臺灣地區住宅用戶之電力需求函數研究

郭騰隆

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臺灣地區住宅用戶之電力需求函數研究

Estimating the Electricity Demand Model for Taiwan's Residential Sector

郭騰隆 , Masters　　Advisor：錢玉蘭　　

繁體中文

住宅電力需求函數；追蹤資料；固定效果模型；隨機效果模型； Panel data ； Fixed effect model ； Random effect model

Abstract │ Reference (30) │ Times Cited (5) │ Altmetrics

Abstract 〈TOP〉

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With the growing of economy, industry and commerce have well developed and people's lifestyles have completely changed in Taiwan since 1970. At the same time, the electricity consumption also grows rapidly and Taipower starts to establish new power plant to solve this situation. But in recent years, Taipower encounters some problems due to the generating cost, land, government policy and people's protest. For descending the electricity consumption and cost, Taipower began a new policy of demand side management in 1979. The management can raise the efficiency of electricity and make people to change their behavior by using some rules. But now we still can see the raising of electricity consumption in Taiwan's residential sector. After reviewing some studies, it is hard to find that using the panel data to establish the electricity demand model. The advantage of panel data is easy to know the people’s behavior in different time, but the disadvantage is hard to collect the data of the same observations. In these studies, we also can find the correlation between electricity and some variables, such as income, price, CDD and HDD. Based on these research, this study uses the panel data of monthly electricity consumption about the 23 counties in Taiwan and some variables, such as real household income, real personal income, price, CDD, HDD and rain, to establish the electricity demand model of Taiwan's residential sector. The methods we use to estimate are fixed effect model and random effect model, and in these models we will consider the group effect and time effect. After estimating, the income elasticity is 0.003 and the price elasticity is positive and statistically significant. Besides we also find that CDD and HDD have positive sign and statistically significant. The rain has the negative sign. Finally, we can use Hausman test to determine the better model between fixed effect model and random effect model. According to the Hausman test, it is easy to find the fixed effect model is better than random effect model and in the fixed effect model we will considers the group effect and time effect at the same time.

Reference ( 30 ) 〈TOP〉

1. Pardo, Angel Pardo, Vicente Meneu, Enric Valor, 2002. “Temperature and Seasonality Influences on Spanish Electricity Load,” Energy Economics. 24:55-70.
連結：
2. Ziramba, Emmanuel Ziramba, 2008. “The Demand for Residential Electricity in South Africa,” Energy Policy. 36:3460-3466.
連結：
3. Hondroyiannis, George Hondroyiannis, 2004. “Estimating Residential Demand for Electricity in Greece,” Energy Economics. 26:319-334.
連結：
4. Bernard, Jean-Thomas Bernard, Denis Bolduc, Nadege-Desiree Yameogo, 2011. “A Pseudo-panel Data Model of Household Electricity Demand,” Resource and Energy Economics. 33:315-325.
連結：
5. Filippini, Massimo Filippini, Shonali Pachauri, 2004. “Elasticities of Electricity Demand in Urban Indian Households,” Energy Policy. 32:429-436.
連結：

Times Cited (5) 〈TOP〉

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