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Analysis of Households' Decision Using Full Demand Elasticity Estimates: an Estimation on Turkish Data

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  • Okay Gunes

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

Households' consumption patterns are deciphered through estimates of demand elasticities based on the domestic production decisions determined by constraints on time use and monetary budgets for different subpopulations. We first estimate the shadow wage rates of the households and later estimate the full demand elasticities which are computed using full prices proposed by Gardes (2016) derived through the hypotheses of complementarity or substitutability existing between monetary and time expenditures. Detailed results are obtained for the whole population by breaking the dataset into age groups and into households according to poverty level, as determined by the OECD-modified equivalence scale.

Suggested Citation

  • Okay Gunes, 2017. "Analysis of Households' Decision Using Full Demand Elasticity Estimates: an Estimation on Turkish Data," Post-Print halshs-01491970, HAL.
  • Handle: RePEc:hal:journl:halshs-01491970
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01491970
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    References listed on IDEAS

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    1. Anil Alpman, 2016. "Implementing Rubin's alternative multiple-imputation method for statistical matching in Stata," Stata Journal, StataCorp LP, vol. 16(3), pages 717-739, September.
    2. Carla Canelas & François Gardes & Silvia Salazar, 2014. "Price and Income Elasticities in LAC Countries: The Importance of Domestic Production," Post-Print halshs-01020350, HAL.
    3. Mark Aguiar & Erik Hurst, 2007. "Measuring Trends in Leisure: The Allocation of Time Over Five Decades," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 969-1006.
    4. Reuben Gronau & Daniel S. Hamermesh, 2006. "Time Vs. Goods: The Value Of Measuring Household Production Technologies," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(1), pages 1-16, March.
    5. Moriarity, Chris & Scheuren, Fritz, 2003. "A Note on Rubin's Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 65-73, January.
    6. Davis, George C. & You, Wen, 2013. "Estimates of returns to scale, elasticity of substitution, and the thrifty food plan meal poverty rate from a direct household meal production function," Food Policy, Elsevier, vol. 43(C), pages 204-212.
    7. Rubin, Donald B, 1986. "Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 87-94, January.
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