34a.

b) If respondent has been legally or con-
sensually married, please give month
and year in which (you separated) (he
died) (you got divorced).

c) If respondent has been legally or con-
sensually married, how old were you
when (you separated) (he died) (you
got divorced)?

d) If respondent has been legally or con-
sensually married, please give month
and year in which you (got married)
(began living in concubinage).

e) If respondent has been legally or con-
sensually married, how old were you
when you (got married) (began living
in concubinage)?

f) If respondent has been legally or con- a) Yes
sensually married, did you have a pre- b) No
vious marital union?

g) If respondent has had more than one
marital union, please give month and
year in which you previously (got mar-
ried) (began living in concubinage).

h) If respondent has had more than one
marital union, how old were you when
you previously (got married) (began
living in concubinage)?









86 APPENDIXES

i) If respondent has had more than one
marital union, in what month and year
was the previous marriage terminated?

j) If respondent has had more than one
marital union, how old were you when
the previous marriage terminated?

35. a) If respondent is either legally or con-
sensually married, please give month
and year in which you (got married)
(began living in concubinage).

b) If respondent is either legally or con-
sensually married, how old were you
when you (got married) (began living in
concubinage)?

c) If respondent is either legally or con- a) Yes
sensually married, did you have a b) No
previous marital union?

d) If respondent is either legally or con-
sensually married and has had more
than one marital union, please give
month and year in which you (got
married) (began living in concubinage).

e) If respondent is either legally or con-
sensually married and has had more
than one marital union, how old were
you when you previously (got married)
(began living in concubinage)?

f) If respondent is either legally or con-
sensually married and has had more
than one marital union, in what month
and year was the previous marriage
terminated?

g) If respondent is either legally or con-
sensually married and has had more
than one marital union, how old were
you when the previous marriage
terminated?

Questions 36 through 49 are applicable only to women either legally or con-
sensually married at the time of the interview.

36. a) Was your husband born in (surveyed a) Yes
country)? b) No

b) If answer to 36a is negative, in what
country was he born?











c) If answer to 36b is positive, was he
born in ?



87. a) What was the last year of formal
education your husband completed?

b) Besides this, has he taken any other
courses? If so, which?


38. a) What is (was) your husband's (last)
occupation?

b) In this occupation, what is (was) your
husband?



c) If husband is (was) employer, does
(did) he employ personnel?


Appendixes 87

a) Capital city
b) Another city
c) Small town
d) No response


a) Yes
b) No


a) Employer
b) Employee
c) Self-employed
d) No response

a) Yes
b) No
c) No response


d) If answer to 38c is positive, how many?

e) What was your husband's main occupa-
tion when you (got married) (began
living in concubinage)?


f) In this occupation, what was your
husband?



39. What is (was) your father-in-law's main
occupation?

40. Have you and your husband ever dis-
cussed the number of children you would
like to have?

41. a) Do you think your husband wants to
have (more) children (than you already
have)?

b) If answer to 41a is positive, how
many?


a) Employer
b) Employee
c) Self-employed
d) No response




a) Yes
b) No
c) No response

a) Yes
b) No


a) 1
b) 2
c) 3
d) 4
e) 5
f) 6
g) 7
h) 8 or more









88 APPENDIXES


42. a) Do you think that having a (another)
child would be inconvenient for you?


b) If answer to 42a is positive, why
would it be inconvenient?


43. If you were to have a (another)
child, when would you want to have it?








44. a) Who usually makes the important de-
cisions in your home, such as buying
expensive goods or choosing a house?


b) Who usually makes decisions on rais-
ing and educating children?




45. a) Does your husband help you with
household chores?


b) If answer to 45a is positive, how often?



46. Do (household chores) (professional
activities) leave you sufficient time for
leisure?



47. On Sundays, is your husband engaged in
leisure activities of his own (i.e., sports,
out with friends, etc.) or is he usually
with you?


As many as might come
Does not know
Not applicable

Yes
No
No response

Economic reasons
Mother's health
Raising children is too much
work
Fear
Other
No response

In 1 year
In 1% years
In 2 years
In 2% years
In 3 years
In 38 years
In 4 years
In 5 years or more
Does not respond

You alone
Your husband alone
Both
No response

You alone
Your husband alone
Both
No response


Yes
No
No response

Frequently
Once in a while
No response


Very much so
Sufficient time
Little time
No time
No response

Frequently with her
Sometimes with her
Seldom with her
Never with her
No response











48. a) There are couples who avoid having
too many children. When do you ap-
prove of this?





b) If answer to 48a was b), c), or d),
after how many children do you
approve of a couple avoiding having
(more) children?








