The interdependence between energy consumption and economic growth in the Polish economy in the last decade

Gurgul, Henryk and Lach, Łukasz (2011): The interdependence between energy consumption and economic growth in the Polish economy in the last decade. Published in: Managerial Economics , Vol. 9, (2011): pp. 25-48.

Abstract

The main aim of this contribution is an analysis of the causal relationship between the total energy consumption in the Polish economy and GDP. In order to assure the correctness of computations a third variable – employment – was included in the dataset. Calculations performed for the period Q1 2000 to Q4 2009 by means of recent econometric techniques indicated the existence of a significant causal relation from total energy consumption to GDP. In addition, some other causalities between employment and GDP for short– and long–run term were detected, which provided a basis for claiming that changes of energy use in Poland are related in the sense of Granger causality to the employment. Because of the relatively small dataset and possible problems with the proper application of asymptotic methods, we additionally applied bootstrap critical values. The results of both methods were generally in line with each other. The results have important policy implications. The statistically significant causality from energy consumption to GDP means that energy is a very important factor in economic growth and therefore that energy policy in Poland cannot be neutral with respect to GDP growth.

• Item Type: MPRA Paper
• Language: English
• Keywords: energy consumption, economic growth, Granger causality, bootstrap techniques
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O10 - General; O - Economic Development, Innovation, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O40 - General

References

[1] Agiakoglu C, Newbold P. Empirical Evidence on Dickey–Fuller Type Tests. J Time Ser Anal 1992;13:471–83.

[2] Akarca AT, Long TV. Energy and employment: a time–series analysis of the causal relationship. Resour Energ 1979;2:151–62.

[3] Akarca AT, Long TV. On the relationship between energy and GNP: a reexamination. J Energy Dev 1980;5:326–31.

[4] Andrews DWK, Buchinsky M. A Three–Step Method for Choosing the Number of Bootstrap Repetitions. Econometrica 2000;68:23–52.

[5] Baek E, Brock W. A general test for Granger causality: Bivariate model, Technical Report, Iowa State University and University of Wisconsin, Madison, 1992.

[6] Brock W. Causality, chaos, explanation and prediction in economics and finance. In: Casti J, Karlqvist A, editors. Beyond Belief: Randomness, Prediction and Explanation in Science. Boca Raton, Fla.: CRC Press; 1991, p. 230–79.

[7] Chang T, Fang W, Wen LF. Energy consumption, employment, output, and temporal causality: evidence from Taiwan based on cointegration and error–correction modelling techniques. Appl Econ 2001;33:1045– 56.

[8] Chen AS, Lin JW. Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract. Appl Econ 2004;36:1157–1167.

[9] Cheng BS. An Investigation of Co–Integration and Causality between Energy Consumption and Economic Growth. J Energy Dev 1995;21:73–84.

[10] Cheng BS. Energy Consumption and Economic Growth in Brazil, Mexico and Venezuela: A Time Series Analysis. Appl Econ Lett 1997;4:671–674.

[11] Cheng JC, Taylor LW, Weng W. Exchange rates and prices: revisiting Granger causality tests. J Post Keynesian Ec 2006;29:259–83.

[12] Chou PH, Zhou G. Using Bootstrap to Test Portfolio Efficiency, Ann Econ Financ, 2006;2:217–49.

[13] Davison AC, Hinkley DV. Bootstrap Methods and Their Application. Cambridge: Cambridge University Press; 1999.

[14] Diks CGH, DeGoede J. A general nonparametric bootstrap test for Granger causality. In: Broer HW, Krauskopf W, Vegter G, editors. Global analysis of dynamical systems, Bristol, United Kingdom: Institute of Physics Publishing; 2001, p. 391–403.

[15] Diks CGH, Panchenko V. A note on the Hiemstra–Jones test for Granger non–causality. Stud Nonlinear Dyn E 2005;9: No. 2, Article 4.

[16] Diks CGH, Panchenko V. A new statistic and practical guidelines for nonparametric Granger causality testing. J Econ Dyn Control 2006;30:1647–69.

[17] Dolado JJ, Lütkepohl H. Making Wald tests work for cointegrated VAR systems. Economet Rev 1996;15:369–86.

[18] Engle RF, Granger CWJ. Co–integration and error–correction: representation, estimation and testing. Econometrica 1987;55:251–76.

[19] Erol U, Yu ESH. On the causal relationship between energy and income for industrialized countries. J Energy Dev 1987;13:113–22.

[20] Ferguson R, Wilkinson W, Hill R. Benefits of electricity generation. Eng Sci Educ J 1997;6:225–59.

