“Can sustainable development goals go hand in hand with economic growth? Evidence from Morocco”

This study investigates the influence of implementing the Sustainable Development Goals (SDGs) on the economic growth of Morocco. The main purpose is to empirically verify whether the pursuit of sustainable development goals can go hand in hand with economic growth. Employing a robust least squares regression, this paper analyzed carefully chosen data that closely aligns with the essence of the SDG indicators. The findings reveal a positive correlation between financial inclusion and financial stability and the economic growth. Conversely, the poverty reduction exerts a positive effect on economic growth, while the quality of education does not sufficiently account for changes in GDP. Moreover, the estimates indicate a favorable outcome stemming from the enhancement of institutional quality, reflected in improved economic freedoms, as well as the reduction of administrative burdens, both of which positively contribute to economic growth. Furthermore, the results demonstrate a negative impact of renewable energy and a negligible influence of energy efficiency on Morocco’s economic growth. The negative impact of renewable energy can be attributed to a number of sources, including high initial costs, structural changes in the industry and the need to set up infrastructure for production. The positive effects of adopting renewable energies on economic growth can take time to be realized over the very long term.


INTRODUCTION
Sustainable development (SD) has gained significant importance in the field of economics.Despite the extensive literature on this topic, there is a need to clarify the issues surrounding SD and further understand its implications for human development.The international community has sought to strike a balance between environmental protection and economic development through the mainstreaming of sustainable development.Sustainability is now considered a guiding principle for global development, even within a capitalist framework.This has fostered a favorable alliance between environmentalists and developmentalists.International initiatives for sustainable development are based on the 17 goals and 169 corresponding targets outlined in the 2030 Agenda.After extensive negotiations involving 193 UN countries, the global Agenda 2030 is now being implemented at national and international levels.The 17 universal goals of the 2030 Agenda will play a crucial role in shaping Morocco's development strategy in the coming years.These new sustainable development goals replace the previous Millennium Development Goals (MDGs).The SDGs are designed to be integrated, interconnected, and indivisible, aiming to achieve what the MDGs could not by encompassing the social, economic, and environmental dimensions of sustainable development.
The SDGs offer a mechanism for attracting investment and mobilizing resources in sectors that contribute to sustainable economic growth.Many of these goals, such as clean energy, infrastructure development and sustainable agriculture, offer opportunities for innovation, job creation and private sector engagement.By focusing on these areas, countries can attract domestic and foreign investment that drives economic growth while advancing sustainable development goals.The SDGs also highlight the importance of inclusive growth, which ensures that the benefits of economic development are shared equitably across all segments of society.By addressing issues such as poverty, inequality, gender gaps and access to education and healthcare, the SDGs promote a more inclusive economic system.Inclusive growth not only reduces social inequalities, but also improves economic productivity by ensuring that all people have equal opportunities to contribute to and benefit from economic progress.In addition, the SDGs recognize the need for sustainable consumption and production patterns.The transition to a more sustainable and circular economy can generate economic growth by creating new markets, promoting resource efficiency, reducing waste, and stimulating technological innovation.This shift towards sustainable production and consumption can stimulate economic activity, create jobs, and strengthen the competitiveness of industries in the long term.

LITERATURE REVIEW
Subsequent to a focused literature review, the forthcoming section will expound upon the development of research hypotheses.These hypotheses will serve as the foundation for constructing an econometric model that can be empirically tested.The theoretical research hypotheses will be systematically classified into four principal axes: i) axis 1 relating to finance and sustainable economic development, ii) axis 2 relating to the social aspect of sustainable economic development, iii) axis 3 relating to the energy sector and sustainable development, and iv) axis 4 relating to economic freedom and sustainable development.

