panel data cointegration, cross-sectional independence, cross-sectional dependence, continuous updated fully modified (CUP-FM) estimator, Monte Carlo results, two-step FM (2S-FM) estimator, OLS estimator
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.
Bai, Jushan and Kao, Chihwa, "On the Estimation and Inference of a Panel Cointegration Model with Cross-Sectional Dependence" (2005). Center for Policy Research. Paper 89.
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