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Ungeachtet der vielfältigen Anstrengungen hat sich die Genauigkeit makroökonomischer Prognosen seit den 1970er Jahren nicht verbessert. Deshalb mahnen (manche) Ökonomen "mehr Wettbewerb" unter den Prognoseinstituten an – und hoffen, dass die allokative Effizienz marktlicher Lösungen auch...
Persistent link: https://www.econbiz.de/10009216328
This paper suggests a combination procedure to exploit the imperfect correlation of cointegration tests to develop a more powerful meta test. To exemplify, we combine Engle and Granger (1987) and Johansen (1988) tests. Either of these underlying tests can be more powerful than the other one...
Persistent link: https://www.econbiz.de/10009216329
Properties of a specification test for the parametric form of the variance function in diffusion processes dXt = b (t,Xt) dt + sigma (t,Xt) dWt are discussed. The test is based on the estimation of certain integrals of the volatility function. If the volatility function does not depend on the...
Persistent link: https://www.econbiz.de/10009216870
We show that the power of the KPSS-test against integration, as measured by divergence rates of the test statistic under the alternative, remains the same when residuals from an OLS-regression rather than true observations are used. This is in stark contrast to residual based tests of the null...
Persistent link: https://www.econbiz.de/10009216912
In this paper a method for including a-priori preferences of the decision makers into Multicriteria Optimization (MCO) problems is presented. A set of Pareto-optimal solutions is determined via desirability functions of the objectives which reveal experts´ preferences regarding different...
Persistent link: https://www.econbiz.de/10009216913
In this paper D-optimal designs for free knot least squares spline estimation are investigated. In contrast to most of the literature on optimal design for spline regression models it is assumed that the knots of the spline are also estimated from the data, which yields to optimal design...
Persistent link: https://www.econbiz.de/10009216931
A central limit theorem for the weighted integrated squared error of kernel type estimators of the first two derivatives of a nonparametric regression function is proved by using results for martingale differences and U-statistics. The results focus on the setting of the Nadaraya-Watson...
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