In this paper, we empirically evaluate competing approaches for combining inflation density forecasts in terms of Kullback-Leibler divergence. In particular, we apply a similar suite of models to four different datasets and aim at identifying combination methods that perform well throughout...

We investigate the small-sample size and power properties of bootstrapped likelihood ratio systems cointegration tests via Monte Carlo simulations when the true lag order of the data generating process is unknown. A recursive bootstrap scheme is employed. We estimate the order by minimizing...

Can long-run identified structural vector autoregressions (SVARs) discriminate between competing models in practice? Several authors have suggested SVARs fail partly because they are fiite-order approx-imations to infinite-order processes. We estimate vector autoregressive moving average (VARMA)...

In this paper, we empirically evaluate competing approaches for combining inflation density forecasts in terms of Kullback-Leibler divergence. In particular, we apply a similar suite of models to four different data sets and aim at identifying combination methods that perform well throughout...

Can long-run identified structural vector autoregressions (SVARs) discriminate between competing models in practice? Several authors have suggested SVARs fail partly because they are finite-order approximations to infinite-order processes. We estimate vector autoregressive moving average (VARMA)...

The finite-sample size and power properties of bootstrapped likelihood ratio system cointegration tests are investigated via Monte Carlo simulations when the true lag order of the data generating process is unknown. Recursive bootstrap schemes are employed which differ in the way in which the...