Sustainable Trends in Decent Work and Economic Growth: A Comprehensive Analysis of GCC Countries

Abstract

Decent work is essential for fostering workers’ professional and personal growth, as well as for guaranteeing social security and welfare through the enforcement of rules and regulations. Recently, the global labour market has been profoundly influenced by technological innovations, the growth of the services sector, and globalization. Consequently, the protection of fundamental workers’ rights has become increasingly important, establishing that decent employment is crucial for generating superior and higher-quality output. In the Gulf Cooperation Council countries, there is an increasing necessity to acknowledge the significance of decent work conditions for sustained economic development. This study aims to examine the influence of decent work determinants on sustained economic development from 1991 to 2022. The analysis employs panel data methodologies, specifically cross-sectionally Augmented Autoregressive Distributed Lag models, alongside robustness assessments utilising Driscoll–Kraay standard errors, Augmented Mean Group, and Common Correlated Effects Mean Group estimators, revealing that GDP per employee exerts a significant and consistent positive influence on economic growth. Conversely, other aspects of decent work, including unemployment, vulnerable employment, and self-employment, do not have statistically significant long-term consequences. The Westerlund ECM cointegration test verifies the lack of a long-term equilibrium link between decent work indices and economic development. The findings indicate that although labour market quality is significant, productivity is the primary catalyst for sustained growth in the GCC setting. Policymakers should prioritise productivity-enhancing changes within comprehensive employment and labour market strategies.

1. Introduction

Decent work (DW) represents the culmination of individuals’ career goals. It promotes workers’ professional and personal development through professional opportunities and social security based in care and laws [1,2]. It is a framework that defines the fundamental principles of labour, as evidenced by the four strategic objectives of the International Labour Organization (ILO): “the promotion of rights at work, employment, social protection, and social dialogue” [3]. However, the world of labour has been significantly transformed by the developments that have occurred in recent decades, including technical advancements, the notable expansion of the services sector, and the process of globalization itself. Given this, safeguarding employees’ fundamental rights has become increasingly important, and DW stands out as a model for producing more and better work [4]. DW is becoming a major concern for economic growth in the modern global economy.

The concept of DW serves as a cornerstone for achieving sustained economic growth. Accomplishing the UN Sustainable Development Agenda depends on both economic growth and DW. Out of the 17 UN 2030 goals, they make up goal eight, with 169 targets. Sustainable Development Goal (SDG) 8 encompasses a total of 12 targets, among which is the objective of attaining full employment, DW for all individuals, and equitable compensation for labour of comparable worth. Full and productive employment encompasses the presence of high-quality job prospects that allow individuals to earn satisfactory salaries and make meaningful contributions to the economy’s expansion [5]. Implementing measures that can result in long-term DW as a component of inclusive economic growth is essential to the agenda’s achievement. This guarantees that these policies are made to consider the different resources, institutional capacities, and growth stages. SDG 8 asks for measures and policies that address the requirements of the environment, society, and economy [6].

This issue has become increasingly important in light of recent developments in the Gulf Cooperation Council (GCC). However, the GCC, which includes Saudi Arabia, the United Arab Emirates, Kuwait, Qatar, Bahrain, and Oman, has heightened the need to recognize the importance of DW conditions for sustainable economic growth. There is increasing apprehension regarding labour market reforms and strategies aimed at accelerating sustained economic growth. To accomplish this, it is imperative to implement development-focused policies that boost productive work, promote equality and inclusivity, and adopt compliant labour market regulations. A common feature of GCC countries, that is growth in these economies is strongly shaped by oil revenues and fiscal cycles, while employment is heavily reliant on imported labour under segmented labour market systems. Although some intensive research has been carried out on DW and sustained economic growth, limited studies have been conducted on the GCC. While existing literature extensively explores the relationship between decent work and economic growth globally, empirical research targeting the unique economic and social landscape of the GCC is sparse. This gap emphasizes the need for tailored studies examining how factors such as employment quality, job security, and vulnerability in the GCC labour market influence long-term economic sustainability. Therefore, this study states a main question: Does decent work, as measured by selected five SDG 8 indicators, have significant effect on sustained GDP growth in the GCC?

This research significantly enhances the existing body of literature by addressing both empirical and regional deficiencies in the interrelationship between decent work and economic growth. Although the predominant body of literature has primarily focused on advanced or emerging economies, investigations pertaining to the GCC nations are notably scarce. In order to address this deficiency, the study employs an extensive temporal framework spanning from 1991 to 2022 and concentrates on five SDG 8 targets that are most directly correlated with economic measurement. From a methodological perspective, it advances the field by utilising dynamic panel techniques, including the Cointegrated Structural Autoregressive Distributed Lag (CS-ARDL) model and Westerlund cointegration tests—methodologies that are infrequently applied within this specific context. These methodological innovations enhance the robustness of the empirical outcomes and facilitate a more nuanced comprehension of the role of decent work in promoting economic growth.

