Measuring the price responsiveness of gasoline demand: Economic shape restrictions and nonparametric demand estimation
AbstractThis 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.
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Bibliographic InfoArticle provided by Econometric Society in its journal Quantitative Economics.
Volume (Year): 3 (2012)
Issue (Month): 1 (03)
Other versions of this item:
- Richard Blundell & Joel 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.
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- Richard Blundell & Joel Horowitz & Matthias Parey, 2013. "Nonparametric estimation of a heterogeneous demand function under the Slutsky inequality restriction," CeMMAP working papers CWP54/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Debopam Bhattacharya, 2013. "Nonparametric Welfare Analysis in Stochastic Models of Binary Choice," Economics Series Working Papers 669, University of Oxford, Department of Economics.
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