Power Law Distribution of the Duration and Magnitude of Recessions in Capitalist Economies : Breakdown of Scaling

Power law distributions of macroscopic observables are ubiquitous in both the natural and social sciences. They are indicative of correlated, cooperative phenomena between groups of interacting agents at the microscopic level. In this paper we argue that when one is considering aggregate macroeconomic data (annual growth rates in real per capita GDP in the seventeen leading capitalist economies from 1870 through to 1994) the magnitude and duration of recessions over the business cycle do indeed follow power law like behaviour for a significant proportion of the data (demonstrating the existence of cooperative phenomena amongst economic agents). Crucially, however, there are systematic deviations from this behaviour when one considers the frequency of occurrence of large recessions. Under these circumstances the power law scaling breaks down. It is argued that it is the adaptive behaviour of the agents (their ability to recognise the changing economic environment) which modifies their cooperative behaviour.Comment: 17 pages, 6 figures, Accepted for Publication in Physica

Random Matrix Theory and the Failure of Macroeconomic Forecasts

By scientific standards, the accuracy of short-term economic forecasts has been poor, and shows no sign of improving over time. We form a delay matrix of time-series data on the overall rate of growth of the economy, with lags spanning the period over which any regularity of behaviour is postulated by economists to exist. We use methods of random matrix theory to analyse the correlation matrix of the delay matrix. This is done for annual data from 1871 to 1994 for 17 economies, and for post-war quarterly data for the US and the UK. The properties of the eigenvalues and eigenvectors of these correlation matrices are similar, though not identical, to those implied by random matrix theory. This suggests that the genuine information content in economic growth data is low, and so forecasting failure arises from inherent properties of the data.Comment: 15 Pages, 2 Figure

The Convergence of European Business Cycles 1978-2000

The degree of convergence of the business cycles of the economies of the European Union is a key policy issue. In particular, a substantial degree of convergence is needed if the European Central Bank is to be capable of setting a monetary policy which is appropriate to the stage of the cycle of the Euro zone economies. We consider the annual rates of real GDP growth on a quarterly basis in the large core economies of the EU (France, Germany and Italy, plus the Netherlands) over the period 1978Q1 - 2000Q3. An important empirical question is the degree to which the correlations between these growth rates contain true information rather than noise. The technique of random matrix theory is able to answer this question, and has been recently applied successfully in the physics journals to financial markets data. We find that the correlations between the growth rates of the core EU economies contain substantial amounts of true information, and exhibit considerable stability over time. Even in the late 1970s and early 1980s, these economies moved together closely over the course of the business cycle. There was a slight loosening at the time of German re-unification, but the economies are now, if anything, even more closely correlated. In contrast, the results obtained with a data set of the EU core plus the UK show no such trend. In the late 1970s and early 1980s, the UK economy did exhibit some degree of correlation with those of the core EU. However, there is no clear evidence to suggest that the UK business cycle has moved more closely into line with that of the core EU economies over the 1978-2000 period.Comment: 22 page