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 introduce a nonlinear semi-parametric model that allows for the robust filtering of a common stochastic trend in a multivariate system of cointegrated time series. The observation-driven stochastic trend can be specified using flexible updating mechanisms. The model provides a general...

We analyze whether financial integration between countries leads to converging or diverging business cycles using a dynamic spatial model. Our model allows for contemporaneous spillovers of shocks to GDP growth between countries that are financially integrated and delivers a scalar measure of...

We analyse whether financial integration between countries leads to converging or diverging business cycles using a dynamic spatial model. Our model allows for contemporaneous spillovers of shocks to GDP growth between countries that are financially integrated and delivers a scalar measure of...

We analyze whether financial integration between countries leads to converging or diverging business cycles using a dynamic spatial model. Our model allows for contemporaneous spillovers of shocks to GDP growth between countries that are financially integrated and delivers a scalar measure of...