C12 Hypothesis Testing

March 1, 2010

Since the 1970s the characteristics of international business cycles have changed and deeper economic integration has modified the features of cross-country comovement. We formally test for correlation shifts in measures of real economic activity and economic/financial integration. In Europe we find evidence of significantly higher correlations following the creation of the EMU in 1999 for several subgroups of countries. We detect significantly more pronounced correlations between Mexico and the US and between Mexico and Canada in North America after the enforcement of the NAFTA in 1994. Results are derived from an econometric framework based on nonparametric iterated stationary bootstrap methods, whose statistical reliability and performance we assess through Monte Carlo simulations.

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March 27, 2011

Since the 1970s the characteristics of international business cycles have changed and deeper economic integration has modified the features of cross-country comovement. We formally test for correlation shifts in measures of real economic activity and economic/financial integration. In Europe we find some statistically significant evidence of higher correlations following the creation of the EMU in 1999 for several subgroups of countries. We detect significantly more pronounced correlations between Mexico and the US and between Mexico and Canada in North America after the enforcement of the NAFTA in 1994. Results are derived from an econometric framework based on nonparametric iterated stationary bootstrap methods, whose statistical reliability and performance we assess through Monte Carlo simulations.

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September 1, 2004

Existing methods for constructing confidence bands for multivariate impulse response functions depend on auxiliary assumptions on the order of integration of the variables. Thus, they may have poor coverage at long lead times when variables are highly persistent. Solutions that have been proposed in the literature may be computationally challenging. The goal of this Paper is to propose a simple method for constructing confidence bands for impulse response functions that is not pointwise and that is robust to the presence of highly persistent processes. The method uses alternative approximations based on local-to-unity asymptotic theory and allows the lead time of the impulse response function to be a fixed fraction of the sample size. These devices provide better approximations in small samples. Monte Carlo simulations show that our method tends to have better coverage properties at long horizons than existing methods. We also investigate the properties of the various methods in terms of the length of their confidence bands. Finally, we show, with empirical applications, that our method may provide different economic interpretations of the data. Applications to real GDP and to nominal versus real sources of fluctuations in exchange rates are discussed.

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