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Nonparametric Welfare Analysis for Discrete Choice

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  • Debopam Bhattacharya

Abstract

Abstract: We consider empirical measurement of exact equivalent/compensating variation resulting from price-change of a discrete good, using individual-level data. We show that for binary and multinomial choice, the marginal distributions of EV/CV are nonparametrically point-identified solely from the conditional choice-probabilities, under extremely general preference-distributions. These results hold even when the distribution/dimension of unobserved heterogeneity are neither specified, nor identified and utilities are neither quasi-linear nor parametrically specified. Welfare-distributions can be expressed as closed-form functionals of observable individual choice-probabilities, thus enabling easy computation in applications. Average EV for price-rise equals the change in average consumer-surplus and is smaller than average CV for a normal good. Point-identification fails for ordered choice if the unit-price is identical for all alternatives, thereby providing a connection to Hausman-Newey's (2013) partial identification results for the limiting case of continuous choice.

Suggested Citation

  • Debopam Bhattacharya, 2013. "Nonparametric Welfare Analysis for Discrete Choice," Economics Series Working Papers 669, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:669
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    References listed on IDEAS

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    1. Stefan Hoderlein & Anne Vanhems, 2011. "Welfare analysis using nonseparable models," CeMMAP working papers CWP01/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Hausman, Jerry A & Newey, Whitney K, 1995. "Nonparametric Estimation of Exact Consumers Surplus and Deadweight Loss," Econometrica, Econometric Society, vol. 63(6), pages 1445-1476, November.
    3. Richard Blundell & Joel L. Horowitz & Matthias Parey, 2012. "Measuring the price responsiveness of gasoline demand: Economic shape restrictions and nonparametric demand estimation," Quantitative Economics, Econometric Society, vol. 3(1), pages 29-51, March.
    4. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
    5. Arthur Lewbel, 2012. "An Overview of the Special Regressor Method," Boston College Working Papers in Economics 810, Boston College Department of Economics.
    6. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," CREATES Research Papers 2013-06, Department of Economics and Business Economics, Aarhus University.
    7. Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-1382, November.
    8. Hausman, Jerry A, 1981. "Exact Consumer's Surplus and Deadweight Loss," American Economic Review, American Economic Association, vol. 71(4), pages 662-676, September.
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    Cited by:

    1. Griffith, Rachel & Nesheim, Lars & O'Connell, Martin, 2015. "Income effects and the welfare consequences of tax in differentiated product oligopoly," CEPR Discussion Papers 10670, C.E.P.R. Discussion Papers.
    2. Su Thet Hninn & Keisuke Kawata & Shinji Kaneko & Yuichiro Yoshida, 2016. "A nonparametric welfare analysis on water quality improvement of the floating people on Inlay Lake via a randomized conjoint field experiment," IDEC DP2 Series 6-2, Hiroshima University, Graduate School for International Development and Cooperation (IDEC).
    3. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers CWP42/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.

    More about this item

    Keywords

    Multinimial choice; Compensating and equivalent variation; unobserved heterogeneity; unrestricted heterogeneity; deadweight loss;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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