Exploring the Relationship between Residential CO 2 Emissions, Urbanization, Economic Growth, and Residential Energy Consumption: Evidence from the North Africa Region

Rapid urbanization, coupled with income growth, will inevitably cause the residential energy consumption in the North Africa region to continue to increase, with adverse effects on the climate, human health, and the economy. In these regards, this paper explores the relationship between residential carbon dioxide emissions (RCO 2 ), urbanization, economic growth, and residential energy use in four North African countries (Morocco, Tunisia, Algeria, and Egypt) over the period 1990–2016. To do this, we used the bounds cointegration and the Toda–Yamamoto Granger causality test. The existence of cointegration relationships was conﬁrmed for the four countries. In the long run, the environment Kuznets curve relationship between increased income per capita and RCO 2 emissions was veriﬁed for only Morocco and Tunisia. The causality analysis also reveals a combination of neutral, unidirectional, and bidirectional relationships for all countries. The RCO 2 emissions have not proved to be a limiting factor in any country’s economic growth. The ﬁndings of this study certainly contribute to advancing the existing literature by emphasizing the income– pollution nexus in African countries. Policy makers and government regulators should implement the necessary policies that accelerate the development of renewable technologies to drive sustainable cooling and heating as well as water management.


Introduction
In the context of global climatic warming and the consequences of greenhouse gas emissions on the whole planet, understanding the social and economic growth impact on the environment becomes crucial, especially for developing countries. The North Africa region has undergone substantial economic and demographic growth over the last 10 years, which is anchored in the sense of global warming. While the region is a weak greenhouse gas emitter [1], it remains vulnerable to the effect of climate crisis, and its natural resources are under rising threat. The region of North Africa, conscious of this fact, is strongly committed to combating climate change. The countries of the region have adopted numerous sectoral strategies that incorporate the environmental dimension into various main economic areas, such as energy [2,3], transport [4], agriculture [5], etc.
As in developed countries, more systematic and comprehensive energy and environmental studies must be carried out in African countries. These studies should target all sectors that contribute to GHG greenhouse gas emissions, especially the building sector, which contributes 28% of the world's total carbon emissions [6]. Thus, the housing stock provides tremendous potential for CO 2 emissions reduction [7,8]. Residential energy consumption (REC) in the North Africa region has continued to grow since 2000 and

Review of Related Literature
There has been little attention paid to the nexus among RCO 2 emissions, urbanization, and economic growth in the existing literature. Most studies have examined the scale or influential factors of emissions from the residential sector. For instance, Venkataraman et al. [13] conducted a study on residential biofuels, and they reported that the primary contributor of black carbon emissions in India is biofuel combustion in particular. They concluded that controlling biofuels consumption would help in the mitigation of climate change in South Asia. Liu et al. [14] performed an analysis of rural RCO 2 emissions in China, which revealed that traditional biomass use presents the greatest potential for GHG mitigation. Still, in China, Zhu et al. [15] used the structural decomposition method to examine the residential indirect CO 2 emissions from 1992 to 2005. They found that the use of residential energy has a positive and dominant role in the promotion of RCO 2 . In addition, they noticed that population growth, contrary to population size, causes indirect residential emissions. In the Iberian Peninsula, Carpio et al. [16] selected six cities with different environmental conditions to assess the impact of the use of biomass boilers on carbon dioxide gas emissions. They found that the use of biomass could achieve a potential decrease of up to 95% in RCO 2 emissions. They also noted that climate, financial costs, and improving the energy rating affect reducing RCO 2 emissions. Poumanyvong and Kaneko [10] are the first, to our knowledge, who analyzed the nexus between RCO 2 and urbanization from 88 nations by employing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The results indicate that the nexus between RCO 2 emissions and urbanization in high-income nations is an inverted U-shape, whereas urbanization in the middle and lowest per capita income countries raises RCO 2 emissions. Most of these studies were conducted in China [17][18][19][20][21].
Regarding Morocco, Tunisia, Algeria, and Egypt, studies have often addressed them during the investigation of the Middle East and North Africa (MENA) region. These investigations have concentrated on the nexus among GDP, energy use, and CO 2 emissions as a gross term and can be categorized into three main groups: the first explores the nexus of economic growth-energy consumption; the second examines the nexus of economic growth-carbon dioxide emissions; however, the third, focuses on the nexus between CO 2 emissions, economic development, and the use of oil. A summary of the selected empirical studies is presented in Table 1.

