Cross-Sectional Correlation Robust Tests for Panel Cointegration

Abstract

We use meta analytic combination procedures to develop new tests for panel cointegration. The main idea consists in combining p-values from time series cointegration tests on the different units of the panel. The tests are robust to heterogeneity as well as to cross-sectional dependence between the different units of the panel. To achieve the latter, we employ a sieve bootstrap procedure with joint resampling of the residuals of the different units. A simulation study shows that the suggested bootstrap tests can have substantially smaller error-in-rejection probabilities than tests ignoring the presence of cross-sectional dependence while preserving high power. We apply the tests to a panel of Post-Bretton Woods data to test for weak Purchasing Power Parity (PPP). --panel cointegration tests,cross-sectional dependence,sieve bootstrap