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Regression Analysis of Electrical Energy Consumption Per Capita

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Regression Analysis of Electrical

Energy Consumption per capita with Cross-Country data

 

Saubhagya Singh Jangpangi

November 2017

 

 

Abstract

This paper performs a cross-country analysis in order to help us determine what affects electric energy consumption across different countries, both in developing and developed countries. High technological electrical appliances in daily activities demand high consumption in the energy. The independent variables are per capita GDP, population, net energy import of a country (as a % of energy use), coal and petroleum reserves of a country, average latitude and mean temperatures in January and June. Demand for higher living standards and rapid population growth are among determinants in the increase of electricity consumption. After performing the linear regression by using data from authoritative websites (like World Bank, Energy Information Administration – EIA, etc.), a correlation between the independent variables and the dependent variable is confirmed.  

 

 

Keywords: Electric energy consumption, GDP, population, coal, temperature, energy resource endowment, petroleum, latitude

 

 

Introduction 

Electrical energy is produced and consumed all the time in all countries. This paper performs a cross-country analysis on what affects annual energy consumption. The data is collected for the year 2013. Annual electric energy consumption per capita is defined as the actual amount of energy consumed in a particular country per person. Since we want the analysis to be as comprehensive as possible, we want to make the sample size as large as possible, so the sample consists of countries of different level: developing countries and developed countries, countries from different states, countries with different culture, etc. People require energy since various economic activities are dependent on electricity and lifestyle change has resulted in people using more electrical appliances such as computer, washing machine, and vacuum cleaner. Increases in income also result in increases in electricity demand since they will use more electrical appliances especially air conditioners, heaters, and refrigerators which consume more energy. A rapid growth in population is causing changes in electricity energy demand from time to time. The goal of the paper is not only to determine the cause of energy consumption, but also to help understand the role of energy in economics. While country develops through time, power plant construction should follow the trend of development. The paper serves as a reference for policy makers to estimate extra power capacity needed according to GDP.  

 

 

Literature Review 

Income is an important determinant of electric energy consumption. Romero, Sandez and Morales (2001), suggest that there is a correlation between energy consumption and income level that is demonstrated in the situation of high income levels with high income energy consumption in Mexico. The paper,

Relationship between Electricity Energy Consumption and GDP growth: Evidence from India”, indicates the causality of energy consumption to GDP in India (Mohanty, 2015). It takes the energy consumption and GDP data from 1950-1951 and 1996-1997 in India to examine the causality and direction of the two variables. Its examination indicates causality of energy consumption to GDP growth and emphasizes the importance of the policy of “energy must lead economic growth”. The paper, "Energy Consumption and GDP: Causality Relationship in G-7 Countries and Emerging Markets", examines G-7 countries and concludes stationary linear relationship between energy consumption and GDP among all G-7 countries (Soytas, 2003).

 

Population is also an important variable that may affect annual electric consumption in different countries. However, it may also be true that a country with a relatively higher population may have a lower per capita electric consumption due to differences in economic development of the country. Various papers such as those by Xiang, Liu and Kim (cross-country analysis) and Lin, Chen, Luo and Liang (residential energy consumption in China) found population to have significant effect on electric energy consumption.  

 

The paper by Xiang, Liu and Kim also establishes that net energy export of a country significantly affects energy consumption, together with income and population.  

 

The paper by Lin, Chen, Luo and Liang, “Factor Analysis of Residential Energy Consumption at the

Provincial Level in China”, also show that coal reserves in particular Chinese provinces is significant at

10% level when regressed with income and population on energy consumption. According to them; Since it is difficult to find a standard indicator to measure the energy cost, coal reserves are used here to represent the energy cost as an approximation”. Average temperature in January also passes the hypothesis testing at 5 % level, though average temperature in August does not.     

 

Data and Methodology 

 

This study uses cross-sectional data of electric energy consumption of 131 countries in 2013. The data of energy consumption per capita (kWh), GDP per capita, total population, net energy import of a country (% of energy use) are taken from the World Bank website. GDP per capita is the ratio of gross domestic product (GDP) (in PPP, constant 2011 international $) to population. The coal and petroleum production values are derived from the U.S. Energy Information Administration (EIA). Since coal and petroleum and other liquids play an important role in energy production and consumption, their production are used as proxies to represent the country’s energy resource endowment. The average latitude of a country is approximated by using average latitude of the country’s capital. Average latitude and average temperature in January and June are taken from authoritative websites (link given in the references).

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