Financial aspects of SDGs and economic growth: financial inclusion and stability
Financial inclusion plays a crucial role in addressing poverty (SDG Goal 1), reducing inequality (SDG Goal 10), and promoting access to healthcare and overall well-being (SDG Goal 3).While extensive research has examined the interplay between financial inclusion and various facets of development, a specific focus on the nexus between financial inclusion and sustainable development remains limited.H1: Economic growth is influenced by the financial targets of the SDGs.
H1a: Financial inclusion has a positive impact on economic growth in Morocco.
H1b: Financial stability has a positive impact on economic growth in Morocco.
H2: Economic growth is influenced by the social goals of the SDGs.
H2a: Poverty reduction has a positive impact on economic growth in Morocco.
H2b: Education has a positive impact on economic growth in Morocco.
H3: Economic growth is influenced by the energy aspects of the SDGs.
H3a: Renewable energy consumption has a positive impact on economic growth in Morocco.
H3b: Energy efficiency has a positive impact on economic growth in Morocco.
H4: Economic growth is influenced by the institutional quality and economic freedoms aspects of the SDGs.
H4a: The simplification of the administrative burden has a positive impact on economic growth in Morocco.
H4b: The reduction of barriers to business start-ups has a positive impact on economic growth in Morocco.

METHODS
Once the research hypotheses have been determined, the econometric model is specified.The data that will be used in the empirical study and that will be used to obtain the results are then presented.

Model specification
Econometricians widely recognize the issue of distributional inconsistency and multicollinearity in time series data, which poses a significant concern.These problems can lead to biased estimations and misinterpretation of models.To address this, econometricians have developed the robust least squares regression method, which aims to mitigate these issues.Robust least squares regression is particularly effective in accounting for autocorrelation and heteroscedasticity commonly associated with time series analysis (Yang 2004; Audiert & Catoni 2010).In this study, robust least squares regression is adopted due to the presence of variables that are stationary in first and second differences, denoted as I(1) and I(2), respectively.This approach ensures the stability and robustness of the results.A simple linear model is employed to establish a functional relationship between the variables considered in this study.The simple linear macroeconomic model is presented explicitly as follows: It is important to note that the simple macroeconomic model described (Table 1) represents a system of equations in which the variables included have mutual influence on each other.

Data
The data utilized in this study comprise both annual and quarterly data sourced from the World Development Indicators (WDI) database.These data span the timeframe from 1980 to 2020.The subsequent provides an overview of the descriptive statistics for the variables employed.
The data used in this analysis is sourced from the World Development Indicators, which is published by the World Bank (2021).By examining Table 2, one can observe the maximum and minimum values, which reflect the range of distribution for each variable over time.Notably, all variables exhibit a significant range between their maximum and minimum values, indicating substantial fluctuations over the study period.Additionally, all variables demonstrate positive skewness, suggesting a right-skewed distribution compared to the normal distribution.This departure from normality violates the assumptions required for ordinary least squares (OLS) regression, rendering it an inefficient estimator for this analysis.
After formulating the research hypotheses and specifying the econometric model, the next step in the empirical study is to select an appropriate econometric method.To this end, tests will be carried out to assess collinearity, examine the stationarity of the time series and study cointegration.In addition, the paper will analyze the robustness of the estimate obtained by the chosen method.Note: 1 The misery index, devised by economist Arthur Okun, is an economic indicator used to gauge the economic well-being of the average citizen.It is computed by summing the seasonally adjusted unemployment rate and the annual inflation rate.
The underlying belief is that increased unemployment and inflation impose social burdens on a country.These steps are crucial to guarantee the reliability and validity of the empirical analysis.

Choice of the econometric method to be used
Once the econometric model is established, research hypotheses are defined, and the model is specified, the subsequent phase involves conducting the empirical study.To proceed effectively, the selection of a fitting econometric method is imperative.This selection is guided by a sequence of crucial steps, including collinearity tests to evaluate the existence of multicollinearity, an assessment of time series data stationarity, and an exploration of potential cointegration among variables.These steps are pivotal in determining the appropriate econometric method that should be employed for the empirical analysis.

