ACEEE (2013) 2013 State Energy Efficiency Scorecard, American Council for an Energy-Efficient Economy, Washington, DC, USA. http://www.aceee.org/files/pdf/summary/e13k-summary.pdf.
Aigner, D. J., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21–37.
Ang, B. W. (2006). Monitoring changes in economy-wide energy efficiency: from energy–GDP ratio to composite efficiency index. Energy Policy, 34, 574–582.
Battese, G. E., & Coelli, T. (1992). Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. Journal of Productivity Analysis, 3, 153–169.
Belzer, D. B. (2014) A comprehensive system of energy intensity indicators for the U.S.: methods, data and key trends. US Department of Energy, PNNL-22267. Available at http://www.pnnl.gov/main/publications/external/technical_reports/PNNL-22267.pdf.
Bossanyi, E. (1979). UK primary energy consumption and the changing structure of final demand. Energy Policy, 7, 253–258.
Boyd, G. A. (2008). Estimating plant level manufacturing energy efficiency with stochastic frontier regression. The Energy Journal, 29(2), 23–44.
Boyd, G. A., & Roop, J. M. (2004). A note on the Fisher ideal index decomposition for structural change in energy intensity. The Energy Journal, 25(1), 87–101.
Buck, J., & Young, D. (2007). The potential for energy efficiency gains in the Canadian commercial building sector: a stochastic frontier study. Energy The International Journal, 32, 1769–1780.
Colombi, R., Kumbhakar, S. C., Martini, G., & Vittadini, G. (2014). Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency. Journal of Productivity Analysis, 42, 123–136.
EC (2000) Action plan to improve energy efficiency in the European community, COM 247 final. Brussels, 26.04.2000.
EPRI (2009) Assessment of achievable potential from energy efficiency and demand response programs in the U.S., Electric Power Research Institute, California, USA. Available at http://www.epri.com/abstracts/pages/productabstract.aspx?ProductID=000000000001016987.
Farrell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, General, 120, 253–281.
Farsi, M. & Filippini, M. (2009) Efficiency measurement in the electricity and gas distribution sectors, Chapter 25 in J. Evans and L. C. Hunt (eds) International handbook on the economics of energy, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, 598–623.
Farsi, M., Filippini, M., & Greene, W. (2005). Efficiency measurement in network industries: application to the Swiss railway companies. Journal of Regulatory Economics, 28, 69–90.
Filippini, M. & Greene, W. (2015) Persistent and transient productive inefficiency: a maximum simulated likelihood approach. Journal of Productivity Analysis (forthcoming).
Filippini, M., & Hunt, L. C. (2011). Energy demand and energy efficiency in the OECD countries: a stochastic demand frontier approach. The Energy Journal, 32(2), 59–80.
Filippini, M., & Hunt, L. C. (2012). US residential energy demand and energy efficiency: a stochastic demand frontier approach. Energy Economics, 34, 1484–1491.
Filippini M. & Hunt, L. C. (2015) Measurement of energy efficiency based on economic foundations. Energy Economics (forthcoming).
Greene, W. H. (2005a). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126, 269–303.
Greene, W. H. (2005b). Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis, 23, 7–32.
Greene, W. H. (2008) The econometric approach to efficiency analysis, Chapter 2 in The measurement of productive efficiency and productivity growth, H. O. Fried, C. A. K. Lovell, and S. S. Schmidt, (eds.). Oxford University Press, 92–250.
Horowitz, M. J. (2007). Changes in electricity demand in the United States from the 1970s to 2003. The Energy Journal, 28(3), 93–119.
Hunt, L. C., Judge, G., & Ninomiya, Y. (2003a). Underlying trends and seasonality in UK energy demand: a sectoral analysis. Energy Economics, 25, 93–118.
Hunt, L. C., Judge, G. & Ninomiya, Y. (2003b) Modelling underlying energy demand trends, Chapter 9 in. Hunt, L. C. (ed.), Energy in a competitive market: essays in honour of Colin Robinson, Edward Elgar, Cheltenham, UK and Northampton, MA, USA, 140–174.
Huntington, H. G. (1994). Been top down so long it looks like bottom up to me. Energy Policy, 22, 833–838.
IEA (2009) Progress with implementing energy efficiency policies in the G8. International Energy Agency, Paris, France. Available at: www.iea.org/publications/freepublications/publication/G8Energyefficiencyprogressreport.pdf.
Jimenez, R., & Mercado, J. (2014). Energy intensity: a decomposition and counterfactual exercise for Latin American countries. Energy Economics, 42, 161–171.
Jondrow, J., Lovell, C. A. K., Materov, I. S., & Schmidt, P. (1982). On the estimation of technical efficiency in the stochastic frontier production function model. Journal of Econometrics, 19, 233–238.
Kopp, R. J. (1981). The measurement of productive efficiency: a reconsideration. The Quarterly Journal of Economics, 96, 477–503.
Kumbhakar, S. C., & Lovell, C. A. K. (2000). Stochastic frontier analysis. Cambridge: Cambridge University Press.
Lin, B., & Du, K. (2013). Technology gap and China’s regional energy efficiency: a parametric metafrontier approach. Energy Economics, 40, 529–536.
McKinsey (2009) Unlocking energy efficiency in the U.S. economy. McKinsey & Company, Inc. Available at www.mckinsey.com/client_service/electric_power_and_natural_gas/latest_thinking/unlocking_energy_efficiency_in_the_us_economy.
Metcalf, G. E. (2008). An empirical analysis of energy intensity and its determinants at the state level. The Energy Journal, 29(3), 1–26.
Mundlak, Y. (1978). On the pooling of time series and cross-section data. Econometrica, 46, 69–85.
Myers, J. G., & Nakamura, L. (1978). Saving energy in manufacturing. Cambridge, MA: Ballinger.
Pitt, M., & Lee, L. (1981). The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9, 43–64.
Schmidt, P., & Sickles, R. E. (1984). Production frontiers and panel data. Journal of Business and Economic Statistics, 2, 367–374.
Sudarshan, A. (2013). Deconstructing the Rosenfeld curve: making sense of California’s low electricity intensity. Energy Economics, 39, 197–207.
Tsionas, E. G., & Kumbhakar, S. C. (2014). Firm heterogeneity, persistent and transient technical inefficiency: a generalized true random effects model. Journal of Applied Econometrics, 29, 110–132.
Zhou, P., & Ang, B. W. (2008). Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy, 36, 2911–2916.