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Measuring the price responsiveness of gasoline demand: economic shape restrictions and nonparametric demand estimation

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  • Richard Blundell

    () (Institute for Fiscal Studies and IFS and UCL)

  • Joel L. Horowitz

    () (Institute for Fiscal Studies and Northwestern University)

  • Matthias Parey

    () (Institute for Fiscal Studies and University of Essex)

Abstract

This paper develops a new method for estimating a demand function and the welfare consequences of price changes. The method is applied to gasoline demand in the U.S. and is applicable to other goods. The method uses shape restrictions derived from economic theory to improve the precision of a nonparametric estimate of the demand function. Using data from the U.S. National Household Travel Survey, we show that the restrictions are consistent with the data on gasoline demand and remove the anomalous behavior of a standard nonparametric estimator. Our approach provides new insights about the price responsiveness of gasoline demand and the way responses vary across the income distribution. We find that price responses vary nonmonotonically with income. In particular, we find that low- and high-income consumers are less responsive to changes in gasoline prices than are middle-income consumers. We find similar results using comparable data from Canada.

Suggested Citation

  • Richard Blundell & Joel L. Horowitz & Matthias Parey, 2011. "Measuring the price responsiveness of gasoline demand: economic shape restrictions and nonparametric demand estimation," CeMMAP working papers CWP24/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:24/11
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    1. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2005. "Why the Apple Doesn't Fall Far: Understanding Intergenerational Transmission of Human Capital," American Economic Review, American Economic Association, pages 437-449.
    2. Hu, Yingyao & Shum, Matthew, 2012. "Nonparametric identification of dynamic models with unobserved state variables," Journal of Econometrics, Elsevier, pages 32-44.
    3. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, pages 1541-1565.
    4. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    5. D’Haultfoeuille, Xavier, 2011. "On The Completeness Condition In Nonparametric Instrumental Problems," Econometric Theory, Cambridge University Press, vol. 27(03), pages 460-471, June.
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