Assessing the Efficiency of the Saudi Economy Through the Lens of the Global Knowledge Index (2021–2024)

INTRODUCTION

Economic diversification refers to shifting from a narrow, resource-based structure toward a broader mix of high-value goods and services, which is essential for adapting to global market fluctuations and achieving sustainable growth. Diversified economies are typically more resilient to external shocks, less vulnerable to commodity price volatility, and better able to generate stable, high-productivity employment and long-term development. This process is particularly critical for developing countries that seek to enhance global competitiveness, improve living standards, and build more robust and sustainable economic systems.

Within a knowledge-economy perspective, the transition from an oil-dependent model to a diversified, innovation-driven structure requires systematic investment in education, skills, research, and information and communication technologies (ICT), supported by a conducive institutional environment and open, competitive markets. ^1,2 For Saudi Arabia, Vision 2030 explicitly frames this shift as a national priority, emphasising the development of human capital, technological capabilities, and high-value services as means to reduce reliance on hydrocarbons and integrate more deeply into global value chains (GVC).

Despite substantial reforms implemented under Vision 2030, an important question remains regarding the extent to which the Saudi economy has improved its knowledge-based efficiency during 2021–2024, and how its performance compares with advanced and low-performing economies according to the Global Knowledge Index? This raises several related issues: What is the overall efficiency level of the Saudi economy as indicated by the Global Knowledge Index (GKI), how does it compare with developed and low-performing economies, which GKI indices exert the strongest influence on the economy index, and which economic pillars contribute most negatively to its performance?

This study aims to evaluate the efficiency of the Saudi economy through the Global Knowledge Index over the period 2021–2024 by: (i) measuring the efficiency level of the Saudi economy based on GKI results; (ii) conducting a comparative analysis of Saudi Arabia’s performance relative to advanced and low-performing economies; (iii) identifying the GKI indicators that have the greatest impact on the Saudi economy index and clarifying how the economic pillars either constrain or enhance this index; and (iv) deriving policy-oriented recommendations to strengthen the position of the Saudi economy among leading global knowledge economies.

Study hypotheses: In line with these questions, the study tests the following hypotheses:

• 1.

  There are statistically significant differences between the efficiency of the Saudi economy and the average efficiency of advanced economies according to the Global Knowledge Index results for the period 2021-2024.1- There are statistically significant differences between the efficiency of the Saudi economy and the average efficiency of advanced economies according to the Global Knowledge Index results for the period 2021-2024.

• 2.

  The innovation, research and development, and enabling environment indicators exert the strongest influence on the performance of the economy index compared with other GKI indicators.

• 3.

  A decline in the economic openness pillar leads to a reduction in the value of the economic index in Saudi Arabia during 2021-2024, relative to the competitiveness and finance & local value-added pillars, thereby constraining the overall economic indicator.

The importance of this study can be summarised on two levels, at the theoretical level, it enhances the academic literature by evaluating national economic efficiency through the GKI, linking the idea of an economy driven by knowledge to the GKI’s multidimensional structure in order to provide an integrated conceptual and empirical assessment.

At the practical level, the study produces quantitative indicators that help policymakers identify the strengths and weaknesses of Saudi Arabia’s knowledge-related economic performance, benchmark the Kingdom against leading and lagging countries, and design evidence-based policies that support Vision 2030 and future development plans in the areas of knowledge, innovation, and institutional reform.

This study adopts a descriptive-analytical and comparative approach supported by quantitative analysis. It relies exclusively on secondary data drawn from the GKI reports for the years 2021-2024. The analysis focuses on Saudi Arabia and two comparison groups: Leading knowledge economies (United States, United Kingdom, Germany, and France) and low-performing economies represented by the lowest-ranked countries in the GKI (Chad and Angola). This design makes it possible to position Saudi Arabia along the global knowledge spectrum and to estimate the magnitude of the “knowledge efficiency gap” between the Kingdom, frontier economies, and laggards.

