• TABLE OF CONTENTS
HIDE
 Main
 Dedication
 Acknowledgement
 Table of Contents
 List of Tables
 Abstract
 Introduction
 Previous work relating socioeconomic...
 Theoretical framework
 Empirical considerations
 Empirical results -- regional...
 Empirical results -- income-group...
 Empirical results -- average weekly...
 Summary and implications for further...
 Appendix
 References
 Biographical sketch














Group Title: econometric analysis of socioeconomic and demographic determinants of fish and shellfish consumption in the United States /
Title: An econometric analysis of socioeconomic and demographic determinants of fish and shellfish consumption in the United States /
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Permanent Link: http://ufdc.ufl.edu/UF00099240/00001
 Material Information
Title: An econometric analysis of socioeconomic and demographic determinants of fish and shellfish consumption in the United States /
Physical Description: x, 176 leaves : ill. ; 28 cm.
Language: English
Creator: Perry, Jonathan S., 1954-
Publication Date: 1981
Copyright Date: 1981
 Subjects
Subject: Fishery products -- United States   ( lcsh )
Market surveys -- United States   ( lcsh )
Food consumption -- United States   ( lcsh )
Fish trade -- United States   ( lcsh )
Shellfish trade -- United States   ( lcsh )
Food and Resource Economics thesis Ph. D
Dissertations, Academic -- Food and Resource Economics -- UF
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Thesis: Thesis (Ph. D.)--University of Florida, 1981.
Bibliography: Bibliography: leaves 173-175.
General Note: Typescript.
General Note: Vita.
Statement of Responsibility: by Jonathan S. Perry.
 Record Information
Bibliographic ID: UF00099240
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: alephbibnum - 000295975
oclc - 07991518
notis - ABS2328

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Table of Contents
    Main
        Page i
    Dedication
        Page ii
    Acknowledgement
        Page iii
    Table of Contents
        Page iv
        Page v
    List of Tables
        Page vi
        Page vii
        Page viii
    Abstract
        Page ix
        Page x
    Introduction
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
    Previous work relating socioeconomic and demographic factors to fish and shellfish consumption
        Page 8
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        Page 10
        Page 11
        Page 12
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    Theoretical framework
        Page 21
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        Page 27
        Page 28
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    Empirical considerations
        Page 33
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    Empirical results -- regional models
        Page 62
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    Empirical results -- income-group models
        Page 96
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    Empirical results -- average weekly expenditures and food stamp models
        Page 140
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    Summary and implications for further research
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    Appendix
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    References
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    Biographical sketch
        Page 176
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Full Text












AN ECONOMETRIC ANALYSIS OF SOCIOECONOMIC AND
DEMOGRAPHIC DETERMINANTS OF FISH AND SHELLFISH
CONSUMPTION IN THE UNITED STATES









BY


JONATHAN S. PERRY


A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY


UNIVERSITY OF FLORIDA


































To my mother and father -- who taught me the important things.














ACKNOWLEDGMENTS


The author expresses sincere appreciation to Dr. F.J. Prochaska,

Dr. J.C. Cato, and Dr. J.A. Koburger for taking time from their sched-

ules to serve on his Advisory Committee. Their comments, criticisms,

and suggestions upon reviewing the drafts of this manuscript served to

make it a more scholarly work and were appreciated. A special note of

thanks is due F.J. Prochaska, Chairman of the Advisory Committee, for

his suggestions and guidance throughout the course of the authors

graduate career.

A special note of gratitude must be extended to Ramona Rochester,

Renelle Phillips, and Shirley Harris, for typing the numerous drafts

of this dissertation. A debt is also owed Carolyn Almeter and Debbie

Miller for their aid with the computational aspects of this work.

Appreciation must also be expressed to Dr. Leo Polopolus, Department

Chairman, and Dr. F.J. Prochaska, for their aid with financial support

throughout the author's graduate study.

Finally, the author is indebted to his family and wife for their

support, understanding, and cooperation throughout the course of his

graduate work.













TABLE OF CONTENTS


ACKNOWLEDGMENTS.. .....
LIST OF TABLES . . . .
ABSTRACT . . . . . .

CHAPTER


I INTRODUCTION . . . . .

Problem Statement . . . . . . . . .
Objectives . . . . . . .. . .
II PREVIOUS WORK RELATING SOCIOECONOMIC AND DEMOGRAPHIC
FACTORS TO FISH AND SHELLFISH CONSUMPTION .. . ...

Demand Analysis of Fish and Shellfish Products..
Consumption Studies of Fish and Shellfish Products.
Focus of the Present Research .. . .......
III THEORETICAL FRAMEWORK .. . . ..........

The Level of Aggregation .. . . .......
The General Expenditure Income Relationship .
Modification of the General Engle Curve Model . .
The Modified Expenditure Income Model .. ....
IV EMPIRICAL CONSIDERATIONS . . . . . . . .

Functional Form . . . . . . . . .
The Data . . . . . . . . . .
The Tobit Model . . . . . . . . .
The Independent Variables .. . ........
The Empirical Model . . . . . . . .
The Fully Specified General Model .. . .....
Food Stamps .............
Statistical Considerations .. . . ......


__








CHAPTER Page

V EMPIRICAL RESULTS--REGIONAL MODELS . . . .... .62

Introduction. .............. ..... 62
Southern Regional Model Results . ... ..... 63
Northeastern Regional Model Results . . ... 74
Western Regional Model Results. . . . . .. 81
North Central Regional Model Results. . .... 88

VI EMPIRICAL RESULTS--INCOME-GROUP MODELS . . . ... 96

Introduction. . . . . . ... ...... .96
Southern Income-Group Model Results . . ... 96
Northeastern Income-Group Model Results . . .. 108
Western Income-Group Model Results. . . . ... 118
North Central Income-Group Model Results. .... . 129

VII EMPIRICAL RESULTS--AVERAGE WEEKLY EXPENDITURES AND FOOD
STAMP MODELS .................. .. 140

Introduction. . . . . .. . . . . 140
Tabular Analysis of Weekly Expenditures . .. 140
Effect of Food Stamps on Household Expenditures . 152
Average Weekly Expenditures of Households Receiving
Food Stamps by Race . . . . . 159

VIII SUMMARY AND IMPLICATIONS FOR FURTHER RESEARCH. .... . 160

Summary . . . . . . . 160
Implications for Further Research . . . .. 167

APPENDIX . . . . . . . . . . . . ... 171

REFERENCES . . . . . . . . . . .. . .. 173

BIOGRAPHICAL SKETCH. . . .... ..... . . . 176















LIST OF TABLES


Table Page

1 Number of observations in BLS CEDS data by survey year.. 39

2 Number of households in regional and income groups after
BLS data was stratified by income and region. . . . 56

3 Income variable coefficient's sign and significance . 64

4 Southern regional model coefficients and standard errors. 65

5 Away-from-home expenditure variable coefficient's sign
and significance. .............. ..... 66

6 Race variable coefficient's sign and significance . .. 67

7 Urbanization variable coefficient's sign and significance 68

8 Occupation variable coefficient's sign and significance 69

9 Education variable coefficient's sign and significance. 69

10 Adult male variable coefficient's sign and significance 70

11 Adult female variable coefficient's sign and significance 71

12 Infant variable coefficient's sign and significance . 72

13 Elderly male variable coefficient's sign and significance 73

14 Elderly female variable coefficient's sign and signifi-
cance .................. .. ... ... 74

15 Regional expenditure income elasticity of demand values 76

16 Northeastern regional model coefficients and standard
errors. . . . . . ... .. . . . . . 77

17 Western regional model coefficients and standard errors 82

18 North Central regional model coefficients and standard
errors. . . . . . . . .. .... 89

19 Southern income group coefficients--sign and significance 97








Table Page

20 Southern total expenditure income group coefficients and
standard errors. . . . . . . . . . .99

21 Southern shellfish expenditure income group coefficients
and standard errors. . . . . ... 100

22 Southern filleted and steaked expenditure income group
coefficients and standard errors . . . . .. 102

23 Southern whole fish expenditure income group coefficients
and standard errors. . . . . . . . . 103

24 Southern canned fish expenditure income group coeffi-
cients and standard errors . ... . . .... 104

25 Northeastern income group coefficients--sign and
significance . . . . . .. . ..... . .109

26 Northeastern total expenditure income group coefficients
and standard errors. ..... . . . . . 111

27 Northeastern whole fish expenditure income group co-
efficients and standard errors ... . . ... .. 112

28 Northeastern shellfish expenditure income group co-
efficients and standard errors . . . . .... .114

29 Northeastern canned fish expenditures income group co-
efficients and standard errors . . . . ... .. 115

30 Northeast filleted and steaked expenditure income group
coefficients and standard errors . . . . . .. 117

31 Western income group coefficients--sign and significance 119

32 Western total expenditure income group coefficients and
standard errors. .... . . . . .. . 120

33 Western filleted and steaked expenditure coefficients
and standard errors. .. .. ... . . . . 122

34 Western canned fish expenditure income group coeffi-
cients and standard errors . . . .... . ... 124

35 Western shellfish expenditure income group coefficients
and standard errors. .. .. ... ........ .125

36 Western whole fish expenditure income group coefficients
and standard errors. . ... . ......... .126

37 North Central income group coefficients--sign and signif-
icance . . . . . . . . . . .. 130


vii









Table Page

38 North Central total expenditure income group coefficients
and standard errors. . . . . ...... . 131

39 North Central whole fish expenditure income group co-
efficients and standard errors . .. . .. . 133

40 North Central filleted and steaked expenditure income
group coefficients and standard errors .. . . . 134

41 North Central canned fish expenditure income group co-
efficients and standard errors . . ... .. .... 137

42 North Central shellfish expenditure income group co-
efficients and standard errors . ... .... . . 139

43 Average weekly expenditures and income by region .. 141

44 Average weekly expenditures and income by region and
urbanization ... ... .. ......... . . 142

45 Average weekly expenditures and income by race .... . 144

46 Average weekly expenditures and income by region and
race . . ... ........ ..... . 145

47 Average weekly expenditures and income by income groups. 147

48 Average weekly expenditure and income by region and in-
come group . . ... .. ...... ....... 149

49 Average weekly expenditures and income by occupation of
household head ....... . . . ..... 150

50 Average weekly expenditures and income by region and
occupation of household head . . . . . . 151

51 Average weekly expenditures and income by education
level of household head. .. ... . . . 153

52 Food stamp model coefficients standard errors and
elasticities . ... ..... ..... . . 155

53 Food stamp model coefficient--sign and significance. . 156

54 Average weekly expenditures and income of food stamp
recipients by race ... .. . .. . . 159














Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy


AN ECONOMETRIC ANALYSIS OF SOCIOECONOMIC AND DEMOGRAPHIC
DETERMINANTS OF FISH AND SHELLFISH CONSUMPTION IN THE UNITED STATES

By

Jonathan S. Perry

August 1981


Chairman: Frederick J. Prochaska
Major Department: Food and Resource Economics

Weekly household expenditures on fish and shellfish products in

the United States were analyzed through estimation of an Engel curve

relationship. Expenditures on five product groups (canned fish, shell-

fish, whole fish, filleted and steaked fish, and total expenditures)

were expressed as a function of thirteen variables reflecting household

socioeconomic and demographic characteristics. Variables included were

income, race, expenditures on food away-from-home, education, occupation,

urbanization and an adult equivalent scale.

Data employed were collected by the Bureau of Labor Statistics

during the 1972-1974 Consumer Expenditure Diary Survey. The 23,186

households studied were segregated into four regions and three income

groups. A separate equation for each expenditure category was estimated

for each region and each income group. Expenditures were considered

limited dependent variables and Tobit analysis used. The solution algo-

rithm chosen was Phelps' version of LIMDEP.









Income, race, and the adult equivalent scale were consistently

significant in explaining expenditures on all product groups. Income

had a significant positive impact on all expenditure categories except

whole fish. The Northeast tended to have the largest income coefficients,

expenditure income elasticities of demand, and average weekly expenditures.

Smallest elasticities occurred in the South while the North Central

states had the smallest average expenditures. Among product groups the

largest elasticities were associated with shellfish and the smallest

with filleted and steaked products.

Race was an important determinant of expenditures with Black house-

holds often predicted to spend $2.00 per week more on fresh fish pro-

ducts than Whites. Whites tended to have larger expenditures on

canned fish. Of the adult equivalent scale variables adult males and

females, and elderly males had a larger impact on expenditures than

infants or elderly females. Occupation had no consistent impact on

purchases while urbanization had an impact only in the Northeast and

West. Education was significant for canned fish expenditures in all

regions.














CHAPTER I

INTRODUCTION

One traditional use of the world's freshwater and marine resources

has been as a source of food. In particular, they have long been ex-

ploited as sources of high quality animal protein. In the United States,

per capital consumption of fish and shellfish products has steadily in-

creased during the past two decades. In 1960, per capital consumption of

fish and shellfish was 10.3 pounds edible meat weight. By 1970, this

had increased to 11.8 pounds. In 1978, per capital consumption reached

a record level of 13.4 pounds [U.S. Department of Commerce, 1979]. These

figures reflect only consumption of those products moving through commer-

cial channels. Per capital consumption from recreational catches is esti-

mated to be three to four pounds annually [U.S. Department of Commerce,

1980]. Thus, actual consumption of fishery products in the United States

is somewhere in the neighborhood of 16 to 17 pounds of edible meat per

person annually. With respect to the overall level of consumption,

the United States ranks 39th of 132 countries worldwide. On a live

equivalent basis, this amounts to 35.1 pounds per capital annually which

compares with a high of 164.7 pounds for Japan and an annual world average

of 28.9 pounds [U.S. Department of Commerce, 1979]. For the world as a

whole and the United States in particular, the increases in consumption

of fishery products seen in recent decades are likely to continue. The

Food and Agricultural Organization of the United Nations predicts fish

and shellfish consumption will probably increase through 1990 at a growth








rate in excess of that seen for beef, pork, vegetables, cereal, and

milk [Office of Technology Assessment, 1977]. This projection is the

result of several factors. In developed countries, changes in tastes

are shifting consumption patterns away from red meats to consumption of

leaner protein sources including fish [Comptroller General of the United

States, 1976]. Combining with this is the continued increase in popula-

tion of developed and developing countries, which in itself increases

overall use of these products. Thus, fish and shellfish are becoming

more prominent parts of household diets and will continue to do so in

the next ten to twenty years. As this trend develops, additional in-

formation about households consuming these products will be useful to

many sectors.

The programs involved with the passage of the Fisheries Conservation

and Management Act of 1976 (PL 94-265) require the public sector to have

information about consumers of fishery products. The legislation has

implications for many areas other than those directly involved in uti-

lizing or regulating the marine resource. Expressed in the bill is the

desire that the ocean resource be used to provide society maximum social,

biological, and economic gain. One stated objective in achieving this

is to encourage expansion of the American fishing industry. Specifically

proposed goals include: ". .. [encouraging] the development of fish-

eries which are currently underutilized or not utilized by United States

fishermen. . and [revitalizing] the existing fishing industry, .. "

(PL 94-265, Section 2, pp. 2,3). In line with these objectives, the

Office of Technology Assessment has identified three critical areas which

must be developed if PL 94-265 is to succeed. These are: 1) stock

enhancement, 2) creation of markets for fish and shellfish U.S. fishermen








do not currently harvest, and 3) a revitalization of the industry as a

whole [Office of Technology Assessment, 1977, p.95]. The programs

developed in these areas will directly affect household use of fish and

shellfish products. However, just as these programs will affect house-

holds, the acceptance with which they are received by this same group

will directly determine their success. In particular, household behavior

will have a pronounced effect on the success of programs coming from the

OTA's latter two mentioned critical areas. This relationship, that

between the success of these programs and the behavior of the American

consumer, arises directly from economic theory. Here it is stated that

in a market economy it is the wants and desires of consumers which ulti-

mately dictate how and where resources are utilized [Leftwich, 1976,

p.19]. The prices consumers are willing to pay and the quantities they

are willing to take ultimately direct production effort. Because of this,

consumer behavior is of paramount importance to the success of any pro-

duction or marketing program. Information giving insight into consumer's

tastes, preferences, or behavior should therefore be a valuable aid. It

should also assist governing bodies enacting legislation affecting

production or marketing programs. Processors, packers, and other com-

ponents away from the actual production process will likewise benefit.

