Growing concern for climate change and rising scarcity of fossil fuels prompted governments to stimulate the development of renewables. This paper empirically tests whether feed-in tariff (FIT) policies have been effective in the development of photovoltaic solar (PV), explicitly taking into...

In this paper, we apply a dynamic innovation diffusion framework to model adoption of full electric vehicles where we explicitly distinguish three major phases of adoption: introduction, growth and maturity. We combine this approach with an SP study to elicit individual preferences for...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

This discussion paper resulted in a publication in the <A href="http://onlinelibrary.wiley.com/doi/10.1002/jae.2411/full">'Journal of Applied Econometrics'</A>, 2014, 29(7), 1164-1182.<P> Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended Phillips Curve (PC) models. It is shown that...</p></a>

We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative...

This discussion paper resulted in a publication in the 'Journal of Econometrics', 2013, 177(2), 213-232.<P> We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several...</p>

In this paper, we study the short-run and long-run comovement between prices and real activity in the G7 countries during the postwar period using vector autoregressive systems and frequency-domain filters. We find several patterns that are robust across countries and time periods. Typically,...

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by...

As both the natural level of output and the New Keynesian output gap cannot be observed in practice, there is quite some debate on the question how these variables look like in practice. Rather than taking the standard approach of using a time trend or the HP-filter to obtain estimates of these...

This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...