How energy consumption, industrial growth, urbanization, and CO2 emissions affect economic growth in Pakistan? A novel dynamic ARDL simulations approach
Introduction
The primary determinant of economic development and social stability is energy supply. The use of energy resources has also increased over time due to rapid growth and technological innovations. Electricity performs a vital role in the productions and consumptions of goods and services within the economy [1]. Pakistan is attempting to overcome a severe, in terms of changing its energy mix, that is directly or indirectly affecting each sector of the economy. However, the inefficiencies of energy in the past has disintegrated the country’s economy. In 2013–18, enormous governmental projects were launched to fix congestion and bottle necks of inefficient delivery of energy services with a combined capacity of 12,230 MW integrated into the supply-side. Furthermore, high energy prices in the present and immediate future are a by-product of such aggressive additional capacity during the aforementioned period. Fig. 1 illustrates electricity generation sources of Pakistan in 2018. Further, Fig. 1 reveals that biofuels and waste, oil and natural gas are the major sources of generation with percentage share 33%, 26% and 25% in kiloton of oil equivalent (ktoe), respectively. Natural gas is an environmentally friendly, renewable, safe and reliable source. The indigenous sources make up approximately 25% of the country’s overall primary energy mix. Pakistan has a large gas network with a reach of more than 12.971 km transmission 139.827 km delivery and 37.058 gas pipelines to meet the needs of more than 9.6 million customers throughout the country. Regarding the proportions of various power generation sources, it should be noted that there has been a decline in hydro electricity generation over the last couple of decades [2]. Water scarcity is the main reason for reducing hydropower production. Biofuels and waste generation currently has the largest share. While, specific cheaper sources include wind and hydro. However, biofuels, oil and natural gas has led to massive demand growth in its energy mix. The Government has emphasized an alternative contribution to the production of electricity by renewables. However, remaining supplies are provided in fertilizer, manufacturing, and transport sectors via various power stations such as KAPCO, Havli Bahadur Shah, Balloki, Saif, Orient, Rousch, Bhiki, Halmore, and Sapphire.
The economic growth factors in Pakistan must be investigated. There is still a considerable gap to improve Pakistan’s economic growth, but the inability to provide sufficient, uninterrupted, and accessible electricity is an enormous obstacle. The main reason for Pakistan’s electricity scarcity is misleading information about future demand in the market, which is crucial for electrical generators, consumers, and policymakers. For long-term sustainable economic development, forecasting needs accurate data on electricity consumption trends, existing infrastructure, and potential challenges. However [4,5], examined energy that can be quickly addressed by referring to electricity demand management. Underestimating the electricity demand would result in possible failures, with overestimation leading to needless redundancy of capability and financial resources loss. Numerous studies have concentrated on economic growth and its factors in the last three decades, for example [6,7], but the findings remain contradictory. The literature on the causal link covers the following three broad areas: the first argues that non-linear causality goes from electricity use to economic progress, known as the theory of growth. Conversely, the second argument is that a unidirectional correlation exists, known as the recycling theory. Ultimately, the third aspect claims that there are no causal links among the variables, recognized as the neutrality hypothesis.
Our research is distinguished from previous studies and refers to the current literature regarding collecting variables and empirical analysis methods. This study contributes and addresses the gap in the literature by using various determinants not recognized in earlier studies, such as [[8], [9], [10], [11], [12]]. These studies have used different variables, period, and methodology in Pakistan, and the economic structure changed significantly during the study period. It is vital to understand to what extent the relationship established in existing literature still holds for Pakistan. Using multivariate time series data from 1972 to 2018, the current study explores the relationship between energy consumption, energy prices, industrial value-added, urbanization, and CO2 emissions and Pakistan’s economic growth. This study also contributes to the literature by incorporating new factors, such as urban population and industry value-added, that, to the best of our knowledge, have not previously been applied in this case. It reveals the time series’ statistical properties and specifies the positive and negative presence of a long- and short-run associations among the determinants. For empirical analysis, we use a novel dynamic autoregressive distributed lag (ARDL) model recently introduced by Ref. [13]. Finally, we applied [14] frequency domain causality (FDC) test because it helps to differentiate permanent causality for long, short and medium-term among time series variables, we also use this test for the robustness check. Our results reveal that electricity consumption and industrial value-added have a long-run impact on Pakistan’s economic growth. This current research helps officials in the energy sector make strategic planning and long-term decisions after reviewing the outcomes.
The remainder of this paper organized as follows. Section II presents a review of the literature. The material and methods are outlined in section III while section IV outlines the empirical results and discussion. Finally, conclusions and policy implications are provided in section V.
Section snippets
Literature review
Energy plays a significant role in economic development. The first study by Ref. [15] investigated the relationship between energy use and economic development through various econometric approaches over different periods. From the perspective of an economist, energy is an input for output; however, empirical data reveals that the source of energy growth is complex. Partly due to the vital role of electricity in viable economic development, there are comprehensive theoretical and empirical
Data collection
The time series secondary data for 1972–2018 are used for empirical analysis. Table 2 reposits the data sources for the variables used in this study.
Model specification
This study empirically analyzes qualitative and inferential statistics methods. A multivariate time series approach is applied for empirical purposes. The main advantage of yearly secondary data excludes the consequences of seasonal variation. All series were transformed into logarithmic form to eliminate the heteroscedasticity issue. Time series
Empirical results and their discussion
We scrutinize the descriptive statistical analysis reported in Table 3 to investigate the characteristics of the variables. Table 3 provides an overview of statistics showing the mean, maximum, minimum, and standard deviations of the variables. In addition to characterizing the summary statistics, it also represents the peak by Kurtosis, and the normal pattern of distribution with the support of Jarque−Bera test statistics where the mean of energy prices is 24.89 greater than other variables.
Conclusion and policy implications
This study explored the relationship between electricity consumption (EC), electricity prices (EP), industrial value-added (IVA), urbanization population growth (UPG), and CO2 emissions with gross domestic product (GDP) for the period 1972–2018 for Pakistan. After carefully reviewing the literature, this study selected distinct determinants to examine the impact of various factors on economic growth in Pakistan. In earlier studies, a simple ARDL bounds testing approach was used for long- and
CRediT author statement
Kashif Raza Abbasi: Conceptualization, Methodology, Formal analysis, Software Data curation, Writing- Original draft preparation Muhammad Shahbaz: Supervision Zhilun Jiao: Software, Validation, Review & Editing Writing Muhammad Tufail: Visualization, Investigation, Resources, Data Curation.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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