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...

Using meta-analytical techniques, we focus on 11 studies that explicitly measure the effect of a net migration variable in neoclassical convergence models and derive 57 comparable effect sizes. The data suggest that an increase in the net migration rate of one percentage point increases on...

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...