The empirical strategy proceeds in three steps. First, descriptive statistics and time-series comparisons are used to track the evolution of GKI scores and sub-indices for Saudi Arabia and the comparison countries over 2021-2024. Gap analysis is then applied to quantify Saudi Arabia’s distance from the top-ranked country in each year, as well as its relative position vis-à-vis advanced and low-performing economies. Second, hypothesis testing for mean differences is conducted using one-sample t-tests to examine whether the efficiency level of the Saudi economy differs significantly from the average efficiency of the advanced economies in the sample. Third, simple regression analysis is employed to explore the association between selected knowledge-related indices and the economy index, with a view to identifying the most influential pillars.

MATERIALS AND METHODS

In the regression framework, the dependent variable is the economy index of the GKI, which captures the knowledge-based performance of the economic sector. The explanatory variables are the GKI indices that represent core knowledge inputs: Pre-university education, technical and vocational education and training, higher education, research and development and innovation, information and communication technology, and a composite index of the enabling environment. Additional analysis is conducted for the three pillars of the economy index itself: Economic competitiveness, economic openness, and finance and local value added, to determine which pillar exerts the strongest positive influence on the overall economy index and which pillar acts as a relative constraint.

Formally, the baseline specification can be expressed as a linear relationship in which the economy index is regressed on the selected knowledge sub-indices, while supplementary regressions relate the economy index to its three internal pillars. Coefficients and significance levels are interpreted as indicative of the direction and relative magnitude of each pillar’s contribution, rather than as evidence of strict causal relationships, given the short time period and the index-based nature of the data. Formally, the baseline specification can be expressed as a linear relationship in which the economy index is regressed on the selected knowledge sub-indices, while supplementary regressions relate the economy index to its three internal pillars. Coefficients and significance levels are interpreted as indicative of the direction and relative magnitude of each pillar’s contribution, rather than as evidence of strict causal relationships, given the short time period and the index-based nature of the data.

In standard economic theory, efficiency refers to the ability of an economy to allocate and utilise its resources in a way that maximises output and welfare given existing constraints, often formalised in terms of optimal combinations of inputs and outputs. ³ In practice, at the macro level, such efficiency is reflected in how effectively countries convert their human, physical, and institutional capital into sustained growth, resilience to shocks, and progress toward development goals. ⁴ However, because this study relies on an international composite index rather than micro-level production data, efficiency is treated in a relative, comparative sense rather than as a formally estimated production frontier. This approach fits the index-based nature of the data and the limited period (2021-2024) and it preserves the original GKI structure while still enabling analysis of convergence, gaps and relative efficiency. Accordingly, differences in the value of economy index and its pillars between Saudi Arabia and advanced economies are thus read as indicators of relative efficiency or inefficiency in leveraging knowledge for economic performance and diversification, rather than as precise measures of technical or allocative efficiency.

This interpretation is consistent with the index’s design and with prior work that uses composite indices to benchmark knowledge-economy readiness and performance across countries.

THEORETICAL FRAMEWORK

In a knowledge-based economy, investment in human capital, research and development, ICT, and institutional quality shapes a country’s capacity to generate, absorb and apply knowledge across sectors, thereby influencing productivity, diversification and international competitiveness. ^1,5

Within this context, the Global Knowledge Index (GKI) which is launched in 2017 by the Mohammed bin Rashid Al Maktoum Knowledge Foundation in partnership with United Nations Development Programme (UNDP) to provide a comprehensive metric of countries’ knowledge-based development, represents a comprehensive international tool that measures countries’ ability to leverage knowledge for development across seven sub-indices: Pre-university education, technical and vocational education and training, higher education, research and development and innovation, information and communication technology, the economy, and the composite enabling environment that reflects the socio-political and economic context of knowledge production and use. ⁶ These sub-indices jointly describe a country’s readiness to build and sustain a knowledge-based economy, and thus offer a suitable lens for analysing how far the Saudi economy has progressed along this path relative to advanced and low-performing economies. It assigns weighted scores to seven sub-indices, with 15% of the overall weight allocated to each of the sub-indices, except 10% to the enabling environment index. Each sub-index comprises a set of pillars and sub-pillars constructed from carefully selected variables, producing a hierarchical structure that allows for both high-level comparisons and detailed diagnostic analysis. ⁷

