This paper proposes a new panel unit root test based on Simes' [Biometrika 1986, An Improved Bonferroni Procedure for Multiple Tests of Significanceʺ] classical intersection test. The test is robust to general patterns of cross-sectional dependence and yet straightforward to implement, only...

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...

Time series cointegration tests, even in the presence of large sample sizes, often yield conflicting conclusions ("mixed signalsʺ) as measured by, inter alia, a low correlation of empirical p-values [see Gregory et al., 2004, Journal of Applied Econometrics]. Using their methodology, we present...

Meta-analytic panel unit root tests such as Fisher's X 2 test, which consist of pooling the p-values of time series unit root tests, are widely applied in practice. Recently, several Monte Carlo studies have found these tests’ Error-in-Rejection Probabilities (or, synonymously, size...

We use recent advances in multiple testing to identify the countries for which Purchasing Power Parity (PPP) held over the last century. The approach controls the multiplicity problem inherent in simultaneously testing for PPP on several time series, thereby avoiding spurious rejections. It has...

We propose new tests for panel cointegration by extending the panel unit root of Choi [2001] and Maddala and Wu [1999] to the panel cointegration case. The tests are flexible, intuitively appealing and relatively easy to compute. We investigate the finite sample behavior in a simulation study....

This paper suggests a combination procedure to exploit the imperfect correlation of cointegration tests to develop a more powerful meta test. To exemplify, we combine Engle and Granger (1987) and Johansen (1988) tests. Either of these underlying tests can be more powerful than the other one...

We propose new tests for panel cointegration by extending the panel unit root of Choi [2001] and Maddala and Wu [1999] to the panel cointegration case. The tests are flexible, intuitively appealing and relatively easy to compute. We investigate the finite sample behavior in a simulation study....

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...

We investigate the OLS-based estimator s2 of the disturbance variance in the standard linear regression model with cross section data when the disturbances are homoskedastic, but spatially correlated. For the most popular model of spatially autoregressive disturbances, we show that s2 can be...