CO 2 Emissions and GDP Nexus
Narayan and Narayan [22] used samples from 43 developing nations (including Morocco, Algeria, and Egypt) to examine the EKC hypothesis. They found that CO 2 emissions had decreased significantly as the incomes of the countries concerned increased. Using data from three African countries (Senegal, Ghana, and Morocco) over the period 1971-2007, Adom et al. [23] suggest that the emissions of carbon dioxide will be a major constraint on Morocco's economic development. Chaabouni and Saidi [24] studied the case of 51 nations during the period 1995-2013. Their findings show that economic growth impacts CO 2 emissions positively and significantly, and that there is a bidirectional causality between them for the case of Morocco, Tunisia, Algeria, and Egypt. However, other studies have reported a neutral effect between carbon dioxide emissions and GDP. For instance, Gorus and Aydin [25] found that there is no causal nexus between income growth and CO 2 emissions in eight MENA nations (including Algeria, Egypt, and Tunisia).

CO 2 Emissions and Energy Consumption Nexus
Al-mulali et al. [26] noted the presence of bidirectional causality between carbon dioxide emissions and energy consumption in the long and short run by analyzing 20 MENA countries, even if the significance rate of the long-run relationship between the variables varied by educational level, level of economic growth, and income. Based on data from 10 MENA countries in 1980-2009, Farhani and Shahbaz [27] found a causality running from the use of renewable and non-renewable electricity to CO 2 emissions in the short run, while it is bidirectional in the long run. Another analysis conducted by Charfeddine and Kahia [28] for 24 countries in the MENA region from 1980 to 2015 revealed that renewable energy consumption has a low impact and could only marginally describe CO 2 emissions.

CO 2 Emissions, Energy Consumption, and GDP Nexus
For the period 1973-2008, the analysis conducted by Farhani and Ben Rejeb [29] on 15 MENA countries supports the presence of univariate causality running from GDP and CO 2 emissions to energy consumption. However, they support the absence of short-run causality between all variables. Arouri et al. [30] studied 12 MENA countries covering the period 1981-2005, and they concluded that energy use impacts CO 2 emissions positively in the long run. They also noted that as GDP per capita continues to rise in the MENA region, CO 2 emissions per capita could be reduced. By studying 14 MENA countries and using data from 1990 to 2011, Omri [31] found that there is unidirectional causality from energy consumption to CO 2 emissions, while there is a bidirectional causality between economic growth and CO 2 emissions throughout the region. Kais and Ben Mbarek [32] reported that income and energy consumption increase the CO 2 emissions in Algeria, Tunisia, and Egypt. The same conclusion was drawn by Muhammad [33], who supported the conservation hypothesis in MENA countries. From all the above literature, the findings were found to be mixed and inconsistent. This may be due to the different characteristics of the countries and different frameworks employed to capture the linkage among CO 2 emissions, income, and energy use.
In this paper, we deviate partly from the existing literature by treating the same concern within a specific framework. We are particularly interested in exploring the residential sector, as it is an important source of total CO 2 emissions. Therefore, the current study underpins the RCO 2 emissions, urbanization, GDP, and REC nexus in the North Africa region. To the best of our knowledge, no study has examined this nexus before. This study partially fills the research gaps by using a more recent dataset, a more robust model, and various modeling approaches that reflect the specificities of each nation. Our findings certainly contribute to advancing the existing literature and will aid policymakers in the four Northern African nations in developing effective policies to control the impacts of urbanization, income, and residential energy use on residential CO 2 emissions.

