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A Framework for Analyzing Rank Ordered Panel Data with Application to Automobile Demand

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Author Info

  • John K. Dagsvik
  • Gang Liu

    ()
    (Statistics Norway)

Abstract

In this paper we develop a framework for analyzing panel data with observations on rank ordered alternatives that allows for correlated random taste shifters across time and across alternatives. As a special case we obtain a nested logit model type for rank ordered alternatives. We have applied this framework to estimate several model versions for household demand for conventional and alternative fuel automobiles in Shanghai based on rank ordered data obtained from a stated preference survey. The preferred model is then used to calculate demand probabilities and elasticities and the willingness-to-pay for alternative fuel vehicles.

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Bibliographic Info

Paper provided by Research Department of Statistics Norway in its series Discussion Papers with number 480.

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Date of creation: Oct 2006
Date of revision:
Handle: RePEc:ssb:dispap:480

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Related research

Keywords: Random utility models; Nested rank ordered logit models; Automobile demand; Alternative fuel vehicles;

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  1. McFadden, Daniel L., 1984. "Econometric analysis of qualitative response models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 24, pages 1395-1457 Elsevier.
  2. Dagsvik, John K. & Wennemo, Tom & Wetterwald, Dag G. & Aaberge, Rolf, 2002. "Potential demand for alternative fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 36(4), pages 361-384, May.
  3. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
  4. Beggs, S. & Cardell, S. & Hausman, J., 1981. "Assessing the potential demand for electric cars," Journal of Econometrics, Elsevier, vol. 17(1), pages 1-19, September.
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Cited by:
  1. Alexandros Dimitropoulos & Piet Rietveld & Jos N. van Ommeren, 2011. "Consumer Valuation of Driving Range: A Meta-Analysis," Tinbergen Institute Discussion Papers 11-133/3, Tinbergen Institute.

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