The evaluation of the impact of an increase in gasoline tax on demand relies crucially
on the estimate of the price elasticity. This paper presents an extended application
of the Partially Linear Additive Model (PLAM) to the analysis of gasoline demand
using a panel of US households, focusing mainly on the estimation of the price
elasticity. Unlike previous semi-parametric studies that use household-level data,
we work with vehicle-level data within households that can potentially add richer
details to the price variable. Both households and vehicles data are obtained from
the Residential Transportation Energy Consumption Survey (RTECS) of 1991 and
1994, conducted by the US Energy Information Administration (EIA). As expected,
the derived vehicle-based gasoline price has significant dispersion across the country
and across grades of gasoline. By using a PLAM specification for gasoline demand,
we obtain a measure of gasoline price elasticity that circumvents the implausible
price effects reported in earlier studies. In particular, our results show the price
elasticity ranges between −0.2, at low prices, and −0.5, at high prices, suggesting
that households might respond differently to price changes depending on the level
of price. In addition, we estimate separately the model to households that buy only
regular gasoline and those that buy also midgrade/premium gasoline. The results
show that the price elasticities for these groups are increasing in price and that
regular households are more price sensitive compared to non-regular