Data Presentation
The current study uses time-series data of urbanization (URB expressed as urban population per total population), real GDP per capita (GDPPC in the thousand US dollars) as a proxy of economic growth, residential energy consumption per capita (RECPC expressed in Koe), and RCO 2 emissions per capita (RCO 2 PC expressed in metric tons) for 4 North African countries from 1990 to 2016. All the data were obtained from the International Energy Agency [1] except urbanization, which has been gathered from the World Development Indicators [34].
Descriptive statistics related with the variables analyzed are summarized in Table 2. The Jarque-Bera (JB) test [35] indicates that all the series are normally distributed. The analysis of the values of the coefficient of variation (CV) shows that Egypt's GDP has the highest variability followed by one of Algeria and Morocco. Moreover, the lowest variability is identified in Egypt's urbanization series. However, Tunisia has the highest mean urbanization rate, while Algeria has the highest mean of RCO 2 PC emissions, GDP per capita, and RECPC by 175 Koe. This means that energy consumption in the Algerian residential sector is more pronounced compared to the other countries and this will, of course, affect the RCO 2 emissions. As shown in Figure 1, the RCO 2 emissions from Morocco are significantly lower than those of the North African countries such as Tunisia, Algeria, and Egypt. Nevertheless, in recent years, Tunisia and Egypt have managed to keep their RCO 2 PC emissions stable, whereas those of Morocco are rising slightly. Finally, Algeria's RCO 2 emissions are the most pronounced and have continued to rise over the years. Thereafter, all the variables are expressed into log-form for consistent and reliable empirical results.

Model Specifications
This paper follows an econometric approach that has been used by many researchers in recent studies [36][37][38], and it has shown promising results when investigating the "economic growth-environmental pollution" nexus. According to the results of numerous studies [39,40], residential CO 2 emissions can be divided into direct and indirect emissions as follows:  Furthermore, indirect RCO 2 emissions are generally defined as resulting from daily human activities related to services and product waste [41]. Several studies [15,18] have shown that urbanization and income are potential determinants of indirect energy consumption and household CO 2 emissions. Then, RCO 2Indirect emissions can be expressed as follows: RCO 2Indirect = f(URB, GDP).
Therefore, residential CO 2 emission per capita are modeled as a function of economic growth, urbanization, and REC as follows: where RCO 2 PC t , URB t , GDPPC t and RECPC t stand respectively for RCO 2 emissions per capita, urbanization, the real gross domestic product per capita, and residential energy consumption per capita, at time t.
In addition, the current study includes a squared term of GDPPC (GDPPC 2 ) to investigate the EKC hypothesis when examining the impacts of high-level incomes on environment. Indeed, the EKC is a hypothesized relationship between several environmental indices and wealth. The relationship between income and environmental quality has been mainly described as an environmental Kuznets U curve, which asserts that there is a negative relationship between low income and environmental quality in the early stages of economic development, but that the relationship becomes positive later on. Finally, as no study has looked for the existence of the EKC relationship between economic growth and environmental pollution related to residential sector for the countries of North Africa, this study aims to investigate it. Thus, our model can be represented as follows: For testing the long-term equilibrium relationship, known as cointegration, among RCO 2 emissions and the other variables, Equation (5) was transformed into logarithmic form to make the estimate easier and free of heteroscedasticity. That is: where α k are the parameters of the model to be determined, with k = 0 . . . 4, and µ t is the error term. The procedure followed for achieving the goal of the study is shown in more detail in Figure 2. After collecting data, we first verified the stationarity of the variables since most economic, energy, and demographic variables are non-stationary, and Granger and Newbold [42] suggested that a non-stationary time series might lead to a misleading conclusion. Second, we used an ARDL bounds cointegration test to determine whether there is a long-run relationship among the series under study. An ARDL bounds cointegration test consists of many steps: determining the optimal Lag; checking the presence of cointegration using an F-statistics test; estimating long and shortrun results; and ensuring that the model is stable. Upon the validation of cointegration between the variables, the third step is to establish the direction of the causal link using the Toda-Yamamoto Granger causality test.

