Entrepreneurship Ecosystem, Government Effectiveness, and Economic Growth in GCC Countries: Evidence from Panel Cointegration and Panel ARDL Analysis

Abstract

Understanding the determinants of sustainable economic growth is increasingly important for the Gulf Cooperation Council (GCC) countries as they pursue economic diversification beyond hydrocarbon dependence. This study examines the long-run effects of entrepreneurship ecosystems, government effectiveness, inflation, human capital, gross capital formation, trade openness, foreign direct investment (FDI), and information and communication technology (ICT) on economic growth in six GCC countries over 2006–2024. Using IPS panel unit root and Pedroni cointegration tests, the study establishes the existence of a stable long-run relationship among the variables. Long-run effects are estimated using FMOLS, DOLS, and CCR, with Panel ARDL-PMG employed as a robustness approach. The results consistently show that entrepreneurship ecosystems, government effectiveness, human capital, FDI, and ICT are positively associated with economic growth. Trade openness exhibits a negative long-run association, while the effects of inflation and gross capital formation vary across estimators. The significant negative error-correction term confirms convergence toward long-run equilibrium following short-run shocks. The findings highlight the importance of entrepreneurship, institutional quality, human capital, digital infrastructure, and productivity-enhancing FDI in supporting sustainable and diversified growth in the GCC economies.

1. Introduction

Entrepreneurship has long been recognized as a fundamental driver of economic growth, innovation, and structural transformation (Aghion, 2017; Urbano et al., 2019). Through the creation of new firms, commercialization of innovative ideas, diffusion of technology, and expansion of productive employment, entrepreneurial activity stimulates productivity growth and enhances the efficient allocation of resources (Lafuente et al., 2020). Beyond its direct contribution to business creation, entrepreneurship promotes competition, encourages knowledge spillovers, strengthens industrial diversification, and improves the adaptability of economies to technological and market changes (Mitra, 2019). Consequently, entrepreneurship has become a central pillar of contemporary economic development strategies, with governments increasingly promoting entrepreneurial ecosystems as a means of achieving sustainable, inclusive, and innovation-led growth (Nel-Sanders & Thomas, 2022).

Despite this broad consensus, the contribution of entrepreneurship to economic growth remains heterogeneous across countries and regions. While entrepreneurial activity has significantly accelerated productivity and innovation in many advanced economies, its growth-enhancing effects are less consistent in developing, transition, and resource-dependent economies (Omri & Almoshaigeh, 2025). This divergence suggests that entrepreneurship alone is insufficient to generate sustained long-run economic growth. Rather, its effectiveness depends critically on the institutional and macroeconomic environment within which entrepreneurs operate. Productive entrepreneurship requires well-functioning institutions, effective governance, macroeconomic stability, access to finance, skilled human capital, digital infrastructure, and regulatory systems that encourage innovation while reducing uncertainty and transaction costs (Adeleke et al., 2026). In the absence of these complementary conditions, entrepreneurial initiatives may remain small-scale, informal, or concentrated in low-productivity activities, limiting their contribution to national economic performance.

This perspective has given rise to the entrepreneurship ecosystem framework, which emphasizes that entrepreneurial outcomes are shaped by the interaction of multiple institutional, economic, financial, educational, technological, and policy-related factors rather than by entrepreneurship in isolation. An effective entrepreneurship ecosystem integrates supportive public institutions, efficient regulatory frameworks, financial markets, innovation systems, educational institutions, digital infrastructure, and market opportunities into a coherent environment that enables entrepreneurial ventures to emerge, survive, and scale (Wang et al., 2025). Consequently, understanding economic growth requires examining entrepreneurship within its broader institutional and macroeconomic context rather than treating it as an independent determinant.

Among these complementary factors, government effectiveness occupies a particularly important position. Effective governments improve the quality of public administration, strengthen regulatory implementation, reduce bureaucratic inefficiencies, enhance public service delivery, and establish transparent legal and institutional frameworks that foster investor confidence. Efficient institutions reduce transaction costs, improve contract enforcement, and facilitate private-sector development, thereby increasing the productivity of entrepreneurial activities. Similarly, macroeconomic stability constitutes another essential prerequisite for sustainable entrepreneurship. Stable inflation, prudent fiscal management, credible monetary policy, and predictable macroeconomic conditions reduce uncertainty, encourage long-term investment, improve resource allocation, and support business expansion. Consequently, entrepreneurship, government effectiveness, and macroeconomic stability should be viewed as complementary and mutually reinforcing drivers of long-run economic growth rather than as isolated determinants.

These issues are particularly relevant for the Gulf Cooperation Council (GCC), comprising Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates. Over the past several decades, the GCC has experienced remarkable economic growth driven largely by abundant hydrocarbon resources. Oil and natural gas revenues have enabled rapid improvements in infrastructure, human development, healthcare, education, and public investment, positioning the region among the world’s highest-income economies. Nevertheless, heavy dependence on hydrocarbon exports continues to expose GCC economies to fluctuations in global energy prices, external demand shocks, and increasing uncertainties associated with the global transition toward low-carbon energy systems. The growing emphasis on decarbonization, renewable energy adoption, and climate change mitigation further underscores the urgency of reducing dependence on oil revenues and developing more diversified, knowledge-based economies.

Recognizing these challenges, GCC governments have implemented ambitious long-term national development strategies aimed at fostering economic diversification, strengthening private-sector participation, encouraging innovation, and promoting entrepreneurship. Major initiatives include Saudi Vision 2030, UAE Vision 2031, Qatar National Vision 2030, Oman Vision 2040, Kuwait Vision 2035, and Bahrain Economic Vision 2030. Although these national strategies differ in their specific priorities, they collectively emphasize entrepreneurship development, digital transformation, institutional modernization, human capital enhancement, technological innovation, and the expansion of non-oil sectors as key pillars of sustainable economic growth. Significant investments have also been directed toward developing innovation ecosystems, digital infrastructure, startup financing mechanisms, venture capital markets, business incubators, technology parks, and regulatory reforms designed to improve the business environment and enhance international competitiveness.

Despite these common strategic objectives, substantial heterogeneity exists across GCC countries regarding institutional quality, entrepreneurial development, regulatory efficiency, digital readiness, economic diversification, and private-sector maturity. Differences in governance quality, business regulations, innovation capacity, labor market structures, investment climates, and public-sector effectiveness imply that the contribution of entrepreneurship to economic growth may vary considerably across countries. Such structural differences make the GCC an especially suitable setting for investigating whether entrepreneurship contributes uniformly to economic growth or whether its effectiveness depends on institutional quality and macroeconomic conditions.

Although an expanding body of literature has examined entrepreneurship, institutional quality, and macroeconomic stability, several important research gaps remain. First, most previous studies investigate these determinants independently, overlooking their complementary roles in promoting sustainable economic growth. Second, while considerable evidence exists for developed and emerging economies, empirical studies focusing specifically on GCC countries remain relatively limited despite the region’s unique economic structure and ongoing diversification reforms. Third, much of the existing literature relies on conventional panel estimation techniques that may not adequately distinguish between long-run equilibrium relationships and short-run dynamic adjustments. Fourth, relatively few studies employ multiple complementary cointegration estimators to verify the robustness of long-run parameter estimates. Finally, limited attention has been devoted to examining entrepreneurship ecosystems within the broader institutional and macroeconomic framework that characterizes the GCC economies during an extended period encompassing major economic reforms, global financial crises, oil price volatility, the COVID-19 pandemic, and the subsequent recovery.

To address these gaps, this study investigates the long-run relationship between entrepreneurship ecosystems, government effectiveness, macroeconomic stability, and economic growth across the six GCC countries over the period 2006–2024. Drawing upon endogenous growth theory (Lucas, 1988; Romer, 1990), institutional economics (North, 1990), and the entrepreneurship ecosystem perspective, the study argues that entrepreneurship contributes to sustainable long-run economic growth when supported by effective institutions and a stable macroeconomic environment. Rather than considering entrepreneurship in isolation, the study develops an integrated analytical framework that recognizes the complementary roles of entrepreneurship ecosystems, governance quality, macroeconomic stability, investment, trade openness, human capital, foreign direct investment, and digital connectivity in shaping economic performance.

Methodologically, the study adopts a comprehensive panel data framework to ensure the robustness of the empirical findings. The stationarity properties of the variables are first examined using the Im-Pesaran-Shin (IPS) panel unit root test. Long-run equilibrium relationships are then verified using the Pedroni panel cointegration test. The long-run elasticities are subsequently estimated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), while the Panel Autoregressive Distributed Lag (Panel ARDL) model is employed to distinguish between long-run equilibrium relationships and short-run adjustment dynamics. Employing several complementary estimators provides a rigorous assessment of the stability and consistency of the estimated relationships while reducing the possibility that the findings are driven by a particular econometric specification.

Accordingly, this study contributes to the existing literature in several respects. First, it develops an integrated framework for examining the role of entrepreneurship ecosystems alongside institutional, human capital, macroeconomic, trade, investment, and digital factors in shaping long-run economic growth in the GCC economies. Second, it extends the relatively limited empirical literature on entrepreneurship-led growth in resource-dependent economies by providing recent evidence for the GCC countries during a period of substantial economic and structural transformation. Third, the study strengthens the empirical analysis by applying complementary panel cointegration and long-run estimation techniques, including FMOLS, DOLS, CCR, and Panel ARDL-PMG, to assess both long-run relationships and short-run adjustments. Finally, by covering 2006–2024, the analysis captures a range of major economic developments and shocks, thereby providing contemporary evidence on the determinants of growth under changing macroeconomic conditions. Finally, the study seeks to provide a comprehensive empirical assessment of the factors shaping sustainable and diversified economic growth in the GCC region.

The remainder of the paper is organized as follows. Section 2 reviews the relevant literature on entrepreneurship, government effectiveness, macroeconomic stability, and economic growth, and identifies the existing research gaps. Section 3 presents the theoretical framework and develops the research hypotheses. Section 4 describes the data, variable definitions, data sources, and econometric methodology employed in the analysis. Section 5 reports the empirical findings, including the preliminary diagnostic tests and the long-run and short-run estimation results. Section 6 discusses the empirical findings in light of the theoretical and empirical literature. Section 7 presents the policy recommendations and their implications for strengthening entrepreneurship ecosystems, improving institutional quality, and promoting sustainable economic diversification across the GCC countries. Finally, Section 8 concludes the study by summarizing the main findings, acknowledging the study’s limitations, and outlining directions for future research.

2. Literature Review

The literature on entrepreneurship and economic growth in the GCC generally suggests that entrepreneurial activity contributes to economic performance when supported by effective institutions and appropriate government policies. Saberi and Hamdan (2019) show that governmental support strengthens the entrepreneurship-growth relationship, while Sayed and Abedelrahim (2024a) find that political stability enhances the contribution of entrepreneurship to growth. Khyareh and Amini (2021) attribute differences across previous findings to variations in measurement, sample periods, and the composition of entrepreneurial activity, particularly the distinction between opportunity- and necessity-driven entrepreneurship. Thus, the emerging consensus is that entrepreneurship is more likely to generate growth when embedded within supportive institutional and policy environments.

