Abstract
In this paper we examined the interaction between greenhouse gas emissions, nuclear energy, coal energy, urban agglomeration, and economic growth in Pakistan by utilizing time series data during 1972–2019. The stationarity of the variables was tested through unit root tests, while the ARDL (autoregressive distributed lag) method with long and short-run estimations was applied to reveal the linkages between variables. A unidirectional association between all variables was revealed by performing a Granger causality test under the vector error correction model (VECM) that was extracted during the short-run estimate. Furthermore, the stepwise least squares technique was also utilized to check the robustness of the variables. The findings of long-run estimations showed that GHG emissions, coal energy, and urban agglomeration have an adversative association with economic growth in Pakistan, while nuclear energy showed a dynamic association with the economic growth. The outcomes of short-run estimations also show that nuclear energy has a constructive association with economic growth, while the remaining variables exposed an adversative linkage to economic growth in Pakistan. Similarly, the Granger causality test under the vector error correction model (VECM) outcomes exposes that all variables have unidirectional association. Furthermore, the outcomes of the stepwise least squares technique reveals that GHG emissions and coal energy have an adverse association with economic growth, and variables nuclear energy and urban agglomeration have a productive linkage to the economic growth in Pakistan. GHG emissions are no doubt an emerging issue globally; therefore, conservative policies and financial support are needed to tackle this issue. Despite the fact that Pakistan contributes less to greenhouse gas emissions than industrialized countries, the government must implement new policies to address this problem in order to contribute to environmental sustainability while also enhancing economic development.
Highlights
A unidirectional association between all variables was revealed by performing a Granger causality test under the vector error correction model (VECM)
We investigated the integration order of each variable such as economic growth, greenhouse gas emissions, nuclear energy, coal energy, and urban agglomeration by using the Dickey Fuller (DF-GLS) [67], Philips-Perron (PP) [68], and KPSS [69] unit root tests
We have examined the interaction between greenhouse gas (GHG) emissions, nuclear energy, coal energy, urban agglomeration, and economic growth in Pakistan by utilizing annual sequence data series during 1972–2019
Summary
The consumption of energy has risen dramatically during the past century as a result of many breakthroughs and everyday improvements. Of human life is becoming increasingly reliant on energy. Cheap and dependable energy is essential for all nations, but this is especially true for the developing countries. Demand for energy has risen in many nations as a result of increasing industrialization, agricultural modernization, globalization, and better transportation. In the absence of investment in domestic resources such as water power, natural gas, and lignite, Pakistan remains reliant on energy imports. The biggest source of energy is biomass. Public oil and gas companies are considering privatization for a number of reasons [1]. Pakistan is 43.5% reliant on imported oil for its entire energy mix
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