The effect of gross domestic product, urbanization, trade openness, financial development, and renewable energy on CO₂ emission

Abstract

The purpose of this study is to analyze the influence of GDP, urbanization, trade openness, financial development, and renewable energy consumption on CO₂ emissions in Pakistan using yearly time series data from 1985 to 2018. The study utilized the cointegration technique and Granger causality for empirical estimation. The results of the study indicated that urbanization, financial development, and trade openness upsurge CO₂ emission. Whereas using renewable energy resources is favorable for the environment and possesses negative relation with CO₂ emission. All variables possess long-run relation with Co₂ emission. Granger causality shows unidirectional causality from GDP and renewable energy to CO₂ emission. The study contains insight for policymakers in Pakistan with beneficial policy recommendations to work toward a sustainable green environment.

Introduction

Many global climate-energy initiatives now explicitly aim to achieve net-zero CO₂ emissions. The common characteristics and tradeoffs of energy systems across global scenarios at the point of net-zero CO₂ emissions have not yet been studied, even though considerable research has evaluated net-zero emissions routes. In the broader context of climate stability, the rate of global temperature rise is directly correlated with total CO₂ emissions, meaning that any increase in atmospheric CO₂ will result in more warming in the future (Rogeljet al. 2015). Given these factors and facts, it is a specific target to reach net-zero emissions. This is becoming a more prevalent objective for energy and emissions policymakers worldwide. Rapid and broad energy system transformation, including significant energy and material efficiency increases, extensive electrification of energy end uses, and carbon control, are essential to achieving this aim. Now, there are different policies and procedures or measures which can be adopted to overcome it (DeAngelo et al. 2021).

In light of this environment, energy analysts are increasingly examining the difficulties and potential associated with net-zero emissions energy systems, including in-depth studies of various energy services and technologies. Recent studies have looked at the energy system mitigation paths in integrated assessment model (IAM) scenarios that keep warming to below 1.5 °C, giving insight into potential changes to the energy-economy-land system.

The threat of global warming has increased awareness in all spheres of life by 60 percent to lessen the terrible scenario that faces the entire world. Human activity on the earth’s surface, which results in environmental devastation, is the primary cause of climate change (Adedoyin and Bekun, 2020). Since global warming has become a problem, individual nations and the entire world are expected to prepare and act to mitigate it. Because of the serious climate change issue, domestic and international attention has been drawn to it (Alola et al. 2019). The air is contaminated by the emissions of many energy sources, especially fossil fuels and other nonrenewable energy sources. They will harm the environment and the general public’s health. Clean water sources and wetlands are also accessible to air pollutants, which harm or kill marine life and contaminate clean water. The average temperature of the earth’s surface has increased, ice glaciers started melting, alarming not just humans but also our planet’s weather and climate systems. All this situation enhances natural disasters and could destroy the world’s climate. The annual GDP of countries will shrink to 2–4% by 2040 (Solomon et al. 2007).

Among other things taken into account, economic growth has been said to have a devastating effect on pollution. Many economic practices based on and geared toward economic growth contribute to the emissions of pollutants (Bekun and Agboola, 2019). Economic expansion, including economic activity from many industries (agricultural, petroleum, energy mining, and manufacturing), all operate as pollution and CO₂ triggers (Udemba 2020).

Adebayo et al. (2021a, b) and Kirikkaleli et al. (2022) demonstrate that energy use and economic expansion are the primary causes of environmental degradation in many countries and locations. Zhang et al. (2021) study concluded that using energy from nonrenewable sources produces more CO₂, which reduces the viability of the ecosystem. The positive correlation between the use of fossil fuels and economic growth suggests that GDP growth drives up energy use and CO₂ emissions, which supports this stance.

Pakistan has been one of the top 10 nations impacted by climate change during the past 20 years. Pakistan has been one of the top ten countries most affected by climate change in the past 20 years due to frequent natural disasters like floods, droughts, heat waves, and cyclones. According to a news release, Pakistan had an average climate risk score of 29.1 from 2000 to 2019, saw 173 catastrophic occurrences, had a $3.77 billion economic loss, and had 502.45 fatalities per year (https://www.thenews.com.pk/print/937671-pakistan-among-top-10-countries-affected-by-climate-change-in-last-20-).

Research objective

This research aimed to investigate.

• the impact of renewable energy (RE) on CO₂ emissions in Pakistan,

• the impact of consumption on CO₂ emissions in Pakistan,

• the impact of gross domestic product on CO₂ emissions in Pakistan,

• the impact of urbanization on CO₂ emissions in Pakistan,

• the impact of trade openness (TO) on CO₂ emissions in Pakistan, and

• the impact of financial development on CO₂ emissions in Pakistan.

