Estimation of residential electricity demand function in Seoul by correction for sample selection bias

Abstract This paper attempts to estimate the residential electricity demand function in Seoul. To this end, we collected the data from a survey of households in Seoul and employed the bivariate model to rectify the undesirable impacts of non-response data. The results show that the size of family, the size of house, dummy for having a plasma display panel television, dummy for having an air conditioner, and the household's income have positive relationships with the residential electricity demand. On the other hand, electricity price contributes negatively to the residential electricity demand. In addition, the price and income elasticities were estimated as −0.2463 and 0.0593, respectively, implying that residential electricity demand in Seoul is price- and income-inelastic. Such useful information is expected to help policy-makers regulate the residential electricity supply and predict the effect of the price on the residential electricity demand in the future.

[1]  G. Hondroyiannis Estimating residential demand for electricity in Greece , 2004 .

[2]  Russell Smyth,et al.  The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration , 2005 .

[3]  Kjell Vaage,et al.  HEATING TECHNOLOGY AND ENERGY USE, A DISCRETE/CONTINUOUS CHOICE APPROACH TO NORWEGIAN HOUSEHOLD ENERGY DEMAND , 2000 .

[4]  F. Vella Estimating Models with Sample Selection Bias: A Survey , 1998 .

[5]  Jeffrey A. Dubin,et al.  An Econometric Analysis of Residential Electric Appliance Holdings and Consumption , 1984 .

[6]  Massimo Filippini,et al.  Swiss residential demand for electricity , 1999 .

[7]  Frederick L. Joutz,et al.  Residential electricity demand in Taiwan , 2004 .

[8]  J. Heckman Sample selection bias as a specification error , 1979 .

[9]  Ferda Halicioglu,et al.  Residential electricity demand dynamics in Turkey , 2007 .

[10]  Ada Ferrer-i-Carbonell,et al.  The ex post impact of an energy tax on household energy demand , 2004 .

[11]  Jeffrey A. Dubin,et al.  Selection Bias in Linear Regression, Logit and Probit Models , 1989 .

[12]  Lester D. Taylor,et al.  The demand for electricity: a survey , 1975 .

[13]  R. Halvorsen,et al.  Residential Demand for Electric Energy , 1975 .

[14]  Ernst R. Berndt,et al.  The Practice of Econometrics: Classic and Contemporary. , 1992 .

[15]  M. Parti,et al.  The Total and Appliance-Specific Conditional Demand for Electricity in the Household Sector , 1980 .

[16]  T. Amemiya Tobit models: A survey , 1984 .

[17]  Chandra R. Bhat,et al.  Imputing a continuous income variable from grouped and missing income observations , 1994 .

[18]  I. Krinsky,et al.  On Approximating the Statistical Properties of Elasticities , 1986 .

[19]  Jeffrey A. Dubin Consumer Durable Choice and the Demand for Electricity , 1985 .

[20]  Gebhard Flaig,et al.  Household production and the short- and long-run demand for electricity , 1990 .

[21]  S. Yoo Electricity consumption and economic growth: evidence from Korea , 2005 .

[22]  S. Pachauri,et al.  Elasticities of electricity demand in urban Indian households , 2004 .