In this study we collect information on what economists would suggest for reducing German unemployment. This was done by conducting a detailed survey containing 35 measures at two conferences of different kind. One conference was a small conference at the Humboldt-University in Berlin attended...

We consider problems in modelling job-matching in the Czech Republic during the transition to a market economy. Special interest is devoted to functional form considerations and the analysis of returns to scale of the matching function. This explorative study aims to shed some light into the...

We provide empirical evidence on the nature of spatial externalities in a matching model for the UK. We use a monthly panel of outflows, unemployment and vacancy stocks data from the registers at Jobcentres in the UK; these are mapped on to travel-to-work areas. We find evidence of significant...

The regional distribution of unemployment rates in the Czech Republic over the transition period is shown to be characterized by twin peaks, e.g. a high and a low unemployment equilibrium. The emergence of strong regional disparities at the beginning of the 1990s can, at least partially, be...

A local linear estimator of generalized impulse response (GIR) functions for nonlinear conditional heteroskedastic autoregressive processes is derived and shown to be asymptotically normal. A plug-in bandwidth is obtained that minimizes the asymptotical mean squared error of the GIR estimator. A...

Optimal bandwidths for local polynomial regression usually involve functionals of the derivatives of the unknown regression function. In the multivariate case, estimates of these functionals are not readily available, primarily because estimating multivariate derivatives is complicated. In this...

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...

Newly developed and advanced methods for nonlinear time series analysis are in general not available in standard software packages. Moreover, their implementation requires substantial time, computing power as well as programming skills. The recent results on lag and bandwidth selection methods...

Applying nonparametric variable selection criteria in nonlinear regression models generally requires a substantial computational effort if the data set is large. In this paper we present a selection technique that is computationally much less demanding and performs well in comparison with...