Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171641
Authors: 
Filippini, Massimo
Tosetti, Elisa
Year of Publication: 
2014
Series/Report no.: 
Economics Working Paper Series 14/198
Abstract: 
In this paper we propose a general approach for estimating stochastic frontier mod- els, suitable when using long panel data sets. We measure efficiency as a linear combi- nation of a finite number of unobservable common factors, having coefficients that vary across firms, plus a time-invariant component. We adopt recently developed economet- ric techniques for large, cross sectionally correlated, non-stationary panel data models to estimate the frontier function. Given the long time span of the panel, we investigate whether the variables, including the unobservable common factors, are non-stationary, and, if so, whether they are cointegrated. To empirically illustrate our approach, we estimate a stochastic frontier model for energy demand, and compute the level of the “underlying energy efficiency” for 24 OECD countries over the period 1980 to 2008. In our specification, we control for variables such as Gross Domestic Product, energy price, climate and technological progress, that are known to impact on energy consumption. We also allow for hetero- geneity across countries in the impact of these factors on energy demand. Our panel unit root tests suggest that energy demand and its key determinants are integrated and that they exhibit a long-run relation. The estimation of efficiency scores points at European countries as the more efficient in consuming energy.
Subjects: 
Energy demand
panels
common factors
principal components
JEL: 
C10
C31
C33
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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