Time-Varying and Asymmetric Relationship between Energy Use and Macroeconomic Activity

Yıl 2019, , 235 - 252, 31.07.2019

Ayşen Sivrikaya Mübariz Hasanov

https://doi.org/10.17233/sosyoekonomi.2019.03.12

Öz

In this paper, we analyze the dynamic interactions among energy use, output, capital stock and employment for the USA. Our results suggest that these interactions are time-varying and show asymmetries in terms of the one variable’s responses of big versus small and positive versus negative shocks to another variable. In particular, we find that negative energy shocks have greater impact on macroeconomic variables than positive shocks. Furthermore, small energy shocks have greater effects than big shocks. Our results also suggest that the shocks to production factors reduce energy use, implying that energy and the other factors of production are substitutes rather than compliments. These results have clear policy implications. Namely, aggressive energy saving policies might be more politically viable. In addition, the policies promoting more efficient and energy-saving capital and production technologies could help reducing energy use.

Anahtar Kelimeler

Asymmetry, Employment, Energy Demand, Structural Change, Output Growth

Enerji Kullanımı ile Makroekonomik Aktivite Arasındaki Zamanla Değişen ve Asimetrik İlişki

Öz

Bu çalışmada, enerji kullanımı, çıktı, sermaye stoku ve istihdam arasındaki dinamik etkileşimler ABD verileri kullanılarak analiz edilmiştir. Bu çalışmadan elde edilen bulgular, bu etkileşimlerin zamanla değiştiğini ve bir değişkenin başka bir değişkende gerçekleşen büyük ve küçük şoklara verdiği tepkilerin asimetrik olduğunu göstermektedir. Benzer şekilde, bir değişkene vuran pozitif ve negatif şokların diğer değişkenler üzerindeki etkileri birbirinden farklıdır. Daha özel olarak bu çalışmada, makroekonomik değişkenlerin negatif enerji şoklarına pozitif şoklara göre daha fazla tepki verdiği bulgusuna ulaşılmıştır. Ayrıca, çalışma sonuçlarına göre, küçük enerji şoklarının büyük şoklara göre makroekonomik değişkenler üzerindeki etkileri daha büyüktür. Bunlara ek olarak, üretim faktörlerine yönelik şoklar enerji kullanımını azaltmaktadır. Bu bulgu, enerji ve diğer üretim faktörlerinin tamamlayıcı olmak yerine ikame olduğuna işaret etmektedir. Bu çalışmadan elde edilen bulguların çok açık politika sonuçları bulunmaktadır. Çalışma sonuçlarına göre, enerji tasarrufunu destekleyen politika uygulamaları ekonomik büyümeye engel olmamaktadır. Ayrıca, daha verimli ve enerji tasarrufu sağlayan sermaye ve üretim teknolojilerini teşvik eden politikalar, enerji kullanımını azaltmaya yardımcı olabilmektedir.

