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

• Autorzy: Gurgul H. , Lach Ł.

Warianty tytułu

PL

Wzajemne zależności pomiędzy zużyciem energii a wzrostem gospodarczym w Polsce w ostatniej dekadzie

• Języki publikacji: EN

Abstrakty

EN

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 correetness of computations a third variable - employment - was included in the dataset. Calculations performed on the basis of quarterly data for the period Q1 2000 to Q4 2009 by means of recent econometric techniques indicated the existence of a significant causal relation running 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.

PL

Głównym celem tej pracy jest analiza związków przyczynowych między całkowitym zużyciem energii a PKB w Polsce. W celu zapewnienia poprawności obliczeń trzecia zmienna - zatrudnienie - została dodatkowo dołączona do zbioru danych. Obliczenia przeprowadzone dla danych kwartalnych z okresu Q1 2000 do Q4 2009 z wykorzystaniem aktualnie stosowanych metod ekonometrycznych wykazały istnienie związku przyczynowego w kierunku od zużycia energii do PKB. Dodatkowo zostały również wykryte pewne krótko- i długoterminowe zależności przyczynowe między zatrudnieniem a PKB, co jednocześnie pozwoliło stwierdzić, że między zużyciem energii w Polsce a zatrudnieniem istnieje zależność przyczynowa w sensie Grangera. Z powodu stosunkowo małej próbki i możliwych problemów z zastosowaniem teorii asymptotycznej w pracy dodatkowo wykorzystano bootstrapowe wartości krytyczne. Wyniki uzyskane za pomocą obu metod zasadniczo nie odbiegały od siebie. Wyniki badań empirycznych przekładają się na ważne implikacje w zakresie polityki energetycznej. Istotny statystycznie wpływ zużycia energii w Polsce na PKB oznacza, że energia jest bardzo ważnym czynnikiem wzrostu gospodarczego i polityka energetyczna w Polsce nie może być neutralna względem wzrostu PKB.

Słowa kluczowe

EN

economic growth; energy consumption; linear Granger causality; nonlinear Granger causality

PL

wzrost gospodarczy; zużycie energii; liniowa przyczynowość w sensie Grangera; nieliniowa przyczynowość w sensie Grangera

• Wydawca: Wydawnictwa AGH
• Czasopismo: Ekonomia Menedżerska
• Rocznik: 2011
• Tom: nr 9
• Strony: 25--48
• Opis fizyczny: Bibliogr. 49 poz., tab., wykr.

Twórcy

autor

Gurgul H.

• AGH University of Science and Technology, Faculty of Management, Department of Application of Mathematics in Economics

autor

Lach Ł.

• AGH University of Science and Technology, Faculty of Management, Department of Application of Mathematics in Economics

