On the causality between energy efficiency and technological innovations: limitations and implications

References

• Ajayi, V., and D. Reiner. 2018. European industrial energy intensity: The role of innovation 1995–2009, Cambridge University Working Papers in Economics, no. 1835. Cambridge, UK. doi:10.17863/CAM.24683.
   Google Scholar
• Aydin, E., N. Kok, and D. Brounen. 2017. Energy efficiency and household behavior: The rebound effect in the residential sector. The Rand Journal of Economics 48 (3):749–82. doi:10.1111/rand.2017.48.issue-3.
   Web of Science ®Google Scholar
• Bahmani-Oskooee, M., T. Chang, and T. Wu. 2014. Revisiting purchasing power parity in African countries: Panel stationary test with sharp and smooth breaks. Applied Financial Economics 24:1429–38. doi:10.1080/09603107.2014.925068.
   Google Scholar
• Belke, A., F. Dobnik, and C. Dreger. 2011. Energy consumption and economic growth: New insights into the cointegration relationship. Energy Economics 33:782–89. doi:10.1016/j.eneco.2011.02.005.
   Web of Science ®Google Scholar
• Breusch, T. S., and A. R. Pagan. 1980. The Lagrange multiplier test and its applications to model specification in econometrics. Review of Economic Studies 47 (1):239–53. doi:10.2307/2297111.
   Web of Science ®Google Scholar
• Chitnis, M., S. Sorrell, A. Druckman, S. K. Firth, and T. Jackson. 2013. Turning lights into flights: Estimating direct and indirect rebound effects for UK households. Energy Policy 55:234–50. doi:10.1016/j.enpol.2012.12.008.
   Web of Science ®Google Scholar
• Chitnis, M., S. Sorrell, A. Druckman, S. K. Firth, and T. Jackson. 2014. Who rebounds most? Estimating direct and indirect rebound effects for different UK socioeconomic groups. Ecological Economics 106:12–32. doi:10.1016/j.ecolecon.2014.07.003.
   Web of Science ®Google Scholar
• Deichmann, U., and F. Zhang. 2013. Growing green: The economic benefits of climate action. Washington, DC: World Bank Publication.
   Google Scholar
• Druckman, A., M. Chitnis, S. Sorrell, and T. Jackson. 2011. Missing carbon reductions? Exploring rebound and backfire effects in UK households. Energy Policy 39 (6):3572–81. doi:10.1016/j.enpol.2011.03.058.
   Web of Science ®Google Scholar
• Frondel, M., and C. Vance. 2013. Re-identifying the rebound: What about asymmetry? Energy Journal 34 (4):43–54.
   Web of Science ®Google Scholar
• Gillingham, K., D. Rapson, and G. Wagner. 2016. The rebound effect and energy efficiency policy. Review of Environmental Economics and Policy 10 (1):68–88. doi:10.1093/reep/rev017.
   Web of Science ®Google Scholar
• Griliches, Z. 1990. Patent statistics as economic indicators: A survey. Journal of Economic Literature 28 (4):1661–707.
   Web of Science ®Google Scholar
• Hediger, C., M. Farsi, and S. Weber. 2016. The direct and indirect rebound effects for residential heating in Switzerland. Working paper no.16–11 University of Neuchatel Institute of Economic Research IRENE, Neuchatel, Switzerland.
   Google Scholar
• Herring, H. 2005. Energy efficiency: A critical view? Energy 32 (1):10–20.
   Google Scholar
• Herring, H., and R. Roy. 2007. Technological innovation, energy efficient design and the rebound effect. Technovation 27 (4):194–203. doi:10.1016/j.technovation.2006.11.004.
   Web of Science ®Google Scholar
• Horowitz, J. 2001. The bootstrap. in handbook of econometrics, ed.Z. Griliches and M. D. Intriligator, Chap. 52, Vol. 5, 3159–228. Elsevier
   Google Scholar
• Igami, M., and J. Subrahmanyam. 2015. Patent statistics as an innovation indicator? Evidence from the hard disk drive industry. https://ssrn.com/abstract=2263318.
   Google Scholar
• Karimu, A., R. Brännlund, T. Lundgren, and P. Söderholm. 2017. Energy intensity and convergence in Swedish industry: A combined econometric and decomposition analysis. Energy Economics 62:347–56. doi:10.1016/j.eneco.2016.07.017.
   Web of Science ®Google Scholar
• Kónya, L. 2006. Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling 23:978–92. doi:10.1016/j.econmod.2006.04.008.
