arXiv 8 Feb 2022 · Econometrics · 3 citations (OpenAlex)
arXiv:2202.03960 · PDF · DOI · OpenAlex · Extracted main text
In dynamic discrete choice (DDC) analysis, it is common to use mixture models to control for unobserved heterogeneity. However, consistent estimation typically requires both restrictions on the support of unobserved heterogeneity and a high-level injectivity condition that is difficult to verify. This paper provides primitive conditions for point identification of a broad class of DDC models with multivariate continuous permanent unobserved heterogeneity. The results apply to both finite- and infinite-horizon DDC models, do not require a full support assumption, nor a long panel, and place no parametric restriction on the distribution of unobserved heterogeneity. In addition, I propose a seminonparametric estimator that is computationally attractive and can be implemented using familiar parametric methods.
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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 | Kasahara, Hiroyuki, Shimotsu, Katsumi (2009) Nonparametric identification of finite mixture models of dynamic discrete choices | 1.000 | 18 | 3 | 100% |
| 2 | Heckman, James, Singer, Burton (1984) A method for minimizing the impact of distributional assumptions in econometric models for duration data | 1.000 | 5 | 3 | 100% |
| 3 | Kristensen, Dennis, Mogensen, Patrick K, Moon, Jong Myun, Schjerning… (2021) Solving dynamic discrete choice models using smoothing and sieve methods | 0.950 | 7 | 4 | 86% |
| 4 | Altuğ, Sumru, Miller, Robert A (1998) The effect of work experience on female wages and labour supply | 0.928 | 15 | 4 | 80% |
| 5 | Kwon, Caleb, Mbakop, Eric (2021) Estimation of the number of components of nonparametric multivariate finite mixture models | 0.822 | 6 | 2 | 83% |
| 6 | Rust, John (1987) Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher | 0.811 | 4 | 2 | 100% |
| 7 | Aguirregabiria, Victor, Mira, Pedro (2010) Dynamic discrete choice structural models: A survey | 0.737 | 3 | 2 | 100% |
| 8 | Hu, Yingyao, Shum, Matthew (2012) Nonparametric identification of dynamic models with unobserved state variables | 0.693 | 8 | 1 | 100% |
| 9 | Fox, Jeremy T, Kim, Kyoo Il, Yang, Chenyu (2016) A simple nonparametric approach to estimating the distribution of random coefficients in structural models | 0.693 | 6 | 3 | 33% |
| 10 | Johnson, Edward G (2004) Identification in discrete choice models with fixed effects | 0.693 | 6 | 1 | 100% |
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