Bibliografia

• [1] Agiakoglu C., Newbold P., Empirical Evidence on Dickey–Fuller Type Tests, “Journal of Time Series Analysis” 1992, Vol. 13, pp. 471–83.
• [2] Akarca A.T., Long T.V., Energy and employment: a time–series analysis of the causal relationship, “Resources and Energy” 1979, Vol. 2, pp. 151–162.
• [3] Akarca A.T., Long T.V., On the relationship between energy and GNP: a reexamination, “Journal of Energy and Development” 1980, Vol. 5, pp. 326–331.
• [4] Andrews D.W.K., Buchinsky M., A Three-Step Method for Choosing the Number of Bootstrap Repetitions, “Econometrica” 2000, Vol. 68, pp. 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. (Eds.), Beyond belief: randomness, prediction and explanation in science, CRC Press, Boca Raton, Fla. 1991, pp. 230–279.
• [7] Chang T., Fang W., Wen L.F., Energy consumption, employment, output, and temporal causality: evidence from Taiwan based on cointegration and error–correction modelling techniques, “Applied Economics” 2001, Vol. 33, pp. 1045– 1056.
• [8] Chen A.S., Lin J.W., Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract, Applied “Economics” 2004, Vol. 36, pp. 1157–1167.
• [9] Cheng B.S., An investigation of co–integration and causality between energy consumption and economic growth, “Journal of Energy and Development” 1995, Vol. 21, pp. 73–84.
• [10] Cheng B.S., Energy consumption and economic growth in Brazil, Mexico and Venezuela: a time series analysis, “Applied Economics Letters” 1997, Vol. 4, pp. 671–674.
• [11] Cheng J.C., Taylor L.W., Weng W., Exchange rates and prices: revisiting Granger causality tests, “Journal of Post Keynesian Economics” 2006, Vol. 29, pp. 259–283.
• [12] Chou P.H., Zhou G., Using bootstrap to test portfolio efficiency, “Annals of Economics and Finance” 2006, Vol. 2, pp. 217–249.
• [13] Davison A.C., Hinkley D.V., Bootstrap methods and their application, Cambridge University Press, Cambridge 1999.
• [14] Diks C.G.H., DeGoede J., A general nonparametric bootstrap test for Granger causality, in: Broer H.W., Krauskopf W., Vegter G. (Eds.), Global analysis of dynamical systems, Institute of Physics Publishing, Bristol 2001, United Kingdom, pp. 391–403.
• [15] Diks C.G.H., Panchenko V., A note on the Hiemstra–Jones test for Granger non–causality, “Studies in Nonlinear Dynamics and Econometrics” 2005, Vol. 9, No. 2, Article 4.
• [16] Diks C.G.H., Panchenko V., A new statistic and practical guidelines for nonparametric Granger causality testing, “Journal of Economic Dynamics and Control” 2006, Vol. 30, pp. 1647–1669.
• [17] Dolado J.J., Lütkepohl H., Making Wald tests work for cointegrated VAR systems, “Econometric Reviews” 1996, Vol. 15, pp. 369–386.
• [18] Engle R.F., Granger C.W.J., Co–integration and error–correction: representation, estimation and testing, “Econometrica” 1987, Vol. 55, pp. 251–276.
• [19] Erol U., Yu E.S.H., On the causal relationship between energy and income for industrialized countries, “Journal of Energy and Development” 1987, Vol. 13, pp. 113–122.
• [20] Ferguson R., Wilkinson W., Hill R., Benefits of electricity generation, “Engeineering Science and Education Journal” 1997, Vol. 6, pp. 225–259.
• [21] Ferguson R., Wilkinson W., Hill R., Electricity use and economic development, “Energy Policy”, 2000, Vol. 28, pp. 923–934.
• [22] Gelo T., Causality between economic growth and energy consumption in Croatia, “Journal of Economics and Business” Proceedings of Rijeka Faculty of Economics, 2009, Vol. 27, pp. 327–348.
• [23] Granger C.W.J., Some recent developments in the concept of causality, “Journal of Econometrics” 1988, Vol. 39, pp. 199–211
• [24] Granger C.W.J., Huang B., Yang C., A bivariate causality between stock prices and exchange rates: evidence from recent Asian Flu, “The Quarterly Review of Economics and Finance” 2000, Vol. 40, pp. 337–354.
• [25] Granger C.W.J., Investigating causal relations by econometric models and cross spectral methods, “Econometrica” 1969, Vol. 37, pp. 424–438.
• [26] Granger C.W.J., Newbold P., Spurious regression in econometrics, Journal of “Econometrics” 1974, Vol. 2, pp. 111–120.
• [27] Gurgul H., Lach Ł., Linear versus nonlinear causality of DAX companies, “Operations Research and Decisions” 2009, Vol. 3, pp. 27–46.
• [28] Gurgul H., Lach Ł., The causal link between Polish stock market and key macroeconomic aggregates, “Betriebswirtschaftliche Forschung und Praxis”2010, Vol. 4, pp. 367–383.
• [29] Hacker R.S., Hatemi J. A., Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application, “Applied Economics” 2006, Vol. 38, pp. 1489–1500.
• [30] Hiemstra C., Jones J.D., Testing for linear and nonlinear Granger causality in the stock price–volume relation, “Journal of Finance” 1994, Vol. 49, pp. 1639–1664.
• [31] Horowitz J.L., Bootstrap methods in econometrics: Theory and numerical performance, in: Kreps D.M., Wallis K.F. (Eds.), Advances in Economics and Econometrics: Theory and Applications, Cambridge University Press, Cambridge 1995, pp. 188–232
• [32] Johansen S., Likelihood–based inference in cointegrated vector autoregressive models, Oxford University Press, Oxford 1995.
• [33] Keho Y., Causal relationship between energy consumption and GDP: An empirical analysis of five West African countries, “Journal of Energy and Development” 2007, Vol. 33, pp. 23–32.
• [34] Kraft J., Kraft A., On the relationship between energy and GNP, “The Journal of Energy and Development” 1978, Vol. 3, pp. 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, Vol. 8, pp. 167–186.
• [36] MacKinnon J.G., Haug A.A., Michelis L., Numerical distribution functions of likelihood ratio tests for cointegration, “Journal of Applied Econometrics” 1999, Vol. 14, pp. 563–577.
• [37] Mantalos P., A graphical investigation of the size and power of the Granger causality tests in integrated–cointegrated VAR systems, “Studies in Nonlinear Dynamics and Econometrics” 2000, Vol. 4(1), Article No. 2.
• [38] Masih A.M.M., Masih R., Energy consumption, real income and temporal causality: results from a multi–country study based on cointegration and error–correction modeling techniques, “Energy Economics” 1996, Vol. 18, pp. 165–183.
• [39] Masih A.M.M., 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, “Journal of Policy Modeling” 1997, Vol. 19(4), pp. 417–440.
• [40] Osterwald-Lenum M., A note with quantiles of the asymptotic distribution of the maximum likelihood cointegration rank test statistics, “Oxford Bulletin of Economics and Statistics” 1992, Vol. 54, pp. 461–472.
• [41] Phillips P.C.B., Understanding the spurious regression in econometrics, “Journal of Econometrics” 1986, Vol. 33, pp. 311–340.
• [42] Shiu A., Lam P.L., Electricity consumption and economic growth in China, “Energy Policy” 2004, Vol. 32, pp. 47–54.
• [43] Skaug H.J., Tjostheim D., Nonparametric tests of serial independence, in: Subba Rao T. (Ed.), Developments in Time Series Analysis, Chapman and Hall, London 1993, pp. 207–229.
• [44] Stern D.I., Energy and growth in the USA. A multivariate approach, “Energy Economics” 1993, Vol. 15, pp. 137–150.
• [45] Stern D.I., A multivariate co–integration analysis of the role of energy in the US macro economy, “Energy Economics” 2000, Vol. 62, pp. 540–552.
• [46] Toda H.Y., Yamamoto T., Statistical inference in vector autoregressions with possibly integrated processes, “Journal of Econometrics” 1995, Vol. 66, pp. 225–250.
• [47] Yang H.Y., Coal consumption and economic growth, “Energy Sources, Part B: Economics, Planning and Policy” 2000, Vol. 22, pp. 109–115.
• [48] Yu E.S.H., Choi J.Y., The causal relationship between energy and GNP: an international comparison, “Journal of Energy and Development” 1985, Vol. 10, pp. 249–272.
• [49] Yu E.S.H., Chow P.C.Y., Choi J.Y., The causal relationship between energy and employment: An reexamination, “Energy Systems and Policy” 1988, Vol. 11, pp. 287–295.