Collinearity test
The correlation matrix table (Table 3) presents the relationships between the variables under consideration.The findings indicate that financial inclusion, financial stability, and energy efficiency exhibit a positive correlation with per capita income.Similarly, poverty, education quality, renewable energy, and the respective economic variables demonstrate a positive correlation with GDP per capita.However, it is noteworthy that the explanatory variables display substantial and statistically significant correlations among themselves, suggesting the presence of multicollinearity in the model.This raises concerns about the potential interdependence and shared information among the variables, which can impact the accuracy and reliability of the analysis.The existence of multicollinearity has the potential to cause inflation in the variances of both the model and its coefficients, subsequently undermining the reliability of inferences drawn from the analysis.The consequences may include coefficients with incorrect signs or implausible magnitudes.The Belsley, Kuh, and Welsch (BKW) test, using eigenvalue values exceeding the 0.5 threshold, can identify collinearity.Table 4 indicates the presence of collinearity based on this criterion.

Analysis of time series stationarity
Time series data frequently display patterns such as trends, seasonal and non-seasonal cycles, and outliers.These characteristics can contribute to the non-stationarity of the data.The existence of non-stationarity, identifiable through the presence of a unit root, contradicts the assumptions of constant means and variances inherent in OLS regression.Conducting a unit root test is crucial to avoid spurious results in regression models that ignore stationarity properties.The augmented Dickey-Fuller (ADF) test is used instead of the Dickey-Fuller (DF) test as it considers potential serial correlation by including lagged differences of the dependent variable.When the series displays an order of integration of either I(0) or I(1), the autoregressive distributed lag (ARDL) approach becomes applicable.In cases where this condition is not met, the RLS method stands as a viable alternative.
The ADF test in Table 5 indicates that the variable for quality of education (QEDUC) is stationary at the level, denoted by integration order I(0).This is supported by the ADF t-statistic.On the other hand, the variable for financial inclusion (INCFIN) requires two differentiations to achieve stationarity, indicating an integration order of I(2).The remaining variables exhibit an integration order of I(1).It is important to note that the distributions of these variables are not consistent throughout the study period, except for quality of education.Therefore, any interpretations based on these variables should be considered temporary.To examine the long-term relationship between the variables, it is necessary to conduct the autoregressive distributed lag (ARDL) Bounds cointegration test.

Cointegration analysis
Differentiating time series variables can often lead to the loss of important long-term information and properties related to the equilibrium relationship between the variables.It is important to consider the non-stationarity of residuals, as it violates the standard assumptions necessary for applying OLS methods.To assess the long-run equilibrium connection between economic growth and the explanatory factors, the ARDL bounds test approach implemented by Pesaran and Shin (1999) and Pesaran et al. ( 2001) has been adopted.This procedure allows for the examination of the long-term relationship while considering the non-stationarity of the variables.tionship, while the alternative hypothesis is embraced, signifying the presence of a long-run relationship among the variables within the model.Nevertheless, the notably elevated F-statistic in relation to the upper bound critical value raises a potential red flag regarding the presence of multicollinearity among the variables in the model.To tackle this concern, the decision is made to employ the robust least squares method for estimation.This method adeptly prevalent issues like autocorrelation, heteroscedasticity, and multicollinearity that often arise in the context of time series analysis (Audiert & Catoni, 2010).

RESULTS
After opting for the robust least squares method, the focus shifts to analyzing the robustness of the estimation process.This analysis unfolds in the following manner: i) Testing the model's specification; ii) Conducting an examination of autocorrelation and partial correlation among the residuals; iii) Assessing the normality of the residuals; iv) Carrying out tests for both serial correlation and heteroscedasticity; and v) Evaluating the model's stability.

