Stochastic Frontier Models for Long Panel Data Sets: Measurement of the Underlying Energy Efficiency for the OECD Countries

Massimo Filippini and Elisa Tosetti

No 14/198, CER-ETH Economics working paper series from CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich

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.

Keywords: Energy demand; panels; common factors; principal components. (search for similar items in EconPapers)
JEL-codes: C10 C31 C33 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2014-06
New Economics Papers: this item is included in nep-ecm, nep-eff, nep-ene and nep-ore
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