Panel cointegration with global stochastic trends

By Jushan Bai, C. Kao, Serena Ng. 2008

418 citations recorded by the source corpus.

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 (mixed) normal and permit inference to be conducted using standard test statistics. The estimators are also valid when there are mixed stationary and non-stationary factors, as well as when the factors are all stationary.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/74644c2de7d5a831f5cd9c585e2fafe846f09bca

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In Economics and Econometrics

Citations in the corpus

Impact of corruption in public sector on environmental quality: Implications for sustainability in BRICS and next 11 countries (2019, methodology): “Cointegration testing For checking the cointegrating association among the variables, we have employed Westerlund and Edgerton (2008) test and continuously updated FMOLS test (Bai et al., 2009).”
Cointegration in Panel Data with Breaks and Cross-Section Dependence (2006, neutral): “[7] Bai, J.”
Common Correlated Effects Estimation of Dynamic Panels with Cross-Sectional Dependence (2016, background): “Note that the restricted CCEP estimator bears some similarities with the continuously updated (Cup) estimator presented in Bai et al. (2009). The difference being that the CCEP estimates the unobserved components via the cross-sectional averages of both dependent and indepent variables, whereas the ”
Estimating Panel Time-Series Models with Heterogeneous Slopes (2012, neutral): “2002; Maddala and Wu 1999; Pedroni 1999, 2004), to a second generation of methods which explicitly addressed the concerns of correlation across panel members (e.g. Bai and Ng 2004; Bai et al. 2009; Pesaran 2006, 2007).”
Testing for Panel Cointegration Using Common Correlated Effects Estimators (2017, background): “Despite the presence of the operator (I L) in equation (2), Ft does not have to be I(1).”