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Flexible but Parsimonious Demand Designs: The Case of Gasoline

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  • Mark Coppejans

    (Duke University)

Abstract

We consider expectations of the form E[logy|x] = Σ j=1 -super-d α j log x j as a good starting point for a more general analysis. We show why this naturally leads to the following flexible functional form: E[y|x] = f(Σ j=1 -super-dh j (x j )), where f(ċ) and the h j (ċ)'s are estimated by cubic splines. The main objective of this paper is to provide a straightforward method to estimate E[y|x]. We demonstrate the usefulness of this approach by estimating gasoline demand from the 1994 RTECS data set, and in doing so, uncover interesting relationships of income and age to expected gasoline use. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Mark Coppejans, 2003. "Flexible but Parsimonious Demand Designs: The Case of Gasoline," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 680-692, August.
    • Handle: RePEc:tpr:restat:v:85:y:2003:i:3:p:680-692
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    Cited by:

    1. Chen, Haotian & Smyth, Russell & Zhang, Xibin, 2017. "A Bayesian sampling approach to measuring the price responsiveness of gasoline demand using a constrained partially linear model," Energy Economics, Elsevier, vol. 67(C), pages 346-354.
    2. Manzan, sebastiano & Zerom, Dawit, 2008. "A Semiparametric Analysis of Gasoline Demand in the US: Reexamining The Impact of Price," MPRA Paper 14386, University Library of Munich, Germany.
    3. H. Spencer Banzhaf & Garima Bhalla, 2012. "Do Households Prefer Small School Districts? A Natural Experiment," Southern Economic Journal, John Wiley & Sons, vol. 78(3), pages 819-841, January.
    4. Sebastiano Manzan & Dawit Zerom, 2010. "A Semiparametric Analysis of Gasoline Demand in the United States Reexamining The Impact of Price," Econometric Reviews, Taylor & Francis Journals, vol. 29(4), pages 439-468.
    5. Wadud, Zia & Noland, Robert B. & Graham, Daniel J., 2010. "A semiparametric model of household gasoline demand," Energy Economics, Elsevier, vol. 32(1), pages 93-101, January.

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