By better understanding their target markets, they will be in a position

to use society's resources more efficiently. They will gain the ability

to cater more directly to the whims and desires of their customers. In-

formation of this type should eventually affect advertising programs,

product development and design.

The difficulties resulting from ignoring market and consumer informa-

tion have been recognized. Academic institutions frequently act as a








research and development arm for private industry. When they make

recommendations regarding new products and product forms they have to

seriously examine information relating to potential consumers of these

products. The Sea Grant program of the National Oceanic and Atmospheric

Administration is an excellent example of one area in which information

of this type can provide guidance. Historically, product development

and work to reduce costs and streamline processing have dominated re-

search efforts. The consumer's end of the market spectrum has often been

ignored. Because of this, much Sea Grant effort to develop new products

has been unproductive [Smith, n.d.]. This has resulted in part from the

tendency to examine the situation from the producer's veiwpoint, ignoring

the implications of consumer characteristics, desires and tastes [Smith,

n.d.]. Too few conscious attempts have been made to coordinate produc-

tion activities with the wants of consumers. Information about consumer

behavior can be used to guide development of products and lessen the

chance of wasting resources on products which are likely to fail or

enjoy only limited success. In this way, knowledge of consumer desires,

tastes, preferences and other characteristics can be used to enhance

the possibilities of success of the products recommended by institutional

research as well as those of the private sector.

The amount of information available about consumer behavior relating

specifically to fishery products has been limited. The actual and poten-

tial increases in consumption of fish and shellfish foreseen because of

changing preferences, continued increases in population level, and

consequences of stated goals of several aspects of PL 94-265 will, in

all likelihood, be substantial. Information about consumer behavior

relating to these goods will therefore be a valuable aid to the various








groups whose decisions will affect the production, processing, marketing

and consumption of these products.


Problem Statement


Through the past twenty years, per capital consumption of fish and

shellfish in the United States has increased. This has resulted in part

from a shift in tastes and preferences away from red meats to leaner

sources of protein including fish [Comptroller General of the United

States, 1976]. Thus, markets for fishery products have strengthened

gradually through these two decades. This trend is projected to con-

tinue with gains in consumption of fish and shellfish products exceeding

projected growth of such traditional protein sources as beef, pork, and

milk. Higher per capital consumption of fishery products is expected to

continue at least through 1990.

The passage of the Fisheries Conversation and Management Act of

1976 may affect the trend in seafood consumption. As a component to

meeting the stated objective of revitalizing the U.S. fishing industry

it encourages increased usage of the food potential of the nation's ocean

resource. The strengthening of existing markets and development of

markets for new products are essential if this is to be accomplished.

The success of the programs designed to affect this increase in con-

sumption depend directly on consumer motivations and their attitude to-

ward the resulting products. Consumer behavior plays a critical role

in determining the products they select in the market. Knowledge of

consumer characteristics, motivations, preferences, and the implication

these factors have on behavior can aid those designing programs to carry

out policy goals by providing insight into how consumers can be expected








to react to alternative program schemes. This information can give

valuable guidance in program formulation and in selecting for imple-

menting those which will be most effective and efficient and likely to

succeed.

Coupled with this specific need for information about consumer be-

havior and expenditure patterns on fishery products is a more fundamental

need for basic fish and shellfish consumption information. In the past,

basic information relating to parameter magnitudes has been infrequently

available for broad aggregates of these products at the national and

regional level. As fish and shellfish become a more significant part

of the American diet, such information will be useful in providing more

knowledge about consumption of these goods. Possibly of even more value,

it will allow comparisons with similar parameters of other consumer pro-

ducts. The understanding gained through comparisons of this type is

one avenue through which knowledge is increased. An increased level in

the store of basic information places the research, production, marketing

and consumption coalition in better position to make even greater improve-

ment in the efficient utilization of this and other food resources.


Objectives
The purpose of this dissertation was to provide basic information

relating to household consumption of fish and shellfish products in the

United States. Specifically, the objectives of the research were to:

1) Develop an econometric model relating household expenditures

on fishery products to the household's socioeconomic and demo-

graphic characteristics.

2) Determine behavioristic parameters elasticitiess), quantifying

consumer response to changes in given variables both in the





7


household and in the market place for broad aggregates of

fishery products.

3) To determine the significance of food stamps on fishery

product expenditures for those households receiving them in

the 1972-1974 Bureau of Labor Statistics diary survey sample.

4) To allow comparisons with previous research, a tabular analysis

of average fish and shellfish expenditures made by households

included in the Bureau of Labor Statistics, survey is made

after the sample was stratified by a series of socioeconomic

and demographic factors.














CHAPTER II

PREVIOUS WORK RELATING SOCIOECONOMIC AND
DEMOGRAPHIC FACTORS TO FISH AND SHELLFISH CONSUMPTION


Demand Analysis of Fish and Shellfish Products


Previous analyses examining the income consumption relationship

specifically for fishery products have not been available with great

frequency. The balance of previous work has examined the Engel re-

lationship only for particular species or groups of species [Johnston

and Wood, 1974]. Other research has examined characteristics affecting

consumption of fish and shellfish products by households in given cities

or regions of the country. Work relating to consumption of broad aggre-

gates of these products by households at the national level has been

provided [Nash, 1970] but has not been available with the regularity

of literature on other comparable food commodities such as milk pro-

ducts, red meats or poultry.

Purcell and Rauniker [1968] analyzed household demand for fish and

shellfish focusing on consumer reactions to changes in prices, price

relations, income, and other socioeconomic factors. The data were

obtained from a consumer panel in Atlanta made up of 160 households from

1958 through 1962. Pooling of the cross-sectional and time series data

yielded 3,200 observations on which their analysis was based. The authors

divided their analysis into two parts. The first involved a cross-

tabulation of socioeconomic effects on the consumption and expenditures

for various fishery products; the second involved the effects of various








explanatory variables on consumption and expenditures for selected

fish and shellfish products.

Included in the cross-tabulation was information for both house-

hold and per capital quantity consumed, average value of consumption,

quantity purchased by income groups, quantity purchased by household

size, expenditure by household size, and quantity purchased and expendi-

ture by race. Twenty-seven fish and shellfish categories were examined

for each of the socioeconomic characteristics considered. The results

were reported in dollars for each commodity and as a percent of total

expenditure. All information considered related to five-year averages.

Purcell and Rauniker's [1968] second analysis centered around four

different models and seventeen different variables. All models were

based on the simple linear form with the differences involving the income

variables. The four forms of the income variable considered were linear,

squared, square root, and cubed root. Other variables included were

race, five age categories of household members, quarters of the year,

quantities received as gifts, a time trend and a single variable repre-

senting the price of the given fishery product category. Summary

statistics (weighted average purchases by quarter, by income, etc.) were

reported for price, race, trend, number of persons, income and season

coefficients. The information reported involved thirteen different

fish and shellfish categories.

The cross-tabulations showed the quantity of fresh fish purchased

per household to be 14.53 pounds, which was the largest for any category

or product considered. Total average annual expenditure for all fish

and shellfish by household was $17.46. On a per capital basis, annual

expenditure and quantity consumed of all fish and shellfish were $5.24








and 11.33 pounds, respectively. The largest total expenditure for all

fish and shellfish occurred in the highest income category ($12,000 or

more per year). This translated into an average per capital expenditure

on fishery products of $8.56 for this income group. Per capital consump-

tion of fishery products was lowest in households with more than six

members and highest in one-person households. The quantity of fish and

shellfish purchased by non-white households (51.55 pounds) was 82 per-

cent higher than the quantity purchased by White households (28.31

pounds). Comparably, expenditures for fish and shellfish by non-white

households were 36 percent greater than the expenditures by White

households.

Appropriate negative signs were obtained for the net effect of own-

price on the quantity purchased for all categories of products with the

exception of fresh fish. The categories on which the effect of price

was statistically significant were salmon, other fish, oysters, fresh

shrimp, frozen shrimp, and all shrimp. Differences of quantity and ex-

penditure level attributable to race were found for all fish and shell-

fish groups except tuna. The greatest differences were for fresh fish:

White households spent $2.20 less and consumed 7.73 fewer pounds per

quarter than non-white households. Purchases of fresh fish, tuna, and

sardines in oil decreased significantly throughout the twenty quarters

of the study. Quantity and expenditure for other fish, frozen shrimp,

and total shrimp increased throughout the study period. Age was found

to have a considerable impact on consumption. The 6-10 and 11-18 age

groups had the greatest effect on the quantity purchased for total fish

and shellfish. For expenditures, however, the greatest effect for total

fish and shellfish was found for 18 years and older (adult) groups. For








all fish and shellfish categories except one, quantities and expendi-

tures per quarter increased as income increased. Purchases during the

winter were generally greater than in other quarters except for tuna,

sardines in oil, and oysters. The categories in which expenditures

differed most from winter quarter expenditures were fresh fish and total

fish and shellfish (spring), other fish and total fish (summer), and

oysters (spring and summer).

Nash and Bell [1969] in a working paper compiled a set of demand

equations which were estimated for fishery products. The paper resulted

from a 1968 conference sponsored by the Division of Economic Research of

the Bureau of Commercial Fisheries. The purpose of the conference was

to draw together, on a species basis if possible, all of the statistical

demand relationships which had been estimated in past research. Fish

consumption was mathematically related to demand determinants such as

per capital income and prices. It was the conference's task to determine

the function for each species which could be expected to give the best

performance in future research. The equations presented in the working

paper were selected as the most representative of all those submitted.

Equations were presented for twenty-three species. Information relating

to the product, the geographic area of the data, the market level to which

the equation related, the econometric approach used, the form of the

equation, the researcher, and a statistical measure of fit were provided.

Also, in each case the variables used, their t-values, and regression

coefficients were reported.


Consumption Studies of Fish and Shellfish Products


Nash [1970] published the results of one of the first comprehensive

studies examining purchasing patterns for fresh and frozen fish and









shellfish products through a tabular analysis of national data. The

report's primary aim was to present data collected from 1,500 households

from February 1969 to January 1970. The goal of the survey was to ob-

tain a complete record of the fishery product expenditures of the

participants. With this knowledge, information about consumer buying

habits across a broad range of social, economic, and regional character-

istics was provided. The 1,500 households represented nine geographic

regions and eight social, economic and ethnic groups.

Several household characteristics were found to significantly affect

purchases of fish and shellfish products for use in the home. Specific

characteristics considered were race, religion, region, seasonality,

income, and other household characteristics such as size, age of head,

and number of children. Race was found to be the "singularly important"

ethnic factor determining fish and shellfish consumption. Black house-

holds purchased twice the quantity of fresh and frozen shrimp and more

oysters, crabs, ocean perch, red snapper, catfish, and whiting than did

White households. White households tended to purchase more lobster and

halibut. Expenditures on the given categories of products also differed

by race. Whites tended to pay higher prices for salmon and red snapper

while Blacks reported higher prices for lobsters, clams, and crabs.

Religious factors also had a pronounced effect in some cases.

Jewish households, as opposed to Catholics and Protestants, were the

"unquestioned leader" in consumption of flounder-sole, salmon, and the

miscellaneous fish groups. Their purchases of shrimp, crabs, scallops,

halibut, and cod were also "measurably higher." Catholic households

purchased more shrimp, lobster, lobster tails, clams, scallops, haddock,

flounder-sole, and cod. Oysters, red snapper, catfish and whiting

showed higher consumption among Protestant households.








Regional effects on consumption were pronounced in some cases, yet

of no consequence in others. Shrimp was the one product showing the most

even consumption across all geographic regions considered. Crab and

oyster consumption were highly regional--declining rapidly as distance

from the areas of production increased. These products were "virtually

unknown" in interior regions. Because of their use in frozen fish sticks

and portions, ocean perch and groundfish were consumed in all regions.

Income was not found to be as important in explaining purchases as

economic theory would indicate. There was a general, though not steady,

increase in purchases as income increased through the sample. Regarding

the effects of occupational classes, significant differences attributable

to this factor were not noticed.

The effects of household characteristics were found to be important

seafood consumption determinants. Except for catfish, red snapper, and

whiting, greater consumption levels were associated with higher age

classes of the household's head. Nash states that in nearly every case

consumption fell as household size increased.

Away-from-home consumption was also considered. Here a great deal

of specificity was found. Comparisons for lobsters and clams indicated

that these products are consumed more frequently away-from-home. Also,

in the away-from-home market, income seemed to have a more pronounced

effect than in determination of at-home consumption. Age of household

head was also found to increase the frequency with which fish and shell-

fish meals were consumed away-from-home. Regarding race and religion,

away-from-home consumption followed the same general pattern as that

identified for home purchases. As would be expected, Nash found regional

patterns to closely follow those found for home consumption. Seasonal








effects on away-from-home purchases were not pronounced for any product

considered.

Miller and Nash [1971] present additional results of the 1969 to

1970 survey of 1,500 households. This analysis focuses on several

characteristics affecting shellfish consumption. All major shellfish

species were included in their report. Five aspects of consumption were

examined: geographic concentration and distribution patterns, seasonality,

comparison between volumes consumed at home and away from home, relation-

ships between size of incomes and volumes consumed, and the effects of

age on consumer preferences.

Regional factors were found to have a profound effect on consumption.

At-home per capital shellfish consumption in the New England area was

found to be more than twice the national average. The West South Central

states had per capital consumption of shellfish which was well below

average. The rate of finfish consumption in the West South Central region

exceeded the national average by 75 percent.

Oysters were found to show a great deal of regionality in consump-

tion. The South Atlantic states from Maryland south consumed almost 30

percent of the total oysters eaten at home, yet ranked only fourth

nationally in population. Per capital oyster consumption in this region

was nearly double the national average. The regional pattern indicates

oyster consumption is largely confined to major production areas, probably

because of cultural influences and the fact that a large proportion of

this product is consumed in the fresh form. Two other areas, the

South Central and Mountain states, had consumption levels exceeding the

national average. Despite the pronounced regional concentration in

consumption, oysters were known and consumed in all parts of the country.








Clams were also found to be highly regionalized in consumption.

The New England, Middle Atlantic, and Pacific states were the areas of

heaviest use. These three regions accounted for some 37 percent of the

U.S. population, but accounted for 85 percent of the nation's clam con-

sumption during the 1969 to 1970 time period. Tradition was identified

as a major factor influencing this regionality. New England was again

the undisputed leader with an average consumption some nine times the

national average. This region alone accounted for 50 percent of con-

sumption of these products at home. By comparison, the two other regions

of heavy home use of clam products -- the Middle Atlantic and Pacific

regions -- consumed 18 percent and 6 percent of the national total,

respectively. In all other areas per capital consumption was less than

half the national average.

Crab consumption was heavily concentrated in the Pacific Coast area.

The per capital rate of consumption (King and Dungeness crabs) was greater

than three times the national average, amounting to more than 40 percent

of the U.S. total. Outside this region, consumption in all remaining

areas was approximately proportional to the area's population, thus

yielding a consumption level of about the national per capital average.

The top three regions in at-home consumption were the Pacific, South

Atlantic, and Middle Atlantic states.

Regarding American lobster consumption, New England households

showed the highest levels accounting for almost two-thirds of the nation's

purchases for at-home use. The largest part of the remaining one-third

was made by households in the Middle Atlantic and South Atlantic regions.