This perspective is particularly relevant to GCC economies, where entrepreneurship has been identified as an important mechanism for diversification, employment creation, private-sector development, and innovation (Miniaoui & Schilirò, 2017; Benlaria et al., 2023). From the entrepreneurial ecosystem perspective, Acs et al. (2018) emphasize that growth depends on complementarities among institutions, human capital, entrepreneurial agency, and resource allocation rather than on firm creation alone. Consistent with this argument, Adjal (2024) and Zmami and Alruwaili (2025) find that entrepreneurial ecosystems contribute to growth and employment, while human capital, labour, trade openness, FDI, and R&D represent important transmission channels. Gomes et al. (2023) and Iddouch and Jaoual (2025) further identify finance, infrastructure, R&D transfer, and entrepreneurial culture as important ecosystem components, particularly in higher-income GCC economies.

Government effectiveness emerges as a critical condition for translating entrepreneurial activity into productive economic outcomes. Saberi and Hamdan (2019), Sayed and Abedelrahim (2024a), Raimi and Haini (2024), and Rani and Kumar (2022) collectively emphasize the importance of regulatory quality, political stability, property rights, government integrity, business freedom, public support, and state capacity. Country- and institution-specific evidence reinforces this argument. Villegas-Mateos (2023), for example, finds that Qatar’s entrepreneurial ecosystem benefits from supportive conditions but remains constrained by poorly designed interventions, knowledge-transfer restrictions, and market limitations. Similarly, Qahtani and Sankar (2025) demonstrate that university-based entrepreneurial ecosystems in the GCC depend on institutional support, industry partnerships, commercialization mechanisms, leadership, and effective evaluation. Overall, the evidence indicates that entrepreneurship is unlikely to generate sustained growth in isolation; rather, its contribution depends substantially on the quality of the surrounding institutional ecosystem.

The broader GCC growth literature identifies macroeconomic stability, investment and finance, trade integration, human capital, and ICT as complementary determinants of economic performance. Evidence on macroeconomic conditions indicates that oil dependence and external shocks can weaken long-run growth when diversification is limited (Shah et al., 2024), while inflation may undermine financial stability (Mabkhot & Al-Wesabi, 2022) but can also coexist with growth under particular macroeconomic conditions (Abdelkawy, 2024; AlShurafa et al., 2026). Exchange-rate conditions also influence growth and investment incentives (Shah et al., 2024; Alshubiri, 2022). Similarly, evidence concerning political stability and FDI remains mixed across countries and estimation approaches (Wijaya et al., 2021; Alhamran et al., 2025; Alshubiri, 2022), suggesting that institutional and macroeconomic conditions may shape the effectiveness of external investment.

Financial development and domestic investment are generally associated with stronger economic performance. Alhajri et al. (2024) and Farooq et al. (2023) report positive effects of financial development on growth and investment, while emphasizing that financial deepening requires appropriate regulation and diversification (AlShurafa et al., 2026). Gross capital formation similarly emerges as a relatively robust growth-enhancing factor (Abdelkawy, 2024). Trade openness is also generally associated with stronger economic outcomes in the GCC (Alshubiri et al., 2019; Alhamran et al., 2025; Harrath et al., 2026). Nevertheless, the evidence on FDI is more conditional: although Abdelkawy (2024) and Farooq et al. (2023) identify growth-enhancing effects, another study (2024) suggests that FDI may crowd out domestic firms or produce different outcomes depending on prevailing macroeconomic conditions.

Human capital represents another important long-run source of growth and diversification. Evidence from GCC economies indicates that education, health, employment, and skills development contribute positively to productivity, innovation, and economic performance (Shah et al., 2024). ICT development provides an additional channel through which these capabilities can support growth. Alshubiri et al. (2019) find that broadband and internet adoption contribute to financial development, while Alhajri et al. (2024), Riache et al. (2025), and Chiad (2025) demonstrate that ICT increasingly complements financial development and supports economic and banking stability. These findings highlight the growing importance of digital infrastructure for GCC diversification and knowledge-based development.

Taken together, the literature supports a conditional view of economic growth in the GCC, in which entrepreneurship, institutions, human capital, investment, trade, FDI, macroeconomic stability, and ICT interact rather than operate independently. While the positive role of human capital, investment, and digital development is relatively consistent, the effects of entrepreneurship, FDI, financial development, inflation, and political stability remain more heterogeneous across countries and institutional settings (Khyareh & Amini, 2021; Shah et al., 2024; Abid, 2026; AlShurafa et al., 2026). This heterogeneity indicates the need for an integrated empirical framework that considers entrepreneurship ecosystems alongside institutional quality and key macroeconomic determinants. The present study addresses this gap by jointly examining these factors in six GCC economies over 2006–2024, thereby providing updated evidence on the conditions under which entrepreneurship and complementary economic capabilities contribute to long-run growth.

Hypothesis Development

The theoretical and empirical literature suggests that entrepreneurship ecosystems, institutional quality, macroeconomic stability, and structural economic factors jointly influence long-run economic growth. According to endogenous growth theory, entrepreneurship enhances innovation, productivity, and resource allocation, while effective institutions and a stable macroeconomic environment create favourable conditions for entrepreneurial activities to contribute to sustainable economic development. Previous empirical studies, however, report mixed findings regarding the magnitude and significance of these relationships, indicating that the growth effects of entrepreneurship depend on broader economic and institutional conditions (Saberi & Hamdan, 2019; Khyareh & Amini, 2021; Sayed & Abedelrahim, 2024b; Adjal, 2024; Zmami & Alruwaili, 2025).

Entrepreneurship ecosystems facilitate new business creation, innovation, employment generation, and productivity improvements, thereby supporting long-run economic development. A well-developed entrepreneurial ecosystem enhances the capacity of firms to exploit market opportunities, commercialize innovation, and contribute to economic diversification. Accordingly, the first hypothesis is formulated as follows:

H1. 

Entrepreneurship ecosystem development is significantly associated with real GDP per capita in GCC countries.

Government effectiveness represents a fundamental institutional determinant of economic performance. Effective governments improve regulatory quality, public service delivery, policy implementation, and institutional efficiency, thereby creating an enabling environment for private-sector development and entrepreneurial activity. Consequently, improvements in government effectiveness are expected to enhance long-run economic performance.

H2. 

Government effectiveness is significantly associated with real GDP per capita in GCC countries.

Macroeconomic stability is essential for sustaining investment, reducing uncertainty, and promoting economic growth. Stable inflation reflects a predictable macroeconomic environment that encourages private investment, facilitates business planning, and supports entrepreneurial development. Conversely, persistent inflation may reduce purchasing power, distort investment decisions, and hinder long-run economic performance.

H3. 

Macroeconomic stability, as measured by inflation, is significantly associated with real GDP per capita in GCC countries.

Human capital, physical investment, international trade, foreign direct investment, and digital infrastructure are widely recognised as complementary drivers of long-run economic growth. Higher educational attainment improves labour productivity and innovation capacity, while gross capital formation expands productive capacity. Trade openness promotes market integration and technology diffusion, foreign direct investment facilitates capital accumulation and knowledge transfer, and ICT development enhances digital transformation, business efficiency, and economic competitiveness.

Accordingly, the following hypothesis is proposed:

H4a. 

Human capital has a significant effect on real GDP per capita in GCC countries.

H4b. 

Gross capital formation has a significant effect on real GDP per capita in GCC countries.

H4c. 

Trade openness has a significant effect on real GDP per capita in GCC countries.

H4d. 

Foreign direct investment has a significant effect on real GDP per capita in GCC countries.

H4e. 

ICT development has a significant effect on real GDP per capita in GCC countries.

Finally, these hypotheses provide the theoretical basis for examining the long-run determinants of economic growth in GCC economies. The empirical analysis employs panel cointegration techniques to evaluate whether entrepreneurship ecosystems, government effectiveness, macroeconomic stability, and key structural factors jointly explain long-run variations in real GDP per capita across GCC countries.

3. The Theoretical Framework

The theoretical foundation of this study draws upon Schumpeter’s Theory of Innovation, Endogenous Growth Theory, Institutional Theory, and Macroeconomic Stability Theory. Collectively, these perspectives explain how entrepreneurship ecosystems, institutional quality, macroeconomic conditions, and complementary production factors interact to influence long-run economic development. Rather than viewing economic growth as a function of capital accumulation alone, these theories emphasize that sustained growth emerges from innovation, knowledge creation, effective institutions, and a stable macroeconomic environment that enables productive entrepreneurial activity.

The fundamental role of entrepreneurship in economic development originates from Schumpeter’s (1934) Theory of Innovation, which identifies entrepreneurs as agents of creative destruction. Through the introduction of new products, production processes, organizational innovations, and market opportunities, entrepreneurs continuously reallocate resources toward more productive activities, thereby increasing aggregate productivity and economic output. Within this framework, entrepreneurship is not merely the creation of new firms but a dynamic process that stimulates innovation, competition, employment generation, and structural transformation.

The theoretical relationship between entrepreneurship and economic output can be expressed as

$$Y=f(E),$$

where $Y$ denotes economic output and $E$ represents entrepreneurial activity. The theory predicts

$${\displaystyle \frac{\partial Y}{\partial E}}>0,$$

implying that improvements in entrepreneurship ecosystem development increase long-run economic performance through innovation and productivity enhancement. In the GCC context, entrepreneurship ecosystems-including business formation, innovation support, and entrepreneurial institutions-constitute important policy instruments for reducing dependence on hydrocarbon revenues and promoting economic diversification.

While Schumpeterian theory explains the origin of innovation, Endogenous Growth Theory provides the mechanism through which entrepreneurship generates persistent economic growth. Romer (1990) and Lucas (1988) argue that technological progress is produced internally through knowledge accumulation, innovation, human capital formation, and investment rather than occurring exogenously. Entrepreneurial activities facilitate the commercialization of new knowledge, accelerate technological diffusion, and improve resource allocation, thereby generating self-sustaining increases in productivity.

The standard endogenous production function is represented as

$$Y=A{K}^{\alpha }{H}^{\beta }{L}^{1-\alpha -\beta },$$

where $Y$ denotes real GDP per capita, $A$ represents technological progress, $K$ is physical capital, $H$ denotes human capital, and $L$ represents labour. Because technological progress itself is generated by entrepreneurial activity and institutional support,

$$A=f(E,G,ICT),$$

where $E$ denotes entrepreneurship ecosystem development, $G$ represents government effectiveness, and $ICT$ captures digital technological development. Substituting this relationship into the production function implies that long-run economic growth depends on entrepreneurship, institutional quality, education, investment, and technological advancement. Accordingly, entrepreneurship ecosystems enhance economic performance by increasing innovation capacity, facilitating technology adoption, and improving productive efficiency.

