We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with …-aware CIs that are uniformly valid regardless of whether the factors are strong or not. Our approach applies the theory of … minimax linear estimation to form a debiased estimate using a nuclear norm bound on the error of an initial estimate of the …

applying panel data, a new and more accurate fatality risk measure, and systematic selection of panel estimator in our research …. Controlling for measurement error, endogeneity, individual heterogeneity, and state dependence yields both a reasonable average …

This paper presents a model for the heterogeneity and dynamics of the conditional mean and the conditional variance of … proposed. The expression for a modified likelihood function is obtained for estimation and inference in a fixed-T context …. Using a bias-corrected likelihood approach makes it possible to reduce the estimation bias to a term of order 1/T². The …

nonlinear network and panel models with unobserved two-way effects, strictly exogenous covariates, and possibly discrete outcome …

Since little is known about the degree of bias in estimated fixed effects in panel data models, we run Monte Carlo …

We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel …

This paper develops a model for dynamic binary choice panel data that allows for unobserved heterogeneity to be … eliminate the unobserved heterogeneity term and at the same time to identify the parameters of the model. We then propose GMM …

This paper develops a model for dynamic binary choice panel data that allows for unobserved heterogeneity to be … eliminate the unobserved heterogeneity term and at the same time to identify the parameters of the model. We then propose GMM …