Model specification test
When the functional form of a model is misspecified, it often indicates the omission of crucial variables or the disregard of non-linear relation-ships.Such misspecification can yield biased coefficients, heteroscedasticity, and autocorrelation.Four widely used techniques are employed to test for such misspecification: BAMSET, WSET, the Q-Sum test, and the RESET test.Among these, the RESET test stands out for its resilience against issues stemming from non-linearity, heteroscedasticity, and autocorrelation.The outcomes of the Ramsey RESET test provide assurance that the model maintains proper specification, supported by the probability value surpassing 5%, as displayed in Table 7.

Auto-correlation and partial correlation testing of residuals
In this study, various diagnostic tests were conducted to assess the adequacy of the model.These assessments included examining the correlogram, histogram, autocorrelation, and heteroscedasticity.Table 8 presents the correlogram statistics, illustrating the absence of significant autocorrelation or partial correlation within the model.Moreover, the Q statistic remains statistically insignificant at the 5% confidence level, further support for the lack of autocorrelation.

Testing the stability of the model
To evaluate the model's stability, two tests were utilized: the CUSUM and CUSUMSQ tests.These tests represent the statistical value over time, along with the associated confidence inter-val.Should the test statistic lie beyond the limits of the confidence interval, it suggests a possible disturbance in the model's structure or disparities in its parameters.Figure 2 illustrates that, at the 5% confidence level, the model maintains stability, as the test statistic remains within the confines of the confidence interval.
Figure 3 showcases confidence ellipses for the variables being examined.The significant aspect here is that all variables fall within their corresponding ellipses, signifying that the model's coefficients sustain stability at the 5% significance level.This finding serves to bolster the overall stability of the estimated model and demonstrate additional confidence in the credibility of the coefficients.

Serial correlation test and heteroscedasticity test
Heteroscedasticity can occur when a regression model is misspecified, important variables are omitted, or outliers are present.It does not bias estimated coefficients, but it affects the accuracy of standard errors, test statistics, and confidence intervals.The LM serial correlation test estimated using the Breusch-Godfrey method and the heteroscedasticity test performed using the ARCH test, indi- cated that the model is not affected by serial correlation or heteroscedasticity issues.This conclusion is based on the probability value, which is higher than the 5% significance level, as shown in Tables 9 and 10.Furthermore, the coefficient on poverty is statistically significant at the 10% level, leading us to accept hypothesis H2a.However, the quality of education does not provide an explanation for the impact on GDP per capita, resulting in the rejection of hypothesis H2b.The results also demonstrate a contrary effect of renewable energies, contradicting the initial hypothesis.Additionally, the impact of energy efficiency on the economic growth of Morocco is found to be insignificant.Consequently, hypothesis H3 is rejected based on these findings.
The results show that reducing the administrative burden has a positive relationship with economic growth in Morocco, which has made fundamental changes in this direction.Finally, the estimation shows a significant impact of the reduction of procedures for business creation on GDP per capita.These results lead us to accept the two sub-hypotheses, H4a and H4b, and thus to accept the hypothesis H4.

