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Analysing Russian Food Expenditure Using Micro-Data

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  • Elsner, Karin

Abstract

Since the beginning of transition, the level and structure of average food consumption and expenditure of Russian households has changed substantially. This development has gone together with a steep increase in the share of food in total expenditure. Notable differences with respect to food expenditure are observed between distinct household strata. In this paper, food demand of Russian households is investigated. For this purpose, households are classified by sociodemographic characteristics, and differences between food demand patterns of various household types are described using data of a Russian household survey of 1996. Russian food demand is econometrically estimated for seventeen food commodities belonging to five groups using a two-stage linear approximation of the Almost Ideal Demand System (LA/AIDS). Total expenditure allocation on food and non-food is analysed using Working's Engel model. The basic models are extended by sociodemographic factors. In a first step, unit values of food commodities are adjusted for quality differences and Probit analyses are carried out to analyse the decision to purchase food commodities. In a second step, the Engel model and the LA/AIDS are estimated applying the Generalised Heckman procedure in order to account for estimation bias introduced from zero expenditures. The estimates are used to calculate total expenditure and own price elasticities for different household groups. The results indicate that sociodemographic characteristics exert an important influence on the level and composition of food expenditure and on food demand elasticities. Therefore, if demand analysis shall contribute to the design of comprehensive food and social policies, not only average estimates for the population as a whole, but estimates for specific population groups should be considered.

Suggested Citation

  • Elsner, Karin, 1999. "Analysing Russian Food Expenditure Using Micro-Data," IAMO Discussion Papers 14909, Institute of Agricultural Development in Transition Economies (IAMO).
  • Handle: RePEc:ags:iamodp:14909
    DOI: 10.22004/ag.econ.14909
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    References listed on IDEAS

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    1. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-371, July.
    2. Brosig, S., 1998. "Trends der Nahrungsmittelnachfrage tschechischer Privathaushalte im Transformationsprozess," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 34.
    3. Heien, Dale & Durham, Cathy, 1991. "A Test of the Habit Formation Hypothesis Using Household Data," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 189-199, May.
    4. Laraki, Karim, 1989. "Ending Food Subsidies: Nutritional, Welfare, and Budgetary Effects," The World Bank Economic Review, World Bank, vol. 3(3), pages 395-408, September.
    5. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    6. Pollak, Robert A & Wales, Terence J, 1980. "Comparison of the Quadratic Expenditure System and Translog Demand Systems with Alternative Specifications of Demographic Effects," Econometrica, Econometric Society, vol. 48(3), pages 595-612, April.
    7. Elsner, Karin & Hartmann, Monika, 1998. "Convergence of food consumption patterns between Eastern and Western Europe," IAMO Discussion Papers 13, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    8. Thomas L. Cox & Michael K. Wohlgenant, 1986. "Prices and Quality Effects in Cross-Sectional Demand Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(4), pages 908-919.
    9. Heien, Dale & Jarvis, Lovell S. & Perali, Federico, 1989. "Food consumption in Mexico : Demographic and economic effects," Food Policy, Elsevier, vol. 14(2), pages 167-179, May.
    10. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    11. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762.
    12. Pollak, Robert A & Wales, Terence J, 1978. "Estimation of Complete Demand Systems from Household Budget Data: The Linear and Quadratic Expenditure Systems," American Economic Review, American Economic Association, vol. 68(3), pages 348-359, June.
    13. John L. Park & Rodney B. Holcomb & Kellie Curry Raper & Oral Capps, 1996. "A Demand Systems Analysis of Food Commodities by U.S. Households Segmented by Income," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 290-300.
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