ARDL Bounds Cointegration Test
Verifying the nature of the data series is mandatory before exploring the time-series model. As shown in Table 3, the Augmented Dickey-Fuller (ADF) and Phillips-Peron (PP) unit root tests reveal that the test statistics for the log levels of the four variables are statistically insignificant, except for LnURB of Algeria and LnURB of Egypt. The order of integration is necessary to determine which cointegration technique should be applied, and since none of our series is I(2), we used the ARDL bounds testing approach to investigate whether there is a long-run association between variables. The choice of ARDL method was considered more suitable for our analysis for many reasons: Firstly, the ARDL model outperforms all traditional cointegration testing methods for small sample data. Secondly, the ARDL approach can be used whether the variables are stationary at I(0) or I(1) or a combination of I(0) and I(1). Moreover, this approach provides both the short and long-run relationships between variables at the same time. Indeed, in an econometric context, the short run generally is defined as the time horizon over which the inputs deviate or are inflexible; however, the long run is measured over the period of time required for these inputs to adjust. Lastly, the ARDL model is not impacted by the endogeneity, since the lags of dependent and independent variables are added into the model. Therefore, using this approach, the functional form of the unrestricted error correction model is modeled as follows: where I refers to country, and t is the time period. The bounds testing approach to cointegration guarantees performing an F-test on the estimated equation with suitable lag lengths. Equation (7) was first estimated using ordinary least squares. The presence of long-run relationships among variables is confirmed by the standard F-test or Wald test on the null hypothesis, λ 1 = λ 2 = λ 3 = λ 4 = λ 5 = 0, meaning that no cointegration exists between the variables, against the alternative hypothesis, λ 1 = λ 2 = λ 3 = λ 4 = λ 5 = 0, indicating that variables are cointegrated. Then, we calculate the F-statistic and compare it with the critical values bound values proposed by Pesaran et al. [43]. In fact, the null hypothesis of no cointegration is rejected once the F-statistic is above the upper critical bound (UCB) value. If the lower critical bound (LCB) value exceeds our calculated F-statistic, there is no cointegration between the variables. If the F-statistic lies somewhere in between the critical bounds, the "Bounds Test" is deemed inconclusive. Once we find that the variables are cointegrated, then, the error correction model that defines short-run impacts can be estimated using the following equation: where ECM t−1 refers to the estimate of the lagged error correction term. Furthermore, the ARDL approach offers the possibility of incorporating "dummy variables" in the model that define the different regime shifts. Generally, external factors such as war, conflicts, and natural disasters can impact the trend of variables; thus, dummy variables are used in the model to account for this. In the case of our study, the set of popular protests that occurred in many countries of the Arab world from December 2010, known as the Arab Spring or Jasmine Revolution [44], was the catalyst for political instability in North Africa, particularly in Tunisia and Egypt. The Jasmine Revolution [44] has had far-reaching consequences for the economy and many sectors in North African countries. Therefore, a dummy variable was introduced into each country's ARDL model, reflecting the years of the Jasmine Revolution [44], and it is expressed as follows:

