This paper studies estimation of a panel data model with latent structures where individuals can be classified into … within each group is not required but can be used to improve the accuracy of classification and estimation in finite samples …. Simulations evaluate performance and corroborate the asymptotic theory in several practical design settings. Two empirical …

. The tests are consistent and divergence rates are faster when the predictor is stationary. Asymptotic theory and …

, observational data computations, and Monte Carlo simulations to assess the use of various estimation methodologies, including … massive bias in system GMM estimation of the dynamic panel regression parameters, which arise from fixed effect heterogeneity … across individual station level observations. Difference GMM and Within Group (WG) estimation have little bias and WG …

applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in …

likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation … classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform … consistency. For PPL estimation C-Lasso also achieves the oracle property so that group-specific parameter estimators are …

-specific coefficients. C-Lasso achieves simultaneous classification and consistent estimation in a single step and the classification … exhibits the desirable property of uniform consistency. For PLS estimation C-Lasso also achieves the oracle property so that … identity information. For PGMM estimation the oracle property of C-Lasso is preserved in some special cases. Simulations …