Derives sufficient statistics for feedback and heterogeneity in dynamic panel logit models, proves conditional likelihood identification is infeasible for Markov covariates, and proposes two assumptions to restore identification.
Moment restrictions for nonlinear panel data models with feedback
2 Pith papers cite this work. Polarity classification is still indexing.
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econ.EM 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
Dynamic random coefficient panel models with predetermined regressors are partially identified in short panels, with characterized identified sets for the mean, variance, and CDF of the coefficient distribution enabling tractable estimation.
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Sufficient Statistics for Markovian Feedback Processes and Unobserved Heterogeneity in Dynamic Panel Logit Models
Derives sufficient statistics for feedback and heterogeneity in dynamic panel logit models, proves conditional likelihood identification is infeasible for Markov covariates, and proposes two assumptions to restore identification.
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Identification and estimation of dynamic random coefficient models
Dynamic random coefficient panel models with predetermined regressors are partially identified in short panels, with characterized identified sets for the mean, variance, and CDF of the coefficient distribution enabling tractable estimation.