The knowledge economy contributes to national performance through several channels. First, it enhances productivity by enabling the adoption and adaptation of modern technologies and management practices. Second, it stimulates innovation and the creation of new products and services, which can expand exports and move the country up the value chain. Third, it strengthens human capital by focusing on education, technical training, and skills upgrading, thereby improving labour market outcomes. Finally, it increases the attractiveness of foreign direct investment and supports economic diversification by developing knowledge-intensive sectors such as ICT, advanced manufacturing, and digital services. ⁷

The GKI framework is well-suited to capture these channels because it explicitly measures performance in education, research and innovation, ICT, and the enabling environment, in addition to the economy index itself. By examining how Saudi Arabia scores on these dimensions relative to advanced and low-performing economies, the study positions the Saudi case within the broader literature on knowledge-based development, with particular attention to whether strong or improving knowledge pillars are reflected in higher economy index scores and a narrowing of the gap with frontier countries. ⁶

The economy index within the GKI reflects the interaction between the economic sector and the broader knowledge system. It encapsulates how economic structures, markets and financing mechanisms support or constrain knowledge-based development and, in turn, how knowledge capabilities enhance economic performance. The index is built around three main pillars:

• 1.

  Economic competitiveness, which captures the quality of economic infrastructure, the flexibility of trade and business operations, and the institutional conditions that support competition and investment. Sub-pillars include indicators related to gross fixed capital formation, logistics performance, transport capacity, construction quality, ease of starting a business, insolvency recovery and market transparency.

• 2.

  Economic openness, which reflects the degree of integration into global markets and financial systems, focusing on trade volume, the share of high-technology trade, export and import concentration, as well as financial openness indicators such as the Chinn–Ito index, net foreign investment flows, and debt dynamics. This pillar is crucial for understanding the extent to which an economy can access external knowledge, capital and markets.

• 3.

  Finance and local value added, which assesses the ability of the financial system and tax structure to support productive investment and the extent to which domestic production generates medium- and high-tech value added. It includes measures of domestic credit to the private sector, the financing gap for small and medium-sized enterprises, tax burdens, non-performing loans, the share of medium- and high-tech activities, value added in industry and services, underemployment, and workers’ share of GDP. ⁶

These three pillars are used to interpret the composition and dynamics of Saudi Arabia’s economy index over 2021-2024, rather than constructing an independent efficiency metric. The analysis investigates which pillar contributes most strongly to the economy index and which pillar performs relatively weakly, particularly in comparison with advanced economies. The evidence that economic openness has a lower coefficient and weaker performance than the competitiveness and finance & local value-added pillars is interpreted as a sign that limited openness acts as a constraint on the overall economy index and on Saudi Arabia’s ability to attract investment, diversify exports, and facilitate international knowledge transfer. By grounding the empirical analysis in this index-based theoretical framework, the study remains consistent with the structure and purpose of the GKI while providing a conceptually coherent interpretation of “efficiency” as relative performance and convergence within the global knowledge economy.