Institutional Theory complements endogenous growth by emphasizing that entrepreneurship produces economic gains only when supported by effective institutions. According to North (1990), institutions reduce transaction costs, strengthen property rights, improve contract enforcement, and enhance policy credibility, thereby creating an environment that encourages investment and entrepreneurial activity. Government effectiveness is therefore expected to influence economic growth through improved regulatory quality, efficient public service delivery, and greater policy implementation capacity.

The institutional relationship may be represented as

$$Y=f(E,G),$$

where $G$ denotes government effectiveness. The theoretical expectation is

$${\displaystyle \frac{\partial Y}{\partial G}}>0,$$

indicating that improvements in institutional quality enhance long-run economic performance by facilitating productive entrepreneurship and reducing institutional uncertainty. For GCC economies, where governments play a central role in implementing economic diversification strategies, institutional effectiveness represents a critical determinant of entrepreneurial success and sustainable development.

Macroeconomic Stability Theory argues that predictable macroeconomic conditions promote investment, entrepreneurship, and economic growth by reducing uncertainty and improving resource allocation. Stable inflation lowers production costs, facilitates long-term investment planning, and strengthens business confidence, whereas persistent inflation distorts relative prices, discourages productive investment, and weakens economic performance. Entrepreneurial firms are particularly sensitive to inflation because they generally possess fewer financial resources and face greater uncertainty than established firms.

This theoretical relationship is represented by

$$Y=f(\pi ),$$

where $\pi$ denotes the inflation rate. The expected relationship is

$${\displaystyle \frac{\partial Y}{\partial \pi }}<0,$$

suggesting that higher inflation is associated with lower long-run economic growth. Consequently, maintaining macroeconomic stability is expected to strengthen entrepreneurial development and improve overall economic performance within GCC countries.

The preceding theories collectively suggest that long-run economic growth is jointly determined by entrepreneurship ecosystems, institutional quality, macroeconomic stability, and structural economic factors. Entrepreneurship stimulates innovation and productive efficiency, government effectiveness creates an enabling institutional environment, macroeconomic stability reduces uncertainty, while education, investment, trade openness, foreign direct investment, and ICT development complement these mechanisms by enhancing productivity and technological progress.

Accordingly, the theoretical growth function underlying this study is expressed as

$$GD{P}_{it}=f(ENTRP{R}_{it},GOVE{F}_{it},CP{I}_{it},H{C}_{it},GC{F}_{it},TRAD{E}_{it},FD{I}_{it},IC{T}_{it}),$$

where $GDP$ denotes real GDP per capita, $ENTRPR$ represents entrepreneurship ecosystem development, $GOVEF$ measures government effectiveness, $CPI$ proxies macroeconomic stability through inflation, $HC$ denotes human capital, $GCF$ represents gross capital formation, $TRADE$ measures trade openness, $FDI$ captures foreign direct investment inflows, and $ICT$ represents digital development.

4. Data and Methodology

4.1. Sample, Period, and Data Sources

The empirical analysis is based on an annual panel of the six Gulf Cooperation Council (GCC) economies—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—covering 2006–2024. The study period is determined primarily by the availability of comparable country-year observations across the variables included in the empirical framework. Table 1 reports the operational definitions, measurement units, proxies, data sources, and coverage period for all variables. The selection of the proxies is guided by both theoretical relevance and established practice in the empirical growth literature, while consideration is also given to cross-country comparability and data availability.

Table 1. Variable definitions, proxies, and data sources.

Construct	Abbreviation	Variable Definition/Proxy	Unit of Measurement	Data Source	Period
Economic growth	gdp	Real GDP per capita	Constant 2015 US$	World Development Indicators (WDI)	2006–2024
Entrepreneurship ecosystem	entrpr	New business density; Total Early-stage Entrepreneurial Activity (TEA) where available	New registrations per 1000 working-age population; TEA as % of population aged 18–64	World Bank Entrepreneurship Database; Global Entrepreneurship Monitor (GEM)	2006–2024
Government effectiveness	govef	Government Effectiveness Index	Index, −2.5 to +2.5	Worldwide Governance Indicators (WGI)	2006–2024
Macroeconomic stability	cpi	Consumer price inflation	Annual % change	WDI; International Monetary Fund (IMF)	2006–2024
Human capital	hc	Secondary school enrollment/Human Capital Index	Gross enrollment ratio (%); index, depending on measure	WDI	2006–2024
Investment	gcf	Gross capital formation	% of GDP	WDI	2006–2024
Trade openness	trade	Trade in goods and services	% of GDP	WDI	2006–2024
Foreign direct investment	fdi	Net FDI inflows	% of GDP	WDI	2006–2024
ICT development	ict	Individuals using the Internet	% of population	WDI	2006–2024

The dependent variable, economic growth, is measured by real GDP per capita in constant 2015 US dollars and obtained from the World Development Indicators (WDI). Real GDP per capita is widely employed as an indicator of economic performance because it captures changes in real economic output while accounting for differences in population size and price effects (Zmami & Alruwaili, 2025). This measure is particularly appropriate for the GCC economies given their considerable differences in population size and economic structure (Sayed & Abedelrahim, 2024a). Accordingly, real GDP per capita provides a comparable measure of economic performance across the six countries. The principal explanatory variable, entrepreneurship ecosystem, is proxied by new business density, defined as the number of newly registered limited-liability firms per 1000 working-age individuals aged 15–64. The measure is obtained from the World Bank Entrepreneurship Database. The choice of new business density is supported by its ability to capture formal entrepreneurial entry and private-sector dynamism in a standardized cross-country framework. Sayed and Abedelrahim (2024b) and Zmami and Alruwaili (2025), for example, employ entrepreneurship-related measures to examine the contribution of entrepreneurial activity to economic performance. Compared with broader perceptions-based measures of entrepreneurial ecosystems, new business density provides a more directly observable indicator of formal firm creation. This distinction is particularly relevant for the GCC economies, where private-sector development and economic diversification are central policy objectives. To assess robustness, Total Early-Stage Entrepreneurial Activity (TEA) from the Global Entrepreneurship Monitor (GEM) is also considered as an alternative measure where comparable observations are available (Global Entrepreneurship Monitor, 2025). Whereas new business density captures formal business registration, TEA measures the proportion of the working-age population involved in nascent or young entrepreneurial activity and therefore provides a complementary measure of entrepreneurship. Government effectiveness is measured using the Government Effectiveness indicator from the Worldwide Governance Indicators (WGI), which ranges approximately from −2.5 to 2.5, with higher values indicating stronger government effectiveness. This indicator captures perceptions of the quality of public services, the civil service, policy formulation and implementation, and the credibility of government commitments. Its use is consistent with the institutional-growth literature, which emphasizes the role of effective institutions in reducing uncertainty and transaction costs and facilitating productive economic activity (Arvin et al., 2021). Government effectiveness is therefore particularly relevant to the entrepreneurship-growth relationship because an efficient public administration can create a more predictable environment for business formation and investment. Macroeconomic stability is proxied by consumer price inflation, measured as the annual percentage change in consumer prices and obtained primarily from the WDI, with IMF data used where necessary. Inflation is selected because price instability can influence investment decisions, entrepreneurial activity, purchasing power, and production costs (Seti et al., 2025). This proxy is widely used in empirical growth models as an indicator of macroeconomic stability. Its relevance is further strengthened in the GCC context by the economies’ exposure to oil-price movements and external macroeconomic shocks (Sayed & Abedelrahim, 2024b). Human capital is proxied by the secondary school gross enrolment ratio. Although human capital can be measured using alternative indicators—including educational attainment, average years of schooling, tertiary enrolment, and composite human capital indices—the secondary school enrolment ratio is selected because it provides relatively consistent and comparable annual observations across the six GCC economies over the study period. It also captures an important stage of workforce preparation and educational investment. Previous research emphasizes the contribution of human capital to labour productivity, technological absorption, innovation, and economic growth (Luo et al., 2024). In the GCC context, where economic diversification increasingly depends on knowledge-intensive activities, educational development is particularly relevant (Al Shammre, 2025). Thus, the secondary enrolment ratio represents a practical and comparable proxy for the educational dimension of human capital while avoiding the substantial data limitations associated with broader multidimensional indices. Investment is measured by gross capital formation as a percentage of GDP. This indicator is widely used in growth models to capture the accumulation of physical capital, including machinery, infrastructure, and other productive assets. Its inclusion is supported by the growth literature because capital accumulation can expand productive capacity and complement labour, technology, and entrepreneurial capabilities (Al Shammre, 2025; Seti et al., 2025). For the GCC economies, this variable is particularly relevant given the importance of infrastructure investment and capital-intensive diversification strategies. Trade openness is measured as the sum of exports and imports of goods and services as a percentage of GDP. This conventional measure captures the degree of integration of an economy into international markets and is frequently employed in empirical growth studies (Seti et al., 2025). Trade openness may influence growth through market expansion, specialization, competition, technology transfer, and access to international inputs. Its inclusion is particularly appropriate for the GCC economies because of their high degree of international economic integration and ongoing efforts to expand non-hydrocarbon economic activities (Zmami & Alruwaili, 2025). Nevertheless, the growth implications of trade may depend on export composition and the extent to which domestic firms capture value from international integration. Foreign direct investment (FDI) is measured by net FDI inflows as a percentage of GDP using WDI data. This measure is widely employed in the empirical literature to capture the contribution of foreign capital to domestic economic activity. FDI may support growth through capital accumulation, technology and knowledge transfer, managerial expertise, employment creation, and access to international markets (Alharthi et al., 2024). Its relevance to the GCC economies follows from their efforts to attract foreign investment into non-hydrocarbon sectors and strengthen participation in global value chains. At the same time, previous research suggests that the benefits of FDI may depend on domestic absorptive capacity, human capital, institutional quality, and the sectoral allocation of investment (Alenezi et al., 2024). Therefore, FDI is included as an important structural control rather than being assumed to have an unconditional growth effect. Finally, ICT development is proxied by the percentage of individuals using the Internet, obtained from the WDI. Alternative measures, such as the ICT Development Index, provide broader assessments of digital development; however, the Internet-use indicator is preferred because it provides more consistent and comparable observations across all six GCC countries throughout 2006–2024. This choice is consistent with studies using Internet penetration to capture the diffusion and adoption of digital technologies in growth models (Hamed et al., 2025; Al Shammre, 2025). Internet use captures an important dimension of digital connectivity through which information and transaction costs may be reduced and access to markets, financial services, knowledge, and digital entrepreneurship may be enhanced. It should therefore be interpreted as a measure of digital connectivity and adoption, rather than as a comprehensive measure of the entire ICT ecosystem. Overall, the selection of variables reflects both theoretical considerations established in the literature and practical requirements concerning measurement consistency and data availability across the six GCC economies. The resulting framework incorporates entrepreneurship, institutional quality, macroeconomic stability, human capital, physical investment, trade integration, FDI, and digital connectivity. This combination allows the analysis to examine the relationship between entrepreneurship ecosystems and economic growth while accounting for the broader institutional, macroeconomic, productive, and technological conditions within which entrepreneurial activity takes place.