Use of this product at home in almost all other regions was found to be

almost insignificant. Tradition and high shipping costs are identified








as the primary factors contributing to this regionality. Nash [1970]

postulates that the local market is so strong for the product that the

incentive for opening markets in other areas for the relatively limited

supplies is not great.

In contrast to the above fishery products, shrimp, which are mar-

keted largely in the frozen form, were consumed relatively evenly through-

out the country. Four regions were above average in at-home consumption,

one was about average, and four were below average. The Middle Atlantic

states consumed 24 percent of the total purchased for at-home use. South

Atlantic households were second with 19 percent of the total, while the

East North Central was third with 15 percent.

Like shrimp, scallops are marketed largely in a frozen form, but

here at-home consumption showed geographic concentration. Highest per

capital consumption was found in New England and the Middle Atlantic

regions, which accounted for nearly half the scallops consumed at home.

The Central and Southern states consumed the smallest percentages of

the total. Relative to their percent of the total population, the

Mountain area states were high consumers of scallops with a consumption

level two and a half times the national average.

Frozen lobster tails are most heavily consumed in the Middle Atlantic

region, which accounted for 29 percent of the national total. The East

North Central and East South Central states were also high consumers of

this product, accounting for 27 percent and 16 percent of the nation's

total, respectively.

In a summary of aggregated finfish and shellfish consumption the

authors showed that the Middle Atlantic states who rank second in popula-

tion were the nation's leading market for fishery products. These









states ranked first or second in per capital quantity consumed of four

out of the seven individual specied considered. The South Atlantic

region was just behind the Middle Atlantic in consumption which Nash [1970]

states was consistent with its population. The West North Central states

ranked fifth in population but third in fish and shellfish consumption.

The East North Central region was the nation's most populous area,

but ranked fourth in consumption of fishery products. New England was

eighth in population, but ranked seventh in consumption of fishery

products, thus providing the high per capital levels found in this region

for some species. Of the four remaining areas, the Pacific region ranked

above the remaining three in consumption of these products. All of the

above comparisons relate to per capital levels of consumption for both

finfish and shellfish product.

Miller and Nash [1971] also investigated the effects of seasonality

on consumption and found oysters with the most pronounced pattern with

highest consumption found in the months in which most of the catch is

landed. Clam consumption also showed a seasonal swing which complemented

the shift in oyster consumption. Crab consumption was variable, but not

to the extent found of oysters and clams. Here consumption peaked in July

and again in the winter during January--February. Scallops and shrimp

showed almost no seasonality at all relative to the above three groups.

Both products did show a mild winter peak with a gradual but steady decline

through to November. Nash [1970] found that proportionally more shell-

fish meals are eaten away-from-home than finfish meals. Lobster and

clams are more likely to be eaten out than the other products considered.

Nash's survey "indicated that 59 percent of lobster consumption and 48

percent of clam consumption occur away-from-home." Shrimp and oyster








consumption away-from-home accounts for 21 percent and 19 percent of

the total, respectively. Of the finfish he examined, the proportions

of halibut and flounder eaten out were 11 percent each, while that for

haddock was only 7 percent of total consumption.

in all cases, except oysters, a clear tendency to consume more of

the product as income increased was revealed. The income spread con-

sidered ran from $5,000 and under to $10,000 and over. Regarding ages,

a similar effect was identified. During their survey 50 percent of U.S.

household heads were 45 years or older. However, this group consumed

72 percent of the oysters, 68 percent of the clams, and 70 percent of

the scallops. Conversely, households with the head younger than 35

years consumed only 20 percent of the oysters, 14 percent of the clams,

and 13 percent of the scallops. Shrimp consumption was found to be

even across all age groups. For the finfish, 59 percent was consumed

by families with the head 45 years or older, while those with a head

younger than 35 years consumed 23 percent of the total.

Pippen and Morrison [1975] examined the effects of various economic

and demographic factors on purchases of farm raised catfish. Regarding

income the highest group (annual gross income of $10,000 and above)

tended to purchase the product more often than those in the $5,000 to

$9,999 group or the $4,999 and below group. They state that the differ-

ences were significant and support the idea that as incomes increased

homemakers tend to increase their purchases. In line with this those

households whose head was in a "socially higher occupation" (white collar

as opposed to blue collar, unskilled, or retired) were found to purchase

more catfish. Differences in purchases were significant between all

groups except for unskilled or retired household heads possibly indicating








those groups belong to a common occupation class. In view of the re-

sults obtained for income these conclusions seem consistent.

Regarding size and composition, households with one or two members

were found to purchase catfish more often than those with three, four,

five, or more than five members. For the composition variable it was

found that homemakers with children less than twelve years old tended

not to purchase these products as opposed to those with children 17 and

above. The authors felt the abundance of small bones to be the reason

homemakers with smaller children discriminated against the product.

The relationship between the level of formal education of the

homemaker, who presumably makes the purchase, and the level of purchases

of this product was found to be positive. The reasoning behind this

may be that homemakers who have attained a higher level of education

place a greater value on maintaining nutritional diversity in the meats

making up this portion of the diet. The effect of race on purchases

was unexpected. Those purchasing were classified as either White or

Black since no other races were prevelant in the Little Rock area when

the data were collected. Of the sample taken 77.6 percent of the sales

were to White households, while Blacks made up the remaining 22.4 per-

cent. When compared with 1970 census figures for this area it was found,

however, that Black household's purchases of this product was signifi-

cantly greater than expected. The analysis indicated that race did not

have as great an effect in determining number of purchases as that of

other economic and demographic factors.








Focus of the Present Research


The balance of previous work examining household expenditures and

consumption of fish and shellfish products has been tabular in nature

and has provided information relating to average levels of consumption

by consumer units possessing certain characteristics. Studies of this

type allow characterization of households using fishery products but do

not provide a mechanism through with the partial effects of these

characteristics can be examined. Likewise this type of analysis in-

cludes no mechanism through which causality among the factors included

in the consumption relationship can be explored. Specification of an

econometric model relating household expenditures on this product category

to the socioeconomic and demographic characteristics of the household

allows the above mentioned partial effects as well as causality among

the variables included in the study to be examined.

The analysis undertaken in this dissertation has endeavored to

provide information at the national and regional level for broad aggre-

gates of fishery products allowing consideration of causality among the

variables included in the relationship as well as the opportunity for

examination of their partial effects on observed expenditure behavior.

In this, and any other research involving development of models examin-

ing relationships of this type, neoclassical consumption theory should

serve as the foundation of the analysis.














CHAPTER III

THEORETICAL FRAMEWORK


Neoclassical theory begins with a series of axioms, or assumptions,

the most fundamental of which is the existence, for each consumer, of

a continuous real valued utility function. To insure the existence of

this function some restrictions are placed on the behavior of the con-

sumers to which it applies. In addition, a series of assumptions are

also made endowing the function with properties making its behavior,

upon maximization, applicable to the observed marketplace behavior of

consumers. Beyond the existence of the utility function the axioms

commonly considered are: 1) comparability, which insures that the con-

sumer will always be able to make comparisons between bundles of goods,

2) transitivity, insuring that the rankings the consumer makes are con-

sistent, 3) continuity, insuring against a lexicographic or other

ordering which cannot be represented by a real valued function, 4) domi-

nance, insuring that the utility function will be a strictly increasing

function of quantities consumed, 5) strict convexity, implying that the

utility function is at least strictly quasi-concave, and 6) differenti-

ability, which insures that the utility function's first- and second-

order partial derivities exist. The first two stated axioms are suffi-

cient to establish a preordering of all possible bundles a consumer may

face in the market. With the addition of the axiom of continuity to this

group, the existence of a utility function capable of assigning real








number values to all commodity bundles reflecting the consumer's under-

lying preferences is defined. The aim of the remaining three axioms is

to insure the function will monotonically increase as quantities are in-

creased, provide convex indifference curves, and have first- and second-

order partial diversitives which exist.

Depending on the available data, and the aims of the individual

researchers, a variety of functional forms have been proposed as candi-

dates to represent this underlying ordering. On purely theoretical

grounds only those forms satisfying the above axioms are legitimate

candidates. Generally the utility function of a given consumer, for a

defined period of time can be represented as follows

Ui = Ui(X1, X2,X3, ..... XnMi) (1)

where Ui is the utility derived by the ith individual from consumption

of the n goods X (j = 1, . ., n). The utility function is an open

ended monotonically increasing relation providing information about what

bundles a consumer would prefer over others if all were equally available.

The question of behavior, as determined by this raw function based on

preferences, is trivial. Through the assumption of dominance, the con-

sumer always prefers more of a good to less, and the assumption of

differentiability, which specifies that marginal utilities must always

be positive, the consumer will always desire as much of a good as possible.

In this form the utility function provides no mechanism through which the

consumer can interact with the conditions he faces in the market. To

accurately represent observed behavior these preferences must be allowed

to interact with market conditions and the constraint represented by the

consumer's income. The relevance of the utility function to observed

market behavior is dependent upon its interaction with the consumer's








available income and market prices. The income or budget constraint is,

therefore, an integral component in the determination of consumer behavior.

If Pj represents the price of the jth commodity and Xj the quantity of

the jth commodity consumed by the ith consumer,then the budget constraint

can be represented by the following:
n
M = jl PjXj (2)

where M. is the scaler quantity representing total expenditure or income

of the ith consumer. This constraint contains information relating to

market prices as well as dividing the set of all available bundles into

two subsets, those the consumer can effort to purchase and those he can-

not. To depict consumer activity as it is found in the market the pref-

erence ordering, via the utility function, and the budget constraint must

be considered simultaneously. The conventional mechanism allowing inter-

action between the utility function and budget constraint is the forma-

tion of a Lagrangean equation from (1) and (2). This provides the

following form which can be optimized to give the necessary constrained

utility maximization
n
L = Ui(X X2,X3 . XnM ) + (ti. j P.X.) (3)

where all variables are as defined and x is the Lagrangian multiplier.

Partial differentiation of (3) with respect to the n commodities and A

gives n + 1 first order conditions necessary for the maximization of the

function

aL 1- P 0
aX1 1

aL U- P = 0
SX2 P 2








3L = P3 = 0
a 3
X3 "1 3 0


(4)

a L -AP = 0
3X 1 n
aX i "n 0
n
ML n0
S= Mi Pj.X =
3A 1 -=1 J j

where all variables are as previously defined and UW (j=, ..., n)

represents 1, the first order partial derivitive of the ith individual
aXj'
utility function.

The sixth axiom on which preference orderings and neoclassical

consumption theory are based insures that the utility function is twice

differentiable. The first order conditions outlined by (4) are used to

locate a stationary value satisfying both budget constraint and utility

function. To insure that this extreme value is the desired maximum the

second order, or sufficient conditions, must also be fulfilled. From

total differentiation of (4) the Hessian matrix of second-order partial

and cross-partial derivatives can be obtained


0 PI P2 P3 P
11 12 13

P U21 U2 U23
2 1 1 1 (5)

P U31 U32 U33
P U U "




P u~l n2 Un3 nn
n 1 1 1 1








where U.k (r and k = 1, . n) represents X a- the second order
Xr x k
partial derivatives of the ith individual's utility function. For a

constrained maximization involving a single constraint the sufficient

conditions dictate that the determinant of the broadened hessian matrix

have sign of (-1)n where n is the number of choice variables in the

utility function. The determinant of the largest principal minor should

have sign the opposite of this with the determinants of each successively

smaller principal minor alternating in sign down to the principal minor

of order two. If these conditions are satisfied the stationary value

identified by the first order conditions (4) will be the desired maximum.

Consumer expenditure behavior as detailed by neoclassical theory

is outlined by the first order conditions. Through manipulation of the

first n conditions a series of ratios can be obtained which describe a

consumer's behavior in allocating his income among the n goods entering

his utility function. When the consumer is able to establish himself in

equilibrium he will allocate his expenditures in such a way that the rate

of commodity substitution (RCS) between any pair of goods (here 1 and m)

will equal the ratio of the prices of these same goods. This can be

represented as

RCS -= (6)


where RCS = Ui Ui, the ratio of the marginal utilities of the two
aX1 / aXm
goods for consumer i. Equation (6) states that in order to put himself

in the most favorable position, with respect to the maximization procedure

described above, the consumer will substitute among expenditures on the

various goods to the point that the ratio of the marginal utilities will

equal the ratio of the prices of the goods. The n + 1 first order








conditions can be manipulated into n demand equations with quantities

expressed as functions of the prices of all goods and income. The

general form of these equations can be represented as

Xij = Xij (P1P2P3 .' P i ) (7)


where Xij represents the quantity of the jth good consumed by the ith

consumer and P.(j=1 . ., n) the prices of the n goods entering the

consumer's utility function. Therefore, the general demand relation

delivered by neoclassical theory from maximization of (3) relates

quantities consumed to prices faced by the consumer in the market and

the consumers available income.


The Level of Aggregation


All computations and analyses made in this dissertation were per-

formed at the household level as opposed to examination of models speci-

fied for the behavior of individual consumers. No loss of generality

or applicability of the theory is encountered as a consequence of this

change in emphasis. Prais and Houthakker [1971] have examined the impli-

cations and benefits of working at this level of aggregation from a theo-

retical standpoint and encourage analysis along these lines. Lancaster

[1966] has also provided an extensive examination of consumption theory

interpreted at the household level.

Most data available for examination of income consumption relation-

ships relate to observed household expenditure behavior and do not pro-

vide expenditure detail for individual family members. Likewise, govern-

mental legislation designed to alter consumption of given components of

the population is often directed at households as the basic behavioral

unit. Thus by conducting the analysis at the household level the guidance








provided by theory is still available, the analysis corresponds more

directly with the variables on which information is available in data

sources, and the information provided may be more directly applicable

to the needs of legislative bodies.


The General Expenditure Income Relationship


Most data sources currently available contain information on

household expenditures on given commodities and not actual quantities

consumed. With this the dependent variable of equation (7) becomes

E.. (where Ei = P.X. .), expenditures of the ith household on the jth

commodity rather than simple quantity (Xij).

The Engle curve relates expenditures on a given commodity and the

income of the household for a specified period of time. Because the

emphasis of this analysis was on the variation in expenditures occurring

at different income levels the effects of price variation are not of

prime importance. With this type of study the data employed are collected

from cross sectional surveys involving a time frame designed to be short

enough to preclude the possibility of price variations influencing ex-

penditures. With this assumption the model delivered by neoclassical

theory in equation (7) simplifies to

Eij = Eij(Mi) (8)

where the emphasis is on expenditures rather than quantities consumed.


Modification of the General Engle Curve Model


As discussed to this point the general neoclassical model describing

the Engel relationship is not applicable to available data and empirical








research. In many respects the theory provides insufficient guidance in

the development and examination of applied relationships. Extensive

research (Allen and Bowley [1935], Brown [1954], Prais and Houthakker

[1971], Brown and Deaton [1972], and Phlips [1974]) has identified and

addressed the fact that other factors, not included in the general

theoretical model represented by (8), impinge significantly on household

expenditure decisions. The theory is defined and operates in terms of

consumer units which are assumed to be identical in all factors except

income. Variation in observed expenditures between households in the

empirical world can be attributed to different income levels as well as

other factors such as family size, education level, ethnic influences,

location, and region. Prais and Houthakker [1971] have stated that

observed expenditure variation is the result of these factors working

in concert on preferences which would prompt the consumer units to re-

act, if in the same circumstances, in substantially the same manner.

The ceteris paribus condition present in the theoretical development

of the Engel relation allows it to focus exclusively on income as the

primary agent generating expenditure variations. Some explicit modi-

fications must be made in the empirical analysis to account for the

ceteris paribus assumption allowing application of the theory in applied

investigations.

