Publication in the 'Journal of Business & Economic Statistics' forthcoming.<A> We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and...</a>

Recent models for credit risk management make use of Hidden Markov Models (HMMs). The HMMs are used to forecast quantiles of corporate default rates. Little research has been done on the quality of such forecasts if the underlying HMM is potentially mis-specified. In this paper, we focus on...

This discussion paper led to an article in the <I>Journal of Financial Econometrics</I> (2013). Volume 11, pages 76-115.<P> We develop a systematic framework for the joint modelling of returns and multiple daily realised measures. We assume a linear state space representation for the log realised...</p></i>

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...

Likelihood based inference for multi-state latent factor intensity models is hindered by the fact that exact closed-form expressions for the implied data density are not available. This is a common and well-known problem for most parameter driven dynamic econometric models. This paper reviews,...

This paper has a twofold objective. First, we develop a new method to assess the monetary valuefor individuals of external effects. The method makes use of an ordinal index of life satisfaction asscored by individual respondents who are subjected in varying intensity to the external effect....

We asked participants of a large-scale, real-life peak avoidance experiment to provide estimates of their average in-vehicle travel time for their morning commute. Comparing these reported travel times to the corresponding actual travel times, we find that travel times are overstated by a factor...

A common way to determine values of travel time and schedule delay is to estimate departure time choice models, using stated preference (SP) or revealed preference (RP) data. The latter are used less frequently, mainly because of the difficulties to collect the data required for the model...

In binary discrete regression models like logit or probit the omis-sion of a relevant regressor (even if it is orthogonal) depresses the re-maining b coefficients towards zero. For the probit model, Wooldridge(2002) has shown that this bias does not carry over to the effect ofthe regressor on...

We compare reported job satisfaction with vignette evaluations of hypothetical jobs by using a British, Greek and Dutch data set, containing 95 randomly assigned vignettes. In order to test comparability of international data sets recently the method of anchoring vignettes has been introduced by...