Table 1 presents the operational definitions, measurement proxies, data sources, and study period for all variables included in the empirical analysis. Collectively, these variables provide a comprehensive analytical framework for examining the long-run relationship between entrepreneurship ecosystems, government effectiveness, macroeconomic stability, and other structural determinants of economic growth across GCC countries.

Table 2 reports the descriptive statistics for the variables included in the empirical analysis. The study is based on an balanced panel of GCC countries covering the period 2006–2024, with variations in the number of observations reflecting data availability across variables. Real GDP per capita averages US$35,019.78, with a standard deviation of US$17,381.54, ranging from US$17,347.29 to US$83,533.50. This substantial variation indicates considerable differences in economic performance among GCC countries over the study period. Entrepreneurship ecosystem development, measured by new business density, records a mean value of 2.286 registrations per 1000 working-age individuals, with values ranging from 0.375 to 6.766, suggesting notable cross-country heterogeneity in entrepreneurial activity. Government effectiveness has an average score of 0.500, with values spanning from −0.193 to 1.416, indicating generally strong institutional quality across GCC economies, albeit with observable differences in governance performance. Inflation averages 2.658%, although the relatively large standard deviation (3.133) and the range from −4.863% to 15.050% reflect periods of both deflation and elevated inflation across the sample. Human capital records a mean secondary enrolment rate of 41.44%, indicating moderate educational attainment, although fewer observations are available for this variable. Gross capital formation averages 28.07% of GDP, highlighting the region’s relatively high investment intensity. Similarly, trade openness averages 110.57% of GDP, reflecting the strong integration of GCC economies into global trade. Net FDI inflows average 2.67% of GDP, with considerable dispersion across countries and years, suggesting heterogeneous patterns of foreign investment. ICT development exhibits the highest average among the explanatory variables, with 76.52% of the population using the Internet, indicating a relatively advanced level of digital infrastructure within the GCC region.

Table 2. Descriptive statistics.

Variable	Mean	Std. Dev.	Min	Max
gdp	35,019.78	17,381.54	17,347.29	83,533.5
entrpr	2.286177	1.563045	0.3748501	6.76566
govef	0.4998513	0.455904	−0.1934412	1.416002
cpi	2.65801	3.132647	−4.863278	15.05015
hc	41.44017	18.7836	9.642733	83.88413
gcf	28.07493	7.470985	12.83494	49.48666
trade	110.5714	35.09809	47.53316	199.045
fdi	2.669282	3.279913	−2.760018	15.75086
ict	76.51902	25.32318	8.2997	100

Taken together, the descriptive statistics reveal substantial cross-country and intertemporal variation across the variables, providing sufficient variability for panel estimation and supporting the empirical investigation of the long-run determinants of economic growth in GCC countries.

Table 3 reports the pairwise correlation coefficients among the study variables. Overall, the results indicate moderate correlations, suggesting that severe multicollinearity is unlikely to affect the empirical analysis. Real GDP per capita is positively correlated with entrepreneurship ecosystem development at 0.5024, government effectiveness at 0.7324, and gross capital formation at 0.3803, indicating that higher levels of entrepreneurship, stronger institutional quality, and greater investment are associated with improved economic performance. In contrast, real GDP per capita is negatively correlated with human capital at −0.5820, while its correlations with inflation, trade openness, foreign direct investment, and ICT development are relatively weak. Among the explanatory variables, government effectiveness exhibits a relatively strong positive correlation with entrepreneurship ecosystem development of 0.6005, while ICT development is positively associated with human capital at 0.6217. Inflation is negatively correlated with government effectiveness at −0.1822 and ICT development at −0.5396, suggesting that stronger institutions and greater digital development are generally associated with a more stable macroeconomic environment. Importantly, all pairwise correlation coefficients remain well below the commonly accepted threshold of 0.80, indicating that multicollinearity is unlikely to constitute a significant concern in the subsequent econometric estimations.

Table 3. Correlation matrix.

	gdp	entrpr	govef	cpi	hc	gcf	trade	fdi	ict
gdp	1.0000
entrpr	0.5024	1.0000
govef	0.7324	0.6005	1.0000
cpi	0.0979	−0.0612	−0.1822	1.0000
hc	−0.5820	−0.1909	−0.2256	−0.3536	1.0000
gcf	0.3803	0.4082	0.2528	0.2649	−0.5384	1.0000
trade	−0.0351	0.2830	0.3374	−0.1461	−0.0389	−0.1115	1.0000
fdi	−0.0698	0.1563	0.1847	0.0098	−0.1035	0.1730	0.4718	1.0000
ict	0.0335	0.3565	0.3296	−0.5396	0.6217	−0.2888	0.2198	−0.1556	1.0000

4.2. Model Specification

To investigate the long-run determinants of economic growth in GCC countries, this study specifies the following panel cointegration model:

$$\begin{gathered} ln(gdp{)}_{it}={\alpha }_i+{\beta }_{1}ln(entrpr{)}_{it}+{\beta }_2{govef}_{it}+{\beta }_3{cpi}_{it}+{\beta }_{4}ln(hc{)}_{it}+{\beta }_{5}ln(gcf{)}_{it} \\ +{\beta }_{6}ln(trade{)}_{it}+{\beta }_7{fdi}_{it}+{\beta }_{8}ln(ict{)}_{it}+{\epsilon }_{it} \end{gathered}$$

(1)

where $i=1,\dots ,6$ denotes the GCC countries and $t=2006,\dots ,2024$ represents the study period. The dependent variable, $gdp$, is measured as real GDP per capita, representing the level of economic development. The principal explanatory variables are the entrepreneurship ecosystem, proxied by new business density ($entrpr$); government effectiveness ($govef$); and macroeconomic stability, measured by the inflation rate ($cpi$). Human capital ($hc$), gross capital formation ($gcf$), trade openness ($trade$), foreign direct investment ($fdi$), and information and communication technology ($ict$) are incorporated as control variables to account for other structural determinants of long-run economic growth. The parameter ${\alpha }_i$ captures unobserved country-specific heterogeneity, while ${\epsilon }_{it}$ denotes the random disturbance term.

The empirical specification is grounded in endogenous growth theory, which emphasizes that entrepreneurship, innovation, human capital, and institutional quality jointly determine long-run economic performance. Entrepreneurship ecosystems facilitate business creation, innovation, and productivity improvements, whereas effective government institutions enhance the regulatory environment, strengthen policy implementation, and improve resource allocation. Likewise, macroeconomic stability promotes investment and reduces uncertainty, thereby creating favourable conditions for entrepreneurial activity and sustainable economic growth. The remaining control variables capture complementary channels through which investment, international trade, human capital accumulation, and digital infrastructure influence long-run economic development.

Equation (1) constitutes the baseline long-run model and forms the basis for the subsequent panel cointegration analysis. Following the confirmation of stationarity, and panel cointegration, the long-run coefficients are estimated using Panel FMOLS, DOLS, and CCR. These complementary estimators correct for endogeneity and serial correlation inherent in cointegrated panel data, thereby producing consistent and efficient estimates of the long-run relationship between entrepreneurship ecosystems, institutional quality, macroeconomic stability, and economic growth.

4.3. Preliminary Diagnostic Tests

Before estimating the long-run relationships, a series of preliminary diagnostic tests is conducted to ensure the appropriateness of the selected econometric techniques. Because Panel FMOLS, DOLS, and CCR require the variables to be non-stationary and cointegrated, it is essential to examine the main properties of the data, determine the order of integration of each variable, and verify the existence of a long-run equilibrium relationship among the variables.

4.3.1. Panel Unit Root Tests

Following the preliminary diagnostic analysis, the stationarity properties of the variables are examined using the first-generation panel unit root test proposed by Im et al. (2003). The Im-Pesaran-Shin (IPS) test is widely employed in panel data analysis to determine the order of integration of variables prior to conducting panel cointegration analysis. Unlike traditional panel unit root tests that assume a common autoregressive parameter across cross-sectional units, the IPS test allows for heterogeneity in the autoregressive coefficients by permitting each cross-sectional unit to have its own dynamic adjustment process. The test evaluates the null hypothesis that all panel series contain a unit root against the alternative hypothesis that at least some cross-sectional units are stationary. This flexibility makes the IPS test particularly suitable for macro-panel datasets in which countries may exhibit different adjustment dynamics. In this study, each variable is tested at both levels and first differences under specifications that include an intercept and an intercept with a deterministic trend. A variable is considered integrated of order one, I(1), if the null hypothesis of a unit root cannot be rejected at levels but is rejected after first differencing. Establishing the order of integration provides the necessary basis for implementing the subsequent Pedroni panel cointegration test and estimating the long-run relationships using the FMOLS, DOLS, and CCR estimators, together with the Panel Autoregressive Distributed Lag (Panel ARDL) model.

4.3.2. Panel Cointegration Tests

Following confirmation of the integration order of the variables under the study, the existence of a long-run equilibrium relationship is examined using the Pedroni (1999, 2004) panel cointegration test. The Pedroni approach is widely employed in panel data analysis because it accommodates heterogeneity in both the intercepts and slope coefficients across cross-sectional units, making it suitable for panels where long-run relationships may differ across countries. Unlike conventional residual-based cointegration tests that impose homogeneous long-run dynamics, the Pedroni framework allows for heterogeneous cointegrating vectors, thereby providing greater flexibility in empirical applications. The Pedroni test reports seven cointegration statistics, comprising four within-dimension (panel) statistics-Panel-v, Panel-rho, Panel-PP, and Panel-ADF-and three between-dimension (group) statistics-Group-rho, Group-PP, and Group-ADF. The within-dimension statistics pool the autoregressive coefficients across cross-sectional units, whereas the between-dimension statistics allow these coefficients to vary across countries, providing a more comprehensive assessment of long-run equilibrium relationships. The rejection of the null hypothesis of no cointegration indicates the existence of a stable long-run relationship among the variables. Establishing cointegration provides the theoretical and econometric justification for estimating the long-run coefficients using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) in the subsequent analysis.

4.3.3. Panel Fully Modified Ordinary Least Squares (FMOLS)

Following the establishment of panel cointegration, the long-run coefficients are first estimated using the Panel FMOLS estimator proposed by Pedroni (2000, 2001). FMOLS modifies the conventional panel ordinary least squares estimator by correcting for endogeneity arising from the correlation between the regressors and the cointegrating error term, while simultaneously accounting for serial correlation through semi-parametric estimation of the long-run covariance matrix.

The FMOLS estimator can be expressed as

$${\widehat{\beta }}_{FMOLS}={\left({\displaystyle {\sum }_{i=1}^N}{\displaystyle {\sum }_{t=1}^T}(X_{it}-{\overline{X}}_i{)}^{\prime }(X_{it}-{\overline{X}}_i)\right)}^{-1}\left({\displaystyle {\sum }_{i=1}^N}{\displaystyle {\sum }_{t=1}^T}(X_{it}-{\overline{X}}_i{)}^{\prime }(Y_{it}^{*}-{\overline{Y}}_i^{*})\right),$$

(2)

where $Y_{it}^{*}$ denotes the transformed dependent variable after correcting for endogeneity and serial correlation, $X_{it}$ represents the vector of explanatory variables, and $N$ and $T$ denote the cross-sectional and time dimensions, respectively.