LITERATURE REVIEW

Several recent studies have used the Global Knowledge Index (GKI) as a framework to assess education and knowledge performance in Arab countries, including Saudi Arabia. Al-Shahri and Al-Badrani examined the efficiency of education and training in Saudi Arabia using GKI data for 2017-2022, ⁸ focusing on the Kingdom’s position relative to major economies and on the evolution of its education-related sub-indices. Their descriptive-analytical analysis showed that Saudi Arabia improved its ranking in the GKI over time, particularly in pre-university and technical and vocational education, yet still lagged behind leading countries such as the USA, the UK, and Germany. The study attributed these gains mainly to better educational outcomes and increased attention to skills and innovation, while emphasising persistent weaknesses in spending on scientific research and in higher education efficiency. Although informative, this work remains sector-specific (education) and does not extend the analysis to the broader economy index or to the efficiency of economic performance in transforming knowledge inputs into outputs.

In a similar vein, Hesham and Ahmed (2024), ⁹ assessed Egypt’s knowledge performance through the GKI over 2017-2024, combining descriptive statistics with SWOT analysis. Their results indicated only modest improvements in Egypt’s GKI position, with the country surpassing the global average briefly in 2021 before declining thereafter. They found the smallest gap relative to the global average in ICT infrastructure and the largest in the socio-economic enabling environment and concluded that Egypt’s strengths lie in digital infrastructure, while its weaknesses involve underdeveloped research, development, and innovation policies. The authors recommended strengthening education, scientific research and investments in innovation and digital infrastructure. Like Al-Shahri and Al-Badrani, their study uses the GKI as a diagnostic tool but does not explicitly address economic efficiency or cross-country efficiency gaps at the level of the economy index.

Mahfoud and Boualabais (2024) ¹⁰ also applied a descriptive analytical approach to GKI data to analyse the state of the knowledge economy in Arab countries. They documented substantial disparities among Arab states, with Gulf countries occupying relatively advanced positions and Algeria and Iraq ranking lower, thereby revealing a wide intra-regional knowledge gap. While this work situates Saudi Arabia within a broader Arab context, it remains largely descriptive and does not quantify how knowledge performance translates into economic performance or efficiency gaps relative to global leaders.

Beyond GKI-specific studies, a second strand of the literature uses broader knowledge-economy indicators to examine their impact on economic growth and efficiency. (Al-Qasim et al. 2024), ¹¹ employed panel data for twelve Arab countries over 2017-2021 to assess how GKI scores affect GDP and GDP per capita. Their econometric results showed that higher GKI values significantly raise both aggregate output and income per capita, but also that education and ICT pillars are structural weaknesses for most Arab states, including Saudi Arabia. Another study on Saudi Arabia, published by the Middle East Center for Studies Journal, analysed the impact of knowledge-economy indicators (education, RD, ICT, innovation) on real GDP and found generally positive, yet often limited or statistically weak, effects. The authors interpreted this as evidence that Saudi Arabia has not yet fully converted its investments in knowledge inputs into proportional economic returns. Together, these studies confirm that the knowledge economy is an important determinant of growth in the region, but they also highlight an “efficiency gap” between knowledge-related investments and realised economic outcomes.

These works are methodologically stronger in terms of causal inference than purely descriptive GKI studies, yet they typically treat knowledge indicators as explanatory variables for GDP or growth, rather than focusing on composite indices like the GKI economy index. As a result, they shed light on the macroeconomic benefits of knowledge but do not directly examine how GKI-based economic performance in Saudi Arabia compares with the performance of advanced knowledge economies along a common, multidimensional benchmark.

A third line of research focuses on the internal dynamics of the Saudi knowledge economy in the context of Vision 2030. Khan et al. (2021), ¹² combined survey data from Saudi Aramco employees with secondary macro indicators to analyse knowledge-management practices and their implications for diversification and competitiveness. Their findings showed that intellectual capital and ICT adoption improve organisational performance and support the broader transition from an oil-based to a knowledge-based economy. This micro-level perspective reinforces the idea that knowledge assets and digital capabilities are central to Saudi Arabia’s structural transformation, but it does not provide a systematic cross-country comparison or a directly GKI-based assessment.

