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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 causality?. In particular, it is often of interest to assess whether...
Persistent link: https://www.econbiz.de/10010263216
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/10010263220
Rationality of early release data is typically tested using linear regressions. Thus, failure to reject the null does not rule out the possibility of nonlinear dependence. This paper proposes two tests that have power against generic nonlinear alternatives. A Monte Carlo study shows that the...
Persistent link: https://www.econbiz.de/10010282830
Persistent link: https://www.econbiz.de/10001732255
Persistent link: https://www.econbiz.de/10002033313
Persistent link: https://www.econbiz.de/10001625176
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
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
Persistent link: https://www.econbiz.de/10003913382
This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, we first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. Then, we...
Persistent link: https://www.econbiz.de/10009130687