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Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators

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  • Peñasco, Cristina
  • del Río, Pablo
  • Romero-Jordán, Desiderio

Abstract

A comparative analysis of electricity and gas demand in the industrial sector over a long period of time appears to be absent in the literature. In fact, unlike electricity demand, natural gas demand in the industrial sector has not been well researched. Our paper aims to cover this gap. It analyses electricity and gas consumption patterns by the Spanish manufacturing sector, between 1995 and 2010. A novel and innovative quantitative approach based on, both, homogenous and heterogeneous estimators was used for this purpose. The results of the no-spurious estimations (the Augmented Mean Group Estimator) show that the price elasticity of gas demand is significantly negative and within the −0.44 to −0.48 range. In contrast, the price elasticity of electricity demand is not statistically significant. The income elasticities show the opposite pattern: those of natural gas are not statistically significant, whereas the income elasticities for electricity are statistically significant and within the 0.22 to 0.29 range. Compared to previous findings, our preferred estimation shows some variation regarding price elasticities of natural gas demand.

Suggested Citation

  • Peñasco, Cristina & del Río, Pablo & Romero-Jordán, Desiderio, 2017. "Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators," Utilities Policy, Elsevier, vol. 45(C), pages 45-60.
  • Handle: RePEc:eee:juipol:v:45:y:2017:i:c:p:45-60
    DOI: 10.1016/j.jup.2017.01.005
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    1. Markus Eberhardt & Christian Helmers & Hubert Strauss, 2013. "Do Spillovers Matter When Estimating Private Returns to R&D?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 436-448, May.
    2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    3. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    4. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    5. Urga, Giovanni & Walters, Chris, 2003. "Dynamic translog and linear logit models: a factor demand analysis of interfuel substitution in US industrial energy demand," Energy Economics, Elsevier, vol. 25(1), pages 1-21, January.
    6. Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2012. "Estimation of elasticity price of electricity with incomplete information," Energy Economics, Elsevier, vol. 34(3), pages 627-633.
    7. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    8. Coakley, Jerry & Fuertes, Ana-Maria & Smith, Ron, 2006. "Unobserved heterogeneity in panel time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2361-2380, May.
    9. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    10. Andersen, Trude Berg & Nilsen, Odd Bjarte & Tveteras, Ragnar, 2011. "How is demand for natural gas determined across European industrial sectors?," Energy Policy, Elsevier, vol. 39(9), pages 5499-5508, September.
    11. Swamy, P A V B, 1970. "Efficient Inference in a Random Coefficient Regression Model," Econometrica, Econometric Society, vol. 38(2), pages 311-323, March.
    12. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    13. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
    14. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    15. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    16. Andrews,Donald W. K. & Stock,James H. (ed.), 2005. "Identification and Inference for Econometric Models," Cambridge Books, Cambridge University Press, number 9780521844413, October.
    17. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LP, vol. 8(2), pages 232-241, June.
    18. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    19. Patricia Renou-Maissant, 1999. "Interfuel Competition in the Industrial Sector of Seven OECD Countries," Post-Print hal-02562575, HAL.
    20. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    21. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    22. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    23. Arthur Lewbel, 2012. "An Overview of the Special Regressor Method," Boston College Working Papers in Economics 810, Boston College Department of Economics.
    24. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    25. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio & Minea, Alina A., 2010. "Analysis and forecasting of nonresidential electricity consumption in Romania," Applied Energy, Elsevier, vol. 87(11), pages 3584-3590, November.
    26. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    27. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    28. Gowdy, John M., 1983. "Industrial demand for natural gas : Inter-industry variation in New York state," Energy Economics, Elsevier, vol. 5(3), pages 171-177, July.
    29. Rolf Larsson & Johan Lyhagen & Mickael Lothgren, 2001. "Likelihood-based cointegration tests in heterogeneous panels," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-41.
    30. Andrea Vaona, 2008. "STATA tip: A quick trick to perform a Roy-Zellner test for poolability in Stata," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0804, USI Università della Svizzera italiana.
    31. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