Empirically there are two means through which the characteristics

of a household can be incorporated in an analysis to account for their

effect on household expenditure decisions. The first is to implicitly

account for these sources of variation as done by Brown and Deaton

[1972] and many other early investigators. The data used were subdivided

into groups by factors felt to impinge on consumption decisions. The








intent was to obtain data sets composed of consumer units which were

as homogeneous as possible with respect to these sources of variation.

The Engle relation was then examined within each homogeneous set with

the income variable now isolated as responsible for the majority of the

remaining variation.

The second approach is to explicitly introduce the factors identi-

fied as responsible for the expenditure variation in the estimated model

as variables included in equation (8). This has been the procedure

followed by Phlips [1974], Prais and Houthakker [1971], and Brown and

Deaton [1972]. This approach is somewhat different from that discussed

above. Rather than removing the variation due to these factors prior

to the examination of a relationship they are allowed to remain and their

partial effect quantified in the estimated model.


The Modified Expenditure Income Model


The social and demographic factors commonly considered are those

relating to the ethnic background, social class, and location (region,

urbanization, etc.) of the household. Additionally a measure of relative

household size is often incorporated in the model through some form of

adult equivalent scale. Inclusion of these factors in (8) yields an

expenditure income relation for the jth good consumed by the ith house-

hold given by

Eij = Eij(MiBiLiEiAi) (9)

where Mi is the income of the ith household for a given time period, B.

variables reflecting the social class of the household, Li variables re-

flecting the household's location, Ei variables reflecting the ethnic

characteristics of the consumer unit, and A. variables incorporating
1








some measure of the household's size and age/sex composition. The

variables making up Bi, Li, Ei, and Ai explicitly incorporate the

socioeconomic characteristics of the household.

Elements of both approaches discussed above were incorporated in

this dissertation. Phlips [1974] stated that preferences are expected

to change across income groups and between households with differing

socioeconomic characteristics just as much, if not more, than tastes may

be expected to change through time. To allow for these differences the

data in this research have been segregated along two dimensions: region

and income class. The data employed in the research contained informa-

tion on household expenditures rather than actual quantities consumed.

If the product categories are broad, such as total expenditures on fish

and shellfish, expenditures on whole fish, etc., the number and type of

products included in the commodity classes can be great. The number of

products is large because of the many different fish and shellfish

species involved and the fact that most species are capable of yielding

several different consumption products. Fishery products included in

these expenditure categories include some of the most basic and simple

sources of protein, through a broad spectrum of goods to some of the

most luxurious foods available. Because of the potential for a wide

range of goods to be included in any one expenditure category, regional

and income effects on household consumption should be pronounced.

Regional differences in consumption of more highly processed fishery

products will not be as great as those observed for fresh forms because

these products are somewhat standardized, have long shelf lives, and

are easily transported with little loss of quality. Products included

here are canned tuna, breaded frozen fish portions, fish sticks, frozen








scallops, and breaded frozen shrimp. For many available fishery products

transportation over great distances is prevented by deterioration of the

product. With this limitation on shipping it is not uncommon for 90

percent of the annual catch of some species to be consumed within 200

miles of the port landed [Miller and Nash, 1971]. Oysters, some crabs,

and fresh clams are examples of products in this category. In other

instances, as with the American lobster, local markets for the available

catch are so strong that little of the annual harvest is available for

shipment to distant markets. Because of these factors and the regionali-

ty of production of many fish and shellfish species, products consumed

in one given region of the United States should not be expected to be

greatly similar to those consumed in another. The danger with this

situation is that the differences in products consumed may warrant that

allowances be made for the coefficients of different regions to vary

accordingly. Running one model for all regions restricts the estimated

coefficients to be the same when in fact the variations in products con-

sumed may demand that they differ.

The situation with income is somewhat similar. There is normally

a wide spectrum of fishery products available for consumption in any

given area and the household's income will directly affect where in

this spectrum it is able to consume. With the income situation and the

impacts described above for regional effects, the fish and shellfish

products consumed by a low income household located in the South may

have little in common with those products consumed by a household with

high income in the Northeast. The effect within the same region but

at different levels of income should be similar. The products consumed

by households in the lower half of the income spectrum may differ from

those consumed by households in the upper half.








It is difficult to determine the exact manner in which the above

effects will enter the estimated relationship. They may enter through

changes in intercept, changes in slope, or both. This uncertainty justi-

fies breaking the data into subsets based on income and region and esti-

mating the proposed relationship separately within each subset. In this

way the restrictions placed on the estimated coefficient's behavior are

reduced.

Socioeconomic variables were included in the model to examine the

influence of other household characteristics on expenditure levels. The

general form of the Engel relations given in (9) can be respecified as

Eij = Eij(Mi B Ei, Zi, Ai) (10)

All variables are as defined in (9) with Zi composed of the same variables

making up Ri in equation (9) but without those relating to the region of

the household which has been treated implicitly in the grouping of the

data. Specific inclusion of these variables not only accounts for

consumption variations between households due to factors other than

income but it also provides empirical estimates of their partial effects.














CHAPTER IV

EMPIRICAL CONSIDERATIONS


Functional Form


The functional form selected for equation (10) is influenced by

empirical considerations. Several studies investigated the proper

functional form for estimated Engel curves. Prais [1953], Allen and

Bowley [1935], Nicholson [1949], Leser [1963], Houthakker [1957],

Salathe [1979], and Chang [1977] compared the performance of various

specifications for this relation with the same data and examined the

effects on estimated income elasticities. Other authors, Aitchison

and Brown [1955] and Fisk [1959], reported in detail the properties

and performance of particular specifications they used for this re-

lationship. The specification is important because of the volatility

of the elasticities provided by different models and the problem that

some forms propose elasticity behavior which is implausible on theo-

retical and empirical grounds.

If the income variable in the data represents a wide range of

values, the Engle curve for a normal good on constant quality would be

expected to assume a sigmoid shape given the ceteris paribus assumptions

[Aitchison and Brown, 1955, p. 37]. The lower regions of the curve

should provide income elasticities of greater magnitude than those found

in higher regions. In the lower portion of the curve the good may be

held as a luxury with income elasticity greater than 1.0. In middle








regions where the curve's slope is more constant a normal good will come

to be held as a necessity providing income elasticities greater than 0.0

but less than 1.0. At extremely high income levels the curve becomes

concave and eventually provides an income elasticity less than 0.0 in-

dicating that the commodity is not considered an inferior good with

expenditures declining as income increases. With most data the observed

variation in income is not wide enough to capture all stages of the

signoid curve but only particular regions. In these cases, Prais and

Houthakker [1971] have suggested use of functional forms capable of

approximating the portions) of the overall curve the data represent.

As stated above, a wide spectrum of products and qualities of

goods are available within a given fish and shellfish commodity class.

As incomes increase, substitution of different goods and different

qualities of the same good, all falling in the same fish and shellfish

class, are easily accomplished.1 Because of this substitution, the

range in income necessary to transcend each of the luxury-necessity-

inferior good classes is broadened considerably. Thus, the curve

specified for total household expenditures on a given fishery product

class need not necessarily have the capability of representing all

three regions of the sigmoid curve detailed above.

The proportion of households sampled which would hold the balance

of available fishery products as luxuries is not likely to be large in

any given data source. Likewise, the proportion holding them as inferior

goods is not likely to be great. The regions in which these goods are



The data used in this research contained expenditure information
on broad aggregates of fishery products composed of a variety of indi-
vidual items. Categorization of expenditures on the individual commodi-
ties making up the classes were not reported.








held as necessities is, therefore, likely to predominate in most data.

The functional form these conditions imply would be convex to the origin,

have first derivative with respect to income which is positive, and have

positive intercept to avoid the possibility of negative expenditure

levels.


The Data


In any applied research the move from theoretical considerations

to empirical estimation must be concerned initially with the data to

be used in the analysis. An attempt must be made to secure a data

source meeting as many of the peculiar needs of the study as possible.

The data should represent the population the research hopes to address

and hold information on those variables which are felt to be important

in determining expenditures on the products of interest. In selection

of a data base for a study of the Engel relationship several specific

factors must be considered. The length of the survey generating the

data must be sufficiently short so variation in product price is mini-

mal. This must be balanced, however, with the desire that the survey

be of sufficient duration to allow an accurate record of expenditures.

The nature of the good in question will therefore have a great bearing

on the time frame considered appropriate in meeting these opposing

desires. Ideally, the data selected should cover a period of time

sufficient for an accurate representation of consumer purchasing be-

havior but not so long that variation in prices becomes significant.

The Bureau of Labor Statistics (BLS) 1972-1974 Consumer Expenditure

Diary Survey (CEDS) meets these data requirements for use in cross

sectional analysis. The data are representative of the entire U.S.









population. Information was collected on a broad spectrum of socio-

economic and demographic factors, and involves a time frame allowing

an adequate understanding of expenditures on fishery products without

great danger of fluctuations in commodity prices. The CES presents

information collected in the diary portion of the BLS 1972-1974 consumer

expenditure survey. The data relate to expenditures of 23,186 households

who participated in the survey. The survey was designed to determine

expenditures for two consecutive one week periods. The diary portion of

the survey was executed over a two year period between the fourth week

of June 1972 and the third week of June 1973 and the fourth week of June

1973 and the third week of June 1974. The principal motivation behind

the survey was to obtain the necessary data for updating the Consumer

Price Index. It was pointed out however, by the designers of the survey,

that the data:

Provides the only comprehensive body of income and
expenditure information available for satisfying a
broad range of analytical activities. . The data
can be used in examination and analysis of consumer
demand and income . in market research analysis
of demand for different products or market areas ..
[U.S. Department of Labor, 1974, p. 1]

The diary data were collected with two different questionnaires. A

household characteristics questionnaire was designed to gather informa-

tion on the race, marital status, region, location of residence, educa-

tion and age/sex composition of the household. The second component was

a self reporting daily expense record to be used by respondents in re-

cording expenditures made during the two week period. The diary survey

was initiated with an interview in which the household characteristics

questionnaire was used by an interviewer to obtain descriptive information

about household members. During this initial interview, a daily expense








record for one week's expenditures was placed with the homemaker in each

participating household. After the first week, the interviewer returned,

reviewed the diary with the homemaker, reconciled any discrepancies, and

left an expense record for the second week. At the end of the second

week, the interviewer again returned and cleared any questions in the

record. At this time the household characteristics questionnaire was

completed by the interviewer. Information regarding the occupations and

industries of the working members of the household, retirement status,

earning from family members' wages and salaries, and various other

measures of income were collected.

To collect the sample and insure that it was representative of the

underlying population, the nation was divided into 216 geographic areas

defined in accordance with the framework used for the current population

survey. Of these 216 geographic areas, thirty were self-reporting

(selected with certainty) because of their population sizes. Of these

units, half were included in the first survey year and the remainder

in the second year. The remaining 186 less populated and nonmetropoli-

tan areas were divided into two 93-area groups, each of which was also

covered in one of the survey years. For each of these geographic areas,

a primary sampling unit was randomly selected using a controlled

sampling procedure to insure proper geographic distribution. These

survey units included both urban and rural areas as well as farm and

non-farm areas [U.S. Department of Labor, 1974, p. 5]. Housing units

falling in the 216 primary geographical areas were assigned to housing

unit strata. Occupied units were stratified by income level, housing

tenure, and size of primary family. Vacant units were assigned to other

strata as were individuals living in rooming or boarding houses or in

doctors or nurses quarters of hospitals (institutional persons).









The actual sample of housing units was selected by computer from the

1970 census 20 percent sample data file which included those households

completing the long form questionnaire. Augmenting this were a number of

newly constructed housing units selected to update the sample for the

three-year period from the census to the time of the diary survey. These

were chosen from reports of building permits issued for privately financed

residential construction and were sampled independently within each

primary sampling unit. The placement of the diaries was distributed

throughout the two-year period of the survey. They were not all distrib-

uted in one given quarter or portion of a year, but were placed contin-

uously throughout the two years of the survey. Because of this, the

danger of the data providing a biased view of expenditures, because of

seasonality in availability of products, was substantially reduced. Some

fish and shellfish products are highly seasonal. This character of the

data helps to reduce the inflated or depressed impact on expenditures

which would result if the entire sample were collected before of after

the harvest.

Buse [1979] reformulated the BLS public use tape and checked the

information for accuracy. A total of 15 tests and checks for consistency,

outliers and coding errors were performed on the information recorded

for each household. Reformulating the tape included the addition of some

50 subtotals which are summations of two or more expenditure fields from

the BLS tape. To increase convenience and allow all information to fit

on one 2,400 foot reel at 1,600 BPI all expenditure categories, where

appropriate, were summed together and relate to expenditures over a

two-week period rather than two consecutive single weeks. In addition,

expenditure fields were combined. In all cases where aggregation of








expenditure fields occurred, it involved only the lowest levels of

expenditure reported for a particular commodity class. Thus the

actual loss of expenditure detail was minimized while the managability

of the data were greatly increased. A breakdown of the observations on

the tape by survey year is as follows:




Table 1. Number of observations in BLS CEDS data by survey year

Survey year Number of observations

Survey year 1 (1972-1973) 11,065

Survey year 2 (1973-1974) 12,121

Total (1972-1974) 23,186







Of the 23,186 reporting, 963 households reported expenditures for

only the first week of the survey while 934 reported information only

for the second week. Some 20,477 households reported expenditure infor

mation for both weeks while 812 reported no expenditures at all. To

allow the model to relate to as much of the sample as possible, and

avoid the problem of possibly biasing the results by omitting those

households reporting expenditures for only one week, the expenditures

reported and summed for two weeks were divided so the analysis could be

carried out on a weekly basis. Households make expenditures on food

commodities at least once a week and it was felt that the weekly time








frame was long enough to accurately reflect expenditure levels while

avoiding significant variations in price.

Expenditure levels on a wide variety of products were included in

the BLS tape. Information on all major food groups is provided as well

as purchases of many non-food items. Included in the expenditure infor-

mation are five expenditure categories relating to fishery products.

These are expenditures on fish purchases as fillets or steaks, expendi-

tures on whole fish, expenditures on shellfish, expenditures on canned

fish, and a category summing these for total expenditures on fish and

shellfish products.


The Tobit Model


The nature of most cross sectional data precludes the straight-

forward application of least squares analysis in the estimation of the

chosen model. In cross sectional data, for a variety of reasons, many

households report zero expenditures on one or more of the items in-

cluded in the survey. The incidence of zero expenditures in the data

will normally increase, for a given commodity, the shorter the period

of time covered by the survey. Depending on how narrowly the commodity

of interest is defined, a substantial proportion of the households in-

cluded are likely to have zero expenditures due to the time frame of the




IDuring the two years spanned by the BLS survey the CPI for food
rose almost 31 percent [Salathe, 1979, p. 3n]. Because of this a time
frame of more than one week risks introduction of significant price
variation. Regarding the stability of parameters obtained from this
data, Salathe [1979, p. 4] found the parameters did not vary signifi-
cantly between the survey years.








survey. This is especially true for smaller, frequently purchased

items, such as fish and shellfish food products. A dichotomy exists

because as the time frame is shortened to avoid price variations the

incidence of nonresponses by survey participants increases. Because

of these data characteristics least squares analysis cannot be employed

due to violation of assumptions regarding behavior of the error term.

Specifically, the assumption of a homoskedastic error structure is not

fulfilled. The variance of the disturbance will not be constant but

can be shown to vary with the data yielding a heteroskedastic error.

