We analyze the distribution of economic activity across space for different types of activity and different levels of aggregation. Not only is this distribution highly uneven (independently of the type of activity and level of aggregation), it is also remarkably regular regarding its size...

By combining two large data sets (on international trade flows and cross-border mergers and acquisitions - M&As), we test two implications of Neary’s (2003, 2007) general oligopolistic equilibrium (GOLE) model (incorporating strategic interaction between firms in a general equilibrium...

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 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...

Using a comprehensive international trade data set we investigate empirical regularities (known as Zipf’s Law or the rank-size rule) for the distribution of the interaction between countries as measured by revealed comparative advantage. Using the recently developed estimator by Gabaix and...

This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...