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...

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...

To investigate the role of intra-regional trade integration on economic growth in Latin America, we develop a multilevel spatial production network model with time-varying parameters. The theoretical model is established for a multi-country and multi-sectoral economy. The reduced-form...