Aigner, D. J., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Economics, 6, 21–37.
Battese, G.E., & Coelli, T.J. (1992). Frontier production functions, technical efficiency, and panel data: with application to Paddy farmers in India. Journal of Productivity Analysis, 3, 153–169.
Bi, G., Song, W., Zhou, P., & Liang, L. (2014). Does environmental regulation affect energy efficiency in China’s thermal power generation? Empirical evidence from a slacks-based DEA model. Energy Policy, 66, 527–546.
Butler, J., & Moffitt, R. (1982). A computationally efficient quadrature procedure for the one factor multinomial probit model. Econometrica, 50, 761–764.
Chen, G. Q., & Chen, Z. M. (2010). Carbon emissions and resources use by Chinese economy 2007: a 135-sector inventory and input–output embodiment. Communications in Nonlinear Science and Numerical Simulation, 15(11), 3647–3732.
Chen, Z. M., & Chen, G. Q. (2011). An overview of energy consumption of the globalized world economy. Energy Policy, 39(10), 5920–5928.
Chen, Z. M., Chen, G. Q., Zhou, J. B., Jiang, M. M., & Chen, B. (2010). Ecological input–output modeling for embodied resources and emissions in Chinese economy 2005. Communications in Nonlinear Science and Numerical Simulation, 15(7), 1942–1965.
Colombi, R., Kumbhakar, S., Martini, G., & Vittadini, G. (2014). Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency. Journal of Productivity Analysis. DOI 10.1007/s11123-014-0386-y
EIA (2013). International Energy Outlook 2013. U.S. Energy Information Administration.
Farsi, M., & Filippini, M. (2009). Efficiency measurement in the electricity and gas distribution sectors. In J. Evans & L. C. Hunt (Eds.), International handbook on the economics of energy (pp. 598–623). Cheltenham: Edward Elgar.
Farsi, M., Filippini, M., & Greene, W. (2005a). Efficiency measurement in network industries: application to the Swiss railway companies. Journal of Regulatory Economics, 28, 69–90.
Farsi, M., Filippini, M., & Kuenzle, M. (2005b). Unobserved heterogeneity in stochastic frontier models: an application to Swiss nursing homes. Applied Economics, 37, 2127–2141.
Filippini, M. and Greene, W. (2015): Persistent and transient productive inefficiency: a maximum simulated likelihood approach. Journal of Productivity Analysis, forthcoming.
Filippini, M., & Hunt, L. (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. (2012). US residential energy demand and energy efficiency: a stochastic demand frontier approach. Energy Economics, 34, 1484–1491.
Filippini, M. and Hunt, L. (2013). ‘Underlying energy efficiency’ in the US. CER-ETH Economics Working Paper Series 13/181.
Filippini, M. and Hunt, L. (2015 a). Measurement of energy efficiency based on economic foundations, Energy Economics (forthcoming).
Filippini, M. and Hunt, L. (2015 b). Measuring persistent and transient energy efficiency in the US, Energy Efficiency, (forthcoming).
Filippini, M., Hunt, L., & Zoric, J. (2014). Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector. Energy Policy, 69, 73–81.
Fisher-Vanden, K., Jefferson, G., Liu, H., & Tao, Q. (2004). What is driving China’s decline in energy intensity? Resource and Energy Economics, 26, 77–97.
Greene, W. (2005a). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Economics, 126, 269–303.
Greene, W. (2005b). Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis, 23, 7–32.
Greene, W. (2008). The econometric approach to efficiency analysis. Chapter 2. In H. O. Fried, C. A. K. Lovell, & S. S. Schmidt (Eds.), The measurement of productive efficiency and productivity growth (pp. 92–250). Oxford: University Press.
Greene, W. (2011). Econometric analysis (7th ed.). Upper Saddle River: Prentice-Hall.
Hang, L., & Tu, M. (2007). The impacts of energy prices on energy intensity: evidence from China. Energy Policy, 35, 2978–2988.
