This paper deals with the existence and identification of a common European growth cycle. Univariate Markov switching autoregressions are used for individual countries in order to detect changes in the mean growth rate of industrial production. A Markov switching vector autoregression model is then used to identify a common cycle in Europe. Three important results are obtained: we find a common unobserved component governing European business cycle dynamics, suggesting the existence of a common business cycle; we propose a dating of the business cycle, both for an index of industrial protection and GDP, and both chronologies appear to be consistent; and finally we retrieve an important set of stylized facts and relate these with those reported for the US. Finally two further issues are investigated: first, the contribution of the European business cycle to the individual country cycles; and second, we undertake an impulse response analysis to investigate the response of each individual country to European expansions and recessions. sectors the relative importance of country-specific disturbances has declined in the 1980s. Norrbin and Schlaenhauf (1996) 3 extend this analysis to a dynamic setup 4 and analyze the behavior across countries and industries in terms of industry-specific factors, nation-specific factors and the common factor. The set of countries comprises nine industrial economies and the sample extends from 1956:1 to 1992:4. Their analysis suggests that, in this period, the nation-specific factor is the most relevant in explaining the variation of output. Another area of debate has been the extent to which the cyclical component of some measures of economic activity comoves across countries in the Union. An indication of a development of this type can be found in the cyclical crosscorrelation analysis offered by Artis and Zhang (1997) and Artis and Zhang (1999), who examine whether the correlation between the business cycles in ERM countries and the cycle in Germany has increased since the formation of the ERM. Their results show that the cycles in the ERM countries became more synchronized with the German one, suggesting the emergence of a European business cycle. Christodoulakis et al. (1995) focus on the 12 EU countries (as of 1994). They analyze the time series of a set of key macroeconomic variables since the 1960s and find no evidence of a core-periphery distinction. In their study they find that business cycles are similar for the variables they call endogenous (such as income and consumption), whereas this is not the case for those variables they refer to as exogenous (i.e., variables controlled by the government such as government spending or variables dependent on national institutions, such as labour market variables). Contrary to the results in Artis and Zhang (1997) and Artis and Zhang (1999), Dickerson et al. (1998) find no evidence that the business cycles in the EU 12 have become more correspondent after the formation of the ERM. They use data from 1960 to 1993 on GDP, private final co...

We analyze the time-series of prices in the Spanish electricity market by means of a time varyingtransition-probability Markov-switching model. Accounting for changes in demand and cost conditions (which reflect changes in input costs, capacity availability and hydro power), we show that the time-series of prices is characterized by two significantly different price levels. Using a Cournot model among contracted firms, we characterize firms' optimal deviations from a collusive agreement, and identify trigger variables that could be used to discourage deviations. By interpreting the effects of the triggers in affecting the likelihood of starting a price war, we are able to infer some of the properties of the collusive strategy that firms might have followed.JEL classification: C22; L13; L94

This paper intends to harmonize two different approaches employed in the analysis of business cycles and, in doing so, it retrieves the stylized facts of the business cycle in Europe. We start with the ‘classical’ approach proposed in Burns and Mitchell (1946) of dating and analyzing the business cycle. The stylized facts retrieved are commented and compared to those obtained by Harding and Pagan (2002) for the U.S.. Two conclusions can be extracted from the results: a) though the turning points obtained for individual countries seem to cluster and would suggest the idea of a common cycle, there are relevant differences in the stylized facts characterizing the business cycle in the individual European economies under analysis; b) moreover, we find relevant differences in the business cycle stylized facts of the European countries and the U.S., mostly in terms of the duration, the amplitude of the cycle and the shape of the recovery. We then adopt the ‘modern’ alternative: the Markov-switching vector autoregression (MS-VAR). The model’s regime probabilities provide an optimal statistical inference of the turning point of the European business cycle. For assessing the capacity of the parametric approach to generate the stylized facts of the classical cycle in Europe, the stylized facts of the original data are compared to those of simulated data. Contrary to the results reported by Harding and Pagan (2002) , we show that the MS-VAR model is a good candidate to be used as an statistical instrument to improve the understanding of the business cycle. Copyright Springer-Verlag Berlin/Heidelberg 2004International business cycles, European Union, Markov switching, Structural breaks, Time series analysis,

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The Purchasing Power Parity (PPP) hypothesis is one of the most important theoretical relationships in international economics. However, its empirical support remains controversial. We propose an alternative way of modelling the real exchange rate in five industrialized countries in relation to the US dollar, by means of fractionally integrated ARIMA models (i.e. ARFIMA). This approach allows us to capture the low-frequency dynamics relevant for examination of the long-run parity. A crucial fact when estimating with parametric approaches is that the model must be correctly specified, otherwise the estimates are likely to be inconsistent. In fact, misspecification of the short-run components of the series can invalidate the estimation of its long-run behaviour. We propose a model selection criterion based on LR tests on nested parametric hypotheses along with other several likelihood-based criteria. As a validation method of the specified model, we suggest the use of Robinson's (1994) tests. Our empirical results indicate that the PPP might hold as a long-run proposition.