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Semiparametric estimation of the random utility model with rank-ordered choice data
- Yan, Jin, Yoo, Hong Il
- Journal of econometrics 2019 v.211 no.2 pp. 414-438
- econometric models, economic analysis, economic theory, heteroskedasticity
- We propose semiparametric methods for estimating random utility models using rank-ordered choice data. Our primary method is the generalized maximum score (GMS) estimator. With partially rank-ordered data, the GMS estimator allows for arbitrary forms of interpersonal heteroskedasticity. With fully rank-ordered data, the GMS estimator becomes considerably more flexible, allowing for random coefficients and alternative-specific heteroskedasticity and correlations. The GMS estimator has a non-standard asymptotic distribution and a convergence rate of N−1∕3. We proceed to construct its smoothed version which is asymptotically normal with a faster convergence rate of N−d∕(2d+1), where d≥2 increases in the strength of smoothness assumptions.