This paper develops a new method for estimating a demand function and the wel-
fare consequences of price changes. The method is applied to gasoline demand in
the United States and is applicable to other goods. The method uses shape restric-
tions 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 gaso-
line 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 non-monotonically 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.
Keywords. Consumer demand, nonparametric estimation, gasoline demand,
deadweight loss.
JEL classification. D120, H310, C140