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Full-Text Articles in Econometrics
Panel Cointegration With Global Stochastic Trends, Jushan Bai, Chihwa Kao, Serena Ng
Panel Cointegration With Global Stochastic Trends, Jushan Bai, Chihwa Kao, Serena Ng
Center for Policy Research
This paper studies estimation of panel cointegration models with cross-sectional dependence generated by unobserved global stochastic trends. The standard least squares estimator is, in general, inconsistent owing to the spuriousness induced by the unobservable I(1) trends. We propose two iterative procedures that jointly estimate the slope parameters and the stochastic trends. The resulting estimators are referred to respectively as CupBC (continuously updated and bias-corrected) and the CupFM (continuously updated and fully modified) estimators. We establish their consistency and derive their limiting distributions. Both are asymptotically unbiased and asymptotically normal and permit inference to be conducted using standard test statistics. The …
The Asymptotics For Panel Models With Common Shocks, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
The Asymptotics For Panel Models With Common Shocks, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
Center for Policy Research
This paper develops a novel asymptotic theory for panel models with common shocks. We assume that contemporaneous correlation can be generated by both the presence of common regressors among units and weak spatial dependence among the error terms. Several characteristics of the panel are considered: cross sectional and time series dimensions can either be fixed or large; factors can either be observable or unobservable; the factor model can describe either cointegration relationship or a spurious regression, and we also consider the stationary case. We derive the rate of convergence and the distribution limits for the ordinary least squares (OLS) estimates …
On The Estimation And Inference Of A Panel Cointegration Model With Cross-Sectional Dependence, Jushan Bai, Chihwa Kao
On The Estimation And Inference Of A Panel Cointegration Model With Cross-Sectional Dependence, Jushan Bai, Chihwa Kao
Center for Policy Research
Most of the existing literature on panel data cointegration assumes cross-sectional independence, an assumption that is difficult to satisfy. This paper studies panel cointegration under cross-sectional dependence, which is characterized by a factor structure. We derive the limiting distribution of a fully modified estimator for the panel cointegrating coefficients. We also propose a continuous-updated fully modified (CUP-FM) estimator). Monte Carlo results show that the CUP-FM estimator has better small sample properties than the two-step FM (2S-FM) and OLS estimators.