Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach
WIC, the Special Supplemental Nutrition Program for Women, Infants, and Children, is a widely studied public food assistance program that aims to provide foods, nutrition education and other services to at-risk, low-income children and pregnant, breastfeeding and postpartum women. From a policy perspective, it is of interest to assess the efficacy of the WIC program - how much, if at all, does the program improve the nutritional outcomes of WIC families? In this paper we address two important issues related to the WIC program that have not been extensively addressed in the past. First, although the WIC program is primarily devised with the intent of improving the nutrition of "target" children and mothers, it is possible that WIC may also change the consumption of foods by non-targeted individuals within the household. Second, although WIC eligibility status is predetermined, participation in the program is voluntary and therefore potentially endogenous. We make use of a triangular treatment-response model in which the dependent variable is the requirement-adjusted calcium intake from milk consumption and the endogenous variable is WIC participation, and estimate it using Bayesian methods. Using data from the CSFII 1994-1996, we find that the correlation between the errors of our two equations is strong and positive, suggesting that families participating in WIC have an unobserved propensity for high calcium consumption. The direct "structural" WIC parameters, however, do not support the idea that WIC participation leads to increased levels of calcium consumption from milk.
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- Poirier, Dale J & Tobias, Justin L, 2003.
"On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 21(2), pages 258-268, April.
- Poirier, D.J. & Tobias, J.L., 2001. "On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter," Papers 00-01-30, California Irvine - School of Social Sciences.
- Poirier, Dale J & Tobias, Justin, 2003. "On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter," Staff General Research Papers Archive 12014, Iowa State University, Department of Economics.
- Barrett, Christopher B., 2002. "Food security and food assistance programs," Handbook of Agricultural Economics,in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 2, chapter 40, pages 2103-2190 Elsevier.
- Oliveira, Victor & Chandran, Ram, 2005. "Children'S Consumption Of Wic-Approved Foods," Food Assistance and Nutrition Research Reports 33853, United States Department of Agriculture, Economic Research Service.
- Oliveira, Victor & Gundersen, Craig, 2000. "Wic And The Nutrient Intake Of Children," Food Assistance and Nutrition Research Reports 33803, United States Department of Agriculture, Economic Research Service.
- Chib, Siddhartha & Hamilton, Barton H., 2002. "Semiparametric Bayes analysis of longitudinal data treatment models," Journal of Econometrics, Elsevier, vol. 110(1), pages 67-89, September.
- Koop, Gary & Poirier, Dale J., 1997. "Learning about the across-regime correlation in switching regression models," Journal of Econometrics, Elsevier, vol. 78(2), pages 217-227, June.
- Chib, Siddhartha & Hamilton, Barton H., 2000. "Bayesian analysis of cross-section and clustered data treatment models," Journal of Econometrics, Elsevier, vol. 97(1), pages 25-50, July.
- Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99. Full references (including those not matched with items on IDEAS)