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The demand for natural gas in the Northeastern United States

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  • Gautam, Tej K.
  • Paudel, Krishna P.

Abstract

This paper examines the demand for natural gas in the residential, commercial, and industrial sectors of the Northeastern United States, comprising nine states and using annual state-level panel data over the period between 1997 and 2016. It applies panel unit root and cointegration tests, and then estimates the parameters using five alternative estimators: dynamic fixed effects (DFE), mean group (MG), pooled mean group (PMG), common correlated effect mean group (CCEMG), and augmented mean group (AMG). The panel unit root and cointegration tests show that the series are I (1), and cointegrated. The estimated results show that the long run own price elasticities for natural gas in residential, commercial, and industrial sectors are −0.14, −0.29, and −0.28, respectively. The cross price elasticities of fuel oil for natural gas demand in residential, commercial, and industrial sectors are 0.19, 0.52, and 0.24, respectively. The long run natural gas demand is not affected by income in all three sectors. The heating degree days (HDD) have significant positive effects on demand for natural gas in all three sectors.

Suggested Citation

  • Gautam, Tej K. & Paudel, Krishna P., 2018. "The demand for natural gas in the Northeastern United States," Energy, Elsevier, vol. 158(C), pages 890-898.
  • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:890-898
    DOI: 10.1016/j.energy.2018.06.092
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    as
    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. 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.
    3. Liu, Ben-chieh, 1983. "Natural gas price elasticities : Variations by region and by sector in the USA," Energy Economics, Elsevier, vol. 5(3), pages 195-201, July.
    4. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential consumption of gas and electricity in the U.S.: The role of prices and income," Energy Economics, Elsevier, vol. 33(5), pages 870-881, September.
    5. Hsing, Yu, 1994. "Estimation of residential demand for electricity with the cross-sectionally correlated and time-wise autoregressive model," Resource and Energy Economics, Elsevier, vol. 16(3), pages 255-263, August.
    6. Considine, Timothy J., 2000. "The impacts of weather variations on energy demand and carbon emissions," Resource and Energy Economics, Elsevier, vol. 22(4), pages 295-314, October.
    7. Ajmi, Ahdi Noomen & El Montasser, Ghassen & Nguyen, Duc Khuong, 2013. "Testing the relationships between energy consumption and income in G7 countries with nonlinear causality tests," Economic Modelling, Elsevier, vol. 35(C), pages 126-133.
    8. 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.
    9. Dagher, Leila, 2012. "Natural gas demand at the utility level: An application of dynamic elasticities," Energy Economics, Elsevier, vol. 34(4), pages 961-969.
    10. Paul, Anthony & Myers, Erica & Palmer, Karen, 2009. "A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector," RFF Working Paper Series dp-08-50, Resources for the Future.
    11. 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.
    12. Burke, Paul J. & Yang, Hewen, 2016. "The price and income elasticities of natural gas demand: International evidence," Energy Economics, Elsevier, vol. 59(C), pages 466-474.
    13. 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.
    14. Jadidzadeh, Ali & Serletis, Apostolos, 2017. "How does the U.S. natural gas market react to demand and supply shocks in the crude oil market?," Energy Economics, Elsevier, vol. 63(C), pages 66-74.
    15. 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.
    16. Francis Teal & Markus Eberhardt, 2010. "Productivity Analysis in Global Manufacturing Production," Economics Series Working Papers 515, University of Oxford, Department of Economics.
    17. Blázquez, Leticia & Boogen, Nina & Filippini, Massimo, 2013. "Residential electricity demand in Spain: New empirical evidence using aggregate data," Energy Economics, Elsevier, vol. 36(C), pages 648-657.
    18. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential Consumption of Gas and Electricity in the U.S.: The Role of Prices and Income," Sustainable Development Papers 99637, Fondazione Eni Enrico Mattei (FEEM).
    19. 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.
    20. Kalashnikov, V.V. & Matis, T.I. & Pérez-Valdés, G.A., 2010. "Time series analysis applied to construct US natural gas price functions for groups of states," Energy Economics, Elsevier, vol. 32(4), pages 887-900, July.
    21. Eberhardt, Markus & Teal, Francis, 2008. "Modeling technology and technological change in manufacturing: how do countries differ?," MPRA Paper 10690, University Library of Munich, Germany.