For the simple regression model with expenditures Eij of the ith house-

hold on the jth commodity expressed as a linear function of Mi, the

households income, and uij the error term expenditure behavior can be

described as follows:

Eij = BMi + u.. if E. > 0 (11)

Ei = BMi + uij if M i + uij > 0 or u > SMi

Eij = 0 if BM. + u.ij 0

Regarding the behavior of the error

u.. = E.. M if E.. > 0

uij= sMi if Ej <

E(uij) = 0 is assumed, however, with the above behavior present in any

cross sectional data, with zero expenditures prominent, the following

is obtainedl



To avoid confusion to notation, the double subscripted variable
Eij refers to the expenditure level of the ith household on the jth
commodity. E( ), unsubscripted, refers to the statistical expectation
of the expression in parentheses.








E(u .) = 0 assumed

E(u.) = B Mif(-BMi) + (Eij Mi) + (Eij M.) f (Eij Mi) =

where f is the density function of the normal distribution.

The above implies

f(-Mi) = Eij. Mi

F(Eij BMi) = Bi
2 2
var(u.i ) = E(uij) = (-Mi) (Ei sMi) + (Eij Mi) BMi
2 3 2 3
= (sMi) (BMi) + SMi 2(sMi) + (BMi)
2
var(Uij) = (M s ( ) (SM ) 'li( -Mi

The final simplification of the variance of the disturbance is a function

of Mi and thus the variance will not be constant but will vary with the

data.

A similar problem exists if the zero observations are discarded

and the analysis carried out only on the households reporting positive

expenditures. If this is done, the possibility of obtaining biased

coefficients is pronounced, the most prevalent bias being that the

coefficients obtained from the analysis will be overestimated. Coupled

with this, the assumption of zero expectation of the disturbance around

the estimated line will not be realized. This arises because of the

fact that with constant variance of the disturbance, which would be

realized in this case, as the curve approaches the abscissa corresponding

to expenditures made by lower income households, the constant variance

of the disturbance demands that certain of the predicted values fall

outside the first quadrant, which cannot occur. Thus, in this region

the assumption that E(uij) = 0 will be violated. Because of these effects

and the heteroskedastic problem discussed above, least squares cannot

appropriately be used.









Tobin [1958], working with cross-sectional data, developed a

maximum likelihood method of estimation, allowing inclusion of the

zero observations which avoids the heteroskedastic problem associated

with the least squares approach. The procedure Tobin proposes is an

elaboration of Probit analysis [Cornfield and Mantel, 1950], in that it

addresses the magnitude as well as the probability of responses above

some limiting value. The dependent variable's behavior can be character-

ized as that of a limited dependent variable. The limiting variable L

in the present research behaves as a lower bound on expenditures repre-

sented by zero since negative expenditures are not considered. In

situations of this type, the data can be characterized as consisting

of two types of observations: those households which, because of the

nature and value of the variables making up their underlying preference

ordering, are concentrated at the limit (zero response) and those dis-

tributed above the limit (positive response).l

The variable W.. is defined to represent the value of the limited de-

pendent variable of the ith household for the jth commodity. It will equal

the limit (L) for those households reporting zero expenditures on fishery

products and equal some positive expenditure level for those purchasing

fish or shellfish. The behavior of W.. is related by hypothesis to Y..,

expenditures by the ith household on the jth commodity. The variable

Yij is defined to be a linear combination of independent variables,

Xli, X2i . .. Xni; which affect the probability of limit versus non-

limit responses as well as the magnitude of observed responses above the




In the BLS data, 49.7 percent of the households surveyed had posi-
tive expenditures on one or more of the four fishery product categories
while 50.3 percent reported no fish or shellfish purchases.








limit. In the present research Y.i and X X i .. Xni are

comparable to the E. and Mi, Bi, E., Zi and A., respectively, of

equation (10). With the inclusion of an error term, assumed to be

distributed normally with zero mean and constant variance, the

relationship for E.. can be expressed as

Eij = + 2Bi + B 3E + 4Z + 85Ai + u.i (12)

With these relationships the behavior of the limited dependent

variable W.. can be defined:
1j

Wij = L if 0 + ~'ii + 32i + 3 + 4Zi + r A < L (13)


ij 80 + Bi 2 Bi + 4i + Ai

if 0 + 1Mi + 2Bi + 3Ei + 4Zi + 5A > L (14)

This relationship can be equivalently expressed in terms of the

stochastic error u..
13
Wij = L if Eij u.. < L (15)

W-. = E.. u.. if E.. u > L (16)
lJ lJ lJ EJ ij -
With these descriptions of household behavior, household expenditures on

any selected commodity can be expressed as follows. The observed level

of expenditure of the ith household will equal the limiting value of ex-

penditures for that good if the systemic part of equation (12) is such

that the dependent variable in the relation would fall below the limiting

value, equation (13). If the relationship among the variables in the

systemic part of equation (12) is such that expenditures will fall ex-

actly at or above the limit, the limited dependent variable is allowed

to assume that value, equation (14). To obtain the likelihood function








which will feed into the algorithm providing the estimates of the co-

efficients, the n observations included in the sample are ordered so

the first q observations correspond to those which are at the limiting

value. The remaining r observations (r = n-q) correspond to those with

values above the limit. For the first q observations each consists of

the limiting value L to which the limited dependent variable W.. is

equal. Associated with this is the set of explanatory variables (Mi,

Bi, Ei, Zi' Ai) for each of the i = 1, . q observations. The

remaining r observations consist of a value for the limited dependent

variable which exceeds the limiting value by some positive amount. These

observations may be described as (Wij, L, Mi, Bi, Ei, Z., Ai) where i =

S. . r. Tobin [1958] defines the vector (a al, a2' . ... am, a)

to be estimates of the normalized coefficients (e0/o,1/G, .. .., m/o,

1/o) and redefines equation (12) for both limit and non-limit observations

as follows:

Ii = Eija = a0 + a + a2B1 + 3Ei + a4Zi + a5A (17)


I. = Eija = 0 + alii + a2Bi + a3E. + a4Zi + a5Ai (18)

with these the likelihood of the sample becomes
q r
:(a ,al a2, . an,a) = n F(L ; Ei L ) n f(Wi; E.ij Li)
i=1 1 =l J

q E.. L. r E.. W.
= n Q( -) ,aZ(- I-)
i=1 1I/a i=1 i/a


= n Q(I. aWJD) n aZ(I. aWij) (19)
i=1 l i=1

where F and f are the distribution and density functions of the normal

distribution respectively, Q one minus the value of the cumulative stan-

dard normal distribution function and Z the standard normal probability








density function. Upon taking natural logarithms of (19) the likelihood

function becomes
q r 1 r
In = In Q(I. aW. .) + rina -2 ln2r 2 z (I. aW. (20)
i=l i=1

This form of the likelihood function feeds into the algorithm chosen for

its maximization and provides the coefficients and an estimate of the

variance. The algorithm used in this dissertation was Phelps' 1972

version of LIMDEP from the Rand Corporation. The Rand algorithm pro-

ceeds essentially through the same procedure outlined by Tobin.

With the estimated coefficients the user may calculate an expected

value locus for the limited dependent variable through the following

relation provided by Phelps
p( + Y1Mi + B2B. + 3E + + Z +5A L
E(Wij) = P + (-P)(L) +

f0 + 1Mi + o2Bi + B3Ei + + Ai+ L
f ) (21)

where P is the probability of observing W. >L for given X and f is the

density function of the normal distribution. The expected value locus

is of principal interest to the investigation as it encorporates the

desired homoskedastic properties and avoids the danger of predicting

expenditures outside the third quadrant. The Rand LIMDEP package pro-

vides elasticities for the expected value locus as well as equation (12);

both are computed at mean values of all independent variables. The

relationship between the expected value locus and the probability that

the limited dependent variable is above the limiting value for a given

vector of independent variables and coefficients is illustrated by

Figure 1.




























E(E i)--expected
value locus


Eij o= O 1Mi
[Equation (12)]


Figure 1. The total expected value locus [shaded area gives
P(Eij > 0|Mi, .i)]








The Independent Variables


The general form of the Engel relations considered to this point is

as stated in equation (10). With the selection of the BLS survey data

for use in the analysis the general groupings of variables presented in

(10), Mi, Bi, Ei, Zi, and Ai, can be identified in greater detail. In

addition the subdivision of the data may be more completely specified.


Income Measure

The variable chosen to represent M. in the estimated models was

total income from all sources coming to the household during the pre-

vious twelve-month period. Included are income from salaries, wages,

interest payments from all reported investments and savings accounts,

and sale of home-produced goods for all family members. Income from

governmental transfer programs such as Social Security payments or

retirement and unemployment benefits were also included. Total income

from all sources was chosen as the measure of household income over

alternatives such as income of the household head because it was felt

that it provided the most accurate measure of the household's liquid

wealth available for use in purchasing decisions of this type. Other

measures of wealth such as home or automobile ownership were not in-

cluded since they do not represent a liquid income stream immediately

available for use in purchasing products.


Household Social Class

Variables included in the model for Bi, the "social class" in

which the household operates, were included to capture the effect of

taste and preference differences which are likely to exist between








households of different social strata. In addition, households falling

in different classes tend to patronize different markets and encounter

products of differing quality and price. No one variable or household

characteristic can be used to capture these effects singly because a

series of factors and components working together define the social

standing of a particular household. Because of this, a series of

variables were selected. The occupation of the household head, his or

her education level, and the location/urbanization in which the house-

hold finds itself were selected from the BLS tape for inclusion in B..

Urbanization and occupation were included as 0--1 qualitative

variables. Households in rural settings formed the base group of the

urbanization variable while the effect group was made up those in urban

situations. A great deal of detail was provided in the BLS tape with

respect to the occupation of the household head. The categories included

in the survey were as follows:

Salaried

1 -- Self employed, including farm operators

2 -- Salaried professional, technical and kindred workers

3 -- Salaried managers and administrators and kindred workers

Wage and Other Salaried

4 -- Clerical

5 -- Sales

6 -- Craftsmen

7 -- Operatives

8 -- Unskilled laborers and service workers including household

9 -- Retired

10 -- Other -- (armed forces living off post, unemployed)








These 10 occupational groupings were divided into salaried professionals,

(1, 2, and 3 above) forming the effect group, and another group composed

of wage earners, clerks, managers and other salaried personnel which

formed the base group (4 through 10). Justification for including a

variable of this type lies in the fact that the occupation of the house-

hold head, through salary and other factors, can often weigh heavily in

determination of the social class in which the household belongs. In

addition, caloric requirements of different occupations affect expendi-

ture levels.

The level of education of the household head was included as a

quantitative variable. Past research [Pippen and Morrison, 1975] indi-

cates that homemakers with higher levels of formal education may place

greater emphasis on maintaining nutritional diversity in their diets.

Because of this they may be more disposed toward consumption of fishery

products. Also the preparation of dishes containing fish and shellfish

is often involved. The educational level of the homemaker may increase

her facility with weights and measures and prompt her to try available

recipes calling for use of these products more frequently than homemakers

with little or no education. It would be expected that the education

level of the homemaker is at least partially reflected by that of the

household head. The level of education of the household head will also

generally bear on the social class to which the household belongs. The

values of the education variable were as follows

1 -- Some grade school completed

2 -- Some high school completed



All categories relate to the highest level of formal education
attained by the household head.








3 -- High school graduate

4 -- Some college completed

5 -- College graduate, graduate work

0 -- None


Ethnic Factors

Miller and Nash [1971] identified certain ethnic groups and minori-

ties (particularly Blacks) as consuming larger amounts of fishery pro-

ducts than warranted by their representation in the overall population.

To capture this effect the race of the household head was included in

the analysis as one of the variables making up E.. Race entered as a

0 -- 1 qualitative variable with the reference group being White house-

holds including American Indians, Orientals and other non-Black groups.

The effect group was composed of Black households. Combining with race,

the occupation variable discussed above for social class will include some

ethnic effects. In some regions of the country, ethnic groups and

minorities tend to gravitate toward employment in particular industries

and within these industries to certain occupations. Thus, the included

occupation variable will incorporate some ethnic effects.


Locational Factors

The form of the locational variables included in the model has been

discussed above under social class. In the BLS data households were

characterized as residing within central cities of various sizes (urban

households) or outside central cities (rural households).1 Location is




In the BLS data location of place of residence was based on standard
metropolitan statistical areas (SMSA's) with populations of 1,000,000 or
more; 400,000 to 999,999; 50,000 to 399,999, and households falling out-
side SMSA's.








felt to be important because of the effect proximity to markets will have

on the kinds of fishery products available and the prices of these pro-

ducts. Regional price differences are also likely to exist. These have

been accounted for to some degree in the segregation of the data into

regions. Beyond these regional effects local variations in prices and

supplies are likely to exist. Location and urbanization effects were

included for this reason.


Household Size and Composition Factors

The adult equivalent scale employed was that developed by Buse and

Salathe [1978]. The scale departs to a degree from those proposed by

Price [1970], Prais and Houthakker [1971], and Sydenstricker and King

[1921]. The scale Buse and Salathe developed differs from historical

scales by being a continuous rather than a discrete function of age.

Coupled with this, Buse and Salathe's scale incorporates the additional

feature of allowing other market factors to bear on determination of the

scale value rather than relying only on recommended nutritional or dietary

requirements for certain age/sex groups. The system proposed links two

cubic functions of age back to back so the effect an individual will

have on household expenditures may vary continuously without discrete

jumps.

The scale they define may be conceptually written as

Aij = S (a si) (22)

where Aij represents the scale's value for the jth commodity and ith

individual of age a. and sex s.. If S(0,1) and S(0,2) are the scale

values for a male and female at birth, respectively, Buse and Salathe

propose the following properties for their scale.








I. S(0,1) = S(0,2) = c3

aS(a ,si)
II. exists for a. > 0
a. 1 -
equals 0 for 20 < a. < 55

and equals 0 for a. i 75,
1-
62S(a,si) exists for a. > 0
2 1
ai equals 0 for < 20 a. < 55
1-
and equals 0 for a. > 75;

IV. S(20,1) = 1;

V. S(20,2) = c2;

VI. S(75,1) = c6;

VII. S(75,2) = c7.

Property I indicates that male and female scale values at birth are

equal. Property IV specifies that the value for the adult male equal

1.0 while property V indicates the value for adult females equal c2.

The value of c2 may be greater than, equal to, or less than 1.0 (adult

male value) depending on the commodity. Properties VI and VII indicate

that the scale value for elderly males and females (ai > 75), respective-

ly, equals c and c7. Again the relationship of these values to the

adult male value is dependent on the commodity group in question. These

properties are incorporated into four cubic equations in age, one each

for males and females aged 0 to 20 and one each for males and females

aged 55 to 75. The value of the scale is assumed to be constant for

males and females aged 21 to 54. These equations are then solved for a

series of seven variables which, when summed across all household members,

characterize the household's age and sex composition (Appendix). These

variables combine linearly to form the scale for the ith household and

jth commodity








Aj = P + c2i + c3i + c4Si + c5Ti + c6Ui + c7Vi (23)

P, W, R, S, T, U, and V are weighted sums of the ages of household

members which have been rescaled to avoid discontinuity of the scale

function for ages 20 to 55.1 These variables are based on the 7 proper-

ties the authors identify for the scale function and the ages of the

household's members. The scale function, equation (23), is incorporated

directly in the Engel curve model to be estimated, equation (10), which

gives:

Eij = E (Mi, B., Li, Zi, c Pi + c2 i + c3Ri + c + c5T +

c6Ui + c7Vi) (24)

the coefficients; cl, c2, c3, c4, c5, c6, c7; of the adult equivalent

scale are determined at the same time as the other coefficients in the

model. In this way both nutritional factors (through the equations

generating the variables) and other market factors included in the model

(through the estimation delivering the coefficients) are allowed to in-

fluence the determination of the scale's value for each household. This

is to be preferred over previous scales which do not incorporate market

factors. These effects (region, location of household, income, etc.)

certainly have a bearing on the level of expenditures made for each house-

hold member. The use of this scale also provides a convenient method

for determining the effect on expenditures of the addition or deletion



To avoid the problem of discontinuity of the scale function between
the ages 20 to 55 and over 75, ages were rescaled by the following
schedule where the actual age is a and the rescaled age a*.
a* = a if a < 20
a* = 20 if 20 < a < 55
a* = a if 55 < a < 75
a* + 75 if a > 75








of household members of given ages and sexes through elasticities which

can be calculated with the coefficients of the scale variables.

