In this paper we investigate the effect of Donald Trump's campaign for coal in his successful race for the White House in 2016. Using a spatial Durbin model we estimate the effect of coal production on the Republicans vote share in the US Presidential Election of 2016 on the county level. To...

We analyze the effect of wind turbines on the prices of houses in their proximity. Utilizing the universe of Danish house transactions since 1992 and data on all turbines ever established in Denmark, we are able to control for individual house fixed effects. We distinguish between effects of...

In this paper we investigate the effect of Donald Trump’s campaign for coal in his successful race for the White House in 2016. Using a spatial Durbin model we estimate the effect of coal production on the Republicans vote share in the US Presidential Election of 2016 on the county level. To...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

This study evaluates the effectiveness of contracting out mandatory publicly provided counselling and training for long-term unemployed in Flanders (Belgium) to private for-profit and non-profit organisations (FPOs and NPOs). A multivariate transition model exploits timing-of-events and novel...

This paper develops a long run growth model for a major oil exporting economy and derives conditions under which oil revenues are likely to have a lasting impact. This approach contrasts with the standard literature on the Dutch disease and the resource curse, which primarily focus on short run...

Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals...

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...

This paper applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a pre-selection algorithm of indicators for forecasting. By using unique quarterly real gross domestic product data for two German states (the Free State of Saxony and...