Sự hội tụ trong tiêu thụ năng lượng từ góc độ các nước đang phát triển: Trường hợp của Thổ Nhĩ Kỳ

Energy Efficiency - Tập 13 - Trang 1457-1472 - 2020
Etem Karakaya1, Sedat Alataş2, Burcu Yılmaz2
1Aydın, Turkey
2Department of Economics, Faculty of Economics and Administrative Sciences, Adnan Menderes University, Aydın, Turkey

Tóm tắt

Các nghiên cứu gần đây về sự hội tụ trong tiêu thụ năng lượng ở cấp ngành trong một quốc gia cho thấy, tiêu thụ năng lượng tổng hợp có thể che giấu những tác động khác biệt đáng kể mà có thể quan sát được ở cấp ngành. Nghiên cứu này nhằm đóng góp và bổ sung vào tài liệu hiện có về sự hội tụ với nỗ lực phân tích sự hội tụ theo ngành trong tiêu thụ năng lượng từ góc độ các nước đang phát triển. Để đạt được mục tiêu này, chúng tôi chọn Thổ Nhĩ Kỳ là một quốc gia đang phát triển và sử dụng cả hai thử nghiệm đơn vị gốc thông thường và phương pháp hồi quy bậc hai tăng cường các bình phương dư - Lagrange multiplier (RALS-LM) để nghiên cứu sự hội tụ ngẫu nhiên có điều kiện trong tiêu thụ năng lượng trên đầu người ở cấp ngành. Những phát hiện của chúng tôi cho thấy một số kết quả thú vị có thể liên quan đến tiêu thụ năng lượng theo ngành đối với các nước đang phát triển. Mặc dù tiêu thụ năng lượng ở Thổ Nhĩ Kỳ có xu hướng tăng lên, nhưng các ngành hàng đầu về tiêu thụ năng lượng của ngành công nghiệp và vận tải theo đầu người lại phân kỳ khỏi mức tiêu thụ trung bình và do đó dẫn đến việc tăng thêm trong tiêu thụ năng lượng và phát thải liên quan đến năng lượng. Hơn nữa, nông nghiệp và các ngành khác, với giá trị tiêu thụ trên đầu người dưới mức trung bình, đang hội tụ về mức trung bình. Tóm lại, xu hướng tiêu thụ năng lượng theo ngành của Thổ Nhĩ Kỳ theo các mô hình của các nước đang phát triển, và những phát hiện thực nghiệm cho thấy rằng xu hướng này rất đáng lo ngại từ góc độ bền vững.

Từ khóa

#hội tụ #tiêu thụ năng lượng #Thổ Nhĩ Kỳ #quốc gia đang phát triển #phát thải năng lượng