Toda and Yamamoto Granger Causality Test
The ARDL bound testing will reveal the presence of the long-run relationship between the mixed or non-stationary form of variables; however, it will not be able to show the causal direction between the considered variables. Granger suggests a sequential procedure to test the causality between the series, notably by using either the Vector Error Correction Model Granger causality or the Engle and Granger [45] causality test. However, many criticisms have been formulated as to their effectiveness. The weakness of cointegration results coupled with the biased nature of unit root tests, especially for small samples, reduces the effectiveness of the Granger causality test, and that induced Toda and Yamamoto [12] to propose non-sequential procedures for testing the causality between the series. Thus, given our limited sample size, the Toda-Yamamoto approach appears to be a good fit for our research. The use of the Toda and Yamamoto approach is based on the augmented VAR model in levels with the maximum order of integration of the series. Hence, the current study explores the causal relationships among RCO 2 emissions, urbanization, GDP, and residential energy consumption by employing the Modified Wald test (MWALD) as proposed by Toda and Yamamoto [12]: where m = 1, . . . ,4 and y 1 , y 2 , y 3 , y 4 represent Ln RCO 2 PC, LnURB, LnGDPPC, and LnRECPC respectively; p is the optimal lag length of VAR, and d max is the maximum order of integration of the variables in the VAR model.

Empirical Results and Discussion
The first step entails testing the cointegration relationship between Ln RCO 2 PC and other variables. To this end, we used an unrestricted VAR to determine an appropriate lag length of the series of all models. Appendix A summarizes the results that illustrate that lag length 1 for Morocco and lag length 2 for other countries are appropriate according to the Akaike Information Criteria (AIC). This criterion was particularly chosen due to its high explanatory power. Thereafter, the F-statistic was computed, and the outputs are displayed in Table 4. The values found for F-statistics are higher than the UCB values of Pesaran et al. [40] at 1% and 5% significance levels for Algeria and Egypt, respectively, and at 10% in the case of Morocco and Tunisia. This ensures that variables should not diverge too far in the long run. To conclude, our findings confirm a long-run relationship between RCO 2 PC emissions, urbanization, GDPPC, and RECPC for the four neighboring countries.

ARDL Long-Run Results
The ARDL long-run results are presented in Table 5 and reveal that urbanization is the first main factor influencing RCO 2 emissions per capita in Morocco, Algeria, and Egypt. The RCO 2 PC emissions are affected negatively by urbanization for both Algeria and Egypt. The results suggest that a 1% addition in urbanization reduces RCO 2 PC emissions by 0.90% in Algeria and 8.31% in Egypt. Our findings join the ones found by Hu and Tang [17], but they are contradictory with those of Poumanyvong et al. [10], who stated that the urbanization process contributes to increasing the RCO 2 PC emissions in the low and middle-income countries. For Morocco, urbanization appears as a positive factor. A 1% add in the urbanization rate boosts RCO 2 PC emissions by 2.76%. These findings are consistent with Bai et al. [21]. Indeed, the sign (+) of the coefficient attached with the urbanization variable was expected, as the process of urbanization in Morocco is closely linked to the consumption of electricity and butane (more butane, since it is subsidized). However, in Algeria and Egypt, energy subsidies cover electricity, natural gas, and hydrocarbons. This explains the fact that the share of less polluting energies (electricity, biomass, and natural gas) in the residential energy mix of Algeria and Egypt is 85% and 65%, respectively, while that of Morocco is 37% [1]. It should also be noted that the Moroccan residential energy mix does not include natural gas.
The estimated coefficients related to GDPPC and GDPPC 2 appear to be significant for both Morocco and Tunisia. As shown in Table 5, the results suggest that increasing GDPPC reduces RCO 2 PC emissions in Morocco; a 1% add in GDPPC is associated with a 0.34% decrease in RCO 2 PC emissions. However, after reaching a turning point (the GDPPC level of US$ 1,701), further increases in GDPPC increase RCO 2 PC emissions (a 1% add in GDPPC is associated with a 0.32% increase in RCO 2 PC emissions). Therefore, our findings support a U-shaped relationship between wealth and RCO 2 PC emissions in Morocco. However, an inverted U-shaped relationship exists among GDPPC and RCO 2 PC emissions in Tunisia. This means that Tunisia's RCO 2 PC emissions initially increase with an increase in GDPPC and then decrease exactly after GDPPC reaches a level of US$2427. This outcome is coherent with the findings of Fujii et al. [46].  Regarding the effect of RECPC on RCO 2 PC emissions per capita, it is positive and significant at 1% for all North African countries. The results suggest that a 1% add in RECPC is related to RCO 2 PC emissions by 0.23% in Morocco, 0.89% in Tunisia, 0.82% in Algeria, and 0.55% in Egypt. More energy consumption leads to more residential carbon dioxide emissions and hence more environmental degradation, which is coherent with many studies, such as Wang and Yang [47] as well as Wang and Zhao [48]. Moroccan residential energy use is noted to have the smallest effect on RCO 2 PC. This may be attributed to the fact that Morocco relies heavily on energy imports and that it remains a low-income country by international standards. This, of course, affects Moroccan households' energy use patterns and explains the recent interest in using intermittent renewable energy sources.

