the bias in the unpaired sample. In a second step, corrected unpaired observations are used jointly with panel data. This …

A new panel data model is proposed to represent the behavior of economies in transition allowing for a wide range of … formulated as a nonlinear time varying factor model. When applied to a micro panel, the decomposition provides flexibility in … idiosyncratic behavior over time and across section, while retaining some commonality across the panel by means of an unknown common …

This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly … the known correlation pattern, we derive the asymptotic properties of panel least squares estimators. Simulations are used …

, we develop three dimensional (3D) panel data models with hierarchical error components that allow for strong cross … simulation studies. We also demonstrate the empirical usefulness of the proposed approach through an application to a 3D panel …

This paper introduces a spatial panel quantile model with unobserved heterogeneity. The proposed model is capable of … parameters, a new estimation procedure is proposed. When both the time and cross-sectional dimensions of the panel go to infinity …

This paper presents some two-step estimators for a wide range of parametric panel data models with censored endogenous … decomposition of the reduced form residuals. The panel nature of the data allows adjustment, and testing, for two forms of …

This paper extends the Common Correlated Effects (CCE) approach developed by Pesaran (2006) to heterogeneous panel data … cross section averages must be included in individual equations of the panel, and the number of cross section averages must … dimension of the panel is sufficiently large …

. Using a set of 35 annual country-level panel data from 1980 to 2019, we apply the 'bias-corrected' synthetic control …