An analysis of the effects of oil and non-oil export shocks on the Saudi economy

  • Received December 25, 2022;
    Accepted February 7, 2023;
    Published February 13, 2023
  • Author(s)
    Uzma Khan
    ORCID Researcher ID ,
    Aarif Mohammad Khan
    ORCID
  • DOI
    http://dx.doi.org/10.21511/imfi.20(1).2023.12
  • Article Info
    Volume 20 2023, Issue #1, pp. 127-137
  • TO CITE АНОТАЦІЯ
  • Cited by
    1 articles
  • 548 Views
  • 326 Downloads

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

As the world’s largest oil exporter, Saudi Arabia faces the same pressures as any other government to expand its economy. Saudi Vision 2030 is to reduce the country’s reliance on oil exports and revenues. One of the main goals of Saudi Vision 2030 is to increase the share of GDP that does not come from oil. Dynamic autoregressive distributed lag (ARDL) cointegration is used to look at how oil exports and exports of goods other than oil affect GDP growth. The results of the dynamic ARDL simulation show that there is both long-term and short-term cointegration between the variables. The dynamic ARDL simulation tests rely on the presence of cointegration to show that a 1% increase in oil exports will boost Saudi Arabia’s economic growth by about 0.48% in the long run and 0.18% in the short run, depending on the type of time frame. In the same way, the results about non-oil exports showed that an increase in non-oil exports would boost Saudi Arabia’s economic growth by 0.26 percentage points in the long run and by 0.16 percentage points in the short run. This is a good sign of Saudi Arabia’s efforts to diversify its economy away from oil exports and make room for international investors to help the country reach its Vision 2030 goals.

Acknowledgment
This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1444).

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    • Figure 1. ± 10% shocks in oil export
    • Figure 2. ± 10% shocks in non-oil export
    • Table 1. Descriptive statistics
    • Table 2. Correlation matrix
    • Table 3. Unit root test results
    • Table 4. Bound test for ARDL
    • Table 5. Dynamic ARDL simulations
    • Investigation
      Uzma Khan
    • Supervision
      Uzma Khan
    • Writing – original draft
      Uzma Khan
    • Writing – review & editing
      Uzma Khan
    • Conceptualization
      Aarif Mohammad Khan
    • Data curation
      Aarif Mohammad Khan
    • Formal Analysis
      Aarif Mohammad Khan
    • Methodology
      Aarif Mohammad Khan
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