Population forecasts are crucial for many social, political and economic decisions. Official population projections rely in general on deterministic models which use different scenarios for future vital rates to indicate uncertainty. However, this technique shows substantial weak points such as...

This paper explores the optimal risk sharing arrangement between generations in an overlapping generations model with endogenous growth. We allow for nonseparable preferences, paying particular attention to the risk aversion of the old as well as overall "life-cycle" risk aversion. We provide a...

Conventional wisdom states that the statutory split of payroll taxation between firms and workers is of no macroeconomic relevance, because the tax incidence is fully determined by the market structure. This paper breaks with this view by establishing a theoretical link between the statutory...

This paper examines magnitudes and business cycle dynamics of social security contributions (SSC). In most OECD countries studied, we document a negative covariation of payroll tax burdens with GDP and GDP growth at business cycle and lower frequencies. We assess the overall magnitude of the...

We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied Volatility Surface (IVS). Practical applications require reducing the dimension and characterize its dynamics through a small number of factors. Such dimension reduction is...

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...

According to housing investment models, house prices and replacement cost should have an equilibrating relationship. Previous empirical work - mainly based on aggregate-level data - has found only little evidence of such a relationship. By using a unique data set, covering transactions of...

In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...