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The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways:...
Persistent link: https://www.econbiz.de/10005545677
Cet article illustre l’applicabilité des méthodes de rééchantillonnage dans le cadre des tests multiples (simultanés), pour divers problèmes économétriques. Les hypothèses simultanées sont une conséquence habituelle de la théorie économique, de sorte que le contrôle de la...
Persistent link: https://www.econbiz.de/10005729689
In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming that the loading function is ad hoc (e.g., exponential...
Persistent link: https://www.econbiz.de/10005545733
scalar diusion. Among other examples, Stein equation implies that the mean of Hermite polynomials is zero. The GMM approach … contribution of the paper. The second reason for using GMM is that our tests are also valid for time series. In this case, we adopt …
Persistent link: https://www.econbiz.de/10005353211
. We establish the direct links between the usual parametric estimation methods, namely, the QMLE, the GMM and the M …-estimation. The ususal univariate QMLE is, under non-normality, less efficient than the optimal GMM estimator. However, the bivariate … QMLE based on the dependent variable and its square is as efficient as the optimal GMM one. A Monte Carlo analysis confirms …
Persistent link: https://www.econbiz.de/10005729782