This paper proposes new error correction based cointegration tests for panel data. The limiting distributions of the tests are derived and critical values are provided. Our simulation results suggest that the tests have good small-sample properties with small size distortions and high power...

This paper considers a cointegrated panel data model with common factors. Starting from the triangular representation of the model as used by Bai et al. (2008) a Granger type representation theorem is derived. The conditional error correction representation is obtained, which is used as a basis...

This paper illustrates analytically the effects of cross-unit cointegration using as an example the conventional pooled least squares estimate in the spurious panel regression case. The results suggest that the usual result of asymptotic normality depends critically on the absence of cross-unit...

Most empirical evidence suggests that the sustainability hypothesis, stating that government revenues and expenditures should cointegrate with a unit slope on expenditures, does not hold within the European Union, a finding at odds with many theoretical models. This paper argues that these...

In this paper, two new simple residual-based panel data tests are proposed for the null of no cointegration. The tests are simple because they do not require any correction for the temporal dependencies of the data. Yet they are able to accommodate individual specific short-run dynamics,...

Time series unit root evidence suggests that inflation is nonstationary. By contrast, when using more powerful panel unit root tests, Culver and Papell (1997) find that inflation is stationary. In this article, we test the robustness of this result by applying a battery of recent panel unit root...

This article uses panel data from 1976 to 2003 to investigate the ways in which banking and stock markets influence economic growth in situations of high and low country risk. The mean and Standard Deviation (SD) of country risk are adopted to classify 28 countries into Low Risk Low Volatility...