In this article we model the log of the U.S. and the U.K. real oil prices in terms of fractionally integrated processes with a mean shift. We use different versions of the tests of Robinson (1994), which have standard null and local limit distributions. The results indicate that if we model the...

Fractionally integrated models with the disturbances following a Bloomfield (1973) exponential spectral model are proposed in this article for modelling the U.K. unemployment. This enables us a better understanding of the low-frequency dynamics affecting the series, without relying on any...

We make use in this article of a testing procedure suggested by Robinson (1994) for testing deterministic seasonality versus seasonal fractional integration. A new test statistic is developed to simultaneously test both, the order of integration of the seasonal component and the need of seasonal...

This paper entertains the notion that disturbances on the demand side play a central role in our understanding of the Great Depression. In fact, from Euler equation residuals we are able to identify a series of unusually large negative demand shocks that appeared to have hit the U. S. economy...

We show in this article that fractionally integrated univariate models for GDP may lead to a better replication of business cycle characteristics. We firstly show that the business cycle features are clearly affected by the degree of integration as well as by the other short run components of...

This paper examines the role of uncertainty shocks in a one-sector, representative-agent dynamic stochastic general equilibrium model. When prices are flexible, uncertainty shocks are not capable of producing business cycle comovements among key macro variables. With countercyclical markups...

We introduce a dynamic network model of interbank lending and estimate the parameters by indirect inference using network statistics of the Dutch interbank market from mid-February 2008 through April 2011. We find that credit-risk uncertainty and peer monitoring are significant factors in...

This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...

We study the performance of alternative methods for calculating in-sample confidence and out of-sample forecast bands for time-varying parameters. The in-sample bands reflect parameter uncertainty only. The out-of-sample bands reflect both parameter uncertainty and innovation uncertainty. The...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...