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Title:Demand for electricity: a case in South Korea
Author(s):Liu, Tingwen
Director of Research:Cho, In-Koo
Doctoral Committee Chair(s):Cho, In-Koo
Doctoral Committee Member(s):Bera, Anil K.; Deltas, George; Hong, Seung-Hyun
Department / Program:Economics
Discipline:Economics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Electricity market
Demand
Price elasticity
Abstract:This dissertation studies wholesale and sector-wise electricity demand in South Korea. Electricity demand analysis provides useful insights for market performance evaluation, load prediction, market restructuring, tariff schedule design, etc. In recent years, there has been a heated debate in Korea on how to restructure the electricity market, since low reserve margins that have been in operation (6.7% on average in 2010 for instance) have been threatening the stability and integrity of the electricity system. This dissertation thus attempts to address three important questions about Korean electricity demand-side market restructuring: (1) What are the estimates of the price elasticity of electricity demand in the wholesale and retail markets, including the residential, industrial, and commercial sectors? (2) How do inter-temporal price changes affect electricity consumption, and what are the estimates of the inter-temporal electricity cross-price elasticities in the wholesale market? (3) Except for the electricity price, what other factors affect electricity consumption in the wholesale and retail markets, including the residential, industrial, and commercial sectors? In Chapter 2, I review current studies on electricity demand estimations, with the emphasis on price elasticity after the year 2000. Twenty papers (selected on the basis of the author's judgment) are summarized and evaluated, along with six papers that are discussed in relatively more detail. I also present evaluations and critiques of these works. In Chapter 3, I briefly introduce the Korean electricity market and how it functions. In Chapter 4, I investigate the underlying features of the data in each market and sector and present these features both graphically and statistically. In Chapter 5, I study the wholesale electricity market. Under the Real Time Pricing (RTP) structure, I discuss the model specification with respect to hourly consumption data with a consideration of aggregate utilization behaviors to control the complicated cyclical consumption patterns. Identification is established when the exclusion condition is not satisfied in the demand and supply system. The estimated real-time aggregate price elasticity, based on the whole sample, is -0.0034, the corresponding long-run price elasticity is -0.0640, and the estimated cross-price elasticities within the previous twenty-two hours are all negative, suggesting complementarity price effects. Price elasticities are also affected by the size of responsive customers. The effects of interruptible service operated by Korea Electric Power Corporation (KEPCO) and large buyers in the wholesale market with on-site generators on the demand curve are not detected based on a smooth transition model. Price elasticities with regard to each hour within a day are also estimated. Temperature and different types of the day also affect aggregate electricity consumption. In Chapter 6, I study the retail electricity market, with a focus on the residential, industrial, and commercial sectors. Section 6.1 studies the residential sector. A basic regression model is built based on Ito (2012)'s finding that, contrary to the implications of conventional economic theory, households respond to the average electricity price rather than the marginal price when the tariff structure is increasing stepwise. I show that, on average, households respond to the previous month's average electricity price based on encompassing tests, which might be explained by the cognitive cost of a household obtaining the price information for the current monthly bill, as Ito (2012) implied. A structural time series model (STSM) with four different specifications is also applied to take account of the Underlying Energy Demand Trend (UEDT). The estimated aggregate price and income elasticities are around -0.2923 and 1.0388. Even though natural gas is a theoretical substitute for electricity, statistically, it does not affect electricity consumption. Other factors, such as temperature and holidays, have significant effects on electricity consumption. Moreover, the UEDT shows a steady decreasing usage trend, indicating, in the residential sector, that improved energy efficiency is the driving force of the UEDT. Section 6.2 studies the industrial and commercial sectors. A simple theoretical analysis is first provided to model electricity demand for each pricing interval under the Time of Use (TOU) tariff structure. An absence of daily/monthly sector consumption data in different pricing intervals prohibited me from applying the theoretical model in practice. Instead, I take advantage of monthly aggregate data and model demand as monthly aggregate consumption against the monthly average price. This modeling compromise would introduce some bias into the price coefficients, for instance, by masking own- and cross-price effects in different pricing intervals. Except for the basic log-log specification, a seemingly unrelated regressions (SUR) model and an STSM, used to take account of the UEDT, are also applied. I find that firms in the industrial sector are responsive to electricity price variations, with the estimated price elasticity being around -0.19, but that firms in the commercial sector are not. Income elasticities in the commercial and industrial sectors are 1.7326 and 1.4585, respectively. Natural gas substitution elasticity is significant in the industrial sector with the basic and SUR models but this result is not robust to the STSM specification. Substitution effects are all insignificant in the commercial sector. Moreover, both sectors show an increasing UEDT trend. Further, once the UEDT is controlled, the estimated income elasticity becomes smaller (1.2483 in the commercial sector), indicating that part of the UEDT effects are confounded in the income coefficient when the UEDT is not specifically controlled. Other factors, such as temperature and holidays, have significant effects on electricity consumption.
Issue Date:2014-01-16
URI:http://hdl.handle.net/2142/46864
Rights Information:Copyright 2013 Tingwen Liu
Date Available in IDEALS:2014-01-16
2016-01-16
Date Deposited:2013-12


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