نوع مقاله : مقاله پژوهشی

نویسندگان

• پویان کیانی ¹
• کیومرث حیدری ¹
• مریم نفیسی مقدم ²

¹ استادیار، گروه پژوهشی اقتصاد برق و انرژی، پژوهشگاه نیرو، تهران، ایران

² دانش آموخته دکتری اقتصاد، دانشکده اقتصاد و مدیریت، دانشگاه تبریز، تبریز، ایران.

چکیده

هدف این مطالعه تحلیل کشش قیمتی تقاضای برق خانگی و غیرخانگی در 31 استان ایران در دوره زمانی 1400-1390 است. برای برآورد مدل با توجه به وجود چولگی در متغیر وابسته، روش رگرسیون کوانتایل انتخاب شده است. نتایج تحقیق نشان می­دهد که کشش قیمتی برای تقاضای برق خانگی در بازه 069/0- تا 115/0- قرار دارد. در حالی که کشش قیمتی برای تقاضای برق غیرخانگی در بازه 021/0- تا 043/0- قرار می­گیرید. بنابراین می­توان نتیجه گرفت که اگرچه در هر دو بخش کشش قیمتی تقاضا کم است اما تقاضای برق خانگی با کشش­تر از تقاضای برق غیرخانگی است. همچنین افزایش قیمت گاز طبیعی به عنوان نزدیک‌ترین جانشین برق تاثیر اندکی بر مصرف برق بخش خانگی و غیر خانگی داشته است. از دیگر نتایج مدل می‌توان به تاثیر بزرگ عادات مصرفی بر مصرف برق خانگی و غیرخانگی اشاره کرد

کلیدواژه‌ها

• کشش قیمتی
• تقاضای برق خانگی
• رگرسیون کوانتایل
• تقاضای برق غیرخانگی

موضوعات

• • مطالعات اقتصادی مرتبط با حامل‌های انرژی (فسیلی، تجدیدپذیر و برق)

عنوان مقاله [English]

Estimation of Price Elasticity for Electricity Demand in Iran: Using Quantile Regression

نویسندگان [English]

• Pouyan Kiani ¹
• Kioumars Heydari ¹
• Maryam Nafisi Moghadam ²

¹ Assistant Professor, Faculty Member of the Energy Economics Research Group, Niroo Research Institute, Tehran, Iran

² Ph.D. in Economics, University of Tabriz., Tabriz, Iran. Renewable Energy and Energy Efficiency Organization of Iran (SATBA), Tehran, Iran

چکیده [English]

The purpose of this study is to investigate the price elasticity of household and non-household electricity demand across 31 provinces of Iran from 2011 to 2021. Due to the skewness of the dependent variable, the panel quantile regression method was chosen. The results show that the price elasticity of household electricity demand ranges of -0.069 to -0.115. The price elasticity demand of non-household ranges from -0.021 to -0.043. It reveals that price elasticities are less than one for both groups. According to the results, electricity is an inelastic good in Iran. Also, the elasticity of electricity demand is higher for households than for non-household. Moreover, the results show that an increase in the price of natural gas, which is the closest substitute for electricity, has had a negligible impact on the electricity demand of the household and non-household sectors. Among other model results, we can mention the incredible influence of demand habits on household and non-household electricity demand.
 
Introduction
Electricity consumption in Iran has shown a consistent upward trend over time, particularly in the household sector. This increase is largely attributable to expanded access to the electricity grid, improved supply reliability, and the growing use of electrical appliances. Similarly, rising electricity intensity in industry and the increased use of groundwater through electric pumps in agriculture have deepened the reliance of non-household sectors on electricity. Given electricity’s vital role in enhancing welfare and driving economic development, analyzing its demand is of considerable importance.
Although numerous studies have estimated Iran’s electricity demand using various econometric methods, the novelty of this study lies in its application of the quantile regression approach to estimate demand functions for both the household and non-household sectors. This method enables the estimation of price, income, and cross-price elasticities across different demand levels, allowing for a nuanced evaluation of the impacts of pricing and income policies. Consequently, this study provides valuable insights for policymakers in designing effective and timely interventions.
Methods and Material
The primary advantage of quantile regression lies in its ability to capture how changes in independent variables affect different points of the dependent variable’s distribution. An analysis of electricity demand in the household and non-household sectors reveals that their distributions are non-normal, right-skewed, and contain numerous outliers. As a result, the ordinary least squares (OLS) method is not well-suited for identifying the determinants of these variables. Moreover, because quantile regression examines the entire distribution and provides a detailed depiction of the regression relationship, it is particularly appropriate for modeling skewed variables. Unlike conventional regression, which estimates the average effect of explanatory variables, quantile regression assesses these effects across various points of the conditional distribution (Coad and Rao, 2006; Mosteller and Tukey, 1977). Accordingly, this study applies the quantile regression approach to estimate electricity demand functions in both sectors.
Results and Discussion
In this study, electricity demand functions for both household and non-household sectors were estimated across 31 provinces in Iran during the period 2011–2021. The results show that the price elasticity of household electricity demand ranges from –0.069 to –0.115, whereas for the non-household sector it ranges from –0.021 to –0.043. This indicates that household electricity consumption is more sensitive to price changes than the non-household sector. Although substitution elasticities are low in both sectors, the household sector demonstrates greater responsiveness, particularly at higher consumption levels.
Another key finding is the positive effect of cooling degree days on household electricity consumption, suggesting that rising average temperatures and the consequent increase in cooling requirements are likely to boost household electricity demand. Furthermore, the income elasticity of household electricity demand is positive and significant at lower consumption levels, implying that in provinces with lower per capita electricity use, increases in household income lead to a more substantial rise in consumption. In contrast, the income elasticity of non-household electricity demand is higher at upper consumption levels.
Conclusion
A sound understanding of price elasticity enables policymakers to design pricing strategies that effectively influence consumption patterns and promote energy efficiency and conservation. The findings of this study indicate that the price elasticity of household electricity demand is greater than that of the non-household sector, suggesting that households are more responsive to changes in electricity prices. Accordingly, during the study period, electricity pricing policies proved more effective in curbing consumption in the household sector compared to the non-household sector.
The results also show that the price elasticity of non-household electricity demand declines at higher levels of consumption. This implies that pricing policies are more effective in reducing demand among lower consumption quantiles within the non-household sector than among higher ones.
Cross-price elasticity is positive for both sectors. Notably, the cross-price elasticity of household electricity demand is consistently higher than that of the non-household sector across all quantiles. This difference can be attributed to the nature of electricity use in the non-household sector, where substituting electricity with alternative energy sources is often more difficult and costly. For instance, in the industrial and agricultural sectors, switching from electricity to gas involves significant financial and logistical challenges. In contrast, households may more easily respond to rising gas prices by switching to electric stoves or heating appliances.
Based on the findings of this study, the following policy recommendations are offered:

Since consumption habits have a substantially greater influence on electricity use in both household and non-household sectors than electricity prices, there is significant potential for electricity savings through behavioral change. Thus, promoting the development of conscious, energy-saving habits is strongly recommended.

Reforming electricity tariffs is essential to ensure that price signals function effectively. Such reforms should reflect the true cost of electricity supply to support more efficient demand management, enhance energy efficiency, and improve resource allocation

کلیدواژه‌ها [English]

• Price Elasticity
• Household Electricity Demand
• Quantile Regression
• Non-Household Electricity Demand