In parallel, annual GKI reports by UNDP and the Mohammed bin Rashid Al Maktoum Knowledge Foundation consistently position Saudi Arabia as a strong performer in certain knowledge dimensions, particularly pre-university education and technical and vocational education, with overall GKI values around the mid-50s and global rankings near 40–43 in recent years. At the same time, these reports show that Saudi Arabia’s research, innovation and economy sub-indices remain relatively weaker compared to advanced knowledge economies, indicating that substantial gaps persist despite recent progress. These official profiles provide the empirical foundation for benchmarking, but they stop short of conducting formal hypothesis testing on efficiency differences or on the relative influence of specific pillars.

Miller (2017), ¹³ examines the relationship between higher education expansion, research and development (R&D) intensity, and the performance of knowledge economies across Organisation for Economic Co-operation and Development countries (OECD). Using panel data covering several advanced economies over multiple years, the study employs econometric modeling to assess how tertiary education attainment and R&D expenditure contribute to productivity growth and structural transformation. The findings indicate that higher education and R&D investments significantly enhance innovation capacity and long-term economic performance; however, their effectiveness depends on institutional quality, labour market flexibility, and absorptive capacity. The study highlights that merely increasing educational spending does not automatically translate into economic gains unless accompanied by efficient allocation mechanisms and strong governance structures. These findings provide an important comparative benchmark for evaluating the efficiency of knowledge inputs within emerging economies such as Saudi Arabia.

In contrast to OECD countries, emerging economies may face structural constraints in converting knowledge inputs into measurable economic outputs, which justifies the use of efficiency analysis in the present study.

Global positioning of Saudi Arabia (overall index perspective)

To assess Saudi Arabia’s global standing according to the Global Knowledge Index (2021- 2024), the Kingdom’s GKI score was compared with both advanced and lagging economies. The analysis begins with benchmarking Saudi Arabia against advanced economies, as presented in Table 1.

Table 1: Comparative country data according to GKI rankings (2021–2024).

Years	2021		2022		2023		2024
Country	Value	Rank	2022	Rank	2023	Rank	2024	Rank
USA	70	3	68.4	1	66.9	4	66.2	7
UK	69	6	63.9	9	65.7	8	65.8	8
Germany	66.9	12	63.4	11	63.7	15	63.7	16
France	64.9	17	61.5	18	61.1	24	61.7	23
Saudi Arabia	57.6	40	51.1	43	54.5	40	54.8	41
Number of countries	154		132		133		141
Global index average	48.6		46.5		47.8		47.8

Source: Global knowledge index reports (2021–2024).

Table 1 presents Global Knowledge Index (GKI) values and ranks for Saudi Arabia and four advanced economies (USA, UK, Germany, France), alongside the global average over (2021-224), Saudi Arabia’s GKI score ranged from 51.1–57.6 (ranks 40–43), consistently above the global average (46.5–48.6) but well below advanced economies (61.1–70). Its lowest point was at 2022 (51.1, rank 43), with a modest recovery to 54.8 (rank 41) in 2024.

Advanced economies showed minor fluctuations but maintained superior performance: USA peaked at rank 1 (68.4) in 2022; UK, Germany, and France stayed in the mid-60s despite rank declines.

Figure 1 compares the Global Knowledge index score for Saudi Arabia and frontier countries across the period 2021-2024.

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Figure 1: Index results for Saudi Arabia and comparison countries. Source: Researcher, based on study data

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Taken together, the evidence from Table 1 shows that Saudi Arabia occupies an intermediate position in the global knowledge landscape: It outperforms the global average and clearly distances itself from low-performing economies, yet it has not closed the gap with leading knowledge economies. This implies that the Kingdom has made progress in building knowledge-related capacities but still faces a persistent efficiency gap in transforming these capacities into GKI scores comparable to those of frontier countries, which motivates the more detailed pillar-level and hypothesis-based analysis that follows.