ARDL Short-Run Results
As per the short-run ARDL results presented in Table 6, the four countries' environments are not significantly polluted as a result of urbanization. However, the lagged values of the urbanization have a significant negative association with RCO 2 PC emissions in Algeria and Egypt. This outcome may be because both countries have invested heavily in clean energy by completing gas market reforms. Egypt has invested in several projects that allow the most isolated and poorest citizens to be better connected to the natural gas network. In 2018, local natural gas arrived at 2.3 million homes. Moreover, economic growth affects RCO 2 PC emissions negatively in Morocco, meaning that growth is in favor of environmental health. On the other hand, the GDP-squared term has a significant positive association with RCO 2 PC emissions in Morocco. The short-run results further show that the relation between RECPC and RCO 2 PC emissions is positive and significant at a 1% significance level in all countries, except Morocco.
As shown in Table 6, the dummy variable of Tunisia is significant and positive. This implies that since the Jasmine Revolution [44], RCO 2 emissions have accelerated in Tunisia. In addition, the sign (-) with the statistical significance of the Error Correction term (ECM t−1 ) supports the long-term equilibrium relationships defined for the four countries. ECM t−1 suggests that the system shocks will be adjusted by 89% in Morocco, 86% in Tunisia, 58% in Algeria, and 94% in Egypt, over the following year.
To evaluate the accuracy of all individual ARDL models, four standard diagnostic tests are applied and presented in Table 7. The Lagrange Multiplier (LM) test confirms the absence of serial correlation at the 5% significance level in all models. The JB normality test reveals that all residuals have a normal distribution. The Ramsey RESET test results show that the short model is well specified, except for Egypt. Furthermore, the Autoregressive Conditional Heteroscedasticity (ARCH) test shows that the error terms are free from heteroscedasticity problems in all models. The CUSUM and CUSUMQ graphs developed by Brown et al. [49] are plotted to test the stability of the estimated models. As indicated in Figure 3, the trend of both graphs shows that models are stable as they are lying between upper and lower limits in all countries, except for Egypt. Indeed, Figure 3 shows that the CUSUM plot for Egypt is completely stable within 5% of the critical bands contrary to the CUSUMQ plot, which deviates for a small period; nevertheless, the deviation seems to be transient as the CUSUMQ plot returns completely toward the criteria's bounds. Therefore, we argue that the estimated ARDL Egypt model is roughly stable. At the same time, we should bear in mind that our findings should be considered with caution.   Notes: F-statistics appear above the parentheses, whereas p-values appear between the parenthesis. Normality of error term, serial correlation, autoregressive conditional heteroskedasticity, and functional of the short-run model is indicated by χ 2 NORMAL, χ 2 SERIAL, χ 2 ARCH, and χ 2 REMSAY respectively.

