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Identifying the Discount Factor in Dynamic Discrete Choice Models

Jaap H. Abbring, Øystein Daljord

arXiv 31 Aug 2018 · Econometrics · publishedQuantitative Economics (2020) · 50 citations (OpenAlex)

arXiv:1808.10651 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Empirical research often cites observed choice responses to variation that shifts expected discounted future utilities, but not current utilities, as an intuitive source of information on time preferences. We study the identification of dynamic discrete choice models under such economically motivated exclusion restrictions on primitive utilities. We show that each exclusion restriction leads to an easily interpretable moment condition with the discount factor as the only unknown parameter. The identified set of discount factors that solves this condition is finite, but not necessarily a singleton. Consequently, in contrast to common intuition, an exclusion restriction does not in general give point identification. Finally, we show that exclusion restrictions have nontrivial empirical content: The implied moment conditions impose restrictions on choices that are absent from the unconstrained model.

Citation extraction

41
references
107
in-text mentions
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distinct cited
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main-text words

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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
1Fang, H. and Y. Wang (2015) Estimating dynamic discrete choice models with hyperbolic discounting, with an application to mammography decisions1.00053100%
2Magnac, T. and D. Thesmar (2002) Identifying dynamic discrete choice processes0.98930697%
3Arcidiacono, P. and R. Miller (2011) Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity0.87462100%
4Rust, J (1987) Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher0.87452100%
5Yao, S., C. F. Mela, J. Chiang, and Y. Chen (2012) Determining consumers discount rates with field studies0.81142100%
6Arcidiacono, P. and R. Miller (2017) Identifying dynamic discrete choice models of short panels0.73732100%
7Rust, J (1994) Structural estimation of Markov decision processes0.73732100%
8Norets, A. and X. Tang (2014) Semiparametric inference in dynamic binary choice models0.73732100%
9Abbring, J. H. and . Daljord (2019) Estimating dynamic discrete choice models with hyperbolic discounting self0.64422100%
10Keane, M. P. and K. I. Wolpin (1997, June) (1997) The career decisions of young men0.64422100%

Showing the top 10 of 41 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 Models1.000144
2Identifying Present-Biased Discount Functions in Dynamic Discrete Choice Models1.00093
3Identifying Dynamic Discrete Choice Models with Hyperbolic Discounting0.73732
4A Comment on “Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting” by Hanming Fang and Yang Wang0.58531
5Dynamic Games in Empirical Industrial Organization0.51121
6Dynamic demand for differentiated products with fixed-effects unobserved heterogeneity0.51121
7Approximation-Robust Inference in Dynamic Discrete Choice0.40511
8Semiparametric Bayesian Estimation of Dynamic Discrete Choice Models0.40511
9Did Harold Zuercher Have Time-Separable Preferences?0.40511
10Sensitivity Analysis for Dynamic Discrete Choice Models0.40511