Unemployment insurance agencies may combat moral hazard by punishing refusals to apply to assigned vacancies. However, the possibility to report sick creates an additional moral hazard, since during sickness spells, minimum requirements on search behavior do not apply. This reduces the ex-ante...

The generosity of the Unemployment Insurance system (UI) plays a central role for the job search behavior of unemployed individuals. Standard search theory predicts that an increase in UI benefit generosity, either in terms of benefit duration or entitlement, has a negative impact on the job...

In some countries including Germany unemployed workers can increase their income during job search by taking up marginal employment up to a threshold without any deduction from their benefits. Marginal employment can be considered as a wage subsidy as it lowers labour costs for firms owing to...

Unemployment rates are often higher for migrants than for natives. This could result from longer periods of unemployment as well as from shorter periods of employment. This paper jointly examines male native-migrant differences in the duration of unemployment and subsequent employment using...

Since conventional cross-validation bandwidth selection methods do not work for the case where the data considered are serially dependent, alternative bandwidth selection methods are needed. In recent years, Bayesian based global bandwidth selection methods have been proposed. Our experience...

This paper investigates whether or not there are significant changes in the dependence between the Thai equity market and six Asian markets - namely, Singaporean, Malaysian, Hong Kong, Korean, Indonesian and Taiwanese markets - due to 1997-July financial crisis. If so, this may be an indication...

We provide Markov chain Monte Carlo (MCMC) algorithms for computing the bandwidth matrix for multivariate kernel density estimation. Our approach is based on treating the elements of the bandwidth matrix as parameters to be estimated, which we do by optimizing the likelihood cross-validation...

Multivariate kernel regression is an important tool for investigating the relationship between a response and a set of explanatory variables. It is generally accepted that the performance of a kernel regression estimator largely depends on the choice of bandwidth rather than the kernel function....

This paper investigates nonparametric estimation of density on [0,1]. The kernel estimator of density on [0,1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study,...

This paper aims to investigate a Bayesian sampling approach to parameter estimation in the semiparametric GARCH model with an unknown conditional error density, which we approximate by a mixture of Gaussian densities centered at individual errors and scaled by a common standard deviation. This...