Showing 1 - 10 of 94
Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast...
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In this paper, we show the first order validity of the block bootstrap in the context of Kolmogorov type conditional distribution tests when there is dynamic misspecification and parameter estimation error. Our approach differs from the literature to date because we construct a bootstrap...
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Forecasters and applied econometricians are often interested in comparing the predictive accuracy of nested competing models. A leading example of nestedness is when predictive ability is equated with "out-of-sample Granger causalityʺ. In particular, it is often of interest to assess whether...
Persistent link: https://www.econbiz.de/10001848736
We take as a starting point the existence of a joint distribution implied by different dynamic stochastic general equilibrium (DSGE) models, all of which are potentially misspecified. Our objective is to compare "true" joint distributions with ones generated by given DSGEs. This is accomplished...
Persistent link: https://www.econbiz.de/10001848913
This paper introduces bootstrap specification tests for diffusion processes. In the one-dimensional case, the proposed test is closest to the non parametric test introduced by Ait-Sahalia (1996), in the sense that both procedures determine whether the drift and variance components of a...
Persistent link: https://www.econbiz.de/10001848918
In the conduct of empirical macroeconomic research, unit root, cointegration, common cycle, and related test statistics are often constructed using logged data, even though there is often no clear reason, at least from an empirical perspective, why logs should be used rather than levels....
Persistent link: https://www.econbiz.de/10001848931
Mild factor loading instability, particularly if sufficiently independent across the different constituent variables, does not affect the estimation of the number of factors, nor subsequent estimation of the factors themselves (see e.g. Stock and Watson (2009)). This result does not hold in the...
Persistent link: https://www.econbiz.de/10009766692