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

  • Received June 9, 2023;
    Accepted September 1, 2023;
    Published September 18, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.21(3).2023.51
  • Article Info
    Volume 21 2023, Issue #3, pp. 656-670
  • TO CITE АНОТАЦІЯ
  • Cited by
    5 articles
  • 385 Views
  • 111 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

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.

view full abstract hide full abstract
    • Figure 1. Normality test for residuals
    • Figure 2. Stability of the model by the CUSUM test and the CUSUMSQ test
    • Figure 3. Confidence ellipse
    • Table 1. Definition of variables used
    • Table 2. Descriptive statistics
    • Table 3. Correlation matrix
    • Table 4. Variance decomposition of the coefficients
    • Table 5. Augmented Dickey-Fuller (ADF) unit root test
    • Table 6. ARDL limit test
    • Table 7. Ramsey RESET test
    • Table 8. Correlogram statistics
    • Table 9. Heteroscedasticity ARCH test
    • Table 10. LM serial correlation test
    • Table 11. Robust least squares regression estimates
    • Conceptualization
      Mustapha Ziky, Latifa El-Abdellaoui
    • Data curation
      Mustapha Ziky, Latifa El-Abdellaoui
    • Formal Analysis
      Mustapha Ziky, Latifa El-Abdellaoui
    • Funding acquisition
      Mustapha Ziky, Latifa El-Abdellaoui
    • Investigation
      Mustapha Ziky, Latifa El-Abdellaoui
    • Methodology
      Mustapha Ziky, Latifa El-Abdellaoui
    • Project administration
      Mustapha Ziky, Latifa El-Abdellaoui
    • Resources
      Mustapha Ziky, Latifa El-Abdellaoui
    • Software
      Mustapha Ziky, Latifa El-Abdellaoui
    • Supervision
      Mustapha Ziky, Latifa El-Abdellaoui
    • Validation
      Mustapha Ziky, Latifa El-Abdellaoui
    • Visualization
      Mustapha Ziky, Latifa El-Abdellaoui
    • Writing – original draft
      Mustapha Ziky, Latifa El-Abdellaoui
    • Writing – review & editing
      Mustapha Ziky, Latifa El-Abdellaoui