DISCUSSION
The analysis acknowledges that Morocco has made significant progress in promoting financial inclusion, as evidenced by the positive impact of financial inclusion on economic growth, poverty reduction, and overall well-being, as highlighted in the literature (Guru & Yadav, 2019; Cull et al., 2021; Huang & Zhang, 2020).However, the analysis also highlights the challenges faced in achieving broader access to financial services, such as insufficient resources, a shortage of bank branches, and a lack of trust in financial institutions.The results regarding the stability of Morocco's banking sector and its resilience to shocks are consistent with the literature, which emphasized the positive impact of financial stability on economic growth and development (Puatwoe & Piabuo, 2017).This indicates that the country has taken appropriate measures to strengthen its financial sector, contributing to overall economic stability and growth.The study also demonstrates the progress made by Morocco in reducing poverty, but it also identifies it as a significant ongoing challenge, which is in line with the literature recognizing the positive link between poverty reduction and economic growth in the country (Ade'Soyemi et al., 2020).The efforts made by the government, such as the National Human Development Initiative, have contributed to poverty reduction, but there is still a considerable number of people living below the poverty line, particularly in rural areas.
While Morocco has a substantial potential for renewable energy, especially solar energy, and has made efforts to explore hydro, solar, and wind resources for electricity generation, the results contradict the literature, which highlights the importance of renewable energy in achieving sus-tainable development and environmental goals (Arminen & Menegaki, 2019).The positive focus on renewable energy is a step towards ensuring a sustainable and environmentally friendly energy supply, but the negative correlation between renewable energy and GDP and the non-significance of the energy efficiency coefficient indicate that additional efforts are required in this direction in the Moroccan context.The factors behind these negative effects on growth can be identified in several regards.Firstly, the high initial costs associated with the transition to renewable energies, although beneficial in the long term in terms of carbon emissions and sustainability, can lead to significant initial investments.In addition, structural changes within the energy industry are another key factor.The transition to renewable energy sources may require major structural transformations, including adjustments and replacements in jobs and skills linked to fossil fuels, which may cause short-term disruption and impact economic growth.In addition, setting up infrastructures for the production, distribution and storage of renewable energies may require considerable resources and time.
The results also show the positive impacts of economic freedom on Morocco's growth, which aligns with the literature emphasizing the role of economic freedom -as a proxy of institutional quality-in promoting economic performance and sustainable development (Nystrom, 2008).The government's efforts to simplify administrative burdens, tax procedures, and regulatory requirements have led to improvements in the country's ranking and business environment.However, challenges remain, such as brain drain, the informal economy, and restrictive labor market legis- lation, which require further attention and additional reform efforts.Overall, the analysis of the results indicates that Morocco has made progress in various areas related to sustainable development and economic growth.However, it also highlights the challenges that need to be addressed, in line with the findings and recommendations from the literature.Continuous efforts, reforms, and poli-cies are necessary to ensure sustainable development and inclusive growth for all citizens, aligning with the country's commitment to SDGs.The findings suggest that embracing SDGs has the potential to promote economic growth that is both sustainable and equitable across various dimensions, including the economy, society, and quality of institutions.

CONCLUSION
The economic and social development model in the context of the SDGs raises important questions regarding economic sovereignty.This article examines this issue by conducting an empirical analysis and reflecting on the sustainability and inclusiveness of economic policies in Morocco.Despite the implementation of significant reforms since 2002 to promote financial sector openness and achieve the MDGs and SDGs, financial exclusion remains prevalent, particularly among specific groups such as youth, low-income households, women, the least educated, and rural residents.However, the findings indicate that financial stability in Morocco has a positive impact on economic growth.
Furthermore, this study reveals a negative correlation between economic growth and renewable energy consumption.This suggests that the increase in energy demand has outpaced the efforts in renewable energy production.Despite the considerable potential for solar energy, Morocco currently relies heavily on energy imports.To ensure sustainable and environmentally friendly energy supply, Morocco should explore opportunities to harness hydro, solar, and wind resources for electricity generation.Regarding economic freedom, the results align with the assumptions.Morocco has made significant strides in reducing administrative and regulatory burdens.This progress is attributed to a series of government measures that have improved all factors related to economic freedom.Substantial efforts have been made to enhance economic freedoms in Morocco, including simplifying business startup procedures, as supported by the empirical findings.Overall, the adoption of SDGs by Morocco can generate a more sustainable and equitable economic growth, even though additional efforts need to be considered in the energy sector.