The coefficients cl, c2, c3, c4, c5, c6, and c7 when summed together

provide the number of adult equivalents in the household. The coefficient

c2 represents the scale value for an adult female (20-55 years) while c3

provides the effect of a newborn infant. Coefficients c6 and c7 measure

the increase in the number of adult equivalents due to the addition of

an elderly male (> 75 years) and elderly female, respectively. The

coefficients c4 and c5 if not significantly different from zero indicate

for males and females, respectively, that the scale function could have

been appropriately specified as a monotonically increasing function of

age throughout the growth and development years rather than as a cubic

relation. Buse and Salathe [1978] also state that the parameters c2,

c3, c6, and c7 can be interpreted as the change in expenditures for a

given commodity resulting from addition of an infant, adult female,

elderly male, or elderly female, respectively, in comparison to the

change in expenditure resulting from addition of an adult male to a

given household. This can be seen by taking the coefficients of the

estimated expenditure equation for R, W, U and V and dividing by the

coefficient obtained for P.


Expenditure of Food Away from Home

A variable representing amounts of expenditures on food away from

home was included in the model. In many households which consume fishery

products quite often this consumption takes place away from home in

various eating out establishments. Because of this factor expenditures

on these products at home may be depressed or increased. To quantify

this effect the expenditure on food away from home variable was included.








Subdivision of the Data

All households included in the BLS diary survey were placed in one

of four regional categories: the Northeast, North Central, South, and

Western states. Three income classes were used to divide the households:

1) Households with total annual income of $0.0-SlO,000, 2) $10,001-$20,000,

and 3) households with total annual income greater than $20,000. Strati-

fying the data by these factors yielded 12 data sets on which the income

expenditure relation for fishery products was examined. The breakdown

of observations by region and income class was as follows:



Table 2. Number of households in regional and income groups after BLS
data was stratified by income and region


Income Class Region
N. East N. Central South West Total

$0-$10,000 2054 2863 3808 1999 10,724

$10,001-$20,000 1553 2116 1864 1428 6,961

$20,000+ 468 624 529 567 2,188

Total 4075 5603 6201 3994 19,873


The states falling in the regions were the Northeast including:
Connecticut, Maine, New Hampshire, New Jersey, New York, Pennsylvania,
Rhode Island, and Vermont; the North Central states: Illinois, Indiana,
Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota,
Ohio, South Dakota, and Wisconsin; the Southern states: Alabama, Arkansas,
Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana,
Mississippi, Maryland, North Carolina, Oklahoma, South Carolina, Tennessee,
Texas, Virginia, and West Virginia; and the Western states: Alaska, Ari-
zona, Colorado, California, Hawaii, Idaho, Montana, Nevada, New Mexico,
Oregon, Utah, Washington, and Wyoming.








The Empirical Model


The model actually specified for the analysis corresponded to the

linear combination of independent variables outlined by Tobin [1958]

presented in equation (12) above. The explanatory variables were in-

cluded through this equation and the Tobin framework used to estimate

the expenditure-income relationship for each of the data sets described

in Table 2. Initially this appears as a linear specification of the

functional form for the Engel curve. Leser [1943] and Aitchison and

Brown [1955] discuss the dangers involved in a linear specification of

the Engel relationship. Linear forms yield income elasticity behavior

for necessities and moderate luxuries which increase toward unity rather

than a declining elasticity which theory and empirical findings support.

Because of these kinds of difficulties, curvilinear relationships are to

be preferred as the elasticity behavior they imply is more nearly in

accord with theoretical and empirical considerations.

As discussed, a functional form which is convex to the origin pro-

viding a positive intercept and capable of representing the middle ranges

of the general Engel curve is to be preferred. A function with a form

of this type is exactly what the expected value locus obtained through

Tobin analysis provides. The locus, as calculated through equation (20)

above, does not allow for the possibility of a negative intercept and is

convex to the origin. Thus, in addition to allowing inclusion of the

zero observations and avoiding the associated heteroskedastic problem

associated with least squares, Tobin's model also incorporates enough

curviture to avoid the inappropriate elasticity behavior implied by a

strict linear specification of the model. Inferior goods are not pre-

cluded from the analysis as equation (12) may take a negative slope.








With this, the obtained expected value locus would be concave to the

origin with second derivatives less than zero, corresponding to the

upper portion of the sigmoid curve where the commodity in question has

become inferior.


The Fully Specified General Model


With the above discussion, the general model of equation (10) was

fully specified to include the actual variables included in the esti-

mated relationships. Incorporating these changes, the general model for

the ith household becomes:

Eij = Ej (Mi' Ei Zi, FAi' Oi' EDi' Pi' Wi' Ri' Si Ti. Ui Vi) (25)

where the included variables are as follows:

M. 12-month total income of household i

E. 0 -- 1 dummy variable for race

Z. 0 -- 1 dummy variable for urbanization

FAi expenditures on food consumed away from home

0. 0 -- 1 dummy variable for occupation of household head

EDi education level of household head

Pi' Wi' Ri, Si, Ti, U,i and Vi variables of Buse and Salathe's [1978]

adult equivalent scale.

Operationalizing this model for estimation with Tobin's [1958] procedures

by putting the included variables in equation (12) and including a

stochastic error term yields

E j = + Mi + 2Ei + 3Zi + 4FAi + 50i + 6ED. + cl


+ c2Wi + c3R + cS + c5Ti + c6 + c7 + uij
2i i 41 .c6U.+ li ii








where ui. is assumed to be distributed normally with zero mean and con-

stant variance. Equation (26) was then used in the Rand Corporation's

LIMDEP algorithm to solve for the coefficients maximizing the probability

of the observed sample.


Food Stamps


To satisfy the stated objective of determining the impact of food

stamps on fish and shellfish expenditures, a variable for the value of

food stamps received by the household during the previous month was in-

cluded in equation (26). This provided a model exactly like that used

to examine the effects of the various socioeconomic and demographic

factors on consumption with one additional variable included giving the

impact of food stamps. This model was then estimated with the information

available on those households receiving food stamps.

Some 587 households included in the BLS survey indicated that they

received food stamps during the previous month. The food stamp variable

was left on a monthly basis rather than reducing it to a weekly framework

as this was the time frame on which the information was collected and

stamps were issued to recipients monthly. With the variable on this

time frame, as with income, the opportunity exists to explore more

directly fluctuations in variable levels. In this way the effect of

possible governmental changes in food stamp payment levels which would

affect the recipients' monthly allotments of stamps can be easily identi-

fied.


Statistical Considerations


To maintain the statistical integrity of the investigation the model

specified in equation (26) was estimated initially with the data from the








Northeastern region.1 The model was estimated for the three income

classes discussed above with 2,054, 1,553, and 468 observations, re-

spectively. The total number of observations involved was 4,075 or

20.5 percent of the total sample. Respecification of the variables

and other changes in the model were made as a result of indications

from use with these three data sets. The variables and their specifica-

tions which resulted from this were then estimated intact with the data

of the remaining regions.2


Omitted Observations

Some 3,313 observations or 14.34 percent of the total sample were

omitted from the analysis. Among the omitted households were those

reporting no expenditure information of any kind (812 households), and

households refusing to report or providing incomplete income information

(2,501 households). In his work with the data, Buse [1979] discovered

many of the households that provided incomplete income information also

provided poor or incomplete expenditure information in their daily ex-

pense records. The information provided is of such brevity that an

accurate characterization of the consumer unit's expenditure behavior

cannot be obtained. Likewise, those households reporting no expenditures



1To allow the tests of significance of the estimated coefficients
to be meaningful, it is necessary that economic and statistical theory
govern decisions regarding variables and their forms included in the
estimated relationship. Running a model on the entire sample and then
reformulating it based on the obtained results allows the data and not
theory to determine the form of the relationship. With this any reported
significance levels for the estimated coefficients are meaningless.
The only alteration made as a result of the initial estimation was
to broaden the widths of the income groups into which the data was
stratified from $5,000 increments to $10,000 increments. Beyond this
no additions, deletions, or respecifications of the included variables
were made.





61


were deleted as this lack of information also prevents any understanding

of their expenditure behavior.















CHAPTER V

EMPIRICAL RESULTS--REGIONAL MODELS


Introduction


A total of 85 equations were estimated using the BLS data. Twenty

regional equations were estimated (examining expenditures by all house-

holds within each of the four regions) as well as sixty income-group

equations (examining expenditures by households after separation into

the three income categories). In each group of equations, household

expenditures on all five fish and shellfish categories (total expenditures

on fish and shellfish, expenditures on whole fish, filleted and steaked

fish, canned fish, and shellfish) were examined as dependent variables.

Because the quantity of information generated by the analysis was

great, an attempt to describe and discuss each estimated equation and

coefficient was not made. While results from all equations are presented

(both with respect to coefficient value and standard error), primary

emphasis is placed on discussing the results obtained with the regional

models. Additionally, discussion of the income-group equations will

focus primarily on the findings obtained with those models having total

expenditures on fish and shellfish products as the dependent variable.

This expenditure category was chosen as it represents the summation of

expenditures made on the other four product groups and therefore involved

the greatest number of households and provided the greatest amount of

information with respect to behavior and expenditures on fishery products








in general. For ease of comparison and reference, the South was chosen

as the base region to which the findings of the other regions were com-

pared in discussion of both regional and income-group equations.

Results obtained with the regional models are presented in chapter

V, findings with the income-group equations follow in chapter VI. In

both chapters the South is discussed first and is followed by discussion

of findings for the Northeast, West, and North Central states. The

regional models allow examination of the variables included in equation

(26) across all households within each region while the income-group

equations allow examination, by region, of variable effects among house-

holds within each of the three income groups.

Chapter VII contains a tabular analysis of the average expenditure

levels (on the five fish and shellfish categories) made by households in-

cluded in the BLS survey when the sample was segregated into groups based

on selected socioeconomic and demographic factors. Following this is a

discussion of the results obtained with the five models estimated in-

cluding the variable for value of food stamps received by the household

during the previous month.


Southern Regional Model Results


Income (Mi). For the Southern regional models, the estimated income

coefficient for all categories, except one, indicated a positive relation-

ship between total household income and expenditures on fish and shellfish

products.l The exception occurred in the whole fish expenditure equation



For purposes of discussion in this disseration, a coefficient which
was 1.645 times larger than its estimated standard error was considered
significant. This corresponds to the 90 percent significance level for








where no significant relationship of any kind was indicated between

income and expenditures (Table 3).



Table 3. Income variable coefficient's sign and significance

Expenditures
Region Total Shellfish Fish
Filleted/
Canned Whole Fted/
steaked

South + + + 0 +

N. East + + + 0 0

West + + + 0 +

N. Central + + + 0 +





For the total expenditure model an $1,000 increase in annual house-

hold income was predicted to prompt an 5.01 per week increase in expendi-

tures on fish and shellfish productsI (Table 4). This translates into

an annual increase of $.52. The largest effect on weekly household ex-

penditures was found in the shellfish model where it was predicted that

a similar $1,000 increase in income would illicit an increase in weekly

shellfish expenditures of $.013. The smallest significant effect, $.004,



the two tailed test with greater than 30 degrees of freedom. It must be
noted that, because of the estimation technique employed, the statistics
reported here are not exact t statistics but are asymptotically normal
variables.
The expenditure changes discussed relate to the partial effects of
the variables considered working in isolation of all other factors
impinging on the expenditure decision. Because of this, the magnitudes
of the changes examined may not, and most probably would not, be en-
countered in the market place where all factors together shape the ex-
penditure decision.








Table 4. Southern regional model coefficients and standard errorsa

ExDenditures


SOal I


Income
(Mi )
Food away
(FAi)
Race
(E i)
Urbanization
(Zi)
Occupation
(Oi)
Education
(ED )
Adult male
(Pi)
Adult female
(W )
Infant
(Ri )
Curvature
(S )
Curvature
(Ti)
Elderly male
(Ui)
Elderly
female (Vi)
edc


5nei ItlSn


.00001171
(.000002903)
.0086
(.00336)
.5682
(.08909)
-.0057
(.06881)
-.0432
(.08415)
.1245
(.02695)
.2673
(.05987)
.3881
(.05528)
.1277
(.06892)
-.0236
(.01927)
-.0076
(.03079)
.5286
(.13069)
.1996
(.11976)

.069


Fish
Canned Whole


.00000434 .0000013
(.000001407)(.0000066


.00001297
(.000005788)
.0221
(.00757)
.1609
(.23055)
.0728
(.16735)
.1468
(.20599)
.2892
(.06701)
.1948
(.14953)
.3386
(.13753)
.1553
(.17187)
-.0717
(.04739)
-.0564
(.07699)
.7179
(.32705)
.4847
(.30029)

.069


.0136
(.00836
2.4352
(.19602
-.1217
(.17737
-.1399
(.23682
.0314
(.07142
.2331
(.14666
.2806
(.13287
-.0522
(.17612
-.0365
(.04698
.0355
(.07666
1.0881
(.31788
.0917
(.31452

.012


All coefficients relate to the change in weekly household expenditures,
in dollars, resulting from an unit change in the value of the associated
variable.
bFigures in parentheses are standard errors of the coefficients.
Eled denotes the expenditure income elasticity of demand.


Variable


-.0010
(.00173)
-.1630
(.04712)
-.0001
(.03382)
-.0523
(.04234)
.0664
(.01361)
.1636
(.03016)
.1892
(.02792)
.0222
(.03494)
.0158
(.00973)
.0088
(.01552)
.2177
(.06732)
.0683
(.06114)

.062


--`----------


Filleted/
steaked

9 .00000896
563) (.0000029411)
.0029
) (.00317)
.7552
) (.09493)
-.0211
) (.07509)
.0188
) (.09458)
.0111
) (.030182)
.1958
(.06553)
.1948
(.06076)
.2178
(.07479)
-.0277
(.02088)
-.0066
(.03310)
.4745
) (.14333)
.2637
) (.13430)

.082








occurred in the canned fish model while the filleted and steaked equation

predicted an increase of just less than one cent per week.

Regarding the corresponding expenditure income elasticities of de-

mand, the largest value, .082, was found for filleted and steaked ex-

penditures while the smallest, .062, occurred in the canned fish equation

(Table 4). The expenditure income elasticity of demand indicates the

percentage change in expenditures on a given product category illicited

by an one percent change in household income. Elasticity values in the

0.0 -- 1.0 interval are indicative of normal goods, expenditures on these

products will change by a smaller percentage than did income. The total

expenditure model and the shellfish equation both had the same expendi-

ture income elasticity values, .069.


Expenditures on food away from home (FAi). The effect of expendi-

tures on food consumed away from home on household purchases of fishery

products was positive in two of the five equations estimated (Table 5).

For the total expenditure and shellfish models, increases in expenditures

on food consumed away from home prompted increases in purchases of these

products for home consumption.



Table 5. Away-from-home expenditure variable coefficient's sign and
significance

Expenditures
Fish
Region Total Shellfish Canned Whole Filleted/
steaked

South + + 0 0 0

N. East 0 + 0 0 0

West 0 0 0 0 0

N. Central 0 0 0 0 0









No significant relationship between expenditures on food away from home

and the dependent variable was observed for canned fish, filleted and

steaked fish, or whole fish.

In the total expenditure model, a SO1 increase in weekly expenditures

on food consumed outside the home was predicted to prompt an increase in

spending of fishery products for home use of S.086 per week (Table 4).

