Dynamic Nexus Among CO2 Emissions, Fossil Energy Usage and Human Development in East Africa: New Insight From Novel DARDL Simulations

This study investigates the relationship among CO 2 emissions, human development index, and fossil energy usage. Essentially, the study was informed by the Sustainable Development Goal 7, which stipulates universal access to renewable and contemporary energy technologies. We employed the novel dynamic autoregressive-distributed lag (DARDL) simulations with a dataset spanning between1980 and 2020 from East Africa Community (EAC). The study revealed that human development, access to electricity, and trade have a strong correlation with carbon emissions in the long term, whereas fossil energy usage and economic growth have a negative connection with carbon emission. On the other hand, in the short run, human development and fossil energy usage have a positive correlation with carbon emission, while economic growth and foreign direct investment have a negative correlation with carbon emission. Thus, policies that are tailored to enhance the political environment in East Africa are crucial to ensuring realistic access to clean and modern electricity. the links among HDI, energy usage, international trade, and FDI inow with CO 2 emissions in the background of East African communities (EAC). The study applies the novel dynamic ARDL model to analyze EAC data covering the years 1980 to 2020. The study demonstrates that human development has a considerable benecial effect on CO 2 emissions, and both electricity usage and trade boost carbon emissions. The usage of fossil energy usage has been discovered to be a renewable energy source that could aid in the decarbonization of the EAC economy. Among other things, international trade adds to CO 2 emissions, while FDI does not seem to do so. GDP was identied to have a decreasing benecial inuence on climate change mitigation.

development in the region. Qualitative measures like per capita GDP and social indicators like education and life expectancy are more reliable proxy estimates of living standards (Shinkevich, Yakunina, & Klimenko, 2021). Interestingly, suppose the study questions concern long-run mechanisms. In that case, the direction of causality is seldom addressed in current literature (Lawson, Nguyen-Van, & others, 2021) or the factors that contribute to GHG emissions and the presence of an environmental Kuznets curve (EKC), (Lawson, Martino, & Nguyen-Van, 2020) and (Liddle, Smyth, & Zhang, 2020). Even in the African sense, studies that use qualitative indicators of development are uncommon. In addition, the goal of this study is to assess the developmental stage using the Human Development Index (HDI).
This study provided a number of signi cant contributions. It argues for comprehensive policy decisions on environmental sustainability in East Africa in order to foster a better relationship among the parameters of the study. Second, the study may assist the EAC governments in countering CO 2 emissions by elucidating the status of GHG emissions for remedial measures. The investigation, which is based on the parameters of the study, is the rst of its type in the EAC. In contrast to fossil energy use, the study looks at human development to see how it satis es the mitigation requirements before developing strategies to incorporate further fossil energy usage into the energy mix. A further contribution of this study is the use of (Jordan & Philips, 2018)'s novel time-series data estimation method. In contrast to previous studies that used analytical time series data tools such as (Pesaran, Shin, & Smith, 2001) commonly used auto distributive regressive model, this analysis employs a newly established approach, the dynamic ARDL simulation process for the spurious impact of regressors on the predictor variables. It discusses numerous complexities associated with the behavior and perception of the prevalent ARDL model. Finally, this study adds to the expanding body of information on ecological preservation by exploring the widespread association between energy usage and ecological regulations.
The remainder of the paper is organized as follows: The next section reviews the related literature. Section 3 gives a description of the data and the methodology used in the study. Section 4 contains empirical ndings and discussions, and Sect. 5 summarizes the key outcomes and provides some policy recommendations based on the empirical ndings.