    32. Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
    33. Iimi, Atsushi, 2010. "Price elasticity of nonresidential demand for energy in south eastern Europe," Policy Research Working Paper Series 5167, The World Bank.
    34. Kamerschen, David R. & Porter, David V., 2004. "The demand for residential, industrial and total electricity, 1973-1998," Energy Economics, Elsevier, vol. 26(1), pages 87-100, January.
    35. Polemis, Michael. L., 2007. "Modeling industrial energy demand in Greece using cointegration techniques," Energy Policy, Elsevier, vol. 35(8), pages 4039-4050, August.
    36. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    37. Francis Teal & Markus Eberhardt, 2010. "Productivity Analysis in Global Manufacturing Production," Economics Series Working Papers 515, University of Oxford, Department of Economics.
    38. Huntington, Hillard G., 2007. "Industrial natural gas consumption in the United States: An empirical model for evaluating future trends," Energy Economics, Elsevier, vol. 29(4), pages 743-759, July.
    39. Christoph Hanck, 2009. "Cross-sectional correlation robust tests for panel cointegration," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 817-833.
    40. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    41. Considine, Timothy J., 1989. "Separability, functional form and regulatory policy in models of interfuel substitution," Energy Economics, Elsevier, vol. 11(2), pages 82-94, April.
    42. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    43. Hsiao, C. & Pesaran, M. H. & Tahmiscioglu, A. K., 1998. "Bayes Estimation of Short-run Coefficients in Dynamic Panel Data Models," Cambridge Working Papers in Economics 9804, Faculty of Economics, University of Cambridge.
    44. Renou-Maissant, Patricia, 1999. "Interfuel competition in the industrial sector of seven OECD countries," Energy Policy, Elsevier, vol. 27(2), pages 99-110, February.
    45. Atkinson, Scott E & Halvorsen, Robert, 1976. "Interfuel Substitution in Steam Electric Power Generation," Journal of Political Economy, University of Chicago Press, vol. 84(5), pages 959-978, October.
    46. Urga, Giovanni, 1999. "An application of dynamic specifications of factor demand equations to interfuel substitution in US industrial energy demand," Economic Modelling, Elsevier, vol. 16(4), pages 503-513, December.
    47. Pindyck, Robert S, 1979. "Interfuel Substitution and the Industrial Demand for Energy: An International Comparison," The Review of Economics and Statistics, MIT Press, vol. 61(2), pages 169-179, May.
    48. Sanchez-Ubeda, Eugenio Fco. & Berzosa, Ana, 2007. "Modeling and forecasting industrial end-use natural gas consumption," Energy Economics, Elsevier, vol. 29(4), pages 710-742, July.
    49. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    50. Atsushi Iimi, 2011. "Effects Of Improving Infrastructure Quality On Business Costs: Evidence From Firm‐Level Data In Eastern Europe And Central Asia," The Developing Economies, Institute of Developing Economies, vol. 49(2), pages 121-147, June.
    51. Asche, Frank & Eggert, Håkan & Gudmundsson, Eyjolfur & Hoff, Ayoe & Pascoe, Sean, 2008. "Fisher's behaviour with individual vessel quotas--Over-capacity and potential rent: Five case studies," Marine Policy, Elsevier, vol. 32(6), pages 920-927, November.
    52. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Scenario analysis of nonresidential natural gas consumption in Italy," Applied Energy, Elsevier, vol. 113(C), pages 392-403.
    53. O'Connell, Paul G. J., 1998. "The overvaluation of purchasing power parity," Journal of International Economics, Elsevier, vol. 44(1), pages 1-19, February.
    54. Badi H. Baltagi & James M. Griffin & Weiwen Xiong, 2000. "To Pool Or Not To Pool: Homogeneous Versus Hetergeneous Estimations Applied to Cigarette Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 117-126, February.
    55. Eberhardt, Markus & Bond, Stephen, 2009. "Cross-section dependence in nonstationary panel models: a novel estimator," MPRA Paper 17692, University Library of Munich, Germany.
    56. Gutiérrez, R. & Nafidi, A. & Gutiérrez Sánchez, R., 2005. "Forecasting total natural-gas consumption in Spain by using the stochastic Gompertz innovation diffusion model," Applied Energy, Elsevier, vol. 80(2), pages 115-124, February.
    57. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    58. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    59. Jones, Clifton T, 1995. "A Dynamic Analysis of Interfuel Substitution in U.S. Industrial Energy Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 459-465, October.
    60. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    61. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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    1. Li, Raymond & Woo, Chi-Keung & Tishler, Asher & Zarnikau, Jay, 2022. "How price responsive is industrial demand for natural gas in the United States?," Utilities Policy, Elsevier, vol. 74(C).
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    More about this item

    Keywords

    Gas; Electricity; Demand; Manufacturing sector; Homogeneous and heterogeneous estimators;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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