It is widely accepted that in liberalized electricity markets log-returns display fattailed densities. Besides qualitative assessments, so far precise characterizations of the shape of the distribution have been seldom provided. In this work, we characterize the conditional and unconditional probability density functions of daily electricity logreturns, and of the underlying shocks from the NordPool market, for each of the 24 hours, through a very flexible and general family of distributions, namely the Subbotin family.Our study contributes with novel results in the field. First, we show that price fluctuations in electricity markets are additive in nature. We do this by exploiting a scaling relationship between price level and volatility, which is in turn a new result in the electricity markets literature. Second, in line with recent studies, we uncover the existence of multiple regimes in price dynamics, and we characterize the distributional shape for each of them. Interestingly, the shocks behind electricity price dynamics are approximately Laplace if one conditions on low price levels, and closer to a Gaussian in correspondence of high initial price levels.These results are at variance with the evidence from financial markets. The peculiar non-storable nature of electricity, and the varying strength of correlations between bidding behaviors at different load levels are suggested as possible key factors behind the specificities of electricity markets outcomes.Keywords: Electricity Markets, Subbotin Distribution, Laplace Distribution, Additive Process, Scaling.JEL Classifications: C16, D4, L94. * Support by the Advanced School for Public Administration, Rome (project "Politiche per la regolazione dei servizi di pubblica utilita'. L'attuazione degli indirizzi dell'Unione Europea nella riforma del settore energetico italiano alla luce della specificita' nazionale"), by the Italian Ministry of Education, University and Research (project "Forme istituzionali ed organizzazione nella risoluzione dei problemi complessi" -COFIN 2002), and by S.Anna School of Advanced Studies (grant no. E6002 GB), is gratefully acknowledged. We are thankful to the NordPool ASA for making the data available, and to Giovanni Dosi. The usual disclaimer applies.

This paper follows a stream of literature on the empirics of sectoral growth rates, originated by Castaldi and Dosi (Income levels and income growth. Some new cross-country evidence and some interpretative puzzles. Our aim is to discuss the statistical properties of growth rates in light of a 'mushroom vision' of growth. In our analysis, we focus on the growth of value added in NACE five-digit sectors in France, Germany, Italy and the United Kingdom between 1995 and 2003. We find that the volatility of sectoral growth rates is negatively correlated with sectoral size, according to a power law, but with steeper slopes than for firms and We wish to thank Giovanni Dosi, Angelo Secchi, Edwin Stuivenwold and Grid Thoma for helpful discussions, and participants of the 11 th International Schumpeter Society Conference in Sophia Antipolis (France) for useful comments. The paper was improved thanks to comments by the editor, Uwe Cantner, and by an anonymous referee. We kindly acknowledge support from the EU funded project DIME. Sandro Sapio also acknowledges support from the EU funded project CO3. All errors remain our own. U.S. sectors. Rescaled sectoral growth rates are well-described by a Laplace distribution in most years. The outcomes of this statistical analysis provide a further empirical foundation to a view of sectoral growth, wherein interfirm correlations, market concentration, and inter-sectoral feedbacks play a major role.

This paper contributes to the characterization of the probability density of the price returns in some European day-ahead electricity markets (NordPool, APX, Powernext) by fitting flexible and general families of distributions, such as the α-stable, Normal Inverse Gaussian (NIG), Exponential Power (EP), and Asymmetric Exponential Power (AEP) distributions, and comparing their goodness of fit. The α-stable and the NIG systematically outperform the EP and AEP models, but the tail behavior and the skewness are sensitive to the definition of the returns and to the deseasonalization methods. In particular, the logarithmic transform and volatility rescaling tend to dampen the extreme returns