An ARDL Approach to Check the Linkage Between Economic Growth, Electricity Access, Energy Use and Population Growth in Pakistan: Long-run and Short-run Analysis

The major aim of this study was to investigate and explores the linkage between economic growth, electricity access, energy use and population growth in Pakistan. To check the variables stationarity, Augmented Dickey-Fuller (ADF) and Phillips-Perron unit root test was applied and an Autoregressive Distributed Lag (ARDL) bounds testing approach to co-integration was applied to investigate the dynamic causality link among the study variables. These tests shed light on the long-run connection among the variables; further, the results revealed that electricity access to population, electricity access to urban population, energy usage, population growth, and urban population growth had a significant impact on economic growth, while the electricity access to rural population and rural population growth has a negative impact on the economic growth in Pakistan. According to these findings, study commends that government of Pakistan pay further attention to increase its electricity production from different sources including, hydroelectric, solar, oil and gas and nuclear in order to fulfill the country’s demands. By using ARDL bounds testing approach, this study filled the literature gap regarding economic growth, electricity access, energy use and population growth in Pakistan.


Introduction
Energy has dominant role in the economic development and also a fundamental part of any national economy. It relates to energy security, economic development and social stability. Electricity has vital value and is considered the useful source of energy that boosts to support every part of the economy. Over past few decades, policies failure in the energy sector of Pakistan plunged the country into a severe power crisis, leading to poor economic performance in the country and demand of electricity is determined by the population growth and other factors, including electricity prices, people movement to the cities and weather. However, Pakistan's unique problems and the transformation of electricity shortage and crisis are due to theft, abuse and excessive usage of electricity in the industrial sectors and home, unreasonably causing huge line losses, corruption, mismanagement, institutional weakness, and political controversy [1]. In 2011, the population growth ration in Pakistan was 176.17 million as it was 79.98 million in 1980, and due to growing population demand is increasing which creates directly effect on the electricity escalation [2].
The South Asian Region (SAR) faces several deficiencies that cause the national system of electricity for a particular time. The electricity supply has not kept stride with growth and demand, resulting in long-term downtime and frequent unplanned outages. These conditions have created difficulties for families and industries and have hampered new investment in the business of any economy [3]. Pakistan has a population of about 184 million people and the rural population is high which is connected with agriculture. The agricultural sector has contributed about 25% to the GDP and provides employment more than 40% to the labor force [4]. The installed power generation in 2011 was 21036 megawatts. The demand of electricity is increasing about 9% a year, while the supply deprived monetary administration are the main reasons for the letdown of electricity sector in Pakistan [19,20]. The shortage is due to the lack of political instability and large investment which has hindered the projects of hydropower or coal, thereby increasing need on imported expensive fuels and plummeting the local natural gas [21]. The country's growing population, industrialization and average household income have contributed to the growth in electricity demand [22]. Social and economic progress depends on energy flow. Currently, country is producing insufficient energy and facing crisis. Despite renewable energy sources, still traditional energy generation methods are using in the Pakistan. In the present period, energy efficiency has amplified, but energy generation systems have not been updated to meet energy needs [23,24]. The electricity deficit in 2013 was 6000 megawatts (MW), which is less than 4000 to 5000 megawatts per year, and gross domestic product decline to 3-4% due to crisis of energy. The crisis has seriously affected the economy of Pakistan due to industry closures [25,26].
Electricity is an important infrastructure for a country's socio-economic development, and it has a robust correlation among consumption of electricity and economic growth [27], but growth in the electricity is hugely sensitive to local differences and domestic income levels [28]. The traditional electricity generation systems typically rely on a large number of power generation equipment. Regarding the huge size, it would be placed in the suitable geographic location. The generated electricity will be delivered to the grid station with heavy duty transmission lines and then from grid station to the users. These sources belong to renewable sources including solar, hydro, and wind [29].
In the agricultural and industrial products Pakistan having good rank in the world due to production, but energy problems are still existing in the country due to lack of government sufficient measures. However, major cause is related to government management measures, and Pakistan is facing a severe energy crisis due to geopolitical uproar and also lack of interest [30][31][32]. In order to gain adequate, inexpensive and environmentally friendly energy, necessary steps should be adopted to produce alternatives mixture and existing renewables sources of energy. Many authors suggest that developing countries and developed countries use renewable energy as an alternative and sustainable energy and conventional energy [33][34][35][36][37][38][39][40][41][42]. Pakistan belongs to South Asia and most of the population living in rural areas is not linked to the power grid. The key part of rural grid electrification does not exist. The reason is that some rural areas have complex geography, moderately low electricity demand, and huge cost of long delivery systems. Furthermore, there is a daily shortage of electricity in rural areas connected to the grid, mainly through the summertime. The electricity access to population, electricity access to rural population, electricity access to urban population, energy usage, population growth, rural and urban population growth from 1980-2016 is illustrated in Figures 1-8.        Figures 1-8 represents the electricity access to population, electricity access to rural population, electricity access to urban population, energy usage, population growth, rural and urban population growth.

