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Forecasting new product penetration with flexible substitution patterns

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  • Brownstone, David
  • Train, Kenneth

Abstract

We describe and apply choice models, including generalizations of logit called 'mixed logits,' that do not exhibit the restrictive 'independence from irrelevant alternatives' property and can approximate any substitution pattern. The models are estimated on data from a stated-preference survey that elicited customers' preferences among gas, electric, methanol, and CNG vehicles with various attributes.

Suggested Citation

  • Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," Department of Economics, Working Paper Series qt1j6814b3, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    • Handle: RePEc:cdl:econwp:qt1j6814b3
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    References listed on IDEAS

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    1. Lee, Lung-Fei, 1992. "On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Cambridge University Press, vol. 8(4), pages 518-552, December.
    2. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
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    6. Stern, Steven, 1992. "A Method for Smoothing Simulated Moments of Discrete Probabilities in Multinomial Probit Models," Econometrica, Econometric Society, vol. 60(4), pages 943-952, July.
    7. Brownstone, David & Bunch, David S. & Golob, Thomas F. & Ren, Weiping, 1996. "A Transaction Choice Model for Forecasting Demand for Alternative-Fuel Vehicles," University of California Transportation Center, Working Papers qt0244r8g2, University of California Transportation Center.
    8. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
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    11. Brownstone, David & Bunch, David S & Golob, Thomas F & Ren, Weiping, 1996. "A Transactions Choice Model for Forecasting Demand for Alternative-Fuel Vehicles," University of California Transportation Center, Working Papers qt3sm7w9zk, University of California Transportation Center.
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