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Estimation of random coefficients logit demand models with interactive fixed effects

Listed author(s):
  • Hyungsik Roger Moon

    (Institute for Fiscal Studies and USC)

  • Matthew Shum

    (Institute for Fiscal Studies)

  • Martin Weidner

    ()

    (Institute for Fiscal Studies and cemmap and UCL)

We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discrete-choice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can be arbitrarily correlated with the observed product characteristics (including price), which accommodates endogeneity and, at the same time, captures strong persistence in market shares across products and markets. We propose a two step least squares-minimum distance (LS-MD) procedure to calculate the estimator. Our estimator is easy to compute, and Monte Carlo simulations show that it performs well. We consider an empirical application to US automobile demand.

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File URL: http://cemmap.ifs.org.uk/wps/cwp081212.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP08/12.

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Date of creation: 30 Mar 2012
Handle: RePEc:ifs:cemmap:08/12
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  17. Susanna Esteban & Matthew Shum, 2007. "Durable-goods oligopoly with secondary markets: the case of automobiles," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 332-354, 06.
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  24. Ahn, Seung Chan & Hoon Lee, Young & Schmidt, Peter, 2001. "GMM estimation of linear panel data models with time-varying individual effects," Journal of Econometrics, Elsevier, vol. 101(2), pages 219-255, April.
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