Data source
Time span data from 1980-2016 was used in this study which is collected from the WDI (World Development Indicators). Below table represents the variables used in this study:

Model Specification
To check the association among dependent and independent variables, the model follows the Fatai (2014) [43] specification to adopt the regression procedure. The multivariate regression model specification is as follows in its implicit forms as; (1) In the equation 1, GDPPC t indicates the gross domestic product per capita, AEP t represents the electricity access to the population, AERP t indicates the access of electricity to rural population, AEUP t represents the access of electricity to urban population, EN t indicates the energy use, PG t show the population growth in Pakistan, RPG t represent the rural population growth and UPG t indicates the urban population growth.
GDPPC t = Ψ 0 + Ψ 1 AEP t + Ψ 2 AERP t + Ψ 3 AEUP t + Ψ 4 EN t + Ψ 5 PG t + Ψ 6 RPG t + Ψ 7 UPG t + μt (2) By using natural logarithm to equation 2, a log-linear model is as follows: lnGDPPC t = Ψ 0 + Ψ 1 lnAEP t + Ψ 2 lnAERP t + Ψ 3 lnAEUP t + Ψ 4 lnEN t + Ψ 5 lnPG t + Ψ 6 lnRPG t + Ψ 7 lnUPG t + μt (3) is the log-linear form of the variables. lnGDPPC t show the natural logarithm of gross domestic product per capita, lnAEP t show the natural logarithm of access of electricity to population, lnAERP t show the natural logarithm of access of electricity to rural population, lnAEUP t show the natural logarithm of access of electricity to urban population, lnEN t show the natural logarithm of energy use in Pakistan, lnPG t show the natural logarithm of population growth in Pakistan, lnRPG t show the natural logarithm of rural population growth, lnUPG t show the natural logarithm of urban population growth, t is the time dimension, μt is the error term, and the coefficients of the model Ψ 1 to Ψ 7 represent the elasticity of the long-run.

Unit root test for stationarity
Despite the fact that the Autoregressive Distributed Lag (ARDL) model requires no pre-testing for inspection of variables stationarity through the unit root test. The ADF (Augmented Dickey-Fuller) (1979) [44] unit root tests and Phillips-Perron (1988) [45] unit root test with trend and intercept was used to determine that none of the variables considered were integrated to order 2. Because ARDL bounds testing approach is invalidated in cases where I(2) variables are used. Therefore the unit root test was performed using equation 3.
Where, Z indicates the variables being tested for the unit root, T represents a linear trend,  indicates the first difference, t shows the time, μt is the error term and m represents to achieve white noise residuals.

Co-integration with ARDL Model
Pesaran and Shin (1998) [46] developed the ARDL bounds testing approach to check the analysis of long-run and short-run relationships, and further protracted by Pesaran et al., (2001) [47], and Narayan et al., (2004) [48]. The co-integration testing approach (Johansen & Juselius, 1990) [49] is applicable regardless of the integration order with concerned variables, I(0) and or I(1), except for the occurrence of I (2). The long-run and short-run relations examined the ARDL representation of the unrestricted error correction model (UECM) of equation (2) as depicted in equation (5): Where,  indicates the difference operator, Ψ indicates the coefficients of long-run, while γ

Descriptive Statistics and Unit root tests results
Descriptive statistics results are interpreted in the Table 2, and Table 3 reports the results of Augmented Dickey-Fuller (ADF) unit root test and Phillips-Perron unit root test with intercept and then both intercept and trend.  ADF unit root test results and P-P unit root test results indicated that none of the variables was integrated with the order of I(2) and then ARDL model employed.

