Federico A. Bugni, Jackson Bunting
arXiv 19 Feb 2018 · Econometrics · publishedThe Review of Economic Studies (2020) · 7 citations (OpenAlex)
arXiv:1802.06665 · PDF · DOI · OpenAlex · Extracted main text
We study the asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games. We consider K-stage policy iteration (PI) estimators, where K denotes the number of policy iterations employed in the estimation. This class nests several estimators proposed in the literature such as those in Aguirregabiria and Mira (2002, 2007), Pesendorfer and Schmidt-Dengler (2008), and Pakes et al. (2007). First, we establish that the K-PML estimator is consistent and asymptotically normal for all K. This complements findings in Aguirregabiria and Mira (2007), who focus on K=1 and K large enough to induce convergence of the estimator. Furthermore, we show under certain conditions that the asymptotic variance of the K-PML estimator can exhibit arbitrary patterns as a function of K. Second, we establish that the K-MD estimator is consistent and asymptotically normal for all K. For a specific weight matrix, the K-MD estimator has the same asymptotic distribution as the K-PML estimator. Our main result provides an optimal sequence of weight matrices for the K-MD estimator and shows that the optimally weighted K-MD estimator has an asymptotic distribution that is invariant to K. The invariance result is especially unexpected given the findings in Aguirregabiria and Mira (2007) for K-PML estimators. Our main result implies two new corollaries about the optimal 1-MD estimator (derived by Pesendorfer and Schmidt-Dengler (2008)). First, the optimal 1-MD estimator is optimal in the class of K-MD estimators. In other words, additional policy iterations do not provide asymptotic efficiency gains relative to the optimal 1-MD estimator. Second, the optimal 1-MD estimator is more or equally asymptotically efficient than any K-PML estimator for all K. Finally, the appendix provides appropriate conditions under which the optimal 1-MD estimator is asymptotically efficient.
appendix boundary found by appendix_command · 48% of the source is main text. Read the extracted text to check this.
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 | Pesendorfer, M. and P. Schmidt-Dengler (2008) Asymptotic Least Squares Estimators for Dynamic Games | 1.000 | 31 | 5 | 100% |
| 2 | Pesendorfer, M. and P. Schmidt-Dengler (2010) Sequential Estimation of Dynamic Discrete Games: A Comment | 1.000 | 5 | 4 | 100% |
| 3 | Pakes, A., M. Ostrovsky, and S. Berry (2007) Simple estimators for the parameters of discrete dynamic games (with entry/exit examples) | 1.000 | 5 | 3 | 100% |
| 4 | Aguirregabiria, V. and P. Mira (2007) Sequential Estimation of Dynamic Discrete Games | 0.978 | 46 | 7 | 93% |
| 5 | Aguirregabiria, V. and P. Mira (2002) Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models | 0.914 | 17 | 6 | 76% |
| 6 | Kasahara, H. and K. Shimotsu (2008) Pseudo-likelihood Estimation and Bootstrap Inference for Structural Discrete Markov Decision Models | 0.659 | 7 | 3 | 29% |
| 7 | Aguirregabiria, V (2004) Pseudo maximum likelihood estimation of structural models involving fixed-point problems | 0.405 | 1 | 1 | 100% |
| 8 | Altonji, J. G. and L. M. Segal (1996) Small-sample bias in GMM estimation of covariance structures | 0.405 | 1 | 1 | 100% |
| 9 | Arcidiacono, P. and P. B. Ellickson (2011) Practical Methods for Estimation of Dynamic Discrete Choice Models | 0.405 | 1 | 1 | 100% |
| 10 | Arcidiacono, P. and R. A. Miller (2011) Conditional Choice Probability Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 19 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.