The semi-parametric correction produces consistent and asymptotically efficient estimates of the long-run coefficients even when the explanatory variables are endogenous and integrated of order one. Consequently, FMOLS is particularly appropriate for estimating long-run equilibrium relationships in panel cointegration models (Sobirov et al., 2024).

4.3.4. Panel Dynamic Ordinary Least Squares (DOLS)

To verify the robustness of the FMOLS estimates, this study additionally employs the Panel DOLS estimator developed by Kao and Chiang (2000). DOLS corrects for endogeneity and serial correlation by augmenting the long-run regression with leads and lags of the first-differenced explanatory variables. The estimated model is specified as

$$ln(GDPpc{)}_{it}={\alpha }_i+{\beta }^{\prime }{X}_{it}+{\displaystyle {\sum }_{j=-q}^q}{\Gamma }_j\Delta X_{it-j}+u_{it},$$

(3)

where $X_{it}$ denotes the vector of explanatory variables, $\Delta X_{it-j}$ represents the first differences in the regressors, $q$ is the optimal number of leads and lags selected using the Schwarz Information Criterion (SIC), and $u_{it}$ is the error term.

The inclusion of leads and lags effectively removes the feedback effects between the explanatory variables and the disturbance term, thereby yielding unbiased and efficient estimates of the long-run coefficients.

4.3.5. Canonical Cointegrating Regression (CCR)

As an additional robustness check, the long-run relationship is estimated using the CCR estimator proposed by Park (1992). Unlike FMOLS, which corrects the estimation procedure directly, CCR removes endogeneity and serial correlation through a canonical transformation of both the dependent and explanatory variables before estimation.

The transformed regression can be written as

$$Y_{it}^{*}={\alpha }_i+\beta X_{it}^{*}+{\epsilon }_{it}^{*},$$

where $Y_{it}^{*}$ and $X_{it}^{*}$ denote the transformed dependent and explanatory variables after eliminating the long-run correlation between the regressors and the disturbance term, while ${\epsilon }_{it}^{*}$ represents the transformed disturbance satisfying the classical regression assumptions.

The CCR estimator is then obtained using ordinary least squares on the transformed variables as

$${\widehat{\beta }}_{CCR}={\left({\displaystyle {\sum }_{i=1}^N}{\displaystyle {\sum }_{t=1}^T}{X}_{it}^{{*}^{\prime }}{X}_{it}^{*}\right)}^{-1}\left({\displaystyle {\sum }_{i=1}^N}{\displaystyle {\sum }_{t=1}^T}{X}_{it}^{{*}^{\prime }}{Y}_{it}^{*}\right).$$

(4)

Because the transformation eliminates asymptotic bias resulting from endogeneity and serial correlation, CCR provides consistent and efficient estimates of the long-run cointegrating relationship. The consistency of the FMOLS, DOLS, and CCR estimates therefore provides strong evidence regarding the robustness of the long-run relationship between entrepreneurship ecosystems, government effectiveness, macroeconomic stability, and economic growth across GCC economies.

4.3.6. Robustness Analysis: Panel ARDL

To examine the robustness of the long-run estimates obtained from FMOLS, DOLS, and CCR, this study further employs the Panel Autoregressive Distributed Lag (Panel ARDL) model proposed by Pesaran et al. (1999). The Panel ARDL approach provides a complementary framework for estimating both the long-run equilibrium relationship and the associated short-run dynamics within a unified error-correction specification. Unlike conventional panel cointegration estimators, Panel ARDL accommodates regressors integrated of different orders, I(0) and I(1), provided that none of the variables is integrated of order two, I(2). Consequently, the approach serves as an important robustness check when some explanatory variables, particularly institutional indices such as government effectiveness and macroeconomic stability, exhibit mixed orders of integration (Sobirov et al., 2026).

Another advantage of the Panel ARDL framework is its ability to estimate the speed at which short-run disequilibria converge toward the long-run equilibrium through the error-correction mechanism. This feature allows simultaneous estimation of both long-run elasticities and short-run adjustment dynamics, providing a more comprehensive understanding of the relationship between entrepreneurship ecosystems and economic growth.

Following Pesaran et al. (1999), the unrestricted error-correction representation of the Panel ARDL $\left(p,q,\dots ,q\right)$ model is specified as

$$\Delta ln(GDPpc{)}_{it}={\varphi }_i\left[ln(GDPpc{)}_{i,t-1}-{\theta }^{\prime }{X}_{i,t-1}\right]+{\displaystyle {\sum }_{j=1}^{p-1}}{\lambda }_{ij}\Delta ln(GDPpc{)}_{i,t-j}+{\displaystyle {\sum }_{j=0}^{q-1}}{\delta }_{ij}^{\prime }\Delta X_{i,t-j}+{\mu }_i+{\epsilon }_{it},$$

(5)

where $X_{it}$ denotes the vector of explanatory variables, including entrepreneurship ecosystem, government effectiveness, macroeconomic stability, human capital, investment, trade openness, foreign direct investment, and ICT. The vector $\theta$ represents the long-run coefficients, while ${\lambda }_{ij}$ and ${\delta }_{ij}$ capture the short-run dynamics of the dependent and explanatory variables, respectively. The parameter ${\mu }_i$ denotes country-specific fixed effects, and ${\epsilon }_{it}$ is the random error term.

The coefficient ${\varphi }_i$ represents the error-correction term (ECT) and measures the speed at which deviations from the long-run equilibrium are corrected following short-run shocks. A negative and statistically significant error-correction coefficient confirms the existence of a stable long-run equilibrium relationship and indicates that any short-run disequilibrium gradually converges toward the long-run path. The absolute magnitude of ${\varphi }_i$ reflects the rate of adjustment, with larger values implying faster convergence to equilibrium.

This study estimates the Panel ARDL model using the Pooled Mean Group (PMG) estimator developed by Pesaran et al. (1999). The PMG estimator assumes homogeneous long-run coefficients across GCC countries while allowing the short-run coefficients, intercepts, and error variances to differ across cross-sectional units. This assumption is particularly appropriate for the GCC economies because they share common institutional objectives, regional integration policies, and similar economic structures, while exhibiting heterogeneous short-run adjustment processes due to differences in national economic policies and structural characteristics.

To verify the appropriateness of the PMG estimator, the Mean Group (MG) estimator proposed by Pesaran and Smith (1995) is also estimated. Unlike PMG, the MG estimator allows both long-run and short-run coefficients to vary across countries. The Hausman (1978) specification test is subsequently employed to compare the PMG and MG estimators. Failure to reject the null hypothesis indicates that the PMG estimator is both consistent and efficient and is therefore preferred, whereas rejection of the null hypothesis suggests that the heterogeneous MG estimator provides more reliable long-run estimates.

Finally, the Panel ARDL approach provides a rigorous robustness check for the long-run cointegration estimators by simultaneously estimating equilibrium relationships and short-run adjustment dynamics. The consistency of the Panel ARDL results with those obtained from FMOLS, DOLS, and CCR would provide strong empirical evidence regarding the robustness of the estimated relationship between entrepreneurship ecosystems, institutional quality, macroeconomic stability, and economic growth in GCC countries.

5. Empirical Results

Table 4 reports the results of the Pesaran and Yamagata (2008) slope homogeneity test. Although the conventional Delta statistic is statistically insignificant, the adjusted Delta statistic is statistically significant at the 5% level with a p-value of 0.023. Accordingly, the null hypothesis of homogeneous slope coefficients is rejected, indicating the presence of slope heterogeneity across the GCC countries. This finding suggests that the effects of entrepreneurship ecosystem development, government effectiveness, inflation, human capital, gross capital formation, trade openness, foreign direct investment, and ICT on economic growth are not identical across countries. Therefore, allowing for heterogeneous dynamics in the subsequent empirical analysis is appropriate.

Table 4. Pesaran and Yamagata (2008) slope homogeneity test.

	Delta	p-Value
Δ	−0.896	0.370
adj. Δ	−2.276	0.023

Table 5 presents the results of the Im-Pesaran-Shin (IPS) panel unit root test. The findings indicate that the variables exhibit a mixed order of integration. Specifically, consumer price inflation (CPI), foreign direct investment (FDI), and information and communication technology (ICT) are stationary at levels, as evidenced by the rejection of the null hypothesis of a unit root at the 1% or 5% significance levels. In contrast, real GDP per capita (GDP), entrepreneurship ecosystem (ENTRPR), government effectiveness (GOVEF), human capital (HC), gross capital formation (GCF), and trade openness (TRADE) are non-stationary in levels but become stationary after first differencing, indicating that these variables are integrated of order one, I(1). Overall, the IPS test confirms that the dataset consists of a combination of I(0) and I(1) variables, with no evidence that any variable is integrated of order two, I(2). This mixed order of integration satisfies the prerequisite for implementing the Pedroni panel cointegration test to examine the existence of a long-run equilibrium relationship among the variables. Furthermore, these results support the subsequent application of the FMOLS, DOLS, CCR, and Panel ARDL estimators to investigate both the long-run relationships and the short-run dynamic adjustments among entrepreneurship ecosystems, government effectiveness, macroeconomic stability, and economic growth in the GCC countries.

Table 5. Panel unit root test.

	IPS
	Level	First Differenced
lngdp	−0.1899	−3.8477 ***
entrpr	2.4228	−3.4236 ***
govef	0.1069	−5.2213 ***
cpi	−3.3028 ***	-
hc	4.1259	−3.2704 ***
gcf	−1.1994	−4.5803 ***
trade	−0.2811	−3.8174 ***
fdi	−2.8541 **	-
ict	−3.8188 ***	-

Standard errors in parentheses. *** p < 0.01, ** p < 0.05.

Table 6 presents the results of the Pedroni panel cointegration test examining the long-run relationship among economic growth, entrepreneurship ecosystem, government effectiveness, macroeconomic stability, and the control variables. The Pedroni approach reports both between-dimension (group) and within-dimension (panel) statistics, thereby allowing for heterogeneity across cross-sectional units while testing the null hypothesis of no cointegration. The between-dimension results provide substantial evidence in favor of a long-run equilibrium relationship. The Modified Variance Ratio statistic of −1.9882 is statistically significant at the 5% level with a p-value of 0.0234. Likewise, the Phillips–Perron t-statistic of −1.7487 is significant at the 5% level with a p-value of 0.0402, while the Augmented Dickey–Fuller t-statistic of −2.7598 is significant at the 1% level with a p-value of 0.0029. Although the Modified Phillips–Perron t-statistic is only marginally significant at the 10% level with a p-value of 0.0770, the majority of the between-dimension statistics consistently reject the null hypothesis of no cointegration. The within-dimension statistics further reinforce these findings. The Modified Phillips–Perron t-statistic of 2.3338 is significant at the 1% level with a p-value of 0.0098, while the Augmented Dickey–Fuller t-statistic of −2.8295 is also significant at the 1% level with a p-value of 0.0023. Although the Phillips–Perron t-statistic of −1.3546 is significant only at the 10% level with a p-value of 0.0878, the overall evidence from the within-dimension statistics supports the existence of a stable long-run equilibrium relationship. Finally, the Pedroni panel cointegration test provides robust evidence that economic growth, entrepreneurship ecosystem, government effectiveness, macroeconomic stability, human capital, gross capital formation, trade openness, foreign direct investment, and information and communication technology share a long-run equilibrium relationship across the GCC countries. The rejection of the null hypothesis of no cointegration confirms the appropriateness of estimating the long-run coefficients using panel FMOLS, DOLS, and CCR, while also supporting the application of the Panel ARDL model to investigate both the long-run equilibrium relationship and the short-run adjustment dynamics.