Granger Causality
To complete the aim of this study, we proceeded to define the sense of causal relationships using the standard Modified Wald test of Toda and Yamamoto [12]. The Wald test's results and hence the causality directions are summarized in Table 8. Firstly, economic growth Granger causes RCO 2 PC emissions in Morocco and Tunisia, which supports the findings of Liddle and Lung [50]. This suggests that energy policy decisions geared toward reducing CO 2 emissions in the Moroccan and Tunisian residential sector can be made without fear of disrupting economic growth. Secondly, in the same countries, the casual effect is running from urbanization to RCO 2 PC emissions. In fact, urbanization increases resident income and reduces household size, impacting RCO 2 PC emissions in multiple aspects. Therefore, a reasonable urban policy should be developed within the two countries. This result is in line with Yazdi and Dariani [51] who reported a causality relationship from urbanization to CO 2 emissions in Bahrain, Bangladesh, Indonesia, Iran, Iraq, and the Philippines. The results reveal also that the Moroccan and Tunisian residential energy use is driven by urbanization. This means that urbanization contributes to an increase or a decrease in the overall use of residential resources. In addition, the casual effect from the RECPC to RCO 2 PC emissions was expected, as Morocco's residential energy mix is dominated by fossil fuels, especially Liquefied Petroleum Gas (LPG), which leads to a significant RCO 2 emission. Furthermore, the renewable energies introduced into the residential energy mix have not yet met the necessary threshold to begin mitigating CO 2 Notes: F-statistics appear above the parentheses, whereas p-values appear between the parenthesis. Normality of error term, serial correlation, autoregressive conditional heteroskedasticity, and functional of the short-run model is indicated by χ 2 NORMAL, χ 2 SERIAL, χ 2 ARCH, and χ 2 REMSAY respectively.   In the case of Tunisia, no direct link was observed between RECPC and RCO 2 PC emissions. Indeed, the RECPC crosses economic growth to indirectly explain the dynamics of RCO 2 emissions. Therefore, Tunisia should pay attention to this indirect relation, as the feedback hypothesis between economic growth and RECPC was found to be relevant. This means that unlike Morocco, RECPC and income growth are complementary. In this context, policies that focus on reducing residential emissions by reducing residential energy consumption would have an effect on the economy of Tunisia. In parallel, this result may suggest exploring for new sources of energy supply and encouraging the use of clean energy to support long-term economic development.

MOROCCO
The Algerian case shows three causal relationships that are unidirectional. Urbanization causes economic growth, RECPC, and RCO 2 PC emissions. Then, any policy initiated regarding urbanization can affect Algeria's economic growth, energy use, and CO 2 emission in the residential sector. Therefore, to support urbanization along with economic growth and reduce RCO 2 emissions, an urban policy aimed at improving urban infrastructure and using additional economically-viable energy sources should be promoted. However, no causal effect was detected between RECPC or economic growth and RCO 2 PC emissions.
For Egypt, there is unidirectional causality from RCO 2 PC emissions to RECPC. Therefore, introducing new policies to reduce RCO 2 PC emissions can lead the country to an energy crisis and thus impact the development of the Egyptian economy. The unidirectional causality from RECPC to economic growth confirms this conclusion. It means that economic growth is a function of RECPC and therefore, RECPC is a determinant factor of economic growth. The results also revealed that economic growth causes urbanization; i.e., economic growth leads to urbanization. In contrast to Morocco, Tunisia, and Algeria, there is an inverse causality running from RCO 2 PC emissions to urbanization. Hence, a direct strategy to curb RCO 2 PC emissions may have many negative impacts, such as fluctuations in energy prices and unemployment, leading to a slowdown in the urbanization process.

