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...

Macroeconomic disasters (wars, pandemics, depressions) are characterized by drastic shifts and increased volatility of the aggregate consumption to income ratio. By standard intertemporal budget constraint logic, this ratio is linked to expectations of future income and consumption growth rates....

We study the evolution of voter support for climate policies aimed at containing the effect of climate risk, as weather conditions worsens at a time of rising economic inequality. Households differ in age, beliefs and income, and the scale of intervention to preserve habitable land reflects the...

We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...

We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...