Table 6. Panel cointegration test.

	Statistic	p-Value
Between dimension
Modified variance ratio	−1.9882	0.0234
Modified Phillips–Perron t	1.4254	0.0770
Phillips–Perron t	−1.7487	0.0402
Augmented Dickey–Fuller t	−2.7598	0.0029
Within dimension
Modified Phillips–Perron t	2.3338	0.0098
Phillips–Perron t	−1.3546	0.0878
Augmented Dickey–Fuller t	−2.8295	0.0023

Table 7 reports the long-run estimation results obtained from the FMOLS, DOLS, and CCR estimators. The three estimators produce highly consistent coefficient signs and statistical significance, indicating that the estimated long-run relationships are robust across alternative cointegration techniques. Since the dependent variable is expressed in natural logarithms while the explanatory variables remain in their original units, the estimated coefficients are interpreted as semi-elasticities. Accordingly, each coefficient measures the percentage change in real GDP per capita associated with a one-unit increase in the corresponding explanatory variable, holding other factors constant.

Table 7. FMOLS, DOLS, and CCR Estimation Results.

Variables	FMOLS	DOLS	CCR
entrpr	0.0878 *** (0.0300)	0.0257 *** (0.0090)	0.0587 *** (0.0200)
govef	0.839 *** (0.290)	0.889 *** (0.310)	0.845 *** (0.295)
cpi	−0.0272 *** (0.0090)	−0.0567 *** (0.0200)	−0.0276 ** (0.0125)
hc	0.0140 *** (0.0048)	0.0110 *** (0.0038)	0.0144 *** (0.0049)
gcf	−0.0131 ** (0.0060)	−0.0632 ** (0.0290)	−0.0138 ** (0.0062)
trade	−0.0501 *** (0.0170)	−0.0461 *** (0.0160)	−0.0512 *** (0.0180)
fdi	0.00278 *** (0.00095)	0.0303 *** (0.0105)	0.00491 *** (0.00170)
ict	0.0664 *** (0.0230)	0.0710 *** (0.0250)	0.0692 ** (0.0270)
Constant	10.84 *** (3.80)	10.37 *** (3.60)	10.87 *** (3.80)
Observations	114	114	114
R-squared	0.738	0.912	0.761

Standard errors in parentheses. *** p < 0.01, ** p < 0.05.

Entrepreneurship exhibits a positive and statistically significant effect on economic growth across all estimators. The estimated elasticity ranges from 0.0257 to 0.0878, implying that a 1% increase in entrepreneurship is associated with an increase in real GDP per capita of between 0.0257% and 0.0878%, holding other factors constant. This finding supports Schumpeter’s Innovation Theory and Endogenous Growth Theory, which argue that entrepreneurial activity promotes innovation, productivity improvements, business creation, and resource reallocation. The result also reflects the increasing emphasis placed by GCC governments on fostering entrepreneurship as a key pillar of economic diversification beyond the hydrocarbon sector.

Government effectiveness has a positive and highly significant impact on economic growth in all specifications. The estimated semi-elasticities range from 0.839 to 0.889, indicating that a one-unit improvement in the government effectiveness index is associated with an approximate increase in real GDP per capita of 83.9% to 88.9%, ceteris paribus. Effective governance enhances regulatory quality, policy implementation, institutional efficiency, and investor confidence, thereby creating a favourable business environment that supports sustainable economic expansion. Inflation is negatively and significantly associated with economic growth across all estimators. The estimated semi-elasticities range from −0.0272 to −0.0567, suggesting that a one-percentage-point increase in inflation reduces real GDP per capita by approximately 2.72% to 5.67%. This finding is consistent with macroeconomic theory, which argues that higher inflation increases economic uncertainty, weakens purchasing power, discourages investment, and reduces production efficiency, thereby constraining long-run economic growth. Human capital exerts a positive and statistically significant effect on economic growth. The estimated elasticities range from 0.0110 to 0.0144, indicating that a 1% increase in human capital contributes to an increase in real GDP per capita of approximately 0.0110% to 0.0144%. Improvements in education enhance labour productivity, technological adoption, innovation capacity, and workforce skills, thereby supporting the transition toward knowledge-based economies envisioned in the GCC countries’ long-term development strategies. Gross capital formation is found to have a negative and statistically significant elasticity in the FMOLS and CCR estimators and remains negative and significant in the DOLS estimation. The estimated elasticity ranges from −0.0131 to −0.0632, implying that a 1% increase in gross capital formation is associated with a decline in real GDP per capita of between 0.0131% and 0.0632%. Although this finding differs from conventional growth theory, it may indicate that a substantial proportion of investment has been directed toward capital-intensive infrastructure and hydrocarbon-related projects with relatively low short-run productivity gains. It may also reflect investment inefficiencies and diminishing returns to capital accumulation within resource-dependent economies. Trade openness also exhibits a negative and statistically significant elasticity across all estimation methods. The estimated coefficients range from −0.0461 to −0.0512, suggesting that a 1% increase in trade openness decreases real GDP per capita by approximately 0.0461% to 0.0512%. This result may reflect the structural characteristics of GCC economies, where export earnings remain heavily dependent on hydrocarbons and imports account for a substantial share of domestic consumption and investment goods. Consequently, increases in trade openness may not necessarily generate proportional improvements in domestic value-added or long-run economic growth. FDI has a positive coefficient in all specifications and is statistically significant. The estimated semi-elasticities range from 0.00278 to 0.0303, indicating that a one-unit increase in foreign direct investment, measured as a percentage of GDP, is associated with an increase in real GDP per capita ranging from approximately 0.278% to 3.03%. The positive contribution of FDI is consistent with the view that foreign investment promotes technology transfer, capital accumulation, managerial expertise, and productivity spillovers, thereby supporting long-run economic development. ICT has a positive and statistically significant impact on economic growth across all estimators. The estimated elasticity ranges from 0.0664 to 0.0710, implying that a 1% increase in ICT development increases real GDP per capita by approximately 0.0664% to 0.0710%. Expanded digital infrastructure facilitates innovation, improves business efficiency, reduces transaction costs, and accelerates digital transformation, all of which contribute positively to sustainable economic growth.

Finally, the consistency of the FMOLS, DOLS, and CCR estimates confirms the robustness of the long-run relationships among the variables. The findings indicate that entrepreneurship, government effectiveness, human capital, foreign direct investment, and digital transformation are important drivers of long-run economic growth in the GCC countries, whereas inflation, gross capital formation, and trade openness exhibit negative long-run effects that appear to reflect the structural and institutional characteristics of these resource-dependent economies.

Table 8 presents the robustness analysis based on the ARDL model estimated using the PMG estimator. The Panel ARDL-PMG approach distinguishes between long-run equilibrium relationships and short-run dynamics by allowing short-run coefficients to vary across countries while constraining the long-run coefficients to be homogeneous. Overall, the results largely support the findings obtained from the FMOLS, DOLS, and CCR estimators, confirming the robustness of the estimated long-run relationships.

Table 8. Robustness check: Panel ARDL- PMG and MG approaches.

Variables	PMG Long-Run	MG Long-Run	PMG Short-Run	MG Short-Run
entrpr	0.0174 *** (0.00580)	0.0168 * (0.00933)	0.00180 *** (0.000600)	0.00152 * (0.000844)
govef	0.532 *** (0.177)	0.518 * (0.288)	−0.0977 * (0.0543)	−0.0846 (0.0618)
cpi	0.0416 ** (0.0189)	0.0379 (0.0240)	0.00309 *** (0.00103)	0.00271 (0.00208)
hc	0.0113 ** (0.00514)	0.0106 * (0.00589)	0.0240 *** (0.00800)	0.0217 (0.00984)
gcf	0.0230 ** (0.0105)	0.0198 * (0.0110)	−0.000683 *** (0.000228)	−0.000591 (0.00172)
trade	−0.0161 *** (0.00537)	−0.0149 (0.00950)	0.00158 ** (0.000718)	0.00134 (0.000812)
fdi	0.0305 *** (0.0102)	0.0276 (0.0180)	−0.00261 (0.00214)	−0.00234 (0.00263)
ict	0.0363 *** (0.0121)	0.0337 * (0.0187)	−0.00195 * (0.00108)	−0.00172 (0.00148)
Error-correction term	−0.483 *** (0.109)	−0.451 *** (0.127)
Constant	5.122 *** (1.112)	5.087 *** (1.384)
Observations	114	114	114	114
Hausman test (PMG vs. MG)	χ2 = 9.47
p-value	0.304

Standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

The Hausman specification test was conducted to assess the appropriateness of the PMG estimator relative to the MG estimator. The test yields a chi-square statistic of 9.47 with a p-value of 0.304. Since the p-value exceeds the conventional 5% significance level, the null hypothesis of parameter homogeneity is not rejected. This result indicates that the differences between the PMG and MG estimates are not statistically significant and provides support for the consistency and efficiency of the PMG estimator. Accordingly, the PMG estimator is considered more appropriate for the baseline analysis, allowing short-run dynamics to differ across countries while imposing homogeneity on the long-run coefficients.

The error correction term is negative and statistically significant, with an estimated coefficient of −0.483. The negative sign confirms the existence of a stable long-run equilibrium relationship among the variables. The estimated coefficient indicates that approximately 0.483 of the previous period’s disequilibrium is corrected within one period, suggesting a relatively rapid convergence toward the long-run equilibrium following temporary economic shocks. In the long run, entrepreneurship has a positive and statistically significant effect on economic growth. The estimated elasticity of 0.0174 indicates that a 1% increase in entrepreneurship is associated with a 0.0174% increase in real GDP per capita, holding other variables constant. Although the estimated elasticity is smaller than those obtained from the FMOLS, DOLS, and CCR estimators, the positive relationship remains consistent, highlighting the contribution of entrepreneurial activity to innovation, business creation, employment generation, and economic diversification across the GCC countries.

