This discussion paper led to a publication in <A href="http://www.sciencedirect.com/science/article/pii/S0167947304001562">'Computational Statistics & Data Analysis'</A>, 49(2), 417-44.<P>We examine the asymptotic efficiency of OLS and IV estimators in a simple dynamic structural model with a constant and two explanatory variables: the lagged dependent variable and an...</p></a>

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less widespread. In this article it is argued that one...

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less widespread. In this articleit is argued that one...

This discussion paper led to an article in <I>Applied Geography</I> (2014). Volume 49(SI), pages 24-36.<P> The strong world-wide urbanisation trend calls for a repositioning of cities, especially the large cities with a global impact. These cities tend to become economic, logistic and political...</p></i>

This discussion paper has led to a publication in <a href="http://www.sciencedirect.com/science/article/pii/S0165176511002242">'Economics Letters'</A> 113(1), 76-79.<p> We consider the bias of the 2SLS estimator in the linear instrumental variables regression with one endogenous regressor only. By using asymptotic expansion techniques we approximate 2SLS coefficient estimation...</p></a>

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

This paper investigates the asymptotic properties of the ordinary least squares (OLS) estimator of structural parameters in a stylised macroeconomic model in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous variable. In particular, when...

Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels,...

This discussion paper led to an article in <I>Statistica Neerlandica</I> (2003). Vol. 57, issue 4, pages 439-469.<P> The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this...</p></i>