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http://dx.doi.org/10.5855/ENERGY.2014.23.3.036

Analysis of residential natural gas consumption distribution function in Korea - a mixture model  

Kim, Ho-Young (Department of Energy Policy, Graduate School of Energy & Environment, Seoul National University of Science & Technology)
Lim, Seul-Ye (Department of Energy Policy, Graduate School of Energy & Environment, Seoul National University of Science & Technology)
Yoo, Seung-Hoon (Department of Energy Policy, Graduate School of Energy & Environment, Seoul National University of Science & Technology)
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Abstract
The world's overall need for natural gas (NG) has been growing up fast, especially in the residential sector. The better the estimation of residential NG consumption (RNGC) distribution, the better decision-making for a residential NG policy such as pricing, demand estimation, management options and so on. Approximating the distribution of RNGC is complicated by zero observations in the sample. To deal with the zero observations by allowing a point mass at zero, a mixture model of RNGC distributions is proposed and applied. The RNGC distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household RNGC survey data collected in Korea. The mixture model can easily capture the common bimodality feature of the RNGC distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-expenditure significantly varies with some variables. Finally, the goodness-of-fit test suggests that the data are well represented by the mixture model.
Keywords
residential natural gas consumption; zero observations; mixture model; distribution function; Weibull distribution;
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1 Balestra, P., Nerlove, M. "Pooling cross section and time series data in the estimation of a dynamic model: the demand for natural gas." Econometrica, vol. 34, 585-612, (1996)
2 Berndt, E.R., Watkins, G.C. "Demand for natural gas: residential and commercial markets in Ontario and British Columbia." The Canadian Journal of Economics, vol..10, 97-111, (1977)   DOI
3 Blattenberger, G.R, Taylor, L.D., Rennhack, R.D. Natural gas availability and the residential demand for energy. The Energy Journal, vol. 4, 23-45, (1983)
4 Bloch, F.E. Residential demand for natural gas. Journal of Urban Economics, vol. 7, 371-383, (1980)   DOI
5 BP. Statistical review of world energy. Available from: http://www.bp.com (2012)
6 Dursun, B., Alboyaci, B. An evaluation of wind energy characteristics for four different locations in Balikesir. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 33, 1086-1103, (2011)   DOI
7 Emami, N., Behbahani-Nia, A. The statistical evaluation of wind speed and power density in the Firouzkouh region in Iran. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 34, 1076-1083, (2012)   DOI
8 Lim, H.-J., Yoo, S.-H. Natural gas consumption and economic growth in Korea: a causality analysis. Energy Sources Part B: Economics, Policy, and Planning, vol. 7, 169-176, (2012)   DOI
9 Massey, F.J. The Komogorov-Smirnov test for goodness for fit. Journal of American Statistical Association, vol. 46, 68-78, (1951)   DOI   ScienceOn
10 McLachlan, G.J., Basford, K.E. Mixture models. New York: Marcel Dekker (1988)
11 Yoo, S.-H. A note on approximation of mobile communications consumption distribution function using a mixture model. Journal of Applied Statistics, vol. 31, 747-752, (2004)   DOI
12 Yoo, S.-H., Lim, H.-J, Kwak, S.-J. Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias. Applied Energy, vol. 86, 460-465, (2009)   DOI