IV-BASED COINTEGRATION TESTING IN DEPENDENT PANELS WITH TIME-VARYING VARIANCE

Matei Demetrescu, Christoph Hanck and Adina I. Tarcolea

Journal of Time Series Analysis, 2014, vol. 35, issue 5, 393-406

Abstract: type="main" xml:id="jtsa12071-abs-0001"> The distributions of cointegration tests are affected when the innovation variance varies over time. In panels, one must also pay attention to dependence among units. To obtain a panel cointegration test robust to both heteroskedasticity and dependence, we adapt the nonlinear instruments method proposed for the Dickey–Fuller test by Chang (2002, J Econometrics 110, 261–292) to an error-correction framework. We show that IV-based testing of the no error-correction null in individual equations yields standard normal test statistics when computed with heteroskedasticity-robust standard errors. The result holds under endogenous regressors, irrespective of the number of integrated covariates and for any variance profile. A non-cointegration test combining single-equation tests retains these nice properties. In panels of fixed cross-sectional dimension, such test statistics from individual units are shown to be asymptotically independent even under dependence, leading to panel tests robust to dependence and heteroskedasticity. The tests perform well in finite panels.

Date: 2014
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Working Paper: IV-Based Cointegration Testing in Dependent Panels with Time-Varying Variance (2012)
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