A Simple Test for Cointegration in Dependent Panels with Structural Breaks*

Abstract

This paper develops a very simple test for the null hypothesis of no cointegration in panel data. The test is general enough to allow for heteroskedastic and serially correlated errors, unit-specific time trends, cross-sectional dependence and unknown structural breaks in both the intercept and slope of the cointegrated regression, which may be located at different dates for different units. The limiting distribution of the test is derived, and is found to be normal and free of nuisance parameters under the null. A small simulation study is also conducted to investigate the small-sample properties of the test. In our empirical application, we provide new evidence concerning the purchasing power parity hypothesis.

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

“…allows for structural breaks and cross-sectional dependence. Third, the panel cointegration test suggested by Westerlund and Edgerton (2008), which also considers structural breaks and dependence across countries, is introduced. Fourth, Sub-section 3.4 discusses Pesaran (2006)'s common correlated effects (CCE) estimators that are used to estimate the longrun relationship between energy consumption and GDP.…”

“…A panel cointegration test that considers both structural breaks and cross-section dependence was developed by Westerlund and Edgerton (2008). Apart from cross-sectional dependence and unknown structural breaks in both the intercept and slope, their test allows for heteroskedastic and serially correlated errors, as well as cross unit-specific time trends.…”

“…Westerlund and Edgerton (2008) propose two versions to test for the null hypothesis of no cointegration which can be used under those general conditions. Their test is derived from the Lagrange multiplier (LM)-based unit-root tests developed by Schmidt and Phillips (1992), Ahn (1993), and Amsler and Lee (1995).…”

“…Hence, the relationship in Equation (13) For testing purposes the LM principle is used that the score vector has zero mean when evaluated at the vector of true parameters under the null. Westerlund and Edgerton (2008) therefore consider the following pooled log-likelihood function…”

“…Based on LM φ (i) and LM τ (i) Westerlund and Edgerton (2008) propose the two panel LM-based test statistics for the null of no cointegration as…”