This paper proposes estimating linear dynamic panels by explicitly exploiting the endogeneity of lagged dependent variables and expressing the crossmoments between the endogenous lagged dependent variables and disturbances in terms of model parameters. These moments, when recentered, form the...

This paper develops a Stein-like combined estimator for large heterogeneous panel data models under common structural breaks. The model allows for cross-sectional dependence through a general multifactor error structure. By utilizing the common correlated effects (CCE) estimation technique, we...

This paper introduces a new estimator for the fixed effects dynamic panel data model withexogenous variables. This estimator does not share some of the drawbacks of recently developed IVand GMM estimators and has a good performance even in small samples. The nearly unbiased estimatoris derived...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

We investigate the strict exogeneity assumption, a necessary condition for estimator consistency in many finance panel settings. We outline tests for strict exogeneity in both traditional (non-IV) and IV settings. When we apply these tests in common traditional finance panel regressions, we find...

In nonlinear panel models with fixed effects and fixed-T, the incidental parameter problem poses identification difficulties for structural parameters and partial effects. Existing solutions are model-specific, likelihood-based, impose time homogeneity, or restrict the distribution of unobserved...

This paper considers fixed effects estimation and inference in linear and non-linear panel data models with random coefficients and endogenous regressors. The quantities of interest - means, variances, and other moments of the random coefficients - are estimated by cross sectional sample moments...

Across many disciplines, the fixed effects estimator of linear panel data models is the default method to estimate causal effects with nonexperimental data that are not confounded by time-invariant, unit-specific heterogeneity. One feature of the fixed effects estimator, however, is often...