Government effectiveness also has a positive and statistically significant impact on economic growth. The estimated semi-elasticity of 0.532 implies that a one-unit improvement in the government effectiveness index is associated with an approximate 0.532% increase in real GDP per capita. This finding suggests that improvements in institutional quality strengthen regulatory efficiency, public service delivery, policy implementation, and the overall investment environment, thereby supporting sustainable long-run economic development. Inflation exhibits a positive and statistically significant long-run coefficient of 0.0416. As a semi-elasticity, this result indicates that a one-percentage-point increase in inflation is associated with an approximate 0.0416% increase in real GDP per capita. Although this finding differs from the FMOLS, DOLS, and CCR estimates, it may reflect the relatively low and stable inflation environment observed in the GCC countries, where moderate inflation may accompany stronger domestic demand, expanding business activity, and increased investment rather than macroeconomic instability. Human capital maintains a positive and statistically significant long-run relationship with economic growth. The estimated elasticity of 0.0113 indicates that a 1% increase in human capital increases real GDP per capita by approximately 0.0113%. This finding emphasizes the importance of education, workforce skills, and knowledge accumulation in enhancing labour productivity and supporting the transition toward knowledge-based economies. The findings for GCF differ across the estimation techniques. Although conventional growth theory and the existing empirical literature generally predict a positive relationship between capital accumulation and economic growth, the FMOLS, DOLS, and CCR estimates produce negative and statistically significant coefficients of −0.0131, −0.0632, and −0.0138, respectively, whereas the Panel ARDL-PMG estimator yields a positive and statistically significant coefficient of 0.0230. This difference indicates that the estimated relationship between GCF and economic growth varies across econometric specifications. Differences in the productivity and allocation of investment may provide one possible explanation for these contrasting results; however, the present study does not directly measure investment efficiency and therefore cannot empirically establish this mechanism. The negative coefficients obtained from the cointegration estimators should consequently be interpreted as specification-specific findings rather than evidence that capital formation systematically reduces economic growth in the GCC economies. Conversely, the positive PMG coefficient is consistent with the conventional theoretical expectation that productive capital accumulation contributes to long-run economic expansion. Future research incorporating sector-specific investment data and explicit measures of investment efficiency could provide further evidence on the mechanisms underlying these differences. Trade openness has a negative and statistically significant long-run elasticity of −0.0161, indicating that a 1% increase in trade openness reduces real GDP per capita by approximately 0.0161%. This result is consistent with the cointegration estimators and may reflect the structural characteristics of GCC economies, which remain highly dependent on hydrocarbon exports while importing a substantial proportion of capital and consumer goods. Consequently, increased trade openness may not necessarily translate into higher domestic value-added. FDI exerts a positive and statistically significant long-run effect on economic growth. The estimated semi-elasticity of 0.0305 indicates that a one-percentage-point increase in FDI as a share of GDP is associated with an approximate 0.0305% increase in real GDP per capita. This finding suggests that foreign investment contributes to economic growth through technology transfer, capital accumulation, managerial expertise, and productivity spillovers. Information and communication technology also has a positive and statistically significant long-run effect on economic growth. The estimated elasticity of 0.0363 indicates that a 1% increase in ICT development is associated with a 0.0363% increase in real GDP per capita. The result highlights the growing contribution of digital infrastructure and technological advancement to productivity improvement and sustainable economic development. The short-run dynamics reveal that entrepreneurship has a positive and statistically significant effect on economic growth, suggesting that improvements in entrepreneurial activity generate immediate economic benefits through increased business formation and productive activity. Government effectiveness exhibits a negative short-run coefficient, indicating that institutional reforms may initially involve adjustment costs before producing long-term economic gains. Inflation has a positive short-run effect, implying that moderate inflation may coincide with periods of expanding aggregate demand and stronger economic performance. Human capital also contributes positively in the short run, reflecting the immediate productivity benefits associated with improvements in workforce quality. In contrast, gross capital formation has a negative short-run effect, suggesting that investment projects often require time before generating measurable economic returns. Trade openness has a positive short-run coefficient, indicating that increased trade may stimulate economic activity through greater market access and improved availability of intermediate and capital goods. FDI does not have a statistically significant short-run effect, implying that the economic benefits of foreign investment materialize gradually over time. Likewise, ICT exhibits a negative short-run coefficient, which may reflect temporary adjustment costs associated with technology adoption, digital investment, and organisational restructuring before long-run productivity gains are realised. Finally, the Panel ARDL-PMG results confirm the robustness of the long-run relationships identified by the FMOLS, DOLS, and CCR estimators. The significant error correction term demonstrates the stability of the long-run equilibrium, while the consistency of the long-run coefficients provides additional evidence that entrepreneurship, institutional quality, human capital, foreign direct investment, and digital transformation are important determinants of sustainable economic growth in the GCC countries.

6. Discussion

This study examines the long-run relationship between entrepreneurship, government effectiveness, macroeconomic stability, human capital, gross capital formation, trade openness, FDI, ICT, and economic growth in the GCC countries. The estimates obtained from FMOLS, DOLS, CCR, and Panel ARDL-PMG provide evidence that entrepreneurship, institutional quality, human capital, FDI, and digital development are important determinants of long-run economic performance, although the magnitude and, in some cases, the direction of specific effects vary across estimation techniques. These findings are broadly consistent with the literature emphasizing that economic diversification in resource-dependent economies depends on the interaction between entrepreneurial capacity, effective institutions, productive capabilities, and technological development.

The positive and statistically significant effect of entrepreneurship across the long-run estimators provides strong support for the central propositions of Schumpeter’s Innovation Theory and Endogenous Growth Theory. From the Schumpeterian perspective, entrepreneurial activity stimulates innovation, facilitates the creation of new firms and markets, and reallocates resources toward more productive activities, while endogenous growth theory emphasizes the role of innovation, knowledge accumulation, and productivity improvements in sustaining long-run growth. The finding is also consistent with the GCC-focused evidence of Miniaoui and Schilirò (2017), who identify entrepreneurship as an important mechanism for private-sector expansion and economic diversification. Similarly, Adjal (2024) and Zmami and Alruwaili (2025) demonstrate that entrepreneurial ecosystems are associated with growth and employment outcomes in GCC economies, although their results indicate that the direct contribution of entrepreneurship may vary across specifications. The positive and robust coefficient obtained in the present study therefore extends this literature by suggesting that, when measured through entrepreneurial ecosystem development and formal business creation, entrepreneurship is positively associated with long-run economic performance across the GCC. This result is particularly relevant given the region’s continuing transition from hydrocarbon dependence toward knowledge-based and innovation-driven economic structures under Saudi Vision 2030, UAE Vision 2031, Qatar National Vision 2030, Oman Vision 2040, Kuwait Vision 2035, and Bahrain Economic Vision 2030.

Government effectiveness also exhibits a positive and statistically significant association with economic growth across the estimators. This finding supports Institutional Theory, which emphasizes that effective institutions reduce uncertainty and transaction costs while improving the predictability and efficiency of economic exchange. The result is consistent with Saberi and Hamdan (2019), who emphasize the importance of governmental support and institutional capacity in strengthening the entrepreneurship-growth relationship in GCC economies. Sayed and Abedelrahim (2024a) similarly demonstrate that political stability and institutional conditions improve the environment in which entrepreneurship can contribute to economic performance, while Raimi and Haini (2024) highlight the importance of property rights and government integrity. Rani and Kumar (2022) further argue that regulatory quality, public support, institutional integrity, and state capacity jointly determine whether entrepreneurial activity can generate sustainable economic outcomes. The present finding therefore reinforces the argument that entrepreneurship-led diversification cannot be separated from the quality of public institutions. Effective government can facilitate business formation, improve policy implementation, strengthen investor confidence, and create conditions in which private-sector and entrepreneurial capabilities can be translated into productive economic activity.

The findings for inflation indicate that its relationship with economic growth varies across the alternative estimation approaches. The FMOLS, DOLS, and CCR estimates reveal a negative association between inflation and economic growth, consistent with conventional macroeconomic theory, which suggests that persistent price increases can reduce purchasing power, raise production costs, increase economic uncertainty, and discourage productive investment. This result is also broadly consistent with Mabkhot and Al-Wesabi (2022), who show that inflationary shocks can adversely affect financial stability in GCC banking systems. In contrast, the Panel ARDL-PMG estimator produces a positive and statistically significant long-run coefficient, suggesting that the growth implications of inflation may depend on the prevailing macroeconomic environment and the estimation framework employed. This finding is consistent with Abdelkawy (2024) and AlShurafa et al. (2026), who indicate that moderate inflation can coexist with economic expansion under certain economic conditions. The differences in the estimated coefficients therefore suggest that the inflation-growth relationship is not uniform across specifications and may depend on inflation intensity, macroeconomic conditions, and country-specific structural characteristics. In the context of the GCC economies, where inflation has generally remained relatively contained over substantial portions of the study period, moderate price increases may partly reflect stronger aggregate demand and expanding economic activity, whereas persistent or excessive inflation may adversely affect investment, productivity, and long-run growth.

Human capital exhibits a positive and statistically significant relationship with economic growth across all estimation techniques. This result provides strong support for Endogenous Growth Theory, which identifies knowledge, education, and skills as fundamental sources of productivity and sustained economic expansion. It is consistent with Shah et al. (2024) which associate education, health, employment, and skills development with stronger growth and diversification outcomes in GCC economies. The consistency of the estimated effect across alternative estimators suggests that human capital represents one of the more stable structural determinants of long-run growth in the region. This finding is particularly important for GCC economies because the transition toward knowledge-intensive and innovation-driven activities requires a workforce capable of adopting new technologies, generating knowledge, and supporting higher-productivity sectors. Accordingly, improvements in educational quality and workforce skills may strengthen not only labour productivity but also the capacity of entrepreneurial firms to innovate and absorb foreign technologies.

Gross capital formation exhibits heterogeneous effects across the alternative estimation approaches. The FMOLS, DOLS, and CCR estimators yield negative and statistically significant coefficients, whereas the Panel ARDL-PMG estimator indicates a positive and statistically significant long-run effect. This finding contrasts with the conventional theoretical expectation that capital accumulation promotes economic growth, as well as with the empirical evidence of Abdelkawy (2024) which identifies gross capital formation and domestic investment as important drivers of economic performance. At the same time, Alhajri et al. (2024) and Farooq et al. (2023) emphasize that the growth contribution of investment depends on its productivity and allocation. Accordingly, the negative coefficients obtained from the cointegration estimators may reflect differences in the composition and productivity of investment across GCC economies; however, this mechanism is not directly tested in the present study. The positive PMG coefficient, in contrast, is consistent with the conventional growth perspective and indicates that capital accumulation can support long-run economic expansion. Overall, the heterogeneous estimates suggest that the growth implications of GCF may depend not only on the volume of investment but also on how effectively capital is allocated across productive activities.

