We develop an agent-based model for the euro area that fulfils widely recommended requirements for nextgeneration macroeconomic models by i) incorporating financial frictions, ii) relaxing the requirement of rational expectations, and iii) including heterogeneous agents. Using macroeconomic 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...

As both the natural level of output and the New Keynesian output gap cannot be observed in practice, there is quite some debate on the question how these variables look like in practice. Rather than taking the standard approach of using a time trend or the HP-filter to obtain estimates of these...

This paper studies shock transmission across macroeconomic sectors in the UK, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of shocks to assess whether sectors with large bilateral economic linkages as measured through...

This paper develops a discrete-time epidemiological model for the spread of crises across sectors in the United States for the period 1952-2015. It is the first to use an epidemiological approach with macroeconomic (Flow of Funds) data. An extension of the usual one-period Markov model to a...

In this paper, we study the relationship between income inequality and stock market returns. We develop a quantitative general equilibrium model that links shifts in both labour and capital income inequality to stock market variables. An increase of the share of capital owners’ income from...

A flexible predictive density combination model is introduced for large financial data sets which allows for dynamic weight learning and model set incompleteness. Dimension reduction procedures allocate the large sets of predictive densities and combination weights to relatively small sets....

A flexible predictive density combination is introduced for large financial data sets which allows for model set incompleteness. Dimension reduction procedures that include learning allocate the large sets of predictive densities and combination weights to relatively small subsets. Given the...

This paper addresses the poor performance of the Expectation-Maximization (EM) algorithm in the estimation of low-noise dynamic factor models, commonly used in macroeconomic forecasting and nowcasting. We show analytically and in Monte Carlo simulations how the EM algorithm stagnates in a...

In economics and finance, speculative bubbles take the form of locally explosive dynamics that eventually collapse. We propose a test for the presence of speculative bubbles in the context of mixed causal-noncausal autoregressive processes. The test exploits the fact that bubbles are...