-effect models for panel data. We use an asymptotic embedding where the noise shrinks with the sample size to calculate the leading … bias in the empirical distribution arising from the presence of noise. The leading bias in the empirical quantile function … mean and variance have been derived. Given a closed-form expression for the bias, bias-corrected estimator of the …

-effect models for panel data. We use an asymptotic embedding where the noise shrinks with the sample size to calculate the leading … bias in the empirical distribution arising from the presence of noise. The leading bias in the empirical quantile function … for selection bias and shrinkage estimation and is to be contrasted with deconvolution. Simulation results confirm the …

bias arising from the presence of noise. Conditions are obtained under which this bias is asymptotically non … the density and quantile function. Our approach can be connected to corrections for selection bias and shrinkage …

section in Arellano & Bonhomme, 2011) we discuss models with both individual and time effects, split-panel Jackknife bias …This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of … incidental parameter bias caused by the estimation of many fixed effects is our main focus, and the unifying theme is that the …

This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number … & Hahn, 2007; a section in Arellano & Bonhomme, 2011) we discuss models with both individual and time effects, split-panel … Jackknife bias corrections, unbalanced panels, distribution and quantile effects, and other extensions. Understanding and …

Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models …. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables … parameters and average partial effects have normal distributions when the two dimensions of the panel grow large, but might …

Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models …. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables … parameters and average partial effects have normal distributions when the two dimensions of the panel grow large, but might …

We consider estimation and inference in panel data models with additive unobserved individual specific heterogeneity in … parameters in the canonical linear fixed effects model and over coefficients on a fixed vector of endogenous variables in panel …

and size-distorted when some of the factors are weak. We propose estimators with improved rates of convergence and bias … interactive fixed effects. We use the obtained estimate to construct a bias-aware CI taking into account the remaining bias due to …

. Leading examples where this is the case are models for panel and network data that feature fixed effects. In this paper, we … order. Combining these equations with sample splitting yields higher-order bias-corrected estimators of target parameters …