[21] Ferguson R, Wilkinson W, Hill R. Electricity use and economic development. Energ Policy 2000;28:923–34.

[22] Gelo T. Causality between economic growth and energy consumption in Croatia. Journal of Economics and Business, Proceedings of Rijeka Faculty of Economics 2009; 27:327–48.

[23] Granger CWJ. Some recent developments in the concept of causality. J Econometrics 1988;39:199–211.

[24] Granger CWJ, Huang B, Yang C. A bivariate causality between stock prices and exchange rates: evidence from recent Asian Flu. Q Rev Econ Financ 2000;40:337–54.

[25] Granger CWJ. Investigating causal relations by econometric models and cross spectral methods. Econometrica 1969;37:424–38.

[26] Granger CWJ, Newbold P. Spurious regression in econometrics. J Econometrics 1974;2:111–20.

[27] Gurgul H, Lach Ł. Linear versus nonlinear causality of DAX companies. Operations Research and Decisions 2009;3:27–46.

[28] Gurgul H, Lach Ł. The causal link between Polish stock market and key macroeconomic aggregates. Betrieb Forsch Prax 2010;4:367–83.

[29] Hacker RS, Hatemi–J A. Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application. Appl Econ 2006;38:1489–500.

[30] Hiemstra C, Jones JD. Testing for linear and nonlinear Granger causality in the stock price–volume relation. J Finance 1994;49:1639–64.

[31] Horowitz JL. Bootstrap methods in econometrics: Theory and numerical performance. In: Kreps DM, Wallis KF, editors. Advances in Economics and Econometrics: Theory and Applications, Cambridge: Cambridge University Press;1995, p. 188–232.

[32] Johansen S. Likelihood–based Inference in Cointegrated Vector Autoregressive Models. Oxford: Oxford University Press; 1995.

[33] Keho Y. Causal relationship between energy consumption and GDP: An empirical analysis of five West African countries. J Energy Dev, 2007;33:23–32.

[34] Kraft J, Kraft A. On the relationship between energy and GNP. J Energy Dev, 1987;3:401–403.

[35] Lach Ł. Application of bootstrap methods in investigation of size of the Granger causality test for integrated VAR systems. Managing Global Transitions 2010;8:167–86.

[36] Lütkepohl H. Introduction to Multiple Time Series Analysis, 2nd ed. New York: Springer–Verlag; 1993.

[37] MacKinnon JG, Haug AA, Michelis L. Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration. J Appl Econom 1999;14:563–77.

[38] Mantalos P. A Graphical Investigation of the Size and Power of the Granger–Causality Tests in Integrated–Cointegrated VAR Systems. Stud Nonlinear Dyn E 2000:4(1);Article No. 2.

[39] Masih AMM, Masih R. Energy consumption, real income and temporal causality: results from a multi–country study based on cointegration and error–correction modeling techniques. Energ Econ 1996;18:165– 83.

[40] Masih AMM, Masih R. On the temporal causal relationship between energy consumption, real income, and price: Some new evidence from Asian–energy dependent NICs based on a multivariate cointegration/vector error–correction approach. J Policy Model 1997;19(4):417– 40.

[41] Osterwald–Lenum M. A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics. Oxford B Econ Stat 1992;54:461–72.

[42] Paulsen J. Order determination of multivariate autoregressive time series with unit roots. J Time Ser Anal 1984;5:115–27.

[43] Phillips PCB. Understanding the spurious regression in econometrics. J Econometrics 1986;33:311–40.

[44] Shiu A, Lam P–L. Electricity consumption and economic growth in China. Energ Policy 2004;32:47–54.

[45] Skaug HJ, Tjøstheim D. Nonparametric tests of serial independence. In: Subba Rao T, editor. Developments in Time Series Analysis, London: Chapman and Hall; 1993, p. 207–29.

[46] Stern DI. Energy and growth in the USA. A multivariate approach. Energ Econ 1993;15:137–50.

[47] Stern DI. A Multivariate Co–Integration Analysis of the Role of Energy in the US Macro Economy. Energ Econ 2000;62:540–52.

[48] Toda HY, Yamamoto T. Statistical inference in vector autoregressions with possibly integrated processes. J Econometrics 1995;66:225–50.

[49] Yang HY. Coal consumption and economic growth. Energ Source 2000;22:109–15.

[50] Yu ESH, Choi JY. The causal relationship between energy and GNP: an international comparison. J Energy Dev 1985;10:249–72.

[51] Yu ESH, Chow PCY, Choi JY. The causal relationship between energy and employment: An reexamination. Energy Systems and Policy 1988;11:287– 95.