RESULTS

Table 13 indicates a clear disconnect between Saudi Arabia’s GKI knowledge inputs and its economy index outputs, supporting the core efficiency gap stated in H1. Despite strong gains in pre-university education (reaching 84.0 in 2024) and a steady rise in ICT to 73.5, the economy index remains almost flat around 58–60 after 2021, averaging 58.1 compared with an overall GKI average of about 50.0, which suggests that solid knowledge foundations are not fully translating into economic performance. This pattern is consistent with H2’s regression results, where the enabling environment (β = 1.504) and R&D and innovation (β = 0.181) are the main drivers, yet their relatively low and stagnant scores (R&D/innovation around 29–39 and enabling environment near 53) act as transmission bottlenecks, especially during the 2020–2022 volatility when the economy index fell to 45.2 before recovering to 58.2.

The 2024 peak in the economy index (60.5, rank 38) reflects a partial recovery associated with diversification efforts, but persistent weaknesses in higher education and technical and vocational education and training (around 43–44) and continued R&D stagnation point to skill–job mismatches that limit the conversion of knowledge into productivity gains. This configuration suggests that, under Vision 2030, Saudi Arabia has succeeded in strengthening its knowledge inputs faster than its economic outputs, as according to (Al-Shahri and Al-Badrani, 2023)Saudi Arabia improved its pre-university and technical and vocational education over time, yet still lagged behind leading countries placing the economy in a transitional rather than a frontier position in terms of knowledge-driven efficiency.

Table 14 provides empirical support for Hypothesis 3 by showing that economic openness persistently acts as a drag on the overall economy index, with an average value of 55.6, the lowest among the three pillars, and a marked dip to 53.4 in 2023 that coincides with the economy index’s stagnation despite improvements in other areas. This weakness is associated with a low share of high-tech exports (below 5% compared with more than 20% in advanced economies), a high degree of oil export concentration (over 70%), and restrictions captured by the Chinn–Ito financial openness index, all of which limit foreign direct investment and technology inflows (around 2% of GDP) and hinder integration into global value chains that are central to Vision 2030 diversification goals. ⁶

By contrast, the finance and local value-added pillar records the highest average (62.5, peaking at 63.9 in 2024), supported by lower non-performing loan ratios and rising value added in industry and services, while economic competitiveness recovers to 62.9 in 2024 on the back of business start-up reforms and improved construction and infrastructure quality. However, regression results show that these domestic strengths (finance β = 0.772, competitiveness positive but smaller) are not sufficient to offset the limited contribution of openness (β = 0.062), confirming a structural bottleneck in which barriers to trade and financial openness restrict knowledge transfer and export upgrading, thereby maintaining the efficiency gap between Saudi Arabia and frontier economies. ⁶

Economic Openness Sub-Pillars and their Impact on the Economy index:

Economic openness is measured through two sub-pillars: Trade and economic diversification, and financial openness. When these sub-pillars perform poorly, the overall openness score declines, dragging down the average of the economic index. The trade and economic diversification axis examines the intensity, quality, and commodity and geographical distribution of trade. Weaknesses emerge when trade as a percentage of GDP is relatively low, Saudi Arabia’s trade openness (exports + imports % GDP) was 50% (2021), 52% (2022), 54.8% (2023-2024), lagging global averages (60-70%), (World Bank/Trading Economics), indicating limited external exposure and limited utilisation of economies of scale and international competition. Furthermore, a low percentage of high-tech trade in total trade reflects a weak share of knowledge-based goods and services. High-tech exports were 0.5% (2021), 0.59% (2023) of manufactured exports vs. 20%+ in advanced economies, which limits technology transfer and productivity growth. The quality of trade openness improves through technology transfer and increased productivity.

A high product concentration means exports rely on a limited range of goods, reducing the economy’s flexibility in the face of shocks and limiting opportunities to integrate diverse knowledge, oil exports represent more than 70%. Reducing product concentration expands the export basket, lowers risks, boosts trade and diversification, and thereby strengthens openness. Weak performance in these indicators lowers the composite score for trade and diversification, which in turn reduces the overall economic openness pillar and its contribution to the economy index.