    22. Edward F. Blackburne III & Mark W. Frank, 2007. "Estimation of nonstationary heterogeneous panels," Stata Journal, StataCorp LP, vol. 7(2), pages 197-208, June.
    23. Stern, David I., 1993. "Energy and economic growth in the USA : A multivariate approach," Energy Economics, Elsevier, vol. 15(2), pages 137-150, April.
    24. Soytas, Ugur & Sari, Ramazan, 2006. "Energy consumption and income in G-7 countries," Journal of Policy Modeling, Elsevier, vol. 28(7), pages 739-750, October.
    25. Cavalcanti, Tiago V. de V. & Mohaddes, Kamiar & Raissi, Mehdi, 2011. "Growth, development and natural resources: New evidence using a heterogeneous panel analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 305-318.
    26. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    27. Narayan, Paresh Kumar & Smyth, Russell & Prasad, Arti, 2007. "Electricity consumption in G7 countries: A panel cointegration analysis of residential demand elasticities," Energy Policy, Elsevier, vol. 35(9), pages 4485-4494, September.
    28. Helena Meier, Tooraj Jamasb, and Luis Orea, 2013. "Necessity or Luxury Good? Household Energy Spending and Income in Britain 1991-2007," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    29. Beierlein, James G & Dunn, James W & McConnon, James C, Jr, 1981. "The Demand for Electricity and Natural Gas in the Northeastern United States," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 403-408, August.
    30. 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.
    31. Nick, Sebastian & Thoenes, Stefan, 2014. "What drives natural gas prices? — A structural VAR approach," Energy Economics, Elsevier, vol. 45(C), pages 517-527.
    32. Fouquet, Roger, 2014. "Long run demand for energy services: income and price elasticities over two hundred years," LSE Research Online Documents on Economics 59070, London School of Economics and Political Science, LSE Library.
    33. 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.
    34. Zhang, Yi & Ji, Qiang & Fan, Ying, 2018. "The price and income elasticity of China's natural gas demand: A multi-sectoral perspective," Energy Policy, Elsevier, vol. 113(C), pages 332-341.
    35. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LP, vol. 8(2), pages 232-241, June.
    36. Timothy Neal, 2014. "Panel cointegration analysis with xtpedroni," Stata Journal, StataCorp LP, vol. 14(3), pages 684-692, September.
    37. Markus Eberhardt, 2012. "Estimating panel time-series models with heterogeneous slopes," Stata Journal, StataCorp LP, vol. 12(1), pages 61-71, March.
    38. Harold, Jason & Lyons, Seán & Cullinan, John, 2015. "The determinants of residential gas demand in Ireland," Energy Economics, Elsevier, vol. 51(C), pages 475-483.
    39. Schulte, Isabella & Heindl, Peter, 2017. "Price and income elasticities of residential energy demand in Germany," Energy Policy, Elsevier, vol. 102(C), pages 512-528.
    40. Miller, Mark & Alberini, Anna, 2016. "Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from U.S. Data," Energy Policy, Elsevier, vol. 97(C), pages 235-249.
    41. Roger Fouquet, 2014. "Editor's Choice Long-Run Demand for Energy Services: Income and Price Elasticities over Two Hundred Years," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 8(2), pages 186-207.
    42. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    43. Bowden, Nicholas & Payne, James E., 2009. "The causal relationship between U.S. energy consumption and real output: A disaggregated analysis," Journal of Policy Modeling, Elsevier, vol. 31(2), pages 180-188.
    44. 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.
    45. Eberhardt, Markus & Bond, Stephen, 2009. "Cross-section dependence in nonstationary panel models: a novel estimator," MPRA Paper 17692, University Library of Munich, Germany.
    46. 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.
    47. Lester D. Taylor, 1975. "The Demand for Electricity: A Survey," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 74-110, Spring.
    48. 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.
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    2. Halim TATLI, 2022. "Long-term price and income elasticity of residential natural gas demand in Turkey," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(630), S), pages 101-122, Spring.
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    4. Gautam, Tej K. & Paudel, Krishna P., 2018. "Estimating sectoral demands for electricity using the pooled mean group method," Applied Energy, Elsevier, vol. 231(C), pages 54-67.
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    More about this item

    Keywords

    Augmented mean group; Cointegration; Residential; Commercial; Industrial sectors; Natural gas; Unit root;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L97 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Utilities: General

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