Projects per year
Abstract
Partial linear models provide an intuitively appealing way to examine gasoline demand because one can examine how response to price varies according to the price level and people's income. However, despite their intuitive appeal, partial linear models have tended to produce implausible and/or erratic price effects. Blundell et al. (2012) propose a solution to this problem that involves using Slutsky shape restrictions to improve the precision of the nonparametric estimate of the demand function. They propose estimating a constrained partially linear model through three steps, where the weights are optimized by minimizing an objective function under the Slutsky constraint, bandwidths are selected through least squares crossvalidation, and linear coefficients are estimated using profile least squares. A limitation of their threestep estimation method is that bandwidths are selected based on preestimated parameters. We improve on the Blundell et al. (2012) solution in that we derive a posterior and develop a posterior simulation algorithm to simultaneously estimate the linear coefficients, bandwidths in the kernel estimator and the weights imposed by the Slutsky condition. With our proposed sampling algorithm, we estimate a constrained partially linear model of household gasoline demand employing household survey data for the United States for 1991 and 2001 and for Canada for 2006–2009 and find plausible price effects.
Original language  English 

Pages (fromto)  346354 
Number of pages  9 
Journal  Energy Economics 
Volume  67 
DOIs  
Publication status  Published  1 Sep 2017 
Keywords
 Kernel estimator
 Markov chain Monte Carlo
 Price elasticity
 Slutsky condition
 Smoothness
Projects
 2 Finished

Trending Time Series Models with Non and SemiParametric Methods
Gao, J., Zhang, X. & Tjostheim, D.
Australian Research Council (ARC), Monash University
3/01/13 → 21/03/16
Project: Research

Nonparametric Estimation of Regression Models with Unknown Error Distributions
Australian Research Council (ARC), Monash University
4/01/10 → 31/12/13
Project: Research