   Web of Science ®Google Scholar
• Lanjouw, J. O., and A. Mody. 1996. Innovation and the international diffusion of environmentally responsive technology. Research Policy 25:549–71. doi:10.1016/0048-7333(95)00853-5.
   Web of Science ®Google Scholar
• Lee, C., and J. Lee. 2010. A panel data analysis of the demand for total energy and electricity in OECD countries. Energy Journal 31:1–23. doi:10.5547/ISSN0195-6574-EJ-Vol31-No1-1.
   Web of Science ®Google Scholar
• Metcalf, G. E. 2008. An empirical analysis of energy intensity and its determinants at the state level. The Energy Journal 29 (3):1–26. doi:10.5547/ISSN0195-6574-EJ.
   Web of Science ®Google Scholar
• Parker, S., and B. Liddle. 2016. Energy efficiency in the manufacturing sector of the OECD: Analysis of price elasticities. Energy Economics 58:38–45. doi:10.1016/j.eneco.2016.06.003.
   Web of Science ®Google Scholar
• Pesaran, M. H. 2004. General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics No. 0435, Faculty of Economics, University of Cambridge, Cambridge, UK.
   Google Scholar
• Pesaran, M. H., A. Ullah, and T. Yamagata. 2008. A bias-adjusted LM test of error cross- section independence. Econometrics Journal 11:105–27. doi:10.1111/j.1368-423X.2007.00227.x.
   Web of Science ®Google Scholar
• Pesaran, M. H., and T. Yamagata. 2008. Testing slope homogeneity in large panels. Journal of Econometrics 142:50–93. doi:10.1016/j.jeconom.2007.05.010.
   Web of Science ®Google Scholar
• Peters, B., and S. F. McWhinnie. 2018. On the rebound: Estimating direct rebound effects for Australian households. The Australian Journal of Agricultural and Resource Economics 62 (1):65–82. doi:10.1111/ajar.2018.62.issue-1.
   Web of Science ®Google Scholar
• Rajbhandari, A., and F. Zhang 2018. Does energy efficiency promotes economic growth? Evidence from a multicountry and multisectoral panel dataset. Energy Economics 69(C): 128-139. DOI: 10.1016/J.eneco. 2017.11.007.
   Google Scholar
• Sorrell, S., and J. Dimitropoulos. 2008. The rebound effect: Microeconomic definitions, limitations and extensions. Ecological Economics 65 (3):636–49. doi:10.1016/j.ecolecon.2007.08.013.
   Web of Science ®Google Scholar
• Swamy, P. A. V. B. 1970. Efficient inferences in a random coefficient regression model. Econometrica 38:311–23. doi:10.2307/1913012.
   Web of Science ®Google Scholar
• Toda, H. Y., and P. C. B. Phillips. 1993. Vector autoregression and causality. Econometrica 61:1367–93. doi:10.2307/2951647.
   Web of Science ®Google Scholar
• Toda, Y. H., and T. Yamamoto. 1995. Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics 66:225–50. doi:10.1016/0304-4076(94)01616-8.
   Web of Science ®Google Scholar
• Tsong, C. C., and C. F. Lee. 2011. Asymmetric inflation dynamics evidence from quantile regression analysis. Journal of Macroeconomics 33:668–80. doi:10.1016/j.jmacro.2011.08.003.
   Web of Science ®Google Scholar
• Voigt, S., E. De Cian, M. Schymura, and E. Verdolini. 2014. Energy intensity developments in 40 major economies: Structural change or technology improvement? Energy Economics 41:47–62. doi:10.1016/j.eneco.2013.10.015.
   Web of Science ®Google Scholar
• Welsch, H., and C. Ochsen. 2005. The determinants of aggregate energy use in West Germany: Factor substitution, technological change, and trade. Energy Economics 27 (1):93–111. doi:10.1016/j.eneco.2004.11.004.
   Web of Science ®Google Scholar
• Wurlod, J.-D., and J. Noailly. 2018. The impact of green innovation on energy intensity: An empirical analysis for 14 industrial sectors in OECD countries. Energy Economics 71:47–61. doi:10.1016/j.eneco.2017.12.012.
   Web of Science ®Google Scholar
• Yamada, H., and Y. H. Toda. 1998. Inference in possibly integrated vector auto-regressive models: Some finite evidence. Journal of Econometrics 86:55–95. doi:10.1016/S0304-4076(97)00109-7.
   Web of Science ®Google Scholar