Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/326948 
Year of Publication: 
2023
Citation: 
[Journal:] SERIEs - Journal of the Spanish Economic Association [ISSN:] 1869-4195 [Volume:] 14 [Issue:] 3/4 [Year:] 2023 [Pages:] 315-351
Publisher: 
Springer, Heidelberg
Abstract: 
We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter 0, whereas the distribution of unit-specific heterogeneity, as well as the feedback process that maps lagged outcomes into future covariate realizations, is left unrestricted. We provide a simple condition under which 0 is never point-identified, no matter the number of time periods available. This condition is satisfied in most models, including the logit one. We also characterize the identified set of 0 and show how to compute it using linear programming techniques. While 0 is not generally point-identified, its identified set is informative in the examples we analyze numerically, suggesting that meaningful learning about 0 may be possible even in short panels with feedback. As a complement, we report calculations of identified sets for an average partial effect and find informative sets in this case as well.
Subjects: 
Feedback
Panel data
Incidental parameters
Partial identification
JEL: 
C23
C33
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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