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Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 12 [Issue:] 2 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2021 [Pages:] 351-403
Verlag: 
The Econometric Society, New Haven, CT
Zusammenfassung: 
Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non-identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non-additive changes in payoffs or changes to agents' choice sets. In doing so, we propose a general framework that allows the investigation of the identification of a broad class of counterfactuals (covering virtually any counterfactual encountered in applied work). To illustrate the results, we consider a firm entry/exit problem numerically, as well as an empirical model of agricultural land use. In each case, we provide examples of both identified and nonidentified counterfactuals of interest.
Schlagwörter: 
counterfactual
dynamic discrete choice
Identification
welfare
JEL: 
C14
C23
C25
C50
C61
L00
Q15
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
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