Hu, J., & Wang, S. (2006). Total-factor energy efficiency of regions in China. Energy Policy, 34, 3206–3217.
Hu, J., & Wang, S. (2010). Total-factor energy productivity growth, technical progress, and efficiency change: an empirical study of China. Applied Energy, 87, 3262–3270.
IEA (2009). Progress with implementing energy efficiency policies in the G8', International Energy Agency Paper. www.iea.org/publications/free_new_Desc.asp?PUBS_ID=2127
Jaunky, V. C. and Zhang, L. (2016). Convergence of operational efficiency in China’s provincial power sectors. The Energy Journal, forthcoming.
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 Economics, 19, 233–238.
Kumbhakar, S.C. and Lovell, C.A. (2000): Stochastic frontier analysis, Cambridge: Cambridge University Press.
Kumbhahkar, S. C., Lien, G., & Hardaker, J. B. (2014). Technical efficiency in competing panel data models: a study of Norwegian grain farming. Journal of Productivity Analysis, 41, 321–337.
Liao, H., Fan, Y., & Wei, Y. (2007). What induced China’s energy intensity to fluctuate: 1997–2006? Energy Policy, 35, 4640–4649.
Lundgren, T., Marklund, P., and Zhang, S. (2016). Industrial energy demand and energy efficiency—evidence from Sweden. Resource and Energy Economics, forthcoming. doi:10.1016/j.reseneeco.2016.01.003
Ma, C., & Stern, D. (2008). China’s changing energy intensity trend: a decomposition analysis. Energy Economics, 30, 1037–1053.
Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica, 64, 69–85.
Murillo-Zamorano, L. R. (2004). Economic efficiency and frontier techniques. Journal of Economic Surveys, 18(1), 33–77.
Mutter, R. L., Greene, W. H., Spector, W., Rosko, M. D., & Mukamel, D. B. (2013). Investigating the impact of endogeneity on inefficiency estimates in the application of stochastic frontier analysis to nursing homes. Journal of Productivity Analysis, 39, 101–110.
NBS, 2004–2013a, China Statistical Yearbooks. Beijing, China.
NBS, 2004–2013b, China urban life and price yearbook. Beijing, China.
Pitt, M., & Lee, L. (1981). The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9, 43–64.
Polachek, S. W., & Yoon, B. J. (1996). Panel estimates of a two-tiered earnings frontier. Journal of Applied Econometrics, 11(2), 169–78.
Price, L., Levine, M., Zhou, N., Fridley, D., Aden, N., Lu, H., McNeil, M., Zheng, N., Qin, Y., & Yowargana, P. (2011). Assessment of China’s energy-saving and emission-reduction accomplishments and opportunities during the 11th Five Year Plan. Energy Policy, 39(4), 2165–2168.
Song, F., & Zheng, X. (2012). What drives the change in China’s energy intensity: combining decomposition analysis and econometric analysis at the provincial level. Energy Policy, 51, 445–453.
Stock, J. and Yogo, M. (2003) Testing for weak instruments in linear IV regression, mimoe, Harvard University.
Terza, J. V., Basu, A., & Rathouz, P. J. (2008). Two-stage residual inclusion estimation: addressing endogeneity in health econometric modeling. Journal of Health Economics, 27(3), 531–543.
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(1), 110–132.
Wei, C., Ni, J., & Shen, M. (2009). Empirical analysis of provincial energy efficiency in China. China & World Economy, 17(5), 88–103.
Xia, X. H., Huang, G. T., Chen, G. Q., Zhang, B., Chen, Z. M., & Yang, Q. (2011). Energy security, efficiency and carbon emission of Chinese industry. Energy Policy, 39, 3520–3528.
Zhang, L. (2013). Model projections and policy reviews for energy saving in China’s service sector. Energy Policy, 59, 312–320.
Zhao, X., Yang, R., & Ma, Q. (2014). China’s total factor energy efficiency of provincial industrial sectors. Energy, 65, 52–61.
Zhou, P. & Anag, B.W. (2008). Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy, 36, 2911–2916.