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Sensitivity Analysis for Dynamic Discrete Choice Models

Chun Pong Lau

arXiv 29 Aug 2024 · Econometrics

arXiv:2408.16330 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In dynamic discrete choice models, some parameters, such as the discount factor, are being fixed instead of being estimated. This paper proposes two sensitivity analysis procedures for dynamic discrete choice models with respect to the fixed parameters. First, I develop a local sensitivity measure that estimates the change in the target parameter for a unit change in the fixed parameter. This measure is fast to compute as it does not require model re-estimation. Second, I propose a global sensitivity analysis procedure that uses model primitives to study the relationship between target parameters and fixed parameters. I show how to apply the sensitivity analysis procedures of this paper through two empirical applications.

Citation extraction

45
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93
in-text mentions
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distinct cited
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main-text words

appendix boundary found by appendix_command · 78% of the source is main text. Read the extracted text to check this.

Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Rust, J (1987) Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher1.000145100%
2Chen, L. and E. Choo (2023) Identification and Parametric Estimation of Empirical Dynamic Marriage Matching Models0.97112492%
3Igami, M (2017) Estimating the Innovator’s Dilemma: Structural Analysis of Creative Destruction in the Hard Disk Drive Industry, 1981–19980.92843100%
4Jørgensen, T. H (2023) Sensitivity to Calibrated Parameters0.81142100%
5Hotz, V. J. and R. A. Miller (1993) Conditional Choice Probabilities and the Estimation of Dynamic Models0.73732100%
6Ossa, R (2014) Trade Wars and Trade Talks with Data0.73732100%
7Aguirregabiria, V., A. Collard-Wexler, and S. P. Ryan (2021) Chapter 4 - Dynamic games in empirical industrial organization, in0.64422100%
8Aguirregabiria, V. and P. Mira (2002) Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models0.64422100%
9Arcidiacono, P. and R. A. Miller (2011) Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity0.64422100%
10Horowitz, J. and C. Manski (1995) Identification and Robustness with Contaminated and Corrupted Data0.64422100%

Showing the top 10 of 45 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models0.40511
2Choosing What to Calibrate and What to Estimate in Structural Models0.40511