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SELECTION BIAS CORRECTIONS BASED ON THE MULTINOMIAL LOGIT MODEL: MONTE CARLO COMPARISONS
Open accessAbstract
Abstract This survey presents the set of methods available in the literature on selection bias correction, when selection is specified as a multinomial logit model. It contrasts the underlying assumptions made by the different methods and shows results from a set of Monte Carlo experiments. We find that, in many cases, the approach initiated by Dubin and MacFadden (1984) as well as the semi‐parametric alternative recently proposed by Dahl (2002) are to be preferred to the most commonly used Lee (1983) method. We also find that a restriction imposed in the original Dubin and MacFadden paper can be waived to achieve more robust estimators. Monte Carlo experiments also show that selection bias correction based on the multinomial logit model can provide fairly good correction for the outcome equation, even when the IIA hypothesis is violated.
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Cites
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
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Metadata
- Authors
- Bourguignon, F., Fournier, M., & Gurgand, M.
- Venue
- Journal of Economic Surveys
- Publisher
- Wiley
- Published
- 2007-01-25
- Volume
- 21
- Issue
- 1
- Pages
- 174-205
- ISSN
- 0950-0804 (ISSN-L)
- 1467-6419
- OpenAlex
- W3124948514
- Cited by
- 669
- References
- 1
- FWCI
- 24.93
- Type
- journal article
- Language
- en
- Open access
- green
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- Bourguignon, F., Fournier, M., & Gurgand, M. (2007). SELECTION BIAS CORRECTIONS BASED ON THE MULTINOMIAL LOGIT MODEL: MONTE CARLO COMPARISONS. Journal of Economic Surveys. https://doi.org/10.1111/j.1467-6419.2007.00503.x
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