A computationally simple bias correction for linear dynamic panel data models is proposed and its asymptotic properties are studied when the number of time periods fixed or tends to infinity with units. The approach can accommodate both fixed-effects random-effects assumptions, heteroskedastic errors, as well higher-order autoregressive models. Panel-corrected standard errors that allow robust ...

In structural dynamic discrete choice models, unobserved or mis-measured state variables may lead to biased parameter estimates and misleading inference. this paper, we show that instrumental can address such measurement problems when they relate evolve exogenously from the perspective of individual agents (i.e., market-level states). We define a class linear estimators rely on Euler equations ...