I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances characterized by a … transformed data and applies standard techniques for estimation of panel vector-autoregressive models. I compare the small …-sample performance of various estimation strategies in a Monte Carlo study. -- spatial PVAR ; multivariate dynamic panel data model …

I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial … to analyze the relationship between trade and GDP using a panel data over time and across countries …

stationarity assumptions. Ishihara (2020) explores identification of the nonseparable panel data model under these assumptions and …

dynamic panel data (SDPD) model (Qu, Lee, and Yu, 2017). I firstly introduce the bias-corrected score function since the score …

Unconditional quantile treatment effects are difficult to estimate in the presence of fixed effects. Panel data are … effects or differencing of data, however, redefines the quantiles. This paper introduces a quantile estimator for panel data …

A semiparametric fixed effects model is introduced to describe the nonlinear trending phenomenon in panel data analysis …

This paper revisits the panel autoregressive model, with a primary emphasis on the unit-root case. We study a class of …

measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors … inference using the level version of the equation seems superior to inference based on the equation in differences. -- Panel …

This paper investigates the finite sample properties of estimators for spatial dynamic panel models in the presence of … suggest that, in order to account for the endogeneity of several covariates, spatial dynamic panel models should be estimated …