Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing

This paper studies the dynamic demand for residential electricity in Taiwan employing a monthly panel data set, composed of 19 counties and spanning the period from 2007:01 to 2013:12. The partial adjustment model used addresses the endogeneity of the electricity price that results from the increasing-block pricing. The estimated results show that there is a significant seasonal difference in the demand for electricity between the summer and non-summer periods. Both the adjustment speed and own price elasticity during the summer months are found to be lower than those in the non-summer months due to the hot weather in summer. It is easier for consumers to adjust their electricity consumption in response to the changes in electricity pricing during the non-summer time. The estimated inelastic short-run and long-run income effects show that electricity is a necessity for consumers. Moreover, the controversial electricity-conservation policies are found to be ineffective measures for reducing electricity consumption in Taiwan.

[1]  Michael Nieswiadomy,et al.  Comparing Residential Water Demand Estimates under Decreasing and Increasing Block Rates Using Household Data , 1989 .

[2]  M. Hashem Pesaran,et al.  Pooled Mean Group Estimation of Dynamic Heterogeneous Panels , 1999 .

[3]  Michael P. Murray.  The Demand for Electricity in Virginia , 1978 .

[4]  R. Martínez-Espiñeira.  Price specification issues under block tariffs: a Spanish case study , 2003 .

[5]  Anna Alberini,et al.  Residential Consumption of Gas and Electricity in the U.S.: The Role of Prices and Income , 2011 .

[6]  J. Hausman,et al.  The Effect of Taxation on Labor Supply: Evaluating the Gary Negative Income Tax Experiment , 1978, Journal of Political Economy.

[7]  Steven C. Deller,et al.  Instrumental Variables Approach to Rural Water Service Demand , 1986 .

[8]  R. Blundell,et al.  Initial Conditions and Moment Restrictions in Dynamic Panel Data Models , 1998 .

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

[10]  Badi H. Baltagi,et al.  Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption , 2002 .

[11]  Giovanni S. F. Bruno,et al.  Estimation and Inference in Dynamic Unbalanced Panel-data Models with a Small Number of Individuals , 2005 .

[12]  Massimo Filippini,et al.  Residential electricity demand in Spain: New empirical evidence using aggregate data , 2013 .

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

[14]  C. Fuest,et al.  Efficiency wages, employment, and the marginal income-tax rate: A note , 1998 .

[15]  Ann L. Owen,et al.  Estimating dynamic panel data models: a guide for , 1999 .

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

[17]  Cheng Hsiao,et al.  Formulation and estimation of dynamic models using panel data , 1982 .

[18]  B. Archibald,et al.  Seasonal variation in residential electricity demand: evidence from survey data , 1982 .

[19]  D. Kamerschen,et al.  The demand for residential, industrial and total electricity, 1973-1998 , 2004 .

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

[21]  R. P. Wilder,et al.  Residential demand for electricity: a consumer panel approach , 1975 .

[22]  M. Arellano,et al.  Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations , 1991 .

[23]  Anna Alberini,et al.  Response of residential electricity demand to price: The effect of measurement error , 2011 .

[24]  Suleiman Sa'ad,et al.  Electricity demand for South Korean residential sector , 2009 .

[25]  Seung-Jun Kwak,et al.  Estimation of residential electricity demand function in Seoul by correction for sample selection bias , 2007 .

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

[27]  S. Ahsan,et al.  The design of a consumption tax under capital risk , 1998 .

[28]  Romain G. Rancière,et al.  Financial Development, Financial Fragility, and Growth , 2004, SSRN Electronic Journal.

[29]  Tadahiro Nakajima.  The residential demand for electricity in Japan: An examination using empirical panel analysis techniques , 2010 .

[30]  Jan F. Kiviet,et al.  On bias, inconsistency and efficiency of various estimators in dynamic panel data models , 1995 .

[31]  WATER-PRICE EFFECT ON RESIDENTIAL AND APARTMENT Low-FLOW FIXTURES , 1996 .

[32]  M. Flannery,et al.  Estimating Dynamic Panel Models in Corporate Finance , 2012 .

[33]  Badi H. Baltagi,et al.  To Pool or Not to Pool: Homogeneous Versus Heterogeneous Estimators Applied to Cigarette Demand , 2000, Review of Economics and Statistics.

[34]  Denis Bolduc,et al.  A pseudo-panel data model of household electricity demand , 2011 .

[35]  T. Chaudhry,et al.  Estimating Residential Electricity Demand Responses in Pakistan’s Punjab , 2010 .

[36]  Julián Moral-Carcedo,et al.  Modelling the non-linear response of Spanish electricity demand to temperature variations , 2005 .

[37]  Dinusha Dharmaratna,et al.  Estimating Residential Water Demand Using the Stone-Geary Functional Form: The Case of Sri Lanka , 2012, Water Resources Management.

[38]  Shigeyuki Hamori,et al.  Change in consumer sensitivity to electricity prices in response to retail deregulation: A panel empirical analysis of the residential demand for electricity in the United States , 2010 .

[39]  M. Pesaran,et al.  Estimating Long-Run Relationships From Dynamic Heterogeneous Panels , 1995 .

[40]  J. A. Nordin.  A Proposed Modification of Taylor's Demand Analysis: Comment , 1976 .

[41]  Massimo Filippini,et al.  Short- and long-run time-of-use price elasticities in Swiss residential electricity demand , 2011 .

[42]  R. Billings.  Specification of Block Rate Price Variables in Demand Models , 1982 .

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

[44]  W. Michael Hanemann,et al.  A discrete/continuous choice approach to residential water demand under block rate pricing , 1995 .

[45]  B. M. Mitchell,et al.  Estimating Residential Electricity Demand Under Declining-Block Tariffs , 1980 .

[46]  Edward F. Blackburne,et al.  Estimation of Nonstationary Heterogeneous Panels , 2007 .

[47]  C. Garbacz.  A National Micro-Data Based Model of Residential Electricity Demand: New Evidence on Seasonal Variation , 1984 .

[48]  Á. Pardo,et al.  Temperature and seasonality influences on Spanish electricity load , 2002 .

[49]  T. Jung.  Ordered logit model for residential electricity demand in Korea , 1993 .

[50]  Steven E. Henson.  Electricity demand estimates under increasing-block rates , 1984 .

[51]  R. Bose,et al.  Elasticities of electricity demand in India , 1999 .

[52]  Céline Nauges,et al.  Is all domestic water consumption sensitive to price control? , 2004 .

[53]  Emmanuel Ziramba,et al.  The demand for residential electricity in South Africa , 2008 .

[54]  K. Palmer,et al.  A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector , 2009 .

[55]  Peter C. Reiss,et al.  Household Electricity Demand, Revisited , 2005 .

[56]  David Roodman.  How to do Xtabond2: An Introduction to Difference and System GMM in Stata , 2006 .

[57]  David Roodman,et al.  A Note on the Theme of Too Many Instruments , 2008 .