Tài liệu tham khảo

Abid, M., & Alimi, M. (2019). Stochastic convergence in US disaggregated gas consumption at the sector level. Journal of Natural Gas Science and Engineering, 61, 357–368. Abramovitz, M. (1986). Catching up, forging ahead, and falling behind. The Journal of Economic History, 46(2), 385–406. Acar, S., & Yeldan, A. E. (2018). Investigating patterns of carbon convergence in an uneven economy: The case of Turkey. Structural Change and Economic Dynamics., 46(C), 96–106. Acaravci, A., & Erdogan, S. (2016). The convergence behavior of CO2 emissions in seven regions under multiple structural breaks. International Journal of Energy Economics and Policy, 6(3), 575–580. Akram, V., Sahoo, P. K., & Jangam, B. P. (2019). Do shocks to electricity consumption revert to its equilibrium? Evidence from Indian states. Utilities Policy, 61, 1–16. Akram, V., Rath, B. N., & Sahoo, P. K. (2020). Stochastic conditional convergence in per capita energy consumption in India. Economic Analysis and Policy, 65, 224–240. Aldy, J. E. (2006). Per capita carbon dioxide emissions: convergence or divergence? Environmental and Resource Economics, 33(4), 533–555. Anoruo, E., & DiPietro, W. R. (2014). Convergence in per capita energy consumption among African countries: Evidence from sequential panel selection method. International Journal of Energy Economics and Policy, 4(4), 568. Apergis, N., & Christou, C. (2016). Energy productivity convergence: new evidence from club converging. Applied Economics Letters, 23(2), 142–145. Arltová, M., & Fedorová, D. (2016). Selection of unit root test on the basis of length of the time series and value of AR (1) parameter. Statistika, 96(3), 3. Baltagi, B. H. (2011). Econometrics (Fifth Edition). Springer. https://doi.org/10.1007/978-3-642-20059-5. Barassi, M. R., Cole, M. A., & Elliott, R. J. R. (2008). Stochastic divergence or convergence of per capita carbon dioxide emissions: Re-examining the evidence. Environmental and Resource Economics, 40, 121–137. Barassi, M. R., Cole, M. A., & Elliott, R. J. (2011). The stochastic convergence of CO2 emissions: A long memory approach. Environmental and Resource Economics, 49(3), 367–385. Barros, C. P., Gil-Alana, L. A., & Payne, J. E. (2012). Evidence of long memory behavior in US renewable energy consumption. Energy Policy, 41, 822–826. Baumol, W. J. (1986). Productivity growth, convergence, and welfare: What the long-run data show. The American Economic Review, 76(5), 1072–1085. van Benthem, A. A. (2015). Energy leapfrogging. J. Assoc. Environ. Resour. Econ., 2, 93–132. Berk, I., Kasman, A., & Kılınç, D. (2018). Towards a common renewable future: The system-GMM approach to assess the convergence in renewable energy consumption of EU countries. Energy Economics, 103922. Bond, S. R., Hoeffler, A., & Temple, J. R. (2001). GMM estimation of empirical growth models. Borozan, D. (2017). Testing for convergence in electricity consumption across Croatian regions at the consumer’s sectoral level. Energy Policy, 102, 145–153. Bulut, U., & Durusu-Ciftci, D. (2018). Revisiting energy intensity convergence: New evidence from OECD countries. Environmental Science and Pollution Research, 1–7. Carlino, G. A., & Mills, L. O. (1993). Are U.S. regional incomes converging?: A time series analysis. Journal of Monetary Economics, 32(2), 335–346. Carrion-i-Silvestre, J. L., & Sansó, A. (2007). The KPSS test with two structural breaks. Spanish Economic Review, 9(2), 105–127. Caselli, F., Esquivel, G., & Lefort, F. (1996). Reopenning the convergence debate: A new look at cross-country growth empirics. Journal of Economic Growth, 1(3), 363–389. Chen, P. F., & Lee, C. C. (2007). Is energy consumption per capita broken stationary? New evidence from regional-based panels. Energy Policy, 35(6), 3526–3540. Cheong, T. S., Li, V. J., & Shi, X. (2019). Regional disparity and convergence of electricity consumption in China: A distribution dynamics approach. China Economic Review., 58, 101154. Costantini, V., & Martini, C. (2010). The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data. Energy Economics, 32(3), 591–603. De Long, J. B. (1988). Productivity growth, convergence, and welfare: Comment. The American Economic Review, 78(5), 1138–1154. Deichmann, U., Reuter, A., Vollmer, S., & Zhang, F. (2018). Relationship between energy intensity and economic growth: Relationship between energy intensity and economic growth. In World Bank, Policy Research Working Paper, 8322. South Asia: Region. