Cointegration Testing in Panels with Common Factors*

Abstract

Panel unit-root and no-cointegration tests that rely on cross-sectional independence of the panel unit experience severe size distortions when this assumption is violated, as has, for example, been shown by Banerjee, -91] via Monte Carlo simulations. Several studies have recently addressed this issue for panel unitroot tests using a common factor structure to model the cross-sectional dependence, but not much work has been done yet for panel nocointegration tests. This paper proposes a model for panel no-cointegration using an unobserved common factor structure, following the study by Bai panel unit roots. We distinguish two important cases: (i) the case when the non-stationarity in the data is driven by a reduced number of common stochastic trends, and (ii) the case where we have common and idiosyncratic stochastic trends present in the data. We discuss the homogeneity restrictions on the cointegrating vectors resulting from the presence of common factor cointegration. Furthermore, we study the asymptotic behaviour of some existing *Previous versions of this paper were presented at ]. Under the data-generating processes (DGP) used, the test statistics are no longer asymptotically normal, and convergence occurs at rate T rather than ffiffiffiffi N p T as for independent panels. We then examine the possibilities of testing for various forms of no-cointegration by extracting the common factors and individual components from the observed data directly and then testing for no-cointegration using residual-based panel tests applied to the defactored data.

Energy Consumption and Economic Growth Revisited: Structural Breaks and Cross-Section Dependence

“…They applied the Bai and Ng (2004) Even though all these studies provide evidence in favour of the presence of a single or multiple structural breaks none of them consequently consider that issue in both the unit root and cointegration tests. Furthermore, except for the CBL test and the cointegration test approach of Gengenbach et al (2006), all applied methods on total energy consumption neglect the existence of dependence across panel members. Consequently, this study take into account both structural breaks and cross-section dependence when testing for unit roots and cointegration, respectively.…”

Fiscal policy and TFP in the OECD: measuring direct and indirect effects

“…In line with the results in Kao (1999) and Phillips and Moon (1999), for a model with no cross-sectional dependence, and in Banerjee and Carrion-i-Silvestre (2011), for a model with cross-sectional dependence as in equation (6), we conjecture that the CCEPnl estimator yields consistent estimates for the homogenous coefficients β and λ and therefore, using equation (15), also for Ft 8 . This implies that we can obtain a consistent estimate for the composite 7 Using the PANIC approach to testing for panel cointegration in the presence of common factors has also been suggested by Gengenbach et al (2006), Banerjee and Carrion-i-Silvestre (2006) and Bai and Carrion-i-Silvestre (2013). The main difference between these approaches and ours lies in the estimation of the unknown coefficients in the cointegrating relation, for which we use the CCEP estimator while the above references estimate a model in first-differences with the common factors and factor loadings estimated using principal components.…”

Panel cointegration tests of the Fisher effect

“…6 See Banerjee and Carrion-i-Silvestre (2006) and Gengenbach et al (2006) for similar approaches. As shown in the Appendix, e it is a consistent estimate of e it , which suggests that the cointegration test can be implemented using (11) with e it in place of e it .…”