Problem statement

Industrialization and increased consumption of the growing population collaterally damaged the environment slowly with the passage of time. Industries released harmful gasses into the atmosphere without proper treatment. Increased levels of CO₂ started to trap the heat within the hemisphere of the earth. Now, it has been watched that worldwide warming caused by CO₂ outflows is one reason for warm waves, extraordinary climate, increased floods, the yearly increase in average temperature, melting of ice glaciers, and rising sea level. At the start, no one peeped into the matter, but the voice from all over the world rose when this destruction reached to its maximum level. Now, all environmental agencies, governments, and researchers started digging out the causes of CO₂ emissions. The focus of all is a shift of industries toward green methods and green innovations, technology, sustainable environment, and boosting usage of renewable sources of energy to reduce the level of CO₂ in the atmosphere in future decades.

Literature review

Environmental Kuznets curve (EKC), which Kotroni (2020) analyzed, shows mixed results between environmental decadence and economic growth, which intrigued a scholar to look at it unexpectedly. This research states that every country undergoes industrialization, which overcomes agriculture and economy shift to the cities that create an inequality situation where the owner of the industries holds a major part of the income and the employee seems to have decreased in their income. Furthermore, Kuznets stated that inequality had followed an inverted “U” shape as it increased and then decreased again with increased income per capita. He stated initially that GDP (growth) is positively related to environmental pollution, and it causes environmental pollution until it reaches a reasonable point where it starts decreasing because of many changes from new investments in the pollution-free economy and clean industrialization. CO₂ frequently rises with the rise of economic activities.

Nasir and Rehman (2011) for Pakistan revealed a positive relationship between trade openness and CO₂ emissions in the long run. Salah-Uddin et al. (2016) studied the long-run relationship between trade openness, economic growth, energy consumption, and carbon emission in Sri Lanka between 1971 and 2006. The study confirmed a causal long-run relationship between economic growth and CO₂ emissions.

Isik et al. (2018) studied linear and nonlinear relationships between tourism demand, RE consumption, and GDP (growth). The annual data of 126 countries covering the period from 1995 to 2012 was utilized. Results of the study indicate that there are 2-way cause-and-effect relationships between RE and GDP (growth) in countries like T‐7 (51.59–66.11). One way called unidirectional causal relation exists from RE consumption to GDP (growth) in Spain (6.13) and exists from GDP (growth) to RE consumption in China (4.23), Turkey (5.96), and Germany (2.54) was found, further showing that there is a causal relation exist from tourist arrivals to GDP (growth) in the T‐7 countries (31.26). Furthermore, this study investigates scientists and other policymakers who have frequently been working on developing RE alternatives and other sources to reduce the dependence on traditional energy sources because these sources reduce the negative impact on the environment.

Heydari et al. (2019) studied the relationship between renewable energy generation and CO₂ emissions. The data from Canada, Italy, and Iran is utilized from1980 to 2015. Cointegration, regression, and Granger causality tests were used in the study. The study’s results confirmed that increased use of renewable energy reduces fossil fuel utilization, which increases carbon emissions. The finding of this study declared physical evidence to enhance the usage of renewable energy to overcome CO₂ emissions. Marques et al. (2018) empirically analyzed the dimensions of energy growth, the emission of CO₂, and how this affects the Australian environment by energy consumption. The study’s focused variables were coal, oil energy sector, and CO₂. The study period covered from 1965 to 2015. The results indicated that the utilization of RE reduces fossil fuel usage, which in return reduces the emission of CO₂. The study implies that Australia should boost the proportion of RE and decrease the proportion of fossil fuels. Kwakwa and Alhassan (2018) conducted a study on Ghana. They found that hydro energy, waste energy, and combustible renewable reduce CO₂ emissions, while the generation of electricity from fossil fuels puts upward pressure on CO₂ emissions.

Wang and Dong (2019) found in 14 sub-Saharan African countries that environmental pollution can be reduced by renewable energy, while there is the opposite effect of nonrenewable energy. Bulut (2019) studied USA data to investigate the relationship between renewable energy and CO₂. The study found that RE has a negative relation with CO₂ emissions, which means that whenever the consumption of RE increases, it will decrease CO₂ emissions. Moorthy et al. (2019) analyzed some barriers that significantly impact RE development. They found that social and regulatory barriers are directly affecting the development of RE. Breaking these barriers will enable organizations to invest in developing new technologies that are less harmful to the environment and increase the usage of RE further with fewer tariff energy solutions available for local people. Zafar et al. (2019) revealed the variables which affect environmental quality. The study variables included globalization and financial development (OECD countries). The study covered the period from 1990 to 2014. Results showed stimulated relation of energy which consumed on CO₂. Financial development and environmental quality have been negatively associated with CO₂; environmental quality will decrease pollution when FD and environmental quality increase. Results endorsed that long-run cointegration exists, and a bidirectional relationship exists between energy consumption and CO₂. The study’s conclusion shows that energy consumption (EC) is the main culprit in increasing pollution. Researchers recommended that policymakers increase the other energy sources, including wind, solar energy, biodiesel and green technology, to enhance environmental quality.

