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Our overarching goal is to understand critical determinants of low-income elderly Americans’ well being as measured by health status. We focus on whether and how elderly health status is affected by FSP participation, food sufficiency and other determinants. To do so we must first ascertain (1) why so few needy elderly households choose to receive food stamps; (2) what determines their level of food insufficiency and finally; (3) how FSP participation and food insufficiency link to each other and then to health status. To meet our goal, we estimate and assess a unique econometric framework applied to an analysis database created specifically for this project. The analysis data are a subset of elderly households from the 2002 Health and Retirement Survey (HRS), consisting of those eligible for food stamps. State-specific eligibility criteria were obtained from the Urban Institute’s waiver database and from Center on Budget and Policy Priorities publications. The econometric model is structured in two steps. In the first, simultaneous multivariate Probit estimates of endogenous FSP participation and food insufficiency equations are estimated. From the results, we calculate predicted probabilities of participation and insufficiency for use in Step Two. This final step involves Ordered Probit estimation of self-reported health status. Because predicted variables from Step One are included as explanatory variables, we adjust the standard errors of the Ordered Probit estimates to allow for accurate hypothesis testing. We extend Murphy and Topel’s (1985) modification of standard errors for one predicted variable to handle two such variables. After correcting the standard errors, some coefficients lose their significance; most importantly, the positive coefficient for the probability of FSP participation. The significant coefficients that remain are: food insufficiency (+) income (-), widowed (+), Nonhispanic Black (-), exercise (-) and drink alcoholic beverages (-).

In this paper we derive a joint continuous/censored demand system suitable for the analysis of commodity demand relationships using panel data. Unobserved heterogeneity is controlled for using a correlated random effects specification and a Generalized Method of Moments framework used to estimate the model in two stages. While relatively small differences in elasticity estimates are found between a flexible specification and one that restricts the relationship between the random effect and budget shares to be time invariant, larger differences are observed between the most flexible random effects model and a pooled cross sectional estimator. The results suggest the limited ability of such estimators to control for preference heterogeneity and unit value endogeneity leads to parameter bias.

In this paper we derive a joint continuous/censored demand system suitable for the analysis of commodity demand relationships using panel data. Unobserved heterogeneity is controlled for using a correlated random effects specification and a Generalized Method of Moments framework used to estimate the model in two stages. In the first stage reduced form parameters are obtained through either ordinary least squares or heteroscedastic Tobit estimation, followed by the identification of structural parameters and imposition of cross-equation restrictions using minimum distance techniques. The procedure, which is demonstrated on data from Romania, yields elasticity estimates that lie within an intuitively pleasing range and reveals strong cross-substitution patterns between many commodity groups.

Do healthier diets cost more? We estimate a hedonic regression model of the U.S. diet. Given food expenditures and information on dietary intake we infer the marginal cost of improved quality. Meeting the Pyramid recommendations implies decreased expenditures from two of the seven food groups.

Examines linkages between food and health spending patterns, income, and health status of the elderly. Links these relationships to food insecurity and expenditures on nutraceuticals. Methodology includes simultaneous estimation of expenditure systems and health production functions. Preliminary results indicate simultaneity between health production function and spending patterns throughout the life cycle.

Since passage of the Personal Responsibility and Reconciliation Act of 1996 (PRWORA), states have the responsibility of developing and implementing their own Temporary Assistance to Needy Families (TANF) programs to operate in tandem with the Federal Food Stamp Program (FSP). The context for this welfare reform included a booming economy and broad public perception that welfare programs severely reduce the work effort of recipients. This study focuses on a period when the economy was in recession and investigates how the old cash welfare program, AFDC, and the FSP affected labor supply (weekly hours of work) decisions for single mothers, the majority of welfare recipients, across the rural-urban continuum. The central question is how the labor supply of single mothers responded to the availability of AFDC and FSP benefits, respectively, and whether their responses differed depending upon whether they reside in rural or urban areas. To answer this question, we utilize data from a special in-house Census Bureau extract from the Survey of Income and Program Participation with accurate rural and urban sub samples to estimate our three equations model, one for labor supply and one each for AFDC and FSP participation. The econometric model involves two linked components. The first is Bivariate Probit estimation of the AFDC and FSP participation decisions to account for possible correlation between the error terms of the participation equations. The participation estimates are linked to the second component, estimation of the labor supply equation, due to the endogeneity of the participation decisions and the possibility of bivariate selection. Single mothers may and do choose participation in either or both AFDC and the FSP and unobserved characteristics associated with those participation choices are likely to be negatively correlated with unobserved factors affecting labor supply. The participation estimates are used to calculate bivariate sample selection correction factors added as auxiliary variables in the labor supply equation. Because wages play important roles in all three equations, yet are observed only for women who work, we first impute wages based upon Heckman’s two-step sample selection bias correction procedure for rural and urban sub samples. The results show that bivariate rather than univariate participation estimation is necessary. The bivariate selection corrections in the labor supply equations, however, yield mixed results. Nonetheless, the estimated model reasonably explains linkages between AFDC and FSP programs and labor supply. The results show that increasing the AFDC tax on earnings by 10 percent generates almost identical average increases in labor supply by rural and urban single mothers, 0.12 and 0.11 hours per week, respectively. Their responses are also similar with respect to a 10 percent increase in the FSP earnings tax, 0.03 and 0.04 hours per week on average. A 10 percent increase in AFDC and FSP unearned income tax rates yield average rural labor supply increases of 0.11 and 0.02 hours per week, respectively, and corresponding urban responses of 0.01 and –0.02 hours per week. With one exception, rural and urban single mothers reduce hours of work as expected when AFDC and FSP guaranteed benefits increase by 10 percent. For the AFDC benefit increase, rural single mothers reduce labor supply less on average than do urban single mothers, -0.08 vs. -0.12 hours per week. The FSP benefit increase generates the largest reduction in labor supply, -0.35 hours per week for rural single mothers, compared to a labor supply increase of 0.14 hours per week by urban single mothers.

