The paper discusses similarities and differences between NDC and the French and German point systems. The study focuses on how these systems differ when there is an external shock (demographic, economic, or other) and discusses the possible consequences of moving from the point system to NDC....

This paper assesses the impact on growth and the inter-generational redistributive effects of some possible pension reforms in France using a dynamic general equilibrium model with overlapping generations. Results suggest that a reform increasing the effective average retirement age by 1.25...

We analyse the economic impact of a simultaneous aging shock in two countries. The countries are identical in all respects except the financing scheme of their public pension system. While one relies on capitalization, the other one relies on a pay-as-you-go scheme. We show that the two...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

This discussion paper led to a publication in the 'Journal of Econometrics', 2011, 163, 215-230.<P> We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the...</p>

This discussion paper resulted in a publication in the <I>Journal of Economic Dynamics & Control</I>, 34(9), 1596-1609.<P> We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information...</p></i>

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

This paper develops a novel approach to modeling and forecasting realized volatility (RV) measures based on copula functions. Copula-based time series models can capture relevant characteristics of volatility such as nonlinear dynamics and long-memory type behavior in a flexible yet parsimonious...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...