Co-integration Test
Co-integration test was used when F or W statistic applies upper bound of the selected significant level. It is worth noting that the F test assumes that there is no cointegration null hypothesis between variables. Cointegration results are illustrated in the Table 4.

Covariance Analysis
Covariance analysis results are stated in the Table 6, with having correlation among the dependent and independent variables.

Long-run Analysis Results
Long-run analysis results are interpreted in Table 7. Focusing on the elasticity of the variables in the long-run analysis, results revealed that access of electricity to the population of Pakistan has positive and significant impact with economic growth having coefficient of 1.310100 with p-value 0.6983. Similarly the coefficients of the electricity access to urban population, energy usage, population growth, and urban population growth had a positive and significant impact with economic growth. The coefficients of the electricity access to urban population, energy usage, population growth, and urban population growth are 3.079896, 2.288282, 6.617094 and 0.308340 with their p-values 0.3127, 0.0016, 0.0399 and 0.8886 respectively. While the results of the electricity access to rural population and rural population growth has a negative impact on the economic growth having coefficients -0.891821 and -3.988076 with p-values 0.6426 and 0.0089. The negative impact regarding electricity access to rural population caused the reason due to insufficient electricity production in the country and its supply to the rural population of the country. The supply and demand of the energy having huge gap regarding flared with the passage of time, country has limited sources to produce electricity from liable sources including solar, natural gas, wind energy, hydropower and nuclear. The urban areas in the country are facing abundant load shedding while in the rural areas facing more load shedding as compare to urban areas [50,51]. Table 8 depicted the short-run analysis results. Among the connection of variables, cointegration presence requires an error correction model (ECM) to imprisonment the dynamics of the short-run relation with its coefficient, which measures the adjustment speed. The estimated value of the R-squared is 0.996705 in the dynamics of short-run relation, which show about 99% variation in the economic growth was described in the model by the independent variables. The joint significance regarding the independent variables confirmed the F-statistic at level of significance 1%. The value of DW statistic was 2.575, which was not equaled to the standard DW value for resistant of nonappearance of any autocorrelation. While this is great enough to expose the model of any autocorrelation exists.

Short-run Analysis Results
Diagnostic and stability tests results are presented in table 9.

Structural Stability Test
The stability tests using CUSUM and CUSUM Square point to stable the long-run and short-run constraints. The graph of both CUSUM test and CUSUM Square test are mentioned in the Figures 9-10 which specify that all values lie within critical boundaries at significance level of 5%. It confirms the long-run and short-run parameters stability. CUSUM of Squares 5% Significance Figure 10. Plot of CUSUM of Square.

Conclusion and Recommendation
Pakistan has energy crisis from last few decades due to insufficient production and supply which cause the electricity shortage in the country. The key motive of this study was to explore and investigate the linkage between electricity access, energy usage and population growth and economic growth in the Pakistan. ADF unit root test was used to check the variables stationarity, and ARDL bounds testing approach to co-integration was applied to check the causality relationship among the study variables. The results revealed that access of electricity to the population of Pakistan electricity access to urban population, energy usage, population growth, and urban population growth had a significant impact with economic growth, while the electricity access to rural population and rural population growth has a negative impact on the economic growth. As the population of Pakistan is increasing with the passage of time, more electricity is required to fulfil the country needs. New policies should be implemented regarding to boost the energy sector in the country. Government should also pay attention to alternatives of the energy to produce from natural gas, oil, coal, nuclear power, solar and wind. Natural gas and oil are the dominant source of the energy in the country. Possible initiatives are necessary to produce energy from solar system to supply cheap electricity to the population of the countries. Regarding production from hydropower, necessary steps should be taken to build the new dams in the country to store water, which also important for the agricultural growth. Because in coming few years, Pakistan will also face the water crisis, which will be the big threat to the country. There should be short-term, medium-term and long-term energy production plans from the government to produce cheap energy to fulfill country demands.