Dagher, Leila (2011): Natural Gas demand at the utility level: An application of dynamic elasticities. Published in: Energy Economics , Vol. 34, (2012): pp. 961-969.
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Abstract
Previous studies provide strong evidence that energy demand elasticities vary across regions and states, arguing in favor of conducting energy demand studies at the smallest unit of observation for which good quality data are readily available, that is the utility level. We use monthly data from the residential sector of Xcel Energy’s service territory in Colorado for the period January 1994 to September 2006. Based on a very general Autoregressive Distributed Lag model this paper uses a new approach to simulate the dynamic behavior of natural gas demand and obtain dynamic elasticities. Knowing consumers’ response on a unit time basis enables one to answer a number of questions, such as, the length of time needed to reach demand stability. Responses to price and income were found to be much lower—even in the long run—than what has been commonly suggested in the literature. Interestingly, we find that the long run equilibrium is reached relatively quickly, around 18 months after a change in price or income has occurred, while the literature implies a much longer period for complete adjustments to take place.
Item Type: | MPRA Paper |
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Original Title: | Natural Gas demand at the utility level: An application of dynamic elasticities |
Language: | English |
Keywords: | dynamic elasticities; ADL; natural gas demand; Colorado |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply ; Prices |
Item ID: | 116126 |
Depositing User: | Dr Leila Dagher |
Date Deposited: | 25 Jan 2023 14:27 |
Last Modified: | 25 Jan 2023 14:27 |
References: | Andrews, D. W. K., 1993. Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821-856. Baltagi, B. H., 2008. Econometrics. 4th edition. Heidelberg: Springer-Verlag. Baltagi, B. H., Griffin, J.M., 2006. Swedish Liquor Consumption: New Evidence on Taste Change. Contributions to Economic Analysis, Panel Data Econometrics. Edited by Badi Baltagi, Elsevier, Netherlands. Bentzen, J., Engsted, T., 2001. A revival of the autoregressive distributed lag model in estimating energy demand relationships. Energy, 26, 45-55. Berndt, E. R., Watkins, G.C., 1977. Demand for natural gas: residential and commercial markets in Ontario and British Columbia. Canadian Journal of Economics,1, 97-111. Bernstein, M. A., Griffin, J., 2006. Regional Differences in the Price-Elasticity of Demand for Energy. National Renewable Energy Laboratory. Technical Report, Santa Monica, CA: Rand Corporation. Bohi, D. R., 1981. Analyzing Demand Behavior. Baltimore, MD: Johns Hopkins University. Published for Resources for the Future. Bohi, D., Zimmerman, M. B., 1984. An update on econometric studies of energy demand behavior. Annual Review of Energy, 9, 105-154. Charemza, W., Deadman, D., 1997. New Directions in Econometric Practice. 2nd Edition. UK: Edward Elgar Publishing. Chern, W. S., Just, R.E., 1980. Regional analysis of electricity demand growth. Energy, 5, 35-46. Choi, J., 2002. Short-run and long-run elasticities of electricity demand in the public sector: a case study of the U.S. navy bases. Ph D. Thesis, Department of Economics, George Washington University. Cuddington, J. C., Dagher, L., 2008. Dynamic demand functions: estimating short-run and long-run elasticities and associated standard errors. Colorado School of Mines manuscript. Dahl, C. A., 1993. A Survey of Energy Demand Elasticities in Support of the Development of the NEMS. (Prepared for the US Department of Energy under contract De-Ap01-93EI23499). Colorado School of Mines. Dahl, C. A., Pechatnikov, A. 2007. Meta-Analysis for Natural Gas Demand: Notes and Regressions. Colorado School of Mines manuscript. Danielsen, A. L., 1977. A specification analysis of the demand for petroleum products, coal, and natural gas. Review of Business and Economic Research, XIII(2), 1-20. Dickey, D. A., Bell R. W., Miller, B. R., Feb., 1986, Unit roots in time series models: tests and implications. The American Statistician, Vol. 40, No. 1, pp. 12-26. Dolado, J., Jenkinson, T., Sosvilla-Rivero, S., 1990. Cointegration and unit roots. Journal of Economic Surveys, 4, 249-273. Donnelly, W. A., 1987. The Econometrics of Energy Demand. New York: Praeger Publishers. Efron, B., 1981. Nonparametric Estimates of Standard Error: The Jackknife, the Bootstrap, and Other Methods. Biometrika, 68(3), 589-599. Enders, W., 1995. Applied Econometric Time Series. New York: Wiley. Energy Information Administration, State Energy Profiles, Colorado, http://tonto.eia.doe.gov/state/state_energy_profiles.cfm?sid=CO, 11/12/2007. Energy Information Administration (EIA), 2007. State Electricity Profiles 2006, DOE/EIA-0348(01)/2. Energy Information Administration (EIA), 2003. Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Model by Steven Wade. Espey, J. A., 1998. Explaining the Variation in Price and Income Elasticities of the Demand for Residential Electricity: A Meta-Analysis. Masters Dissertation. University of Nevada, Reno. Espey, J. A., Espey, M., 2004. Turning on the lights: a meta_analysis of residential electricity demand elasticities. Journal of Agricultural and Applied Economics, 36(1), 65-81. Fatai, K., Oxley, L., Scrimgeour, F. G., 2003. Modeling and forecasting the demand for electricity in New Zealand: a comparison of alternative approaches. The Energy Journal, 24(1), 75-102. Fisher, F. M., Kaysen, G.S., 1962. The Demand for Electricity in the United States. Amsterdam: North-Holland. Garcia-Cerutti, L. M., 2000. Estimating elasticities of residential energy demand from panel county data using dynamic random variables models with heteroskedastic and correlated error terms. Resource and Energy Economics, 22, 355-366. Greening, L. A., Greene, D. L., Difiglio, C., 2000. Energy efficiency and consumption-the rebound effect-a survey. Energy Policy, 28, 389-401. Halvorsen, R., Palmquist, P., 1980. The interpretation of dummy variables in semilogarithmic equations. American Economic Review, 70, 474-475. Houthakker, H. S., Verleger, P. K. Jr., Sheehan, D. P., 1974. Dynamic demand analyses for gasoline and residential electricity. American Journal of Agricultural Economics, 56(2), 412-418. Hsiao, C., Yanan, W., 2006. Panel Data Analysis – Advantages and Challenges. Wise working paper series, WISEWP0602. Joutz, F., Trost, R. P., 2007. An Economic Analysis of Consumer Response to Natural Gas Prices. Prepared for the American Gas Association. Kennedy P., 2003. A Guide to Econometrics, 5th Edition. Cambridge, MA: MIT Press. Khazzoom, J. D., 1980. Economic implications of mandated efficiency in standards for household appliances. Energy Journal, 1(4), 21-40. Kim, D. W., 2004. Three essays in energy economics. PhD Dissertation, University of California, Davis. Kramer, W., Ploberger, W., Alt, R., 1988. Testing for structural change in dynamic models. Econometrica, 56, 1355-1369. Labandeira, X., Labeaga, J. M., Rodriguez, M., 2005. A residential energy demand system for Spain. Center for Energy and Environmental Policy Research, 05-001 WP. Maddala, G. S., Trost, R., Joutz, F., Li, H., 1997. Estimation of short run and long run elasticities of energy demand from panel data using shrinkage estimators. Journal of Business & Economic Statistics, 15(1), 90-101. McClung, B., 1988. Estimation and interpretation of competing models of electricity demand using the residential energy consumption survey microdata sets. PhD dissertation, Texas A&M University. Munley, V. G., Taylor, L. W., Formby, J. P., 1990. Electricity demand in multi-family, renter-occupied residences. Southern Economic Journal, 57(1), 178-194. Murray, M. P., Spann, R., Pulley, L., Beauvais, E., 1978. The demand for electricity in Virginia. Review of Economics and Statistics, 60(4), 585-601. Pindyck, R., Rubinfeld, D., 1998. Econometric Models and Economic Forecasts, 4th Edition. McGraw-Hill Companies. Rushdi, A. A., 1986. Interfuel substitution in the residential sector of South Australia. Energy Economics,177-185. Shin, J., 1983. Perception of price when price information is costly: evidence from electricity demand. PhD Dissertation Ohio State University. Smith, K., 1980. Estimating the price elasticity of US electricity demand. Energy Economics, 2(2), 81-85. Snyder, J. J., 1979. Residential electricity demand in Colorado municipalities: a time-series cross-section study. PhD Dissertation. University of Colorado, Boulder, CO. Taylor, L. D., 1977. The demand for energy: a survey of price and income elasticities, in William D. Nordhaus, ed., International Studies of the Demand for Energy. Amsterdam: North-Holland. Uri, N. D., 1975. Towards an Efficient Allocation of Electrical Energy. Lexington, MA.: Heath, pp. 11-26. Uri, N. D., 1983. The regional demand for energy by the residential sector in the United States. Applied Energy, 13, 23-44. Varian, H. R., 1992. Microeconomic Analysis. New York, NY: W. W. Norton and Company. Westley, G. D., 1992. New Directions in Econometric Modeling of Energy Demand. Inter-American Development Bank, Washington D. C. Wooldridge, J. M., 2009. Introductory Econometrics- A Modern Approach, Fourth Edition. South-Western Cengage Learning, Canada. Yokohama, A., Ueta, K., Fujikawa, K., 2000. Green tax reform: converting implicit carbon taxes to a pure carbon tax. Environmental Economics & Policy Studies, 3(1), 1-20. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/116126 |