1,721,073 research outputs found
Wage gaps and gender discrimination in the private and public sectors: the case of Italian graduate young workers
Full text linkThe issues of gender discrimination and segregation in the Italian labour market are analyzed in this paper, with a view to understanding whether the public sector is able to mitigate discriminatory outcomes. Based on the analysis of a sample of graduate workers observed 5 years after their degree, provided by the AlmaLaurea consortium, we find: (i) network-based job search channels are more intensely used by women and in the private sector, even when controlling for public examinations; (ii) vertical segregation in similar across sectors; (iii) women employed in the public sector are characterized by higher job satisfaction; (iv) in an Oaxaca-Blinder decomposition of wage differ- entials across genders, the share attributable to discrimination in the public sector is lower
Modeling the distribution of day-ahead electricity returns: a comparison
No full textThis 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
The effects of renewables in space and time: A regime switching model of the Italian power price
No full textRenewable energy production can exercise a downward pressure on electricity prices by partly crowding out conventional units characterized by higher marginal costs (merit order effect). Yet, congestion induced by renewables would partly offset the merit order effect in the congested zone, unless renewables reduce the need for imports and allow the emergence of prosumers. These congestion effects of renewables are hereby jointly tested with the merit order effect by means of an endogenous regime-switching model wherein a regime corresponds to the observable status (congested/non-congested) of the grid. The model is taken to data from the Italian power exchange, observed in 2012 and 2013, with a focus on the line connecting Sicily with the South zone, a frequent bottleneck in the Italian transmission grid. The results confirm the merit order effect previously detected in the literature and highlight a negative congestion effect, i.e. renewables relieve congestion from Sicily, a systematic importer, but not from the Italian peninsula (the exporting region). This effect is mainly driven by the wind power in-feed
Comments on the paper "Environmental taxes, inequality, and technical change" by F. Patriarca and F. Vona
No full textGreener, more integrated, and less volatile? A quantile regression analysis of Italian wholesale electricity prices
No full textComparison and empirical validation of optimizing and agent-based models of the Italian electricity market
No full textIn recent years, several oligopolistic models of the liberalized power exchanges have been proposed, within two paradigms based upon radically different assumptions on rationality, learning and cognition: optimal choice and agent-based computational modeling. This paper is a first attempt to compare the explanatory performances of an agent-based model with a supply function equilibrium model on the same dataset. The models are designed in such a way that differences in performance between them are mainly due to their different behavioral assumptions, and are validated on a unique plant-level dataset on the Italian power exchange. As suggested by our findings, the agent-based model is better able to capture the intraday profile of power prices, but both models tend to overestimate the degree of competition among generating companies
Markets Design, Bidding Rules, and Long Memory in Electricity Prices
No full text[fre] Pour les enchères sous plis scellés et prix uniformes sur les marchés day ahead de l'électricité, le prix de marché est déterminé à l'intersection des fonctions d'offre et de demande agrégées construites par un opérateur de marché. Chaque jour, un seul agent (le générateur marginal) détient l'usine qui permet de solder le marché. De plus, les enchères day ahead sont intégrées dans des systèmes multi segments, dans lesquels divers protocoles coexistent et changent dans le temps. Cet environnement complexe conduit à l'adoption de règles d'enchères simples et adaptatives. Plus précisément, une telle configuration de marché autorise l'émergence de deux types différents de routines, selon que l'agent est un générateur marginal ou infra marginal. Cependant, du fait du mécanisme de prix uniforme, seul le comportement d'enchère du premier peut être reflété dans les prix de marchés. En fonction de la manière spécifique dont les générateurs marginaux traitent l'information passée pour déterminer leurs enchères (« hyperbolique » ou « exponentielle ») les prix de l'électricité sont susceptibles d'exhiber des effets de mémoire longue ou courte. En utilisant une analogie avec l'actualisation hyperbolique (un biais de comportement humain robuste) une conception en mémoire longue du prix de l'électricité est proposée. Cette intuition est confirmée par une analyse spectrale des données journalières issues des marchés NordPool et CalPX, en opposition forte avec de nombreuses études empiriques précédentes. Cet article souligne l'importance des accords institutionnels pour déterminer les relations entre les comportements individuels et les résultats du marché. Il propose une cartographie intéressante des règles d'enchères et des modèles de traitement de l'information selon les propriétés des séries temporelles des prix de marché. [eng] In uniform price, sealed-bid, day-ahead electricity auctions, the market price is set at the intersection between aggregate demand and supply functions constructed by a market operator. Each day, just one agent - the marginal generator - owns the market-clearing plant. Moreover, day-ahead auctions are embedded in multi-segment systems, wherein diverse protocols coexist and change over time. This complex environment leads to adoption of simple, adaptive bidding rules. Specifically, such a market design enables the emergence of two different types of routines, depending on whether the agent is a likely marginal or inframarginal generator. However, because of the uniform price mechanism, only the bidding behavior of the former can be reflected into market prices. Depending on the specific way marginal generators process past information to set their bids - « hyperbolic » or « exponential » - electricity prices are likely to display long- or short-memory. Using an analogy with the hyperbolic discounting - a quite robust behavioral bias in humans - a long-memory view of electricity prices is proposed. This insight is confirmed by spectral analysis of daily data from NordPool and CaIPX markets, in sharp contrast with most previous empirical studies. This paper underlines the importance of institutional settings in determining the relationship between individual behavior and market outcomes, and proposes an interesting mapping of bidding rules and models of information processing into the time series properties of market prices.
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