Using density forecasts, we compare the predictive performance of dur ation models that have been developed fo modelling intra-day data on stock markets. Our model portfolio encompasses the auto regressive conditional duration (ACD) model, its logarithmic version (Log-ACD), the threshold...

We provide numerically reliable analytical expressions for the score of conditionally heteroskedastic dynamic regression models when the conditional distribution is multivariate t. We also derive one-sided and two-sided LM tests for multivariate normality versus multivariate t based on the first...

In this paper we consider the problem of testing the null hypothesis that a series has a constant level against the alternative that the level follows a random walk. This problem has previously been studied by inter alia, Nyblom and Makelainen in the context of the orthogonal random walk plus...

We consider data on jewellery sold in English public auctions between June 1993 and May 1994 at Credit Municipal de Paris. We present the underlying model of this market derived from a "hedonic price equation".

This paper tests a traditional model of asset pricing, the CCAPM (Consumption Capital Asset Pricing Model), using data from the Spanish stock market. A generalized calibration method is used to test this model. This method allows us to judge the degree of correspondance between the population...

Aggregate fluctuations display both persistence and damped oscillations in response to transitory shocks. The one sector growth model cannot explain these patterns. This major defect of this model results in its total inability to produce endogenous cycling, because its stable eigenvalues are...

Using the 1990-1992 wave of the French Labor Force Survey, this paper analyzes the effects of different factors on the probability of leaving unemployment of French young people. It also studies duration dependence of the hazard rate while controlling for unobserved heterogeneity separately for...

Five different identification problems in mixture models are made explicit. Necessary and sufficient relationships among these problems of identification are analyzed using the concepts of weak and strong identification. This analysis is first particularized under a normality assumption and then...

We investigate several important inference issues for factor models with dynamic heteroskedasticity in the common factors. First, we show that such models are identified if we take into account the time-variation in the variances of the factors. Our results also apply to dynamic versions of the...