Figure 2 present the values Saudi Arabia Economy index and its three Pillars over the period 2021-2024.

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Figure 2: Economic index and axis values for the period (2021-2024). Source: Researcher, based on study data

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The financial openness pillar measures the ease of capital inflows and outflows and the economy’s ability to attract and efficiently utilise foreign funding. Weakness is evident when the Chinn–Ito index for financial openness is low, indicating tighter restrictions on the capital account and financial flows, which hinders the movement of capital and associated knowledge. Low net FDI as a percentage of GDP, which represents (1.7%) in Saudi Arabia 2024, (World Bank Group) results in fewer opportunities for cross-border managerial and production technologies, and weaker integration with global value chains - key channels for transferring knowledge, capital, and managerial expertise. Declines in these indicators reduce the value of the financial openness component, thereby exerting downward pressure on the overall openness pillar.

DISCUSSION

The study employed statistical analysis using the one-sample test, a powerful tool for analysing statistical data and understanding relationships between variables. It provides data interpretation and statistical evidence, helping researchers and decision-makers make informed choices and manage processes more effectively. Additionally, the econometric method was used to identify the direction and impact of relationships between economic pillars influencing the economic index during the study period.

Tables 15 and 16: H1 Testing – Economy Index Mean Differences (2021–2024).

Hypothesis One: There are statistically significant differences between the efficiency of the Saudi economy and the average efficiency of advanced economies according to the Global Knowledge Index results (2021–2024).

Economic efficiency was approximated by the ratio of the economy index to the overall Global Knowledge Index for each country (2021–2024). To test H1, a t-test for mean differences was applied to compare the efficiency of Saudi Arabia with the average efficiency of the four advanced economies (USA, UK, Germany, France).

H1 Verdict: Supported (t=88.05, p<0.001). Saudi Arabia’s economy index significantly trails advanced economies by 9.15 points, confirming the efficiency gap despite +11.7 point superiority over the global average.

Hypothesis Two: The Research, development and innovation and enabling environment indices are the most influential on the performance of the economy index.

H2 Verdict: Supported. Enabling environment (β=1.504) and R&D/innovation (β=0.181) dominate, validating their primacy in knowledge-to-economy transmission [Table 17]. The enabling environment is the dominant driver of economic efficiency. This finding aligns with theoretical expectations: Institutional quality, regulatory transparency, and political stability form the foundation upon which all other knowledge sectors can operate effectively. The second-most impactful factor is R&D/innovation, confirming that knowledge creation is crucial for economic advancement. Technical and vocational education shows the smallest coefficient (0.001).

Hypothesis Three: A decline in the economic openness pillar leads to a reduction in the Economic Index value in Saudi Arabia during 2021–2024, compared to other pillars (competitiveness, finance & value-added), thereby constraining the overall economic indicator value.

H3 Verdict: Supported. Openness’s minimal β=0.062 (1/12th finance pillar) confirms that it constrains the composite index, capping Vision 2030 gains amid trade/FDI barriers [Table 18]. The results reveal that the financing & local value-added (0.771580) is the dominant pillar; this indicates that productive capacity, domestic resource utilisation, and local value creation are the primary engines driving economic efficiency measurement in the GKI framework.

Economic Competitiveness (0.214) ranks second in importance, reflecting infrastructure quality, ease of doing business, and competitive advantage as significant contributors to overall economic efficiency. While Economic Openness provides proportionally smaller returns to the economy index. This bottleneck is particularly relevant for Saudi Arabia: while the Kingdom has made progress in domestic competitiveness and value-added production, insufficient economic openness- manifested in limited high-tech trade share, restricted foreign investment flows, and lower trade diversity - restricts the overall economy index value.

CONCLUSIONS