Chien et al. (2021) validated the EKC hypothesis and showed a positive relation between economic growth and CO₂ emission, while renewable energy and technological innovation possess a negative relation with CO₂ emission in the context of Pakistan. Namahoro et al. (2021) studied the long-run effects of energy consumption and economic growth on CO₂ emissions regionally and globally. The study found that extreme energy usage and economic growth promote CO₂ emission, but renewable energy affects CO₂ emission negatively. Godil et al. (2021) investigated the cause and effects of economic growth, technology innovation, and renewable energy in the transport sector on CO₂ emissions in China. The study results show that renewable energy consumption and innovation reduce CO₂ emission, but GDP has a positive relationship with CO₂ emission. In this case, trade is the main component of economic development.

Maheswaranathan and Bhavan (2022) examined the Sri Lankan trade and CO₂ emission relationship over the years, which shows a significant effect of trade on CO₂ emission because trade compels to produce at a massive level with high-level energy consumption. Uğurlu (2022) studies the impact of GDP per capita, renewable energy consumption, and urban population on CO₂ emission in the Visegrad countries and EU climate policies. The study concludes that GDP per capita and urban population have a positive relationship, while renewable energy consumption negatively impacts CO₂ emissions.

Research methodology

Data and variables

The study utilizes yearly time series data covering the period from 1985 to 2018 for six variables, gross domestic product (GDP), urbanization (UP), trade openness (TO), financial development (FD), renewable energy (RE), and carbon dioxide (CO₂), mined from WDI. Table 1 shows the variables statistics summary.

Table 1 Descriptive statistics

Empirical model and method

The study’s econometric model specification is as follows:

$${CO}_{2t}={\alpha }_{0t}+{\beta }_{1t}\left(FD\right)+{\beta }_{2t}\left(GDP\right)+{\beta }_{3t}\left(RE\right)+{\beta }_{4t}\left(TO\right)+{\beta }_{5t}\left(UP\right)+{\varepsilon }_{t}$$

where CO₂ is the per capita emission of carbon dioxide in metric tons; FD (private sector) is the development of institutions and markets, measured as a country-to-country credit provided to the private sector by the financial sector (% of GDP); GDP (growth) is the gross domestic product, calculated by adding exports and imports of goods, services, and productions measured as a significant share of GDP (growth); RE is the consumption of renewable energy produced from hydropower, solar, and wind (% of total final energy consumption); TO (trade openness) is the cross border trade calculated as a percentage of GDP; UP (urbanization) is the percentage of the population living in industrial cities and ɛ (error term).

Model hypothesis

• H1: There is a significant impact of GDP (growth) on CO₂ emissions in Pakistan.

• H2: There is a significant impact of financial development (private sector) on CO₂ emissions in Pakistan.

• H3: There is a significant impact of the urban population on CO₂ emissions in Pakistan.

• H4: There is a significant impact of trade openness on CO₂ emissions in Pakistan.

• H5: There is a significant impact of renewable energy on CO₂emissions in Pakistan.

Results

Unit root analysis

The first variable’s stationary properties were tested using an augmented Dickey-Fuller (ADF) unit root test because time series data mostly contain unit root problems, leading to bogus results. Thus, before moving to the next stage, the stationarity of variables at level or integrated orders must be carefully observed. The stationary level of variables decides the data analysis and method used at the next level (Table 2).

Table 2 Unit root test

Regression analysis

The percentage of change in the dependent variable concerning per unit variation in the independent variable is called the regression coefficient. Regression analysis is used to determine the relationship of variables. It identifies one or more independent variables that keep a relationship with independent variables. Table 3 concludes the regression result summary of variables. The t-stat figures predict that FD (private sector), RE, TO, and UP have a significant effect on CO₂ emission, but these variables impact differently in terms of their signs. TO, FD (private sector), and UP have positive effects on CO₂ emission, which concludes that any upsurge in these variables will increase CO₂ emissions.