Anahtar Kelimeler

Asimetri, İstihdam, Enerji Talebi, Yapısal Değişiklik, Çıktı Büyümesi

Kaynakça

• Apergis, N., and Payne, J. E. 2009. Energy consumption and economic growth in Central America: evidence from a panel cointegration and error correction model. Energy Economics 31:211–216.
• Araç, A, and Hasanov, M. 2014. Asymmetries in the dynamic interrelationship between energy consumption and economic growth: Evidence from Turkey. Energy Economics 44:259-269.
• Aslan, A. N, Apergis N, and Yildirim S. 2014. Causality between energy consumption and GDP in the US: evidence from wavelet analysis. Frontiers in Energy 8(1):1–8.
• Bai, J., and Perron, P. 1998. Estimating and testing linear models with multiple structural changes. Econometrica 66(1):47-78.
• Ball, L., and Mankiw, N. G. 1994. Asymmetric price adjustment and economic fluctuations. The Economic Journal 104:247–61.
• Bartleet, M., and Gounder, R. 2010. Energy consumption and economic growth in New Zealand: results of trivariate and multivariate models. Energy Policy 38:3508–17.
• Beaudreau, B. C. 2005. Engineering and economic growth. Structural Change and Economic Dynamics 16:211–220.
• Berndt, E. R., and Wood, D. O. 1979. Engineering and econometric interpreta-tions of energy-capital complementarity. American Economic Review 69(3):342–354.
• Bowden, N., and Payne J. E. 2010. Sectoral analysis of the causal relationship between renewable and non-renewable energy consumption and real output in the US. Energy Sources Part B: Econ Plan Policy 5:400–8.
• BP (British Petroleum). 2016. Statistical Review of World Energy, June 2016. Available online at: https://www.bp.com/content/dam/bp/pdf/energy-economics/statistical-review-2016/bp-statistical-review-of-world-energy-2016-full-report.pdf
• Carmona, M., Feria, J., Golpe, A. A., and Iglesias, J. 2017. Energy consumption in the US reconsidered. Evidence across sources and economic sectors. Renewable and Sustainable Energy Reviews 77:1055-1068.
• Engle, R.F., 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50 (4): 987–1007.
• Fiorito, G., and van den Bergh, J.C.J.M. 2011. Capital-Energy Substitution forClimate and Peak Oil Solutions? An International Comparison Using the EU-KLEMS Database. In: Working Paper ICTA-UAB.
• Ghali, K.H., and El-Sakka, M.I.T. 2004. Energy use and output growth in Canada: a multivariate cointegration analysis. Energy Economics 26 (2):225–238.
• Granger, C. W. J., and Terasvirta, T. 1993. Modelling Nonlinear Economic Relationships. Advanced Texts in Econometrics. Oxford University Press.
• Gross, C. 2012. Explaining the (non-) causality between energy and economic growth in the U.S.—a multivariate sectoral analysis. Energy Econ 34:489–99.
• Hall, C. A. S., Cleveland, C.J., and Kaufmann, R.K. 1986. Energy and Resource Quality: The Ecology of the Economic Process. Wiley-Interscience,New York.
• Hamilton, J. D. 2003. What is an oil shock?. Journal of Econometrics 113:363–398.
• Hasanov, M., and Telatar, E. 2011. A re-examination of stationarity of energy consumption: evidence from new unit root tests. Energy Policy 39(12):7726-7738.
• Hasanov, M., Arac, A., and Telatar, F. 2010. Nonlinearity and structural stability in the Phillips curve: evidence from Turkey. Economic Modelling 27: 1103–1115.
• Hooker, Mark A. 1996. What happened to the oil price-macroeconomy relationship?, Journal of Monetary Economics 38: 195-213.
• Jorgenson, D.W. 1984. The role of energy in productivity growth. The Energy Journal 5 (3):11–26.
• Koetse, M.J., De Groot, H.L.F. and Florax, R., 2008. Capital-energy substitutionand shifts in factor demand: a meta-analysis. Energy Economics 30:2236–2251.
• Koop, G, Pesaran, M. H., and Potter, S. M. 1996. Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74:119-147.
• Kraft, J., and Kraft, A. 1978. On the relationship between energy and GNP. Journal of Energy and Development 3:401–403.
• Lee, C.C., and Chang C.P. 2008. Energy consumption and economic growth in Asian economies: A more comprehensive analysis using panel data. Resource and Energy Economics 3:50–65.
• Leybourne, S, Newbold, P, and Vougas, D. 1998. Unit roots and smooth transitions. Journal of Time Series Analysis 19:83–97.