49. a) Do you approve of receiving informa-
tion on limiting family size?


b) If answer to 49a is positive, who be-
sides your family should provide you
with this information? Please indicate
only one.


50. Have you ever heard of, or used, or are
you presently using any of the following
means of avoiding children?

a) The douche, or a method of internal
washing.


b) Sterilization, or an operation so that
the woman cannot have children.


c) The diaphragm, or a rubber ring that
the woman can use.


Appendixes 89

a) Never
b) Only if the mother's health
is endangered
c) If the family does not have
enough money
d) Always
e) No response

a) After the first
b) After the second
c) After the third
d) After the fourth
e) After the fifth
f) After the sixth
g) After the seventh or more
h) Whenever the situation calls
for it
i) Whenever they want
j) No response

a) Yes
b) No
c) No response

a) Physicians or medical
personnel
b) Maternity hospitals
c) The Church
d) Sex education courses
e) Books, newspapers, maga-
zines, etc.
f) Others


a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response

a) Never heard of it
b) Has heard but never
operated
c) Has been operated
d) No response

a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response









90 APPENDIXES

d) Chemical jellies.


e) The rhythm, or abstaining from sexual
intercourse over some periods during
the month.




f) The preservative, prophylactic rubber,
or condom.





g) Withdrawal before termination of
the sexual act.





h) Other (specify).







51. For respondents who have used a method
of contraception.
a) How did you first learn about the last
method of contraception you used?








b) How did you first learn about the first
method of contraception you ever used?


a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response

a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response

a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response

a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response


a) Never heard of it
b) Has heard but never used
c) Has used but is not presently
using
d) Is presently using
e) No response



a) Mother
b) Sister
c) Another relative
d) Husband
e) Neighbors or friends
f) Physician or nurse
g) Books, magazines, etc.
h) Other
i) No response

a) Mother
b) Sister
c) Another relative
d) Husband
e) Neighbors or friends
f) Physician or nurse
g) Books, magazines, etc.









Appendixes 91

h) Other
i) No response


c) When did you start using the (first)
method of contraception?









d) Whose idea was it to use the (first)
method of contraception?



52. If respondent is currently using a method
of contraception, how often do you use it?



53. a) For respondents who are not using the
pill at the time of the interview, if you
could have access to contraceptive pills,
would you use them?

b) If answer to 54a is negative, why?


54. a) Why do you think people who limit
their family size do so? Please indicate
only the most important.






b) Do you agree with this reason?


a) Before the first pregnancy
b) After the first pregnancy
c) After the second pregnancy
d) After the third pregnancy
e) After the fourth pregnancy
f) After the fifth pregnancy
g) After the sixth pregnancy
h) After the seventh pregnancy
i) After the eighth pregnancy
j) After the ninth pregnancy
k) No response

a) Wife's alone
b) Husband's alone
c) Both husband's and wife's
d) No response

a) Always
b) Sometimes
c) Seldom
d) No response

a) Yes
b) No
c) No response


a) Does not want to limit
family size
b) Dangerous to health
c) Too expensive
d) They sterilize women
indefinitely
e) Husband's opposition
f) Unpleasant side effects
g) Could affect sexual life
h) Other
i) No response

a) Facilitate economic develop-
ment of the country
b) Improve family situation
c) Raise children better
d) Protect mother's health
e) Selfishness, lack of morality
and religion
f) Other
g) No response

a) Yes
b) No
c) No response









92 APPENDIXES


55. a) Why do you think some people think
they should have as many children as
might come? Please indicate only the
most important.












b) Do you agree with this reason?


a) They like children
b) Religious reasons
c) Danger of sexual promiscuity
in use of contraception
d) Contraception is dangerous
to health
e) Contraception decreases fer-
tility and causes sterility
in women
f) Contraceptives are
unpleasant
g) Contraceptives are
inefficient
h) Other
i) No response

a) Yes
b) No
c) No response


























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