The authors examine simultaneously the causal links connecting monetary policy variables, real activity, and stock returns. Their interest lies in the fact that the dynamics of asset prices can provide key insights--in terms of information--for the conduct of monetary policy, since asset prices...

Our paper reports on Monte Carlo experiments using Evans's data-generating process to gauge the performance of these two kinds of regime-switching tests.

The author proposes a new test for financial contagion based on a non-parametric measure of the cross-market correlation. The test does not depend on the assumption that the data are drawn from a given probability distribution; therefore, it allows for maximal flexibility in fitting into the...

We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances. In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear...

This study tests for a structural break in the volatility of real GDP growth in Canada following the methodology of McConnell and Quiros (1998). A break is found in the first quarter of 1991. Based on disaggregated data, the tests indicate a break in the volatility of the rate of change of...

The authors document the out-of-sample forecasting accuracy of the New Keynesian model for Canada. They estimate their variant of the model on a series of rolling subsamples, computing out-of-sample forecasts one to eight quarters ahead at each step. They compare these forecasts with those...

A new consistent test is proposed for the parametric specification of the diffusion function in a diffusion process without any restrictions on the functional form of the drift function. The data are assumed to be sampled discretely in a time interval that can be fixed or lengthened to infinity....

The author proposes a class of exact tests of the null hypothesis of exchangeable forecast errors and, hence, of the hypothesis of no difference in the unconditional accuracy of two competing forecasts. The class includes analogues of the well-known Diebold and Mariano (1995) parametric and...

This paper describes a new test for evaluating conditional density functions that remains valid when the data are time-dependent and that is therefore applicable to forecasting problems. We show that the test statistic is asymptotically distributed standard normal under the null hypothesis, and...