• Ljung, G.M., Box, G.E.P., 1978. On a measure of a lack of fit in time series models. Biometrika 65 (2): 297–303.
• Lin, C. F. J., and Teräsvirta, T. 1994. Testing the constancy of regression parameters against continuous structural change. Journal of Econometrics 62(2):211-228.
• Lundbergh, S., Teräsvirta, T., and van Dijk, D. 2003. Time-varying smooth transition autoregressive models. Journal of Business & Economic Statistics 21(1):104-121.
• Lutkepohl, H. 1982. Non-causality due to omitted variables. Journal of Econometrics 19: 367–378.
• Luukkonen, R, Saikkonen, P, and Teräsvirta, T. 1988. Testing linearity against smooth transition autoregressive models. Biometrika 75:491-99.
• Menyah, K., Wolde-Rufael, Y. 2015. Electricity consumption and economic growth in transition countries: a revisit using bootstrap panel Granger causality analysis. Energy Econ 44: 325–30.
• Moroney, J. R., 1992. Energy, capital and technological change in the United States. Resour. Energy 14:363-380.
• Oh, W., and Lee, K. 2004. Causal relationship between energy consumption and GDP: the case of Korea 1970–1999. Energy Economics 26 (1):51–59.
• Omri, A. 2014. An international literature survey on energy-economic growth nexus: Evidence from country-specific studies. Renew Sustain Energy Rev 38: 951–959.
• Ozturk, I. 2010. A literature survey on energy–growth nexus. Energy Policy 38:340–349.
• Payne, J. E. 2009. On the dynamics of energy consumption and output in the US. Appl Energy 86(4):575–7.
• Payne, J. E. 2010. Survey of the international evidence on the causal relationship between energy consumption and growth. Journal of Economic Studies 37 (1):53 – 95.
• Payne, J. E. 2011. On biomass energy consumption and real output in the US. Energy Sources Part B: Econ Plan Policy 6:47–52.
• Pesaran, M. H., Shin, Y., and Smith, R. J. 2001. Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics 16:289-326.
• Rahman, S, and Serletis, A. 2010. The asymmetric effects of oil price and monetary policy shocks: a nonlinear VAR approach. Energy Economics 32:1460–1466.
• Sari, R., Ewing, B. T., and Soytas, U. 2008. The relationship between disaggregate energy consumption and industrial production in the United States: an ARDL approach. Energy Econ 30(5):2302–13.
• Smyth, R, Narayan, P. K. 2015. Applied econometrics and implications for energy economics research. Energy Economics 50:351-358.
• Sollis, R. 2004. Asymmetric adjustment and smooth transitions: a combination of some unit root tests. Journal of Time Series Analysis 25:409–417.
• Stern, D. I. 1993. Energy and economic growth in the USA: a multivariate approach. Energy economics 15(2): 137-150.
• Stern, D. I. 2000. A multivariate cointegration analysis of the role of energy in the US macroeconomy. Energy Economics 22:267–283.
• Teräsvirta, T, and Anderson, H. M. 1992. Characterizing nonlinearities in business cycles using smooth transition autoregressive models. Journal of Applied Econometrics 7:119–136.
• Teräsvirta, T. 1994. Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89:208–218.
• Timmer, M. P., Erumban, A. A., Los, B., Stehrer, R., and de Vries, G. J. 2014. Slicing Up Global Value Chains. Journal of Economic Perspectives 28(2):99-118.
• Tiwari, A. K. 2014. The asymmetric Granger-causality analysis between energy consumption and income in the United States. Renewable and Sustainable Energy Reviews 36:362–369.
• van Dijk, D. 1999. Smooth Transition Models: Extensions and Outlier Robust Inference. Tinbergen Institute Research Series, no. 200.
• Wang, Y., Wang, Y., Zhou, J., Zhu, X., and Lu, G.. 2011. Energy consumption and economic growth in China: A Multivariate causality test. Energy Policy 39:4399–406.
• Yu, E.S.H., and Jin, J. C. 1992. Cointegration tests of energy consumption, income, and employment. Resources and Energy 14(3):259–266.
• Zachariadis, T. 2007. Exploring the relationship between energy use and economic growth with bivariate models: new evidence from G-7 countries. Energy Economics 29 (6):1233–1253.
• Zhixin, Z, and Xin R. 2011. Causal relationships between energy consumption and economic growth. Energy Procedia 5:2065–71.