This translates into a S4.47 annual increase. The corresponding effect

for shellfish expenditures was 5.22 per week which translated into an

annual expenditure increase of S11.44.

Race (Ei). The effect of race on fishery product expenditures made

by Southern households was mixed. In three of the five categories;

whole fish, filleted and steaked fish, and total expenditures; a positive

relationship existed between the race variable and the dependent variable

of the equation (Table 6). In the canned fish model, the relationship

was negative while no significant relationship was found for shellfish.



Table 6. Race variable coefficient's sign and significance

Expenditures
Fish
Region Total Shellfish n e Fishted
Canned Whole Filleted/
steaked

South + 0 + +

N. East 0 0 0 + 0

West 0 0 + 0

N. Central + 0 0 + +








Black households were predicted to spend S2.44 per week more on

whole fish products than White households. Expenditure levels by Blacks

on filleted and steaked fish were predicted to exceed those of Whites by

$.76 per week (Table 4). The total fishery product expenditure equation

predicted Black households would spend S.57 per week more than their

White counterparts. For expenditures on canned fish products, the re-

lationship was reversed with White households outspending the Blacks by

$.16 per week (Table 4).


Urbanization (Zi). In the Southern region the estimated models in-

dicated no significant difference in expenditure levels between urban

and rural households (Table 7). In all five expenditure models, the

coefficient of this variable was not found to differ significantly from

zero.



Table 7. Urbanization variable coefficient's sign and significance

Expenditures
Region Total Shellfish Fish
Canned Whole illeted/
steaked

South 0 0 0 0 0

N. East + + + + +

West + 0 0 0 +

N. Central 0 0 0 0 0





Occupation (0i). As with urbanization, the coefficients of the

qualitative variable included in all five expenditure models to capture

expenditure differences due to the occupation of the household head were

not found to differ significantly from zero (Table 8).








Table 8. Occupation variable coefficient's sign and significance


Expenditures
Region Total Shellfish Fish Fi
Canned Whole Fted/
steaked

South 0 0 0 0 0

N. East 0 0 0 0 0

West 0 0 0 0 0

N. Central 0 0 0 0





Thus, no significant expenditure differences between households headed

by salaried individuals and those headed by non-salaried individuals in

the South were predicted.


Education (EDi). In three of the five models estimated, attainment

of higher levels of education by the household head was predicted to have

a positive impact on expenditures (Table 9).



Table 9. Education variable coefficient's sign and significance

Expenditures
Region Fish
Region Total Shellfish Canned hol Filleted/
Canned Whole staked
steaked

South + + + 0 0

N. East 0 0 + 0 0

West 0 0 + 0

N. Central + 0 + + +








The coefficients of the total expenditure, canned fish, and shellfish

models all indicated that movement of the household head into a higher

educational category, as defined in the BLS data, would prompt increased

household expenditures on the given product group. The largest effect,

S.29 per week, was found for shellfish (Table 4). The smallest predicted

increase, just under $.07, occurred for canned fish, while the total ex-

penditure equation predicted weekly expenditures on fishery products as

a whole would increase by $.12. As with the findings for income and

food away from home, the largest impact from additional education occurred

in the shellfish model and the smallest impact in the canned fish model

(Table 4).

No significant impacts on expenditures from changes in the household

head's education level were indicated for whole fish or filleted and

steaked fish.


Adult male scale value (Pi). Addition of an adult male to the

household was predicted to have a significant positive impact on ex-

penditures in three of the five models estimated (Table 10).



Table 10. Adult male variable coefficient's sign and significance

Expenditures
Region Total Shellfish Fish
Canned Whole Filleted/
steaked

South + 0 + 0 +

N. East + + + + +

West + + + + +

N. Central + 0 + 0 +








Those showing this relationship were canned fish, filleted and steaked

fish, and total expenditures. The largest impact, S.27 per week, was

associated with total expenditures (Table 4). The filleted and steaked

model predicted increases of almost $.20 while canned fish showed the

smallest impact with S.16 per week. No significant impact from an

addition of this type was predicted by the shellfish or whole fish

equations.


Adult female scale value (Wi). The impact on Southern household

fishery product expenditures due to addition of an adult female was

positive and significant in all five models estimated (Table 11).



Table 11. Adult female variable coefficient's sign and significance


Expenditures
Region Total Shellfish -Fish
Canned Whole Fte d/
steaked

South + + + + +

N. East + 0 + 0 +

West + + + 0 +

N. Central + + + + +


As with the adult male

for total expenditures


variable the largest impact, $.34, was observed

and the smallest effect, $.19, for canned fish.


The effect predicted by the filleted and steaked equation was $.19; that

for whole fish, S.28; and that for shellfish, $.34 per week (Table 4).

All the female coefficients, where comparisons were appropriate, were

larger than the corresponding male effects estimated in the same models.








Infant scale value (Ri). With the exception of only the total

expenditure and filleted and steaked models, addition of a newborn infant

to a Southern household was predicted to have no significant impact on

expenditures (Table 12). The predicted effect on total expenditures

was an increase of S.13 per week while for fillets and steaks it was

S.22 (Table 4). Included in the filleted and steaked group would be

frozen breaded fish portions and boneless fillets which may be fed safely

with little additional preparation to young children. This is in con-

trast to the products falling in the other expenditure categories which

may contain bones or require involved preparation. These factors may

have contributed to the relative size of this coefficient in the filleted

and steaked model and its insignificance in others.



Table 12. Infant variable coefficient's sign and significance

Expenditures
Region Total Shellfish Fish
Canned Whole Fleted/
steaked

South + 0 0 0 +

N. East 0 0 + 0 0

West 0 0 0 0 0

N. Central + 0 + 0 +





Elderly male scale value (Ui). A positive impact was predicted for

all five expenditure categories as a result of addition of an elderly

male to the household (Table 13).








Table 13. Elderly male variable coefficient's sign and significance

Expenditures
Region Total Shellfish Fish
Filleted/
Canned Whole Fieted
steaked

South + + + + +

N. East + + + + +

West + + + + +

N. Central + 0 + + +





The largest impact, $1.09 per week, occurred in the whole fish model

while the smallest effect, $.22, was found in the canned fish equation

(Table 4). The filleted and steaked model predicted increases of $.47

per week, the shellfish model increases of $.72, while the total

expenditure equation predicted spending increases of S.53. The impact

of an additional elderly male was larger in all cases than the increases

predicted for adult males. This is in line with the findings reported

by Nash [1970] who found households headed by individuals aged 45 years

or older tended to have higher consumption levels than those with heads

aged less than 45 years.


Elderly female scale value (Vi).l The effect on household expendi-

tures from addition of an elderly female was not significant in three of

the five equaitons estimated (Table 14).



Because their significance and magnitude were not integral to the
economic interpretation of the findings of this research, the coefficients
estimated for the two curvature variables, Si and Ti of equation (26),








Table 14. Elderly female variable coefficient's sign and significance

Expenditures
Region Total Shellfish Fish
Canned Whole Fleted/
steaked

South + 0 0 0 +

N. East + 0 + 0 +

West + 0 0 0 +

N. Central 0 0 0 + 0





For fillets and steaks and total expenditures, the predicted impact was

positive. The largest effect was found in the filleted and steaked model,

$.26 per week, while the household's expenditures on fishery products in

general were predicted to increase almost S.20 per week (Table 4).


Northeastern Regional Model Results


Income (Mi). For the shellfish, canned fish and total expenditure

models, as was the case in the South, the relationship between income and

expenditure levels was found to be positive (Table 3). Unlike the South,

the Northeastern filleted and steaked model showed no significant relation-

ship between income and expenditures. For both regions, no relationship

between income and expenditures was found for whole fish.

An $1,000 increase in annual household income was predicted to in-

crease total household expenditures on fishery products by almost $.04



were not discussed in the text of this dissertation. All coefficients
estimated for these variables in the regional, income group, and food
stamp models are presented with their estimated standard errors.








per week (Table 16). On an annual basis, this translated into an in-

crease of 52.08. These values are larger than the comparable partial

effects predicted for the South where the effects were S.01 and $.52,

respectively. Shellfish expenditures showed the largest response to

an $1,000 income increase in the Northeast, as was the case in the South.

The estimated impact was $.06 per week. The smallest significant effect

occurred in the canned fish model, again similar to the South, where the

effect was 5.01 per week. All significant Northeastern impacts were

larger than the corresponding values estimated in the South (Tables 16

and 4).

The largest expenditure income elasticity of demand found in the

Northeast occurred in the shellfish model. This differed from the South

where it was the second largest. The Northeastern value was .344 against

.069 in the South. Overall, the Northeast's expenditure income elastici-

ties were larger than those encountered in the South. The canned fish

elasticity in the Northeast was .175, with the Southern value being .062.

The Northeast's total expenditure elasticity was .204; those for whole

fish and filleted and steaked fish, .145 and .085, respectively (Table

15).




The reader is reminded when examining expenditure levels and ex-
penditure income elasticities of demand between regions that direct
comparisons are of little meaning as there is no assurance that the
commodities included in the expenditures by households in the different
regions were the same. With this in mind, comparisons between coefficient
effects and expenditure income elasticities should be interpreted as the
manner in which a household would respond with expenditures on a broad
category of commodities and not one particular good.








Table 15. Regional expenditure income elasticity of demand values


Expenditure income elasticity value
Region Total Shellfish FishFl ed
Filleted/
Canned Whole steaked
steaked

South .069 .069 .062 .012a .082

N. East .204 .344 .175 .145a .085a

West .136 .235 .111 .045a .100

N. Central .163 .263 .113 .146a .134

Food stamps .084a .299a .217 -.296a -.126a

aDenotes models with coefficients which were not significantly
different from zero.




Expenditures on food away from home (FAi). In the Northeast, the

findings of all models except one indicated that no significant relation-

ship existed between expenditures on fishery products purchased for home

consumption and food eaten outside the home (Table 5). The only signifi-

cant effect was observed for shellfish. Increasing away-from-home food

expenditures $10 per week prompted increases in expenditures on shellfish

products for home consumption of $.16 per week (Table 16). This trans-

lates into an annual increase of $8.32. In the South, the shellfish

equation was one of two models where significance of the food away from

home variable was encountered. The effect predicted for a comparable

$10 spending increase by the Southern shellfish model was $.22 per week.


Race (Ei). Unlike the South, significantly different expenditure

levels between races were predicted only in the Northeast's whole fish

equation. For all other models, no significant difference in expenditure








Table 16. Northeastern regional model coefficients and standard errors

Expenditures
Variable Total Shellfish Fish
Filleted/
Canned Whole staked
steaked


Income
( i )
Food away
(FAi)
Race
(Ei)
Urbanization
(Zi)
Occupation
(0i)
Education
(EDi)
Adult male
(Pi)
Adult female
(Wi)
Infant
(Ri)
Curvature
(Si)
Curvature
(Ti)
Elderly male
(Ui)
Elderly
female (Vi)

Eledc


.00003606
(.000006137)L
.0046
(.00334)
.2247
(.15596)
.5267
(.08630)
.0888
(.10910)
.0593
(.03677)
.4313
(.07646)
.3569
(.06778)
.1280
(.00867)
.0243
(.02377)
-.0611
(.04009)
.6937
(.16072)
.5940
(.15062)

.204


All coefficients relate to the change in weekly household expenditures,
in dollars, that would result from a unit change in the value of the associated
variable.
Figures in parentheses are standard errors of the coefficients.
CEIed denotes the expenditure income elasticity of demand.


.00006118
(.000013251)
.0162
(.00680)
-.5020
(.40587)
.5289
(.20731)
.2602
(.25724)
.0858
(.08910)
.4087
(.18250)
.2579
(.16084)
-.2364
(.22044)
.0333
(.05707)
-.0983
(.10265)
1.1289
(.38646)
-.2029
(.38457)

.344


.00001282
(.0000030671)
.0009
(.00162)
-.0136
(.08066)
.0727
(.04383)
-.0125
(.05514)
.0354
(.01867)
.1698
(.03850)
.1704
(.03404)
.1215
(.0434)
-.0062
(.01193)
-.0154
(.02001)
.1746
(.08353)
.2176
(.07737)

.175


.00001279
(.000011503)
.0014
(.00703)
1.0230
(.25866)
.4393
(.17501)
.3491
(.23564)
.0324
(.07436)
.2760
(.14853)
.0592
(.13822)
.1653
(.17199)
.0979
(.04966)
-.1090
(.08380)
.4809
(.30543)
.3241
(.29427)

.145


.00000985
(.000006598)
-.0015
(.00361)
.1886
(.16147)
.6843
(.09164)
.0404
(.11724)
.0171
(.03907)
.3597
(.08048)
.1830
(.07200)
-.0591
(.09013)
.0490
(.02514)
.0201
(.04333)
.6564
(.16663)
.5577
(.15744)

.085








levels were noted (Table 6). For whole fish, Black households were

predicted to spend $1.02 per week more than Whites. The comparable

effect in the South was $2.44 per week.


Urbanization (Zi). Households living in urban settings were pre-

dicted to have larger expenditures on all fishery product categories than

households in rural settings in the Northeast (Table 7). This differs

from the South where no significant different in expenditures was found

between these two groups.

The largest difference was encountered in the filleted and steaked

model where urban households were predicted to spend S.68 per week more

on these products than rural households (Table 16). The smallest effect,

$.07 per week, was found for canned fish. The total expenditure and

shellfish models both showed urban expenditure levels above those of

rural households by $.53 per week. The whole fish model predicted ex-

penditures between the two groups would differ by $.44 per week.

For the Northeastern region, with its abundance of large metropolitan

centers, locational factors were consistently significant in explaining

expenditures on fishery products while in the South household location

was not of significant importance.


Occupation (O). No significant relationship between the occupation

of the household head and expenditures on any of the fishery product

categories were found (Table 8). This was similar to the findings ob-

served for the Southern region.


Education (EDi). The only model for which the education level of

the household head had a significant impact on expenditures was in the








canned fish equation (Table 9). In all other expenditure classes no

significant effect was noted for this variable.

For canned fish expenditures, movement of the household head into

a higher education category was predicted to increase spending by S.04

per week (Table 16). In the South, the comparable effect was S.07 per

week (Table 4).


Adult male scale value (Pi) In the Northeast, addition of an

adult male to the household was predicted to have a positive impact on

all five expenditure categories (Table 10). This differs from the

South where no significant impacts were predicted for shellfish or whole

fish expenditures. The largest impact in the Northeast occurred for total

expenditures where the partial effect from an addition of this type was

an increase of $.43 per week (Table 16). This translates into an annual

increase of $22.36. The smallest impact was found in the canned fish

equation where an increase of S.17 per week was estimated. The total

expenditure and canned fish models also held the largest and smallest

impacts, respectively, in the South.

The impact predicted for shellfish in the Northeast was an increase

of $.41, that for whole fish, $.28, and that for filleted and steaked

fish, $.36 per week.


Adult female scale value (Wi). In the Northeast, addition of an

adult female to the household was predicted to increase expenditures on

three of the five product groups and have no impact on two (Table 11).

For canned fish, filleted and steaked fish, and the total expenditures,

the predicted impacts were $.17, $.18, and $.36 per week, respectively

(Table 16). For shellfish and whole fish no significant impacts from an

addition of this type were observed.








These findings differ from those of the South where significant

positive impacts were encountered in all five estimated equations. Also

the impacts predicted for adult females in the Northeast tended to be

smaller than corresponding adult male values. The opposite relationship

was observed in the South.


Infant scale value (Ri). In the Northeast only for canned fish was

a significant relationship between addition of an infant to the household

and expenditure level encountered (Table 12). The model predicted

spending on canned fishery products would increase by $.12 per week (Table

16). This translates into an annual expenditure increase of 56.24.

