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 calculate the social cost of carbon (SCC) under stochastic climate volatility resulting from uncertainty about future climate risk regimes where weather extremes are becoming more frequent and intense. Using a stochastic dynamic integrated climate-economy model where representative agents are...

We forecast the term structure of U.S. Treasury zero-coupon bond yields by analyzing a range of models that have been used in the literature. We assess the relevance of parameter uncertainty by examining the added value of using Bayesian inference compared to frequentist estimation techniques,...