2020•Korea International Trade Research InstituteRequires access

Empirical Study of Relationship Between Price Elasticity of Electric Demand and Seasonal Effects

Jin-Woo Dong, Young‐Duk Kim, Jae-Hyun Jung

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Abstract

Purpose - This study investigates the estimation results of price elasticity in previous studies and examines the relationship between temperature effects, or seasonal effect, for the demand function of electricity and price elasticity of electricity demand. Design/Methodology/Approach - We use the monthly data of electricity demand and price from Jan, 1981to Dec, 2018 in KESIS and KEPCO. Estimates of demand functions for electricity using Stata 14 might be biased because of identification problems. It is necessary to analyze whether control of temperature or seasonal effects utilized in many studies significantly deal with the identification of demand functions for electricity. Findings - Past literature showed that controlled temperature or seasonal effects have tended to be more sensitive to price elasticity of electricity than those that did not. Moreover, except for industrial power, estimates of long-term price elasticity on electricity demand is more sensitive when temperature or seasonality is controlled. Research Implications - The results imply that price elasticity estimates are likely to be downward biased in demand function model on electricity with only price and income as variables and these also highlight that control of temperature and seasonality is one of the ways to identify demand.

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What this paper is about

Purpose - This study investigates the estimation results of price elasticity in previous studies and examines the relationship between temperature effects, or seasonal effect, for the demand function of electricity and price elasticity of electricity demand. Design/Methodology/Approach - We use the monthly data of electricity demand and price from Jan, 1981to Dec, 2018 in KESIS and KEPCO. Estimates of demand functions for electricity using Stata 14 might be biased because of identification problems. It is necessary to analyze whether control of temperature or seasonal effects utilized in many studies significantly deal with the identification of demand functions for electricity. Findings - Past literature showed that controlled temperature or seasonal effects have tended to be more sensitive to price elasticity of electricity than those that did not. Moreover, except for industrial power, estimates of long-term price elasticity on electricity demand is more sensitive when temperature or seasonality is controlled. Research Implications - The results imply that price elasticity estimates are likely to be downward biased in demand function model on electricity with only price and income as variables and these also highlight that control of temperature and seasonality is one of the ways to identify demand.

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Available abstract

Purpose - This study investigates the estimation results of price elasticity in previous studies and examines the relationship between temperature effects, or seasonal effect, for the demand function of electricity and price elasticity of electricity demand. Design/Methodology/Approach - We use the monthly data of electricity demand and price from Jan, 1981to Dec, 2018 in KESIS and KEPCO. Estimates of demand functions for electricity using Stata 14 might be biased because of identification problems. It is necessary to analyze whether control of temperature or seasonal effects utilized in many studies significantly deal with the identification of demand functions for electricity. Findings - Past literature showed that controlled temperature or seasonal effects have tended to be more sensitive to price elasticity of electricity than those that did not. Moreover, except for industrial power, estimates of long-term price elasticity on electricity demand is more sensitive when temperature or seasonality is controlled. Research Implications - The results imply that price elasticity estimates are likely to be downward biased in demand function model on electricity with only price and income as variables and these also highlight that control of temperature and seasonality is one of the ways to identify demand.

Key concepts: Price elasticity of demand, Electricity, Economics, Demand curve, Electricity demand, Elasticity (physics), Econometrics, Income elasticity of demand

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