We propose to pool alternative systemic risk rankings for financial institutions using the method of principal components. The resulting overall ranking is less affected by estimation uncertainty and model risk. We apply our methodology to disentangle the common signal and the idiosyncratic...

Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...

It is widely believed that the Millennium Challenge Corporation (MCC) has grossly fallen short of high expectations raised by the Bush administration in 2002. From the perspective of potential recipient countries, the crucial issue is whether the MCC increased the overall pool of aid resources...

Using panel data for 157 countries over the period 1999-2005 we empirically investigate the politics involved in IMF economic forecasts. We find a systematic bias in growth and inflation forecasts. Our results indicate that countries voting in line with the US in the UN General Assembly receive...

We conceptualize global liquidity as global monetary policy and credit components by means of a large-scale dynamic factor model in the spirit of Eickmeier,Gambacorta, and Hofmann (2014). Going beyond previous work, we decompose aggregate credit components into credit supply and demand flows...

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...