arXiv 30 Jan 2025 · Econometrics
arXiv:2501.18746 · PDF · DOI · OpenAlex · Extracted main text
Estimation and counterfactual experiments in dynamic discrete choice models with large state spaces pose computational difficulties. This paper develops a novel model-adaptive approach to solve the linear system of fixed point equations of the policy valuation operator. We propose a model-adaptive sieve space, constructed by iteratively augmenting the space with the residual from the previous iteration. We show both theoretically and numerically that model-adaptive sieves dramatically improve performance. In particular, the approximation error decays at a superlinear rate in the sieve dimension, unlike a linear rate achieved using conventional methods. Our method works for both conditional choice probability estimators and full-solution estimators with policy iteration. We apply the method to analyze consumer demand for laundry detergent using Kantar's Worldpanel Take Home data. On average, our method is 51.5% faster than conventional methods in solving the dynamic programming problem, making the Bayesian MCMC estimator computationally feasible.
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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 | Hendel, Igal and Nevo, Aviv (2006) Measuring the implications of sales and consumer inventory behavior | 1.000 | 15 | 4 | 100% |
| 2 | Arcidiacono, Peter and Miller, Robert A (2011) Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity | 0.843 | 3 | 3 | 100% |
| 3 | Aguirregabiria, Victor and Mira, Pedro (2002) Swapping the nested fixed point algorithm: A class of estimators for discrete Markov decision models | 0.811 | 4 | 2 | 100% |
| 4 | Aguirregabiria, Victor and Magesan, Arvind (2023) Solution and estimation of dynamic discrete choice structural models using Euler equations | 0.811 | 4 | 2 | 100% |
| 5 | Kress, Rainer (2014) Linear Integral Equations | 0.737 | 5 | 3 | 40% |
| 6 | Han, Weimin and Atkinson, Kendall E (2009) Theoretical numerical analysis: A functional analysis framework | 0.693 | 6 | 2 | 50% |
| 7 | Sweeting, Andrew (2013) Dynamic product positioning in differentiated product markets: The effect of fees for musical performance rights on the commerci… | 0.644 | 4 | 1 | 100% |
| 8 | Aguirregabiria, Victor and Mira, Pedro (2007) Sequential estimation of dynamic discrete games | 0.644 | 2 | 2 | 100% |
| 9 | Hotz, V Joseph and Miller, Robert A (1993) Conditional choice probabilities and the estimation of dynamic models | 0.644 | 2 | 2 | 100% |
| 10 | Judd, Kenneth L (1998) Numerical methods in economics | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 66 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Constrained Recursive Logit for Route Choice Analysis | 0.405 | 1 | 1 |