We propose a novel observation-driven modeling framework that allows for time variation in the model's parameters using a proximal-parameter (ProPar) update. The ProPar update is the solution to an optimization problem that maximizes the logarithmic observation density with respect to the...

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specificperiod of time. It is for this purpose that we...

This paper presents results of a meta-regression analysis on empirical estimates of capital-energy substitution. Theoretically it is clear that a distinction should be made between Morishima substitution elasticities and cross-price elasticities. The former represent purely technical...

In this paper we perform a meta-analysis on empirical estimates of the impact between investment and uncertainty. Since the outcomes of primary studies are largely incomparable with respect to the magnitude of the effect, our analysis focuses on the direction and statistical significance of the...

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...

We propose a new semiparametric observation-driven volatility model where the form of the error density directly influences the volatility dynamics. This feature distinguishes our model from standard semiparametric GARCH models. The link between the estimated error density and the volatility...

In this article we introduce a new class of test statistics designed to detect the occurrence of abnormal observations. It derives from the joint distribution of moment- and quantile-based estimators of power variation sigma^r, under the assumption of a normal distribution for the underlying...

This paper examines how productivity effects of human capital and innovation vary at different points of the conditional productivity distribution. Our analysis draws upon two large unbalanced panels of 6,634 enterprises in Germany and 14,586 enterprises in the Netherlands over the period...