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Multinomial Choice and Selectivity

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Abstract

In this paper we discuss two types of selection problems. The first problem is motivated by labor market analyses such as the estimation of sector-specific wage equations where the sector for which the wages are observed are chosen by the agents. In contrast to previous formulations which usually are based on a probit framework, we assume here that the discrete choice is generated by a multinomial logit model with random coefficients (mixed multinomial logit model). The advantage compared to the multinomial probit setting is that choice sets with many alternatives become almost as easy to handle as the binary case. The second problem we analyze is motivated by studies where the interest is to estimate the effect of for example labor market training programs on the labor market opportunities. Previous works have, to the best of my knowledge, focused solely on the effect of labor market programs on earnings. As in the first case we allow for arbitrarily large choice sets of feasible first stage choices (programs) as well as the second stage choices (labor market status).

Suggested Citation

  • John K. Dagsvik, 2000. "Multinomial Choice and Selectivity," Discussion Papers 264, Statistics Norway, Research Department.
    • Handle: RePEc:ssb:dispap:264
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    1. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    2. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    3. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    4. Heckman, James J & Sedlacek, Guilherme L, 1990. "Self-selection and the Distribution of Hourly Wages," Journal of Labor Economics, University of Chicago Press, vol. 8(1), pages 329-363, January.
    5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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    Cited by:

    1. Ugo Colombino & Nizamul Islam, 2021. "Global and digitalised economy, new labour demand scenarios and optimal tax-transfer reforms," CHILD Working Papers Series 90 JEL Classification: H2, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA.
    2. Inés Hardoy, 2005. "Impact of Multiple Labour Market Programmes on Multiple Outcomes: The Case of Norwegian Youth Programmes," LABOUR, CEIS, vol. 19(3), pages 425-467, September.

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    More about this item

    Keywords

    Selection bias; discrete/continuous choice.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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