Asymptotic expansions are employed in a dynamic regression model with a unit root inorder to find approximations for the bias, the variance and for the mean squared error of theleast-squares estimator of all coefficients. It is found that in this particular context suchexpansions exist only when...

We study the optimal choice of quasi-likelihoods for nearly integrated,possibly non-normal, autoregressive models. It turns out that the two mostnatural candidate criteria, minimum Mean Squared Error (MSE) and maximumpower against the unit root null, give rise to different...

We prove that the probability distribution of Hill's estimator can be betterapproximated by a series of appropriate gamma distributions than by the limitingnormal distribution.

Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and...

Estimation using simulation techniques may be very time consuming. Specification tests for structuralstability often require more than one of such computationally demanding estimators. Typically one for thesample, one for the post-sample and one for the combination of sample and post-sample is...

We show that three convenient statistical properties that are known to hold forthe linear model with normal distributed errors that: (i.) when the variance is known, the likelihood based test statistics, Wald, Likelihood Ratio andScore or Lagrange Multiplier, coincide, (ii.) when the variance is...

This paper provides an extensive Monte-Carlo comparison of severalcontemporary cointegration tests. Apart from the familiar Gaussian basedtests of Johansen, we also consider tests based on non-Gaussianquasi-likelihoods. Moreover, we compare the performance of these parametrictests with tests...

In this paper we introduce the STAR-STGARCH model that can characterizenonlinear behaviour both in the conditional mean and the conditionalvariance. A modelling cycle for this family of models, consisting ofspecification, estimation, and evaluation stages is constructed.Misspecification tests...

Diffuse priors lead to pathological posterior behavior when used in Bayesian analyses of Simultaneous Equation Models (SEMs). This results from the local nonidentification of certain parameters in SEMs. When this, a priori known, feature is not captured appropriately, it results in an a...