Table 3 Time series regression (fixed effects)

On the other hand, when we analyze the result of RE and GDP, both have negative coefficients, which means adverse effects on CO₂ emissions. These results validate if there is a one-unit increase in RE, it will decrease the CO₂ emission with the same coefficient defined. Furthermore, Table 3 shows that GDP (growth) insignificantly affects CO₂ emissions. The possible reason behind that the GDP of Pakistan is unsustainable and it also faces several fluctuations. Moreover, there is also a major contribution of agriculture to the GDP of Pakistan. The findings demonstrate that the CO₂ emission will increase by 0.0056 units with a one-unit increase in FD (private sector). On the other hand, a one-unit increase in RE will decrease CO₂ emissions by 0.0093 units. The reason behind such results is that natural energy resource positively and significantly influences the ecological footprint.

Further results show that the emission of CO₂ will increase by 0.0068 units with a one-unit increase TO. A single unit increase in UP will increase CO₂ emission by 0.0531 units. As urban areas are industrial hubs, the increase in population in urban areas will increase the demand for transportation. In Pakistan, all transportation channels utilize fossil fuels and are a big source of CO₂ emissions. Furthermore, it is confirmed that independent variables have a jointly significant effect on CO₂ emission and that the overall model is significant (F-statist value 143.9597). The result of Adj. R² reflects that there are 95.589% chances that the CO₂ emission depends on FD, GDP, RE, TO, and UP. In other words, whenever CO₂ increases, there is a 95.5870% chance that these variables will be the reason for the increase.

Cointegration test

Johansen cointegration test has been applied to estimate long-run relationships among variables. Trace statistics is the main measurement tool for predicting cointegration. The results of Table 4 show that 5% critical values are less than trace values up to most 3*, which means there are three cointegrations among the variables. Results declared a long-run relationship between CO₂ emissions and their related determinant variables since it is confirmed that GDP (growth), UP, FD (private sector), RE, and TO impact CO₂ emissions significantly.

Table 4 Cointegration test

Granger causality analysis

To determine whether one time series predicts the other as caused by happening, the Granger causality test is considered a prominent one. Scholars prefer to use Granger causality analysis in determining the directions of dependent and independent. Lag one is applied for the analysis of causality. Jones (1989) considered ad hoc as one of the best methods for the statistical calculation of this analysis.

The findings of Granger causality are mentioned in Table 5, which reflect that a unidirectional and long-term relationship exists among GDP (growth) to CO₂ emission, RE to CO₂ emission, RE to FD (private sector), and UP to TO in the context of Pakistan.

Table 5 Granger causality test

Conclusion

CO₂ has been damaging the climates and environments around the globe. As we see, the earth’s average temperature is rising yearly. This is because of an increase in the level of CO₂. CO₂ traps the heat and does not allow it to escape from the earth’s surface. The study used prominent variables mentioned in the literature to check their impact on CO₂ levels in the context of Pakistan. The study found a significant positive relationship between financial development, trade openness, and urbanization with the emission of CO₂ because all the variables increase the utilization of fossil fuels in industries and transportation. The gross domestic product shows no significant relationship with the emission of CO₂ in the context of Pakistan. The possible reason may be the regular fluctuation in the GDP growth rate, and the GDP of Pakistan has a major chunk from the agriculture sector. At the same time, the use of renewable energy resources negatively impacts CO₂ emissions.

Future recommendation

• Research shows that FD (private sector) has not only a significant but also a positive relationship with the emission of CO₂, so this reveals that if more credit is given to the private sector in Pakistan, this will increase the emission of CO₂. There are many reasons behind this fact, some of which include because the industries in Pakistan do not utilize proper ways to eliminate wastage. Furthermore, the fuel and energy used by the industries in Pakistan are full of such components that cause the degradation of the environment. Similarly, many small companies operate in residential areas in Pakistan, so their waste is eliminated without proper treatment. The private sector must invest some part of their profit in improving the environment and adopting proper methods for the treatment of wastage and follow green environment practices.

• Trade openness and urbanization both put upward pressure on industries and transportation. In return, fossil fuel usage increases to meet the demand, resulting in the increased emission of CO₂. The government must bind industries to adopt environment-friendly methods and promote small industries, agriculture, and cattle farming in rural areas to reduce population pressure in cities.

• The RE consumption has a negative and significant relation with the emission of CO₂. Pakistan receives about 1 KW of solar energy per square meter of its landmass for 6–7 h per day. Solar panel installation in urban and rural areas is suggested to reduce pressure from fossil fuel usage. Hydro energy, wind energy, and biomass energy are also useful in the same regard.

Future researches

In the future, the research is advised to incorporate some variables like an intention to use CO₂, strict regulations and quality control, and strict penalties for the violation. Furthermore, the context can be more precise if researchers use other countries that reduce CO₂ by implementing such restrictions.