Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

How do different entitlements to unemployment benefits affect the transitions from unemployment into employment?

In Portugal duration of benefits is exclusively age determined while replacement rates are essentially uniform. We exploit differences in potential maximum duration of benefits for nearly matched pairs of individuals to determine the effects of benefit duration on job finding. (C) 2008 Elsevier B.V. All rights reserved.

Do minimum wages raise employment? Evidence from the US retail-trade sector

This paper examines the impact of minimum wages on earnings and employment in selected branches of the retail-trade sector, 1990-2005, using county-level data on employment and a panel regression framework that allows for county-specific trends in sectoral outcomes. We focus on specific subsectors within retail trade that are identified as particularly low-wage. We find little evidence of disemployment effects once we allow for geographic-specific trends. Indeed, in many sectors the evidence points to modest (but robust) positive employment effects. (C) 2009 Elsevier B.V. All rights reserved.