Participants in the Food Stamp Program consume more meats, added sugars, and total fats than they would in the absence of the program, while their consumption of fruits, vegetables, grains, and dairy products stays about the same. Participants in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) consume significantly less added sugars, which may reflect the substitution of WIC-supplied juices and cereals in place of higher sugar soft drinks and cereals. These findings come from a study of low-income Americans using the Continuing Survey of Food Intake by Individuals.

This paper uses nationally representative data to describe a monthly cycle in food expenditure and food intake by food stamp recipients. Food expenditure peaks sharply in the fIrst three days after food stamps are received. Actual food intake drops at the end of the month, for some foods and some people, although food intake over time is always smoother than food expenditure. The food stamp cycle has implications for two areas of research: the measurement ofhunger and food insecurity in the United States, and the measurement ofthe impact ofthe U.S. Food Stamp Program.

Over the past few years the S-216 Regional Project has devoted one day of the two-day annual meeting for a symposium. This year's symposium incorporated presentations by scholars from a number of fields: economics, agricultural economics, anthropology and social psychology. The latter two fields were represented by Mahadev L. Apte and David Brinberg who elucidated the perspectivesoftheirrespective disciplines and enhanced ourunderstanding ofhowthose disciplines conceptualize and empirically study food demand and consumption behavior. Prof. Apte's paper is included as the first in this proceedings volume. Because Prof. Brinberg's work on the role of and means for measuring the effect of attitudes on food consumption decisions (the basis for his presentation) has been published elsewhere, no paper is included in this volume. The second paper in this volume reflects the presentation of the economist, Geoffry Paulin, which addressed the changing food at home budget between 1980 and 1992. The third and final paper, by agricultural economists Parke E. Wilde and Christine K. Ranney and presented by Mr. Wilde, explored the utilization of experimental data to analyze the effects of the Food Stamp Program on food expenditures.

The Southworth hypothesis predicts that inframarginal food stamp recipients should choose the same bundle of goods, whether they receive coupons or cash. Empirical research has contradicted this prediction. Here, we present a model that retains some attractive features of the Southworth hypothesis, while relaxing the key assumption that appears to be incorrect. In particular, we allow different forms of benefits to have distinct effects on desired, or unrestricted food spending. Two categories of previously commonly used empirical models are evaluated as special cases of our more general model. We estimate this model using data from two cash-out experiments.

In this paper, we have recognized that the relatively constant inequality in the distribution of U.S. family income masks dramatic changes in the structure of the income distribution and the composition of personal incomes. Using relatively new procedures for decomposing the Gini measure of income inequality, we have gained a better understanding of the relationships among changes in the sources of income and the income distribution. This is facilitated through the use of data collected by the Census Bureau in the Survey of Income and Program Participation, which is the only set of data currently available that contains exhaustive lists of income and asset information at the household level. The empirical results are used in conjunction with data on transfer program expenditures to gain some perspective on the relative costs of reducing income inequality by increasing program benefits.

As the proportion of farm family income due to nonfarm sources continues to grow nationally, it is important to understand how farm families in various regions or states are affected. This paper develops a better understanding of the contribution of income from nonfarm sources to the level and distribution of income among farm families in New York. In analyzing income distribution, the Gini ratio is decomposed to determine the effects of marginal changes in income by source to overall inequality. The results are compared with the simulated changes in income inequality due to changes in income by source as measured by an "adjusted" Gini ratio which accounts specifically for negative farm incomes. Differences in the policy implications from both procedures are compared. The relationships among sources of income and policy implications can be brought into sharper focus by examining both measures.

This article addresses the questions of who, among eligible low-income consumers, participates in the Food Stamp Program and which variables are influential in determining whether eligible persons will participate. Variables found to be statistically significant in the probit analysis were the number of adult equivalents in the household, the number of persons 65 or older in the household, whether the household head had more than a high school education, whether the household owned a home, whether the household resided in Ohio, whether the household head was employed, whether the household had only unearned income, whether the household did not have any income either earned or unearned, whether the household received public assistance, the monthly household income, whether the respondent was Mexican-American, and lastly, in two of the three equations estimated whether the respondent was Black. The value of the Food Stamp allotment was not significant. Further investigation using appropriately measured theoretical components to estimate the extent to which command over market goods and services and nonmarket social consequences for households enter into the Food Stamp Program participation decision is indicated.

This paper addresses the possibility of biased estimates of the determinants of food expenditures of households eligible for the food stamp program. The source of such bias, sample partitioning, is describes and a correction procedure is utilized. For eligible nonparticipants' food expenditure estimates, bias was found but not for participants

This paper simulates alternative distributions of general purpose state aid to local governments under different combinations of criteria: tax capacity, effort, and revenue needs. Revenue needs are based on Tobit estimates of the costs of providing average levels of 16 categories of services. Segmenting the sample into high and low population jurisdictions provided a more realistic set of cost estimates. Available revenues or capacity are determined by multiplying each jurisdiction's tax bases by standard tax rates. A Need-Capacity gap, the difference between needed revenues and available revenues, is used as a needs-based distribution strategy for general purpose aid. Finally an effort gap, based on above average tax efforts was added to the Need-Capacity gap to define a Need-Capacity-Effort strategy.