arXiv 31 Aug 2020 · Econometrics · publishedThe Review of Economics and Statistics (2026) · 8 citations (OpenAlex)
arXiv:2009.00085 · PDF · DOI · OpenAlex · Extracted main text
This paper proposes a robust method for semiparametric identification and estimation in panel multinomial choice models, where we allow for infinite-dimensional fixed effects that enter into consumer utilities in an additively nonseparable way, thus incorporating rich forms of unobserved heterogeneity. Our identification strategy exploits multivariate monotonicity in parametric indexes, and uses the logical contraposition of an intertemporal inequality on choice probabilities to obtain identifying restrictions. We provide a consistent estimation procedure, and demonstrate the practical advantages of our method with Monte Carlo simulations and an empirical illustration on popcorn sales with the Nielsen data.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Shi, X., M. Shum, and W. Song (2018) Estimating semi-parametric panel multinomial choice models using cyclic monotonicity | 1.000 | 5 | 3 | 100% |
| 2 | Gao, W. Y. and R. Wang (2025) Identification of nonlinear dynamic panels under partial stationarity self | 0.843 | 3 | 3 | 100% |
| 3 | Manski, C. F (1975) Maximum score estimation of the stochastic utility model of choice | 0.811 | 4 | 2 | 100% |
| 4 | Manski, C. F (1985) Semiparametric analysis of discrete response: Asymptotic properties of the maximum score estimator | 0.811 | 4 | 2 | 100% |
| 5 | Manski, C. F (1987) Semiparametric analysis of random effects linear models from binary panel data | 0.811 | 4 | 2 | 100% |
| 6 | Pakes, A. and J. Porter (2024) Moment inequalities for multinomial choice with fixed effects | 0.809 | 17 | 3 | 53% |
| 7 | Chernozhukov, V., H. Hong, and E. Tamer (2007) Estimation and confidence regions for parameter sets in econometric models | 0.644 | 3 | 2 | 67% |
| 8 | Berry, S. and A. Pakes (2007) The pure characteristics demand model | 0.644 | 2 | 2 | 100% |
| 9 | Chernozhukov, V., I. Fernández-Val, and W. K. Newey (2019) Nonseparable multinomial choice models in cross-section and panel data | 0.644 | 2 | 2 | 100% |
| 10 | Gao, W. Y., M. Li, and S. Xu (2023) Logical differencing in dyadic network formation models with nontransferable utilities self | 0.644 | 2 | 2 | 100% |
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