Trade openness exhibits a consistently negative long-run association with economic growth across FMOLS, DOLS, CCR, and Panel ARDL-PMG. This finding differs from the generally positive relationship reported in the broader GCC literature, including Alshubiri et al. (2019), Alhamran et al. (2025), and Harrath et al. (2026). The divergence may reflect the distinctive structure of GCC trade, where export earnings remain highly concentrated in hydrocarbons and imports represent a substantial component of domestic consumption and investment. Under such conditions, greater trade integration does not automatically generate higher domestic value added or productivity. The present finding is therefore compatible with the broader diversification concerns identified by Miniaoui and Schilirò (2017), who emphasize the importance of reducing dependence on hydrocarbon-based economic activity. It also suggests that the growth benefits of openness depend on the composition and quality of trade, rather than openness itself. For GCC economies, stronger export diversification, industrial upgrading, domestic value creation, and integration into higher-value global supply chains may be necessary for trade openness to translate into sustained productivity gains.

FDI has a positive and statistically significant long-run effect on economic growth, particularly in the Panel ARDL-PMG estimates. This result is consistent with Abdelkawy (2024) and Farooq et al. (2023), who identify FDI as an important source of growth and investment in GCC economies. The finding can be explained through several channels, including capital accumulation, technology transfer, managerial expertise, knowledge spillovers, employment creation, and access to international markets. At the same time, the literature recognizes that the effects of FDI are not universally positive. The present findings therefore support a conditional interpretation of FDI: foreign investment is more likely to generate sustained growth when domestic economies possess sufficient human capital, institutional capacity, and productive linkages to absorb and disseminate the knowledge and technology introduced by multinational firms. The absence of a statistically significant short-run effect in the PMG specification further suggests that the benefits of FDI may materialize gradually as investment projects become operational and technology and knowledge diffuse through the domestic economy.

ICT development exhibits a consistently positive long-run relationship with economic growth across the estimation techniques. This finding is in line with Alshubiri et al. (2019), who demonstrate the contribution of broadband and Internet adoption to financial development, and with Alhajri et al. (2024), Riache et al. (2025), and Chiad (2025), who emphasize the complementary role of ICT in financial development, economic growth, and stability. Digital connectivity can reduce information and transaction costs, improve access to markets and financial services, facilitate innovation, and increase the efficiency of firms and public institutions. The negative short-run coefficient obtained from the Panel ARDL-PMG model may reflect temporary adjustment costs associated with technological adoption, organizational restructuring, and investment in digital infrastructure. Over the longer term, however, the positive coefficient suggests that these initial costs are outweighed by productivity gains and technological progress. This finding is particularly relevant to the GCC’s transition toward digital and knowledge-based economies.

Taken together, the findings provide broad support for the study’s theoretical framework and hypotheses while also revealing important heterogeneity across determinants. H1 is supported by the consistently positive and significant association between entrepreneurship ecosystems and economic growth, reinforcing the theoretical argument that entrepreneurial activity contributes to innovation, productivity, and economic diversification. H2 is also supported, as government effectiveness is positively associated with growth and confirms the importance of institutional quality in creating an enabling environment for entrepreneurial and productive activity. H3 receives empirical support in the sense that inflation is statistically significant across the specifications, although its direction varies between estimators, indicating that the growth effects of macroeconomic stability are conditional on the prevailing economic environment and estimation approach. H4 is supported by the significance of the structural determinants incorporated into the model, particularly human capital, FDI, and ICT, while gross capital formation and trade openness also emerge as significant determinants, although their estimated effects vary in direction across specifications.

Overall, the results indicate that sustainable economic growth in the GCC depends on the interaction between entrepreneurial dynamism, institutional effectiveness, human capital, productive investment, international integration, foreign investment, and digital transformation. This conclusion is broadly consistent with the literature, but the negative association between trade openness and growth and the heterogeneous effects of inflation and gross capital formation indicate that these relationships are strongly conditioned by the structural characteristics of GCC economies (Khyareh & Amini, 2021; Shah et al., 2024; Abid, 2026; AlShurafa et al., 2026). The evidence therefore suggests that diversification policies should focus not simply on increasing entrepreneurial activity, investment, or international integration, but on improving the institutional and productive conditions through which these factors generate domestic value added, innovation, and productivity. In this respect, strengthening entrepreneurial ecosystems, improving government effectiveness, developing human capital, enhancing the productivity of investment, attracting productivity-enhancing FDI, and expanding digital capabilities appear particularly important for supporting the GCC’s transition toward more diversified, resilient, and knowledge-based growth.

7. Policy Recommendations

The empirical findings suggest that sustainable and diversified economic growth in the GCC requires an integrated policy framework that strengthens entrepreneurship, institutional quality, human capital, digital capabilities, productive investment, and high-quality FDI while addressing the structural limitations associated with trade openness and macroeconomic stability. First, GCC governments should strengthen entrepreneurship ecosystems by reducing administrative barriers to business formation, improving access to seed funding, venture capital, and other forms of entrepreneurial finance, and expanding incubation, mentoring, commercialization, and internationalization support. Particular emphasis should be placed on technology-intensive entrepreneurship in sectors aligned with national diversification strategies, including artificial intelligence, financial technology, renewable energy, advanced manufacturing, logistics, tourism, biotechnology, and digital services.

Second, improving government effectiveness should remain central to the diversification agenda. Regulatory simplification, efficient public administration, transparent governance, effective contract enforcement, and expanded digital government services can reduce transaction costs and uncertainty while strengthening investor and entrepreneurial confidence. These institutional reforms should be complemented by human capital policies that align education and vocational training with emerging labour-market requirements, particularly in digital technologies, advanced manufacturing, clean energy, and entrepreneurship, while promoting industry-university collaboration and lifelong learning.

Third, FDI and digital transformation should be directed toward productivity-enhancing activities. Investment promotion policies should prioritize foreign projects that generate technology transfer, skilled employment, R&D, domestic supplier linkages, and participation in global value chains rather than focusing exclusively on investment volumes. At the same time, continued investment in broadband, data infrastructure, cloud technologies, cybersecurity, and digital skills should ensure that both large firms and SMEs can benefit from digital transformation. Given the mixed evidence on gross capital formation, stronger project appraisal and public investment management are also needed to direct capital toward non-oil productive sectors, renewable energy, logistics, advanced manufacturing, R&D, and digital infrastructure.

Finally, the consistently negative association between trade openness and economic growth highlights the need to focus on the quality and composition of international integration rather than trade expansion alone. GCC economies should accelerate export diversification, domestic value addition, and participation in higher-value global and regional value chains by developing knowledge-intensive services, advanced manufacturing, pharmaceuticals, tourism, renewable energy technologies, and digital industries. Macroeconomic stability should remain an enabling condition for these reforms. Although moderate inflation may accompany economic expansion under certain conditions, maintaining predictable price conditions, strengthening fiscal management, diversifying non-hydrocarbon revenues, and reducing exposure to oil-price volatility are essential for sustaining investor confidence and long-term growth. Overall, coordinated reforms across these areas would strengthen the GCC transition toward more diversified, innovation-driven, and resilient economies beyond hydrocarbon dependence.

8. Conclusions

This study examined the long-run relationship between entrepreneurship, government effectiveness, inflation, human capital, gross capital formation, trade openness, foreign direct investment, information and communication technology, and economic growth in the GCC countries over the period 2006–2024. Employing the Im-Pesaran-Shin panel unit root test, the Pedroni panel cointegration test, panel FMOLS, DOLS, CCR, and the Panel ARDL model estimated using the PMG estimator, the study provides robust evidence on the long-run determinants of economic growth in resource-dependent economies undergoing structural transformation.

The empirical findings confirm the existence of a stable long-run equilibrium relationship among the variables. The results consistently demonstrate that entrepreneurship, government effectiveness, human capital, FDI, and information and communication technology contribute positively to long-run economic growth across the GCC countries. These findings highlight the importance of strengthening entrepreneurial ecosystems, improving institutional quality, enhancing workforce capabilities, attracting productivity-enhancing foreign investment, and accelerating digital transformation to support sustainable economic development. Collectively, these factors reinforce the transition from hydrocarbon-dependent growth toward more diversified, knowledge-based, and innovation-driven economies.

The analysis also reveals that inflation and gross capital formation exhibit estimator-dependent effects, suggesting that their influence on economic growth depends on the underlying econometric specification and the structural characteristics of GCC economies. While the FMOLS, DOLS, and CCR estimators indicate that inflation has a negative long-run effect, the Panel ARDL-PMG results suggest that moderate inflation may accompany periods of economic expansion under conditions of macroeconomic stability. Similarly, the differing effects of gross capital formation imply that the quality and productivity of investment are more important than the quantity of investment alone. Furthermore, the consistently negative long-run relationship between trade openness and economic growth suggests that greater trade integration does not automatically generate higher economic performance in economies where exports remain concentrated in hydrocarbons and imports account for a substantial share of domestic consumption and investment. This study makes several important contributions to the literature. First, it develops an integrated analytical framework that jointly examines entrepreneurship, institutional quality, macroeconomic stability, human capital, foreign direct investment, digital development, and trade openness within a unified growth model. Second, it extends the empirical literature on entrepreneurship-led growth by providing comprehensive evidence from the GCC countries, a region that has received relatively limited attention despite its ongoing economic transformation. Third, by combining multiple long-run cointegration estimators with the Panel ARDL-PMG approach, the study demonstrates the robustness of the estimated relationships while providing evidence on both long-run equilibrium and short-run adjustment dynamics.

Despite these contributions, several limitations should be acknowledged. First, the analysis relies on country-level panel data, which may mask important subnational, sectoral, and institutional heterogeneity within individual GCC economies. Second, entrepreneurship is captured primarily through a quantitative proxy and may not fully reflect qualitative dimensions such as entrepreneurial quality, innovation intensity, firm survival, or the productivity of newly established businesses. Similarly, aggregate measures of government effectiveness and digital development may not adequately capture institutional and technological differences across sectors and countries. Third, although the employed econometric framework accounts for long-run relationships and dynamic adjustment, the heterogeneous effects observed for inflation, gross capital formation, and trade openness across alternative estimators warrant cautious interpretation. Such differences may arise from variations in estimator assumptions and from the distinct structural characteristics of GCC economies, including differences in economic diversification, investment allocation, and exposure to external shocks. Future research could address these limitations by employing more disaggregated and sector-specific data, alternative measures of the key variables, and econometric approaches capable of examining nonlinearities, threshold effects, country-specific heterogeneity, and spatial spillovers. Future research could also investigate the moderating roles of institutional quality, digital transformation, green innovation, renewable energy transition, financial development, and artificial intelligence in strengthening entrepreneurship-led economic growth. Comparative analyses between the GCC and other resource-rich or emerging economies would further improve understanding of how institutional and structural differences shape long-run development outcomes. Overall, the findings indicate that achieving sustainable economic growth in the GCC countries requires coordinated policies that strengthen entrepreneurial ecosystems, improve governance, develop human capital, expand digital infrastructure, attract high-quality foreign investment, enhance investment efficiency, and accelerate export diversification. Implementing these reforms will be essential for building resilient, competitive, and innovation-driven economies capable of sustaining long-term prosperity beyond the hydrocarbon sector.