Conclusions and Policy Implications
This paper investigated the relationship between residential carbon dioxide emissions, urbanization, economic growth, and residential energy consumption for Morocco, Tunisia, Algeria, and Egypt from 1990 to 2016. To explore that linkage, we opted for the two-stage procedure: first, we examined the long-run relationships between the variables by using the ARDL bounds testing approach. Second, we employed the Toda-Yamamoto non-Granger causality test to examine the causal relationships between variables.
The empirical findings support the occurrence of cointegration between variables for all countries. In the long run, urbanization is the first main factor driving the changes in RCO 2 PC emissions in the four Northern African countries. It has a positive effect on RCO 2 emissions in Morocco, unlike Algeria and Egypt, meaning the increase in urbanization has been to the detriment of environmental quality in Morocco. This outcome can be justified as Morocco is highly dependent on the use of non-renewable energies to meet the residential energy needs. The study also supports the presence of the EKC relationship between GDPPC and RCO 2 PC emissions under the conventional EKC turning point formula in Morocco and Tunisia. The nonlinear relationship between GDPPC and RCO 2 PC emissions, in the long run, is U-shaped in Morocco and inverted U-shaped in Tunisia. This implies that economic growth in Morocco will keep raising residential carbon dioxide emissions if no improvements are applied in the residential energy policy. Instead, the impacts of the linear and nonlinear terms of GDPPC are not statistically significant in Algeria and Egypt. The long-run results also revealed that RECPC has a significant positive impact on RCO 2 emissions in all countries.
Furthermore, the Toda-Yamamoto non-Granger causality test reveals a multiple causal relationship. The results show that there is a unidirectional causality running from GDP to RCO 2 PC emissions in Morocco and Tunisia. Moreover, urbanization Granger causes RCO 2 PC emissions in Morocco, Tunisia, and Algeria. Regarding Egypt, the causality is running from RCO 2 PC emissions to urbanization. The results reveal also that there is a unidirectional Granger causality from residential energy consumption to RCO 2 PC emissions in Morocco. However, in Egypt, the causal link runs in the reverse sense. For Tunisia, residential energy use does not directly affect CO 2 emissions from the residential sector. They use economic growth to explain the RCO 2 PC emissions dynamics in an indirect way. Finally, in the case of Algeria, no causal relationship was found between RECPC and RCO 2 PC emissions.
The empirical results discussed above have the following important policy implications for the four Northern African countries: (i) The current paper confirms that urbanization is the first main factor influencing RCO 2 emissions per capita in Morocco. Moreover, it has been proved that increased urbanization boosts RCO 2 emissions. Limiting urbanization to control RCO 2 emissions cannot be considered, as reducing urbanization could have an adverse effect on the country's development. However, it seems more relevant to try to limit the consumption of butane gas in the sector. In this regard, policymakers should review the programs of subventions, and quite frankly, some subsidies must be removed. Concerning Morocco, butane subsidies widen the gap with other energy sources consumed in the residential sector and must be removed as soon as feasible to minimize the sector's consumption growth and emissions. Indeed, direct support for renewable energy projects in all countries would be more effective. For instance, support and subsidy programs should be put in place to install non-emitting and sustainable heating and cooling systems. (ii) Secondly, the results reveal that income is strongly linked with RCO 2 emissions in Tunisia and Morocco, and since economic development cannot be restrained, a pressure on the environment is expected. Obviously, the households will seek high comfort and luxury in their residences. Therefore, it is important for policy-makers to review existing building standards to take sustainability goals to the next level. Such policies will accelerate the transition of households toward renewable energies, and hence, they will not only reduce residential greenhouse gas emissions but will also relieve the public funds of governments. Notably, the two countries can save a considerable amount of imported energy. (iii) The positive link between RCO 2 emissions and REC in all countries calls for the need to control residential energy consumption in order to mitigate residential GHG emissions. Nevertheless, this is only possible with the involvement of civil society, i.e., social acceptance of the necessary transformations and citizen engagement. In this regard, awareness campaigns should be planned to educate and train households regarding mitigation and adaptation for environmental degradation. In addition, encouraging the direct participation of citizens in decision making in residential energy policy or the context of energy-saving projects would be of value. (iv) Finally, the governments should allocate more funds for research and development activities to improve energy efficiency and develop low-carbon technology. This will ensure energy security, urbanization development, and hence sustainable economic growth.

Data Availability Statement:
The data can be accessed upon request from any of the authors.

Conflicts of Interest:
The authors declare no conflict of interest.