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431. Durlauf, S. N., & Johnson, P. A. (1995). Multiple regimes and cross-country growth behaviour. Journal of Applied Econometrics, 10(4), 365–384. Enders, W. (2014). Applied econometric time series (Fourth Edition). Wiley. isbn:978-1-118-80856-6. Evans, P. (1996). Using cross-country variances to evaluate growth theories. Journal of Economic Dynamics and Control, 20, 1027–1049. Fallahi, F. (2017). Stochastic convergence in per capita energy use in world. Energy Economics, 65, 228–239. Fallahi, F., & Voia, M. (2015). Convergence and persistence in per capita energy use among OECD countries: Revisited using confidence intervals. Energy Economics, 52, 246–253. Gujarati, D. N. (2004). Basic econometrics (Fourth Edition). The McGraw-Hill Companies. Herrerias, M. J., Aller, C., & Ordóñez, J. (2017). Residential energy consumption: A convergence analysis across Chinese regions. Energy Economics, 62, 371–381. Howarth, N., Galeotti, M., Lanza, A., & Dubey, K. (2017). Economic development and energy consumption in the GCC: An international sectoral analysis. Energy Transit, 1(6). https://doi.org/10.1007/s41825-017-0006-3. IEA (2017a). World Energy Outlook 2017. International Energy Agency, OECD/IEA, 2017. IEA. (2017b). Energy Efficiency 2017. OECD/IEA: International Energy Agency. Im, K. S., & Schmidt, P. (2008). More efficient estimation under non-normality when higher moments do not depend on the regressors, using residual augmented least squares. Journal of Econometrics, 144, 219–233. Im, K. S., Lee, J., & Tieslau, M. A. (2014). More powerful unit root tests with non-normal errors. In Festschrift in Honor of Peter Schmidt (pp. 315–342). New York: Springer New York. Islam, N. (1995). Growth empirics: A panel data approach. The Quarterly Journal of Economics, 110(4), 1127–1170. Islam, N. (2003). What have we learnt from the convergence debate? Journal of Economic Surveys, 17(3), 309–362. Ivanovski, K., Churchill, S. A., & Smyth, R. (2018). A club convergence analysis of per capita energy consumption across Australian regions and sectors. Energy Economics, 76, 519–531. Jakob, M., Haller, M., & Marschinski, R. (2012). Will history repeat itself? Economic convergence and convergence in energy use patterns. Energy Economics, 34(1), 95–104. Johnson, P. and Papageorgiou, C. (2018). What remains of cross-country convergence?. Chris Papageorgiou website. 28.06.2018, http://www.chrispapageorgiou.com/ papers/ convergence.pdf Karakaya, E., Alataş, S., & Yılmaz, B. (2019a). Replication of Strazicich and List (2003): Are CO2 emission levels converging among industrial countries? Energy Economics., 82, 135–138. Karakaya, E., Yılmaz, B., & Alataş, S. (2019b). How production based and consumption based emissions accounting systems change climate policy analysis: The case of CO2 convergence. Environmental Science and Pollution Research., 26(16), 16682–16694. https://doi.org/10.1007/s11356-019-05007-2. Karimu, A., Brännlund, R., Lundgren, T., & Söderholm, P. (2017). Energy intensity and convergence in Swedish industry: A combined econometric and decomposition analysis. Energy Economics, 62, 347–356. Kum, H. (2012). Are fluctuations in energy consumption transitory or permanent? Evidence from a panel of East Asia & Pacific countries. International Journal of Energy Economics and Policy, 2(3), 92–96. Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1–3), 159–178. Lean, H. H., & Smyth, R. (2014). Are shocks to disaggregated energy consumption in Malaysia permanent or temporary? Evidence from LM unit root tests with structural breaks. Renewable and Sustainable Energy Reviews, 31, 319–328. Lean, H. H., Mishra, V., & Smyth, R. (2016). Conditional convergence in US disaggregated petroleum consumption at the sector level. Applied Economics, 48(32), 3049–3061. Lee, J., & Strazicich, M. C. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. The Review of Economics and Statistics, 85(4), 1082–1089. Lee, J., Strazicich, M. C., & Meng, M. (2012). Two-step LM unit root tests with trend breaks. Journal of Statistical and Econometric Methods, 1, 81–107. Lescaroux, F. (2011). Dynamics of final sectoral energy demand and aggregate energy intensity. Energy Policy, 39(1), 66–82. Li, Q., & Papell, D. (1999). Convergence of international output time series evidence for 16 OECD countries. International Review of Economics and Finance, 8, 267–280. Lima, F., Nunes, M. L., Cunha, J., & Lucena, A. F. P. (2017). Driving forces for aggregate energy consumption: A cross-country approach. Renewable and Sustainable Energy Reviews, 68, 1033–1050, ISSN 1364-0321. https://doi.org/10.1016/j.rser.2016.08.009. Liu, W. C. (2013). The study on the stationarity of energy consumption in US states: Considering structural breaks, nonlinearity, and cross-sectional dependency, In Proceedings of World Academy of Science, Engineering and Technology (No. 80, p. 626). Engineering and Technology (WASET): World Academy of Science. Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. The Quarterly Journal of Economics, 107(2), 407–437. Markandya, A., Pedroso-Galinato, S., & Streimikiene, D. (2006). Energy intensity in transition economies: Is there convergence towards the EU average? Energy Economics, 28(1), 121–145. Masanjala, W. H., & Papageorgiou, C. (2004). The Solow model with CES technology: Nonlinearities and parameter heterogeneity. Journal of Applied Econometrics, 19, 171–201. Medlock, K. B., & Soligo, R. (2001). Economic development and end-use energy demand. Energy J., 22, 77–105. Meng, M., Payne, J. E., & Lee, J. (2013). Convergence in per capita energy use among OECD countries. Energy Economics, 36, 536–545. Meng, M., Im, K. S., Lee, J., & Tieslau, M. A. (2014). More powerful LM unit root tests with non-normal errors. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt (pp. 343–357). New York: Springer. MENR. (2018). Energy Balance Tables. Several Issues: Ministry of Energy and Resources of Turkey. Miketa, A., & Mulder, P. (2005). Energy productivity across developed and developing countries in 10 manufacturing sectors: patterns of growth and convergence. Energy Economics, 27(3), 429–453. Mishra, V., & Smyth, R. (2014). Convergence in energy consumption per capita among ASEAN countries. Energy Policy, 73, 180–185. Mishra, V., & Smyth, R. (2017). Conditional convergence in Australia’s energy consumption at the sector level. Energy Economics, 62, 396–403. Mulder, P., & de Groot, H. L. (2007). Sectoral energy-and labour-productivity convergence. Environmental and Resource Economics, 36(1), 85–112. de Oliveira, G., & Bourscheidt, D. M. (2017). Multi-sectorial convergence in greenhouse gas emissions. Journal of Environmental Management, 196, 402–410. Ozcan, B. (2013). Are shocks to energy consumption permanent or temporary? The case of 17 middle east countries. Energy Exploration & Exploitation, 31(4), 589–605. Pan, L. and Maslyuk-Escobedo, S. (2017). Stochastic convergence in per capita energy consumption and its catch-up rate: Evidence from 26 African countries. Monash University Department of Economics ISSN number 1441-5429 Discussion number 16/17. Panopoulou, E., & Pantelidis, T. (2009). Club convergence in carbon dioxide emissions. Environmental and Resource Economics, 44(1), 47–70. Papageorgiou, C. (2002). Trade as a threshold variable for multiple regimes. Economics Letters, 77, 85–91. Payne, J. E., Vizek, M., & Lee, J. (2017a). Is there convergence in per capita renewable energy consumption across US states? Evidence from LM and RALS-LM unit root tests with breaks. Renewable & Sustainable Energy Reviews, 70, 715–728. Payne, J. E., Vizek, M., & Lee, J. (2017b). Stochastic convergence in per capita fossil fuel consumption in US states. Energy economics, 62, 382–395. Pettersson, F., Maddison, D., Acar, S., & Söderholm, P. (2014). Convergence of carbon dioxide emissions: A review of the literature. International Review of Environmental and Resource Economics, 7, 141–178. Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regressions. Biometrika, 75(2), 335–346. Sala-i Martin, X. X. (1996). The classical approach to convergence analysis. The Economic Journal, 106(437), 1019–1036. Schmidt, P., & Phillips, P. (1992). LM tests for a unit root in the presence of deterministic trends. Oxford Bulletin of Economics and Statistics, 54, 257–287. Shi, X., Yu, J., & Cheong, T. S. (2020). Convergence and distribution dynamics of energy consumption among China’s households. Energy Policy, 142, 111496. Smyth, R., & Narayan, P. K. (2015). Applied econometrics and implications for energy economics research. Energy Economics, 50, 351–358. Solow, R. M. (1956). A contribution to the theory of economic growth. The Quarterly Journal of Economics, 70(1), 65–94. Strazicich, M. C., & List, J. A. (2003). Are Co2 emission levels converging among industrial countries? Environmental and Resource Economics, 24, 263–271. Swan, T. W. (1956). Economic growth and capital accumulation. Economic Record, 32(2), 334–361. The World Bank (2017). World Development Indicators. https://databank.worldbank.org/data/reports.aspx?source = world-development-indicators. The World Bank (2019). World Development Indicators. https://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE Vieweg, M.; Bongardt, D.; Hochfeld, C.; Jung, A.; Scherer, E.; Adib, R.; Guerra, F. (2018) Towards decarbonising transport : Taking stock of G20 sectoral ambition. Report on behalf of Agora and GIZ. Villaverde, J., & Maza, A. (2008). Productivity convergence in the European regions, 1980–2003: a sectoral and spatial approach. Applied Economics, 40(10), 1299–1313. Yu, S., Hu, X., Fan, J. L., & Cheng, J. (2018). Convergence of carbon emissions intensity across Chinese industrial sectors. Journal of Cleaner Production, 194, 179–192.