Literature Review
Following the empirical works of (Essandoh, Islam, & Kakinaka, 2020) and (Lawson, 2020), a vast body of literature has examined the connection among CO 2 pollution, electricity, and Trade. This set of literature emphasizes the causal relationship between these factors and shows that economic development and energy consumption globally induce environmental degradation (Mahmood Ahmad et al., 2021) and (Ansari, Haider, & Masood, 2021). By focusing on the connection between human development, fossil fuel use, electricity, FDI, and trade in this article, we hope to limit the scope of the literature review to research that employs qualitative indicators of human development. ( (Lawson, 2020), have shed light on the relationships between these phenomena. Furthermore, (Lawson, 2020) and  investigate the correlation among human development, CO 2 emission, and energy consumption in the SSA nations and concluded that considerable advances in human development are feasible in Africa via access to energy. For there is a strong correlation between access to electricity and human development. (Acheampong et al., 2021) examined the effect of energy availability on human development across 79 developing countries from 1990 to 2018 by following the pioneering studies of (Acheampong et al., 2021) and (Pata & Caglar, 2021). Speci cally, (Acheampong et al., 2021) used the Lewbel two-stage least squares methodology to illustrate that access to power, and renewable energy promotes human development in the consolidated group.
In comparison, their ndings show that while access to power and renewable energy boosts human growth in the Sub-Saharan Africa and Caribbean-Latin America, the reverse was observed in South Asia. Similarly, (Pata & Caglar, 2021) highlight the critical signi cance of human capital in reversing environmental pollution in China and that renewable energy alone will not occur to address environmental standards. Additionally, the ndings indicate that globalization, trade openness, and revenue increase pollution, whereas boosting human assets has a long-term bene cial effect on environmental footprint reduction.
A further aspect of the literature examined the impact of renewable energy usage on social quality of life, given current knowledge of climate challenges and the growing renewable energy usage. In general, no convincing conclusion can be drawn on the importance of renewable energy usage in human development. Based on this assertion, (Cerqueira, Soukiazis, & Proenca, 2020) and (Ahmad, Muslija, & Satrovic, 2021) provided evidence for a bidirectional causal association among both renewable energy and HDI. However, (Z. Wang, Bui, Zhang, Nawarathna, & Mombeuil, 2021) discovered no conclusive ndings. Obviously, the area of environmental economics that deals with renewable energy usage and human development requires further exploration.
Similarly, inconclusive ndings are evident in the case of environmental pollution and its correlation between energy usage and human development. The current studies on the above subject also indicate that energy usage facilitates human growth but is inconclusive about the effect of CO 2 emissions on human health (Cerqueira et al., 2020; Rahman, Zaman, & Górecki, 2021). On the same topic,(Akbar, Hussain, Akbar, & Ullah, 2020) demonstrated a causal association between healthcare costs, HDI, and CO 2 emissions. More precisely, they demonstrated a bidirectional causal association between healthcare spending and CO 2 emissions, implying that CO 2 emissions substantially increase healthcare spending in the OECD economies. In conclusion, unlike energy consumption, which has been proven to be causally related to human growth in both directions, the impact of CO 2 emissions on human development remains unclear.
In the case of developing countries, especially those in sub-Saharan Africa, studies examining pollutant pollution, energy usage, and development nexus are much more scarce and dearth. (Oluoch, Lal, & Susaeta, 2021) found positive effects of renewable energy usage on human development in the long term while considering factors such as the literacy rate and life expectancy. Similar ndings were seen in (Ouedraogo, 2017)'s study, who examined the correlation and causal relationship among HDI, energy usage, and electricity usage in the Economic Community of West African States(ECOWAS). The ndings explicitly indicate that electricity consumption and HDI have a favorable cointegration partnership, suggesting that electricity consumption promotes human growth.
In conclusion, while the controversy about sustainable energy usage and economic growth continues to rage, a body of knowledge demonstrates that energy demand and access to power are critical for human development. These studies are among the few that exist on the relationship among human development, fossil fuel usage, and CO 2 emissions. Their outcomes are, however, controversial. None of the studies presented used the hierarchical autoregressive distributed lag framework (Jordan & Philips, 2018), and none is conducted to East African economies. To address these lacunas in research, the present study emphasizes the function of human development in CO 2 emissions in the EAC by investigating the position of access to electricity, international trade, and foreign direct investment (FDI) through the EKC context and application of dynamic ARDL.

Descriptive statistics and variables
The examination of the connection among CO 2 emissions, access to electricity, fossil energy usage, human development (HDI), GDP, FDI, and Trade that have been established in previous studies. As a result, we gathered information on fossil energy consumption, CO 2 emissions, access to electricity, HDI, GDP per capita, Trade, and FDI, among other things. However, due to missing values, the nal dataset comprises East African countries and is restricted to the timeframe 1980-2020. Table 1 summarizes the informative gures of the factors used in this study. By contrasting the minimum and maximum values for CO 2 emissions, the Human Development Index, access to electricity, fossil energy consumption, GDP, trade, and foreign direct investment (FDI), it is possible to observe disparities, implying a reasonably heterogeneous sample. The Correlation analysis reveals a positive monotonic association between all independent variables and CO 2 . Correlation analysis reveals a positive monotonic association between all independent variables and CO 2 . Consequently, prior to performing the econometric analysis, the variables are transformed logarithmically to establish a stable variance. Figure 2 depicts the pattern of logarithmically transformed parameters. According to the pattern shown in Fig. 2, the trend happens to rise periodically.