Figure 2 .
Figure 2. Stability of the model by the CUSUM test and the CUSUMSQ test

Figure 3
Figure 3. Confidence ellipse Stern (2007) Kammen (2010)tion of renewable energy, comprehensive evaluations are essential, encompassing economic costs, secondary advantages, and avenues for financing through climate finance.The viability of renewable energy is underscored by its potential for cost savings relative to fossil fuels, particularly evident in remote rural regions without grid connectivity, an observation made byCasillas and Kammen (2010).In this endeavor, cost considerations assume even greater importance when coupled with burden-sharing frameworks that define the costs and benefits of reducing greenhouse gas emissions as a global public good, a perspective elucidated byStern (2007).
Doris et al. (2009) (2010)that indicators of banking sector and stock market development synergize to propel economic growth.Recent studies in numerous countries underscore the imperative of prioritizing financial inclusion as a pivotal policy objective(Cull et al., 2021).Governments' emphasis on financial inclusion underpins its positive influence on economic growth, financial stability, poverty reduction, and diminished income inequality, as suggested byHuang and Zhang (2020).Cabeza-Garcıa et al. (2019) assert that women's engagement in the financial system contributes to reduced inequality, heightened physical and social well-being, thus bolstering economic advancement.The work ofMatekenya et al. (2021)contends that access to and utilization of financial services foster enterprise creation, facilitate investments in health and education, mitigate risks, cushion financial shocks, and elevate human development.Puatwoe and Piabuo (2017) establish a strong, enduring impact of various financial development indicators on economic growth.Anarfo et al. (2019)suggest a mutual interplay between financial inclusion and financial sector development, with each phenomenon propelling the growth trajectory of the other.ityonmorecomprehensivemetrics of sustainable development.Financial stability can be integrated into the framework of Goal 16 of the SDGs, which calls for, among other things, effective economic and political institutions.This financial stability is closely linked to Goal 8 of the SDGs, which emphasizes that economic growth cannot take place without economic and financial stability.consumption,naturalresources,andgrosscapitalaccumulationoneconomicgrowth,arrivedattheconclusionthat energy consumption fosters GDP growth in high-income countries.Conversely, Davis and Caldeira (2010) attribute the observed decrease in energy intensity within industrialized nations, to some extent, to the migration of energy-intensive industries to developing countries.Clean and dependable energy access holds paramount importance for human development, encompassing domains such as health, gender equality, education, and environmental security.In the context of mitigating greenhouse gas emissions as a global public good, cost considerations must be aligned with burden-sharing frameworks, a concept articulated byStern (2007).Notably, renewable energy exhibits potential for cost savings when compared to fossil fuels, particularly in remote rural regions lacking grid connectivity, as evidenced by research byCasillas and Kammen (2010).Concurrently, enhancements in energy efficiency hold promise for yielding sustainable reductions in production costs and bolstering competitiveness, an assertion supported by Carrillo-Hermosilla et al. (2010).On a broader scale, energy efficiency is acknowledged as a crucial strategy for curbing carbon emissions both nationally and globally, as emphasized byDoris et al. (2009).Enhancing energy efficiency holds the potential to yield lasting reductions in production costs and elevate competitiveness, as indicated by Carrillo-Hermosilla et al.(2010).Recognized as a pivotal strategy, energy efficiency stands as a significant avenue for mitigating carbon emissions both on a national and global scale, a viewpoint emphasized byDoris et al. (2009).1.4.Institutional aspects of SDGs and economic growth: economic freedom Economic freedoms play a crucial role in improving economic performance, advancing economic integration, and promoting sustainable development.These freedoms encompass improvements in institutional frameworks, regulations, and government policies to minimize barriers and create a conducive environment for economic growth.Economic freedom is closely related to the quality of political and economic institutions, making it relevant to Goal 16 of the MDGs.The presence of economic freedoms can contribute to entrepreneurial freedom, job creation, and economic growth, aligning with SDG Goal 8.For instance, economic freedoms can support competitive markets, protect intellectual property, and foster an environment conducive to innovation and investment.Nevertheless, it is crucial to acknowledge that the absence of economic freedoms can yield adverse consequences.This might involve diverting resources from more productive paths, establishing entry

Table 1 .
Definition of variables used

Table 4 .
Variance decomposition of the coefficients

Table 7 .
Ramsey RESET test

Table 10 .
LM serial correlation test

Table 11 .
Robust least squares regression estimates