Assessing the causality relationship and time series model for electricity consumption per capita and human development in Colombia

Abstract

Increasing access to electricity is essential to improve human development in poor and developing countries. To this end, the relationship between electricity consumption and human development is critical to supporting the process of decision-making. However, the discussion on this topic is limited. In Colombia, developing adequate policies requires characterizing the impact of electricity consumption on human development. This study uses time series and the Human Development Index data and per capita electricity consumption between 1990 and 2018 to assess their relationship. Furthermore, the government projections for electricity consumption and population growth are used to forecast the Human Development Index up to 2030. To this end, the econometric and correlation approach is applied. The Lagrangian multiplier unit root was used to verify if variables are stationary, while cointegration tests were used to define if non-stationary variables are cointegrated. Moreover, the Granger causality test was used to assess the causal relationships between the variables, and the ARIMA model was applied for the correlation analysis. Results show a bidirectional relationship between the Human Development Index and the per capita electricity consumption. Moreover, the government’s projection of per capita electricity consumption is forecasted to have little impact on the Human Development Index up to 2030. Therefore, developing adequate policies to improve access to electricity while contributing to human development is essential. Particularly for low-income citizens and rural areas, especially in non-interconnected, vulnerable, and geographically marginalized communities. However, further discussion is needed to characterize energy inequality through income classes, departments, and economic sectors, which is one challenge for the government to meet sustainable development goals.