Model construction
The methodological framework of the analysis is adopted from recent literature (Danish & Ulucak, 2020; Sarkodie et al., 2019) to investigate the relationships among HDI, fossil energy use, GDP, and access to electricity with CO 2 emissions. A schematic overview of the test processes is shown in Fig. 3 to improve the ow of the study. This accounted for FDI and trading, and thus, it can be expressed in Eq. (1) as: lnCO 2 = λ 0 + χ 1 (Ŷ t ) + χ 2 EU t + χ 3 HDI t + χ 4 lnELEC t + χ 5 lnTRA t + χ 6 lnFDI t + ξ t Where t is time, (CO 2 ) refers to carbon dioxide emissions, (Y) stands for GDP, (EU t ) for fossil energy usage, (ELEC t ) is access to electricity, (FDI t ) is foreign direct investment, (TRA t ) stands for the trade, and ξ t is the remainder term.

Unit Root
The central stage in the study process is to establish the initial relations among the parameters to determine the data series sequence. In that regard, the explained parameters must be differentiated at the order I(1). It is not all the explanatory parameters (HDI and fossil energy) that must be stationary or have seasonal unit roots at rst-differenced. The results of the Phillip-Perron (PP) and Augmented-DF unit root tests are reported in Table 2. Speci cally, Table 2 indicates that the null hypothesis presence of a unit root for the approximation of all the research parameters can be accepted at level one but cannot be accepted at a 5% signi cance level at the rst difference. Thus, the parameter being studied holds for rst-order continuous integration.

Cointegration
The results of the unit root test suggest that the fundamental parameters are stationary at rst order I(1). This, therefore, calls for the integration level of the parameters to be investigated. In keeping with recent studies (   Note that when the F-statistic value exceeds the upper bound, the null hypothesis of no cointegration is refuted; This is also true for the F-value in Table 3, as shown by the P-value.