This finding differs from that encountered in the South where the

canned fish model showed no significant effect from an addition of this

type while the filleted and steaked and total expenditure models did show

an effect.


Elderly male scale value (Ui). As was the case with their younger

counterparts, a significant positive impact was observed for all expendi-

ture categories due to addition of an elderly male to the household

(Table 13). The largest impact, $1.13 per week, was found for shellfish.

This was followed by whole fish, $.48 per week; fillets and steaks, $.66

per week; and total expenditures on fish and shellfish, $.69 per week

(Table 16).

As with the South, the predicted impacts in the Northeast from

adding an elderly male to the household were larger, in absolute terms,

in all cases than the impacts from addition of an adult male (Tables 4

and 16).








Elderly female scale value (Vi). No significant impacts from

addition of an elderly female to the household were predicted by the

Northeast's whole fish or shellfish models (Table 14). Positive impacts

were found for fillets and steaks, total expenditures, and canned fish.

The largest predicted impact, $.59 per week, was found for total expendi-

tures. The smallest impact, S.22, was found in the canned fish model

with the filleted and steaked equation predicting expenditures would

increase by $.56 per week.

Compared to the South where significant impacts were found only for

total expenditures and fillets and steaks, the effects predicted by

the Northeast's equations were larger (Tables 4 and 16). Expenditures

on all fishery products in the Northeast would increase by S.59, against

$.20 in the South, while in the filleted and steaked equation expenditures

would increase by $.56, against $.26 in the South.


Western Regional Model Results


Income (Mi). The significance and sign of the income variable in

the Western regional models followed the pattern found in the South

(Table 3). For all categories, except whole fish, a significant positive

relationship was found between income and the dependent variable. In the

whole fish model no significance was observed.

As with the South, the largest predicted effect for an $1,000 in-

crease in annual household income occurred in the shellfish model. In

the West, shellfish expenditures were predicted to increase by $.04 per

week (Table 17). This was larger than the Southern value predicted by

the same model. The smallest effect observed in the West was found for

canned fish where expenditures were predicted to increase by $.008 per








Table 17. Western regional model coefficients and standard errorsa


Expenditures
Variable Total Shellfish Fish
Canned Whole F ted/
steaked


Income
(Mi )
Food away
(FAi)
Race
(E )
Urbanization
(Zi)
Occupation
(Oi)
Education
(EDi )
Adult male
(Pi)
Adult female
(Wi)
Infant
(Ri)
Curvature
(Si)
Curvature
(Ti)
Elderly male
(Ui)
Elderly
female (Vi)

Eled


.00002170
(.000005083)b
-.0022
(.00376)
-.0481
(.22213)
.2465
(.09284)
.0230
(.11177)
.0106
(.03959)
.5862
(.08740)
.4867
(.08023)
.1080
(.09572)
.0689
(.27068)
-.0414
(.04473)
.9021
(.19185)
.3518
(.19116)

.136


.00000827 .00000363 .00001057
(.000002743)(.000009235)(.000005403)


.00003541
(.000009233)
-.0027
(.0070)
.5794
(.44516)
.2640
(.19788)
.1001
(.23546)
.0849
(.08465)
.4408
(.18220)
.2766
(.09504)
.2514
(.20382)
-.0062
(.05563)
-.1841
(.09762)
.7775
(.40673)
.4490
(.40402)

.235


-.0025
(.00213)
-.3874
(.13076)
.0755
(.05182)
-.0581
(.06204)
.0416
(.02218)
.3246
(.04832)
.2254
(.04456)
.0158
(.05324)
.0386
(01501)
.0074
(.02483)
.3330
(.10940)
.0308
(.11016)

.111


.0025
(.00734)
.6979
(.38859)
.2688
(.19086)
.3755
(.22864)
-.1907
(.07959)
.5679
(.16506)
.1890
(.15925)
-.2003
(.20871)
.0734
(.05240)
-.0468
(.09761)
1.1982
(.34513)
.1802
(.37599)

.045


aAll coefficinets relate
in dollars, that would result
associated variable.


to the change in weekly household expenditures,
from a unit change in the value of the


Figures in parentheses are standard errors of the coefficients.
Eled denotes the expenditure income elasticity of demand.
EId dntsteepniueicm lsiiyo ead


.0020
(.00403)
.3070
(.23377)
.1978
(.10323)
.0857
(.12480)
-.0528
(.04379)
.3502
(.09445)
.4586
(.08705)
.1110
(.10102)
.0712
(.02976)
-.0567
(.04889)
.9039
(.20535)
.4365
(.20928)

.100









week for an income increase of this type. In the South, the smallest

effect, $.004 per week, was also associated with canned fish. This boost

in annual income was predicted to increase expenditures on filleted and

steaked fishery products by $.01 per week while the total expenditure

model predicted increases of $.02 per week.

In general, the Western coefficients were larger than those in

corresponding Southern equations, indicating Western households would

respond to a given income increase with larger expenditures on the broad

categories of goods considered than Southern households. When compared

against the Northeast, however (with the exception of fillets and steaks),

the Western coefficients were all smaller.

The expenditure income elasticities of demand in the Western models,

with the exception of the filleted and steaked equation, were all smaller

than those obtained in the Northeast. The largest Western elasticity was

observed for shellfish, .235, while the smallest, .100, occurred in the

filleted and steaked equation (Table 15). The largest and smallest

elasticities in the Northeast were found in these same categories. In

the South, the largest elasticity occurred in the filleted and steaked

equation and the smallest in the whole fish model. The Western

elasticity values in the total expenditure and canned fish models were

.136 and .111 respectively. Both elasticities obtained in these latter

two Western models were larger than the corresponding Southern values

but smaller than those encountered in the Northeast.

The higher cost of living in the Northeast and West can be identi-

fied as a major factor contributing to the larger income coefficients

and elasticity values associated with these regions. Proximity to major

production areas and year-round availability of many products may also









contribute to a stronger preference for fishery products in these

regions than in the South.


Expenditures on food away from home (FAi). No significant relation-

ship between expenditures on food outside the home and purchases of

fishery products for home use were found in the West. This pattern is

similar to that found in the South and Northeast where a significant

relationship was identified in only three of the ten equations estimated.


Race (Ei). Only for the canned and whole fish models were any

significant expenditure differences between races encountered among

Western households. The effects were mixed with that for canned fish

negative and that for whole fish positive.

The coefficient in the canned fish model indicated that expenditures

by White households on canned products would be, on average, $.39 per

week greater than those of Black households (Table 17). The whole fish

model indicated Black households spending on these products would exceed

that of Whites by almost $.70 per week, all other factors held constant.

Comparable effects were also noted in the South and Northeast where

Black households were also predicted to spend more on these products than

White households. The largest difference in whole fish expenditures be-

tween races, more than $2.00 per week, occurred in the South (Table 4).

The predicted difference in the Northeast, $1.02, was also larger than

that found in the West. Like the West, the South also showed Blacks

spending less on canned fish than Whites. The difference predicted by

the Southern model was smaller than that of the West, $.16 against $.39,

respectively. In the Northeast's canned fish model, no significant

difference in expenditure levels between Black and White households was

noted.








Urbanization (Zi). In the West, households in urban central city

areas were predicted to have higher expenditure levels on filleted and

steaked products and fishery products in general than their rural counter-

parts (Table 7). No significant difference in expenditure levels were

found for canned fish, whole fish, or shellfish. The total expenditure

model predicted households in urban settings would spend almost $.25 per

week more on these products than those in rural areas (Table 17). For

filleted and steaked fishery products the difference was almost $.20.

These findings differ from the South where no significant difference

between urban and rural household expenditure levels were found in any

models and the Northeast where significant differences were found in all

models.


Occupation (Oi). As was the case in the South and Northeast for

all five fishery product groups, no significant difference was found in

expenditure levels between households headed by salaried individuals and

those headed by non-salaried individuals (Table 8).


Education (EDi). The education level of the household head had

a significant impact on expenditure levels only in the canned fish and

whole fish models (Table 9). In the canned fish equation, the observed

effect was positive. Attainment of higher levels of formal education

by the household head was predicted to increase expenditures on canned

fish products. This was the same relationship observed in the South and

Northeast. The opposite effect was found in the whole fish model. Here,

higher levels of education attained by the household head tended to lower

expenditure levels on whole fish products. This result differed from

findings in the South and Northeast where no significant effect was ob-

served.








Adult male scale value (Pi). For all five expenditure categories,

addition of an adult male to the household was predicted to have a posi-

tive impact on expenditures (Table 10). This differed from the South

where no significant impact was encountered for whole fish and shellfish.

The Western pattern of significance and sign was the same as that en-

countered in the Northeast.

The largest impact found in the West occurred for total expenditures

where spending was predicted to increase by $.59 per week from an addition

to the household of this kind (Table 17). The smallest impact occurred

in the canned fish equation where weekly expenditures were predicted to

increase by $.32. Filleted and steaked expenditures were predicted to

increase by $.35, shellfish expenditures by $.44, and whole fish expendi-

tures by $.57 per week.

The impacts predicted by the Western total expenditure, canned fish,

and filleted and steaked models were larger than the corresponding

effects in the Southern equations. With the exception of fillets and

steaks, all Western impacts from addition of an adult male were larger

than those predicted for the Northeast.


Adult female scale value (W1). In the Western models, significant

impacts from addition of an adult female to the household were encountered

for canned fish, filleted and steaked fish, shellfish, and total expendi-

tures (Table 11). The effect in each category was positive. The largest

predicted impact, as with their male counterparts, was found in the total

expenditure model. Expenditures on all fishery products were predicted

to increase by $.99 per week (Table 17). The smallest impact, again

similar to adult males, occurred for canned fish where expenditures were

predicted to increase by $.22 per week. The expenditure increases in the








filleted and steaked and canned fish models were predicted to be $.46

and $.23 per week, respectively.

The Western results differed somewhat from those encountered in the

South for this variable where all five models showed significant positive

impacts from household additions of this type. In the Northeast no

significant impact was encountered in the whole fish and shellfish models

with all others being positive.


Infant scale value (Ri). No significant impact on household ex-

penditures were encountered in any of the estimated models from addition

of a newborn infant (Table 12). This differed from the South where

positive impacts were predicted for total expenditures and filleted and

steaked fish and the Northeast where a significant impact was found for

canned fish.


Elderly male scale value (Ui). The predicted impact on expenditures

in all five categories from addition of an elderly male to the household

was positive (Table 13). This was the same finding with the adult male

variable in all expenditure categories for this region. The largest

effect, $1.20 per week, occurred in the whole fish model while the

smallest, $.33, occurred in the canned fish equation (Table 17). Ex-

penditure increases in the filleted and steaked and total expenditure

models were predicted to be $.90 per week while the shellfish model pre-

dicted increases of $.78. These increases were all larger than those

predicted for adult males.


Elderly female scale value (Vi). Only for total expenditures and

fillet and steaked fish were significant impacts from addition of an








elderly female to the household found (Table 14). Both were positive

with the largest, $.44 per week, found in the filleted and steaked model.

The total expenditure model predicted increases of $.35. A similar situ-

ation was encountered in the South where these were the only two models

showing significant impacts from household additions of this kind. As

with the elderly male values, predicted impacts in the West were larger

than those encountered in the Southern models.


North Central Regional Model Results


Income (Mi). The effect of income in the North Central region

followed exactly the pattern of sign and significance found in the West

and South (Table 3). Significant positive relationships were found be-

tween income and expenditures on canned fish, filleted and steaked fish,

shellfish, and total fishery product expenditures. No significant rela-

tion was found between income and purchases of whole fish.

The largest effect encountered for an S1,000 increase in annual

household income occurred; as with the South, Northeast and West; for

shellfish (Table 18). For North Central households, the shellfish

equation predicted expenditures would increase $.03 per week for an

income increase of this type (Table 18). The comparable expenditure

increase predicted for Southern households was S.01 per week (Table 4).

The largest impact of all regions encountered with this model, $.06,

occurred in the Northeast (Table 16).

The smallest effect encountered in the North Central region, $.007

per week, was found for canned fish expenditures. The canned fish equa-

tion also gave the smallest predicted change in the South. In the other

North Central categories where significant effects were observed, the








Table 18. North Central regional model coefficients and standard errors


Expenditures
Variable Total Shellfish Fish
Filleted/
Canned Whole Fiteed
steaked


Income
(Mi)
Food away
(FAi)
Race
(Ei)
Urbanization
(Zi)
Occupation
(Oi)
Education
(EDi)
Adult male
(Pi)
Adult female
(Wi)
Infant
(R )
Curvature
(Si)
Curvature
(T )
Elderly male
(Ui)
Elderly
female (Vi)

Eedc
ed


.00001850
(.000003748)
.0008
(.00221)
.5321
(.09999)
-.0046
(.05509)
-.0258
(.06570)
.0590
(.02357)
.2028
(.04885)
.3909
(.04496)
.1726
(.05431)
.0017
(.01532)
-.0318
(.02487)
.4642
(.10834)
.1413
(.10649)

.163


.00003021
(.000009200)
.0086
(.00537)
.1507
(.27819)
.0220
(.15178)
.2228
(.17659)
.0047
(.06530)
.0719
(.13192)
.2901
(.11692)
.1068
(.14812)
.0141
(.04120)
-.0006
(.06679)
.3907
(.30834)
.2533
(.31219)

.263


.00000659
(.000002338)
-.0015
(.00135)
-.0569
(.06514)
-.0367
(.03422)
.0363
(.04053)
.0257
(.01470)
.1204
(.03010)
.2493
(.02764)
.0659
(.03362)
.0020
(.00937)
-.0081
(.01528)
.2413
(.06479)
.0308
(.67739)

.113


.00001262
(.000012309)
.0061
(.00624)
1.0827
(.03157)
.0903
(.19390)
.6086
(.24732)
.1394
(.08133)
.1520
(.16617)
.3696
(.14635)
.2708
(.18903)
.0072
(.52155)
.1308
(.08749)
1.1186
(.33706)
.6657
(.34484)

.146


.00001263
(.000005322)
-.0036
(.00345)
.7873
(.13509)
.0908
(.07979)
-.1288
(.09645)
.0683
(.03427)
.1988
(.06917)
.2859
(.06349)
.1548
(.07683)
.0157
(.02199)
-.0336
(.03530)
.4464
(.15553)
.2199
(.15432)

.134


aAll coefficients relate to the change in weekly household expenditures,
in dollars, that would result from a unit change in the value of the associ-
ated variable.
Figures in parentheses are standard errors of the coefficients.
cEId denotes the expenditure income elasticity of demand.
Eed dntsteepniueicm lsiiyo ead








filleted and steaked model predicted weekly expenditures would increase

by $.01 and the total expenditure model predicted an increase of S.02.

Like the South, the North Central region's largest expenditure

income elasticity of demand was associated with shellfish. The elasticity

value was .263. This was larger than that found in the South, but smaller

than the Northeast's (Table 15). The smallest elasticity, .113, occurred

in the North Central canned fish model. This was the same situation

observed in the South where the smallest elasticity was also found in

this model. The expenditure income elasticities of the North Central

filleted and steaked and total expenditure models were .134 and .163

respectively.

Examination of Table 15 indicates that the largest elasticities

were generally associated with the Northeast while the smallest were

found in the South. The elasticities of the North Central and Western

states tended to be similar in several models and generally fell between

those of the Northeast and South. The cost of living in various parts

of the country can be identified as the primary factor behind the ob-

served relationship among elasticities, costs being highest in the

Northeast and lowest in the South.


Expenditures on food away from home (FAi). As was the case with the

West, no significant relationship between household expenditures on food

away from home and any of the five fishery product categories were found

(Table 5). This differed from the South where positive effects were found

for shellfish and total expenditures and the Northeast where a positive


effect was found in the shellfish equation.




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