Outcomes of Dynamic stimulated ARDL simulation
The novel dynamic ARDL simulation proposed by (Jordan & Philips, 2018) employs a groundbreaking DARD approach in an investigation to address di culties in current models while analyzing the long and short-term effects in detailed model speci cations. The variables used in the dynamic ARDL simulation process must be cointegrated and have an integration order of one. The parameters meet these conditions under consideration in our analysis. Table 4  The primary energy coe cient is found to be signi cantly negative, which implies that the e cient usage of fossil energy (coal, oil, and gas) results in CO 2 emissions absorption in the distribution channel system. Fossil energy adds to GDP by boosting revenue creation, which keeps the economy a oat without jeopardizing energy requirements for economic sustainability (Solarin, Tiwari, & Bello, 2019; Nathaniel,2020). The energy demand contributes to economic decarbonization by mitigating pollution created by traditional energy sources and related products (Sarkodie, 2021). Primary energy usage facilitates the energy supply transition to a more reliable internal energy supply and boosts long-term energy sustainability. It also improves the quality of the environment by lowering fossil fuel use and the corresponding resource depletion associated with it, which leads to land usage concerns (Bello & Solarin, 2021). Primary energy e ciency empowers manufacturers to invest in fossil energy, as increased economic growth generates investment and research, and innovation opportunities in fossil energy. Primary energy usage substitution for fossil fuels could boost the country's growth. This is because fossil fuel is ideal used for heating, transportation, and electricity generation. Despite the fact that fossil fuel usage is the principal source of CO 2 , primary energy consumption and population access to electricity are anticipated to increase CO 2 emissions substantially. The ndings unequivocally support this view. In other words, the ndings demonstrate a signi cant positive effect of primary energy usage on CO 2 emissions, as reported in Table 4. Similar ndings arguing for a causal connection between fossil energy usage and CO 2 emissions are found in recent contributions (Lawson, 2020) and (Sarkodie, 2021). The quest for growth has also contributed to environmental degradation stemming from industrialization in developed and developing countries. The nding revealed that both the long and short-term GDP coe cients are negative and statistically insigni cant. This indicates that East African countries have higher institutional quality, conducive to economic e ciency and carbon emission reduction. This is consistent with the works of (Olubusoye & Musa, 2020), who showed a short-run negative correlation between GDP and carbon emissions in the Middle-Upper income countries. However, this negative short-term impact is transient as a result of the high rate of deforestation and the export of wood logs to generate revenue for economic development. On the contrary, ( Additionally, as shown in Table 4, the electricity consumption coe cient is signi cantly positive in the short term as well as in the long term. This indicates that electricity usage increases environmental degradation, which is in line with (Lawson, 2020) and (Kwakwa, 2021). Also, ( In terms of other variables, like foreign direct investment, the outcomes obtained from Table 4 demonstrate that FDI has a negative effect on CO 2 emissions but is statistically inconsequential in the short and long run, which is consistent with recent outcomes of (Acheampong et al., 2019). This nding contradicts the outcomes of (Akinlo & Dada, 2021), who discovered that FDI raises carbon emissions in Sub-Saharan Africa(SSA). Several different scenarios explain these outcomes. Firstly, foreign investors in SSA are predominantly from developed economies with more advanced technologies capable of in uencing SSA's Given that dynamic ARDL is initiated by (Jordan & Philips, 2018), which is a more advanced variant of ARDL (Pesaran et al., 2001), the present study examined the long and short-term dynamics using the ARDL method for comparative analysis to enhance robust testing. Table 4 displays that HDI impacts on carbon emission are positive and statistically insigni cant in both the long and short run. Furthermore, the long-run impacts of fossil energy usage and GDP on CO 2 emissions are signi cantly negative. It is, however, statistically insigni cant in the short term. This indicates that both fossil energy usage and GDP contribute to the reduction of carbon dioxide emissions. The coe cient of Electricity is positive and statistically signi cant in both the long and short term. This suggests that Electricity usage contributes to carbon emissions. The coe cient of FDI is negative but inconsequential in the short and long term. This implies that FDI promotes carbon dioxide emissions. Finally, the effect of trade on carbon footprint is statistically inconsequential and bene cial in the long and short term. Generally, the ndings of employing ARDL are consistent with the results of dynamic ARDL. It, therefore, con rms the e ciency and relevance of welldeveloped and policy-relevant results.  Figures (4-5) provide an instinct graph depicting the correlation between energy usage and GDP. The adverse effects of fossil energy usage and carbon emissions endorse the argument that decreasing fossil energy usage would lessen carbon emissions (Lawson, 2020), since a harmful shock is gradually leveled. The long-term strong shock associated with fossil energy usage is constant, despite the fact that it raises CO 2 emissions within the short run. The increasing amount of CO 2 pollution is consistent with the fact that lifespan emissions from traditional sources of energy are not diminishing (Balsalobre-Lorente et al., 2018). Figure 5 depicts the impulsive response of economic growth to CO 2 . A positive shock to economic development reduces CO 2 emissions in the long term, but a negative shock raises CO 2 emissions. Additionally, (Olubusoye & Musa, 2020) found that economic expansion had a signi cant negative effect on short-term carbon emissions in the short term. In contrast,(Balsalobre-Lorente et al., 2018) indicated that economic growth positively affects carbon emissions. Figure 6 depicts the change in predicted electricity consumption on CO 2 emissions. A graphical observation shows that CO 2 emissions react positively to a positive shock in electricity usage. However, a negative shock in electricity consumption triggers a negative response in CO 2   Our analysis shows that attempts to improve human well-being mainly result in primary energy usage in terms of energy factors.
Socioeconomic features of the EAC countries, such as access to electricity and trade, are revealed to stimulate energy requirements and, consequently, primary energy consumption in the EAC. On the basis of this, we can conclude that fossil oil usage is driven primarily by energy demand (as a consequence of electricity) and attempts to enhance living standards. This conclusion further extends to industrialized countries, whereas fossil fuels offset the increased energy demand from improved well-being.
These ndings also have policy implications, such that the EAC governments should spend more on clean energy initiatives, including research and development (RD), to assist the EAC in addressing its severe environmental di culties. This requires the EAC to make additional efforts toward energy conservation and, more broadly, a move away from conventional and fossil fuelbased energy toward less polluting and sustainable sources. Indeed, the EAC places a premium on human well-being.
Nonetheless, if environmental pollution and climate change are not addressed, they will endanger the future of East African Communities. As a result, the EAC countries are urged to address the problem of rising CO 2 pollution at their root by encouraging public and private programs as well as massive investments in green energy and energy-e cient technology.
This modeling approach has drawbacks without a doubt, and this article is not different from those with limitations. Due to data constraints, the modeling was unable to quantify the potential advantages of GHG emission reductions, which, therefore, needs further studies. Additionally, beyond the framework of this study, the model should be examined in other regions in order to gain a broader horizon and a comparative historical perspective.

Declarations Authors contributions
The research idea was conceived following a discussion between Ko Dumor and Yao Li, Edem ko Amouzou, Ko Akakpo and The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Ethics approval and consent to participate Not applicable.
Consent for publication Not applicable.
Competing interests The authors declare no competing interests.