The originality of this manuscript is rooted in its dual focus on regional pertinence and methodological rigor. By synthesizing data from diverse sources, including the World Bank, the ILO, and United Nations Development Agenda databases, it furnishes a comprehensive and empirically substantiated evaluation of how decent work affects sustained economic growth within the GCC. The timeframe for analysis was dictated by the availability of data and encapsulates three decades of economic evolution in the region. Although the analysis did not encompass all SDG 8 targets, the concentration on five core targets ensures both policy significance and empirical practicality. The omission of the remaining targets is rationalized by their limited relevance to labour market-driven growth frameworks in the GCC and the lack of consistent time-series data essential for robust econometric analysis.

This paper is organized into the following sections: the first section is an introduction, the literature review in the second section, the methodology and data collection in the third section, the results in the fourth section, the discussion in the fifth section, and the conclusion and recommendations in the sixth section.

2. Literature Review

The ILO framework positions DW as a transformative concept that fundamentally reshapes our understanding of sustainable development. DW transcends basic employment by emphasizing fair and productive work, workers’ rights recognition, and comprehensive social protection. It is linked to several components, such as employment opportunities, fair wages, safe working conditions, and social security. It serves as the basis for a sustainable human-centred development agenda [7]. Jobs that are productive and pay fairly, job security and social protection for all, increased opportunities for social integration and individual growth, freedom to voice concerns, organize and take part in life-affecting decisions, and equal treatment and opportunities for men and women [8]. SDG 8 of the United Nations agenda aims to allow all individuals to have a decent job, eliminate forced and child labour and human trafficking, and ensure a safe working environment. The ILO defines DW as fair and caring working conditions that should be secured by all employers for their employees. It ensures workers’ safe working conditions, dignity in the workplace, defence against exploitation, and, above all, access to quality jobs. The sustained enhancement of economic growth is facilitated by a structural transformation from low- to high-productivity activities, which requires diversification, technological upgrading, and innovation [9].

2.1. DW and Economic Growth: Global Perspectives

Recent scholarship reveals critical gaps in SDG 8’s conceptualization of decent work. DW and growth recognize the importance of sustainable economic growth and a high level of economic productivity in creating well-paid jobs and ensuring resource efficiency. Several recent studies have discussed SDG 8 and have begun to examine the relationship between DW and economic growth from different perspectives. Skvarciany and Astike [10] highlight that DW indicates full and productive employment, labour rights, universal social protection, and collective bargaining. MacNaughton and Frey [11] investigate the interrelation between DW and human rights and consider whether the DW goals, targets, and indicators proposed in the past 2015 framework truly integrate human rights and the ILO agenda in a way that is consistent with the international legal obligations of the state’s parties. In their analysis and from a gender perspective Rai et al. [12] argue that SDG 8’s focus on DW and economic growth is inadequate and that productive employment and DW for all men and women by 2030 should consider the value and costs of social reproduction. The authors assert that the realization of SDG 8’s promise of inclusive and sustainable DW requires the underpinning of gender and labour rights. Seubert et al. [13] explore the relationship between DW policies and income equality and conclude that countries with strong DW policies have lower income inequality and poverty rates. This, in turn, leads to more inclusive and sustainable economic growth.

Regarding the inclusion of business and entrepreneurship, even though SDG 8 emphasizes full employment and DW, the 2030 agenda incorporates market-centred institutional arrangements that may impede the goal’s attainment [14]. However, emerging evidence suggests that private sector engagement, when properly structured, can serve as a catalyst for human rights advancement and worker productivity enhancement. Aerni et al. [15]; Peiró et al. [16], point to the role that the private sector may play as an enabler of human rights, creator of DW, improver of worker productivity and innovation, and an engine for inclusive development in different settings. Furthermore, they investigate the potential for economic change to be facilitated by the institutional environment, which could result in social empowerment and improved economic opportunities. Empirical studies provide compelling evidence for the decent work-growth relationship. Hales and Birdthistle [17] conducted an empirical study on the significance of some socioeconomic factors of DW on economic growth. Their findings reveal unemployment as a critical mediator, strongly influenced by educational attainment and macroeconomic stability. Moreover, they find that the unemployment rate is strongly affected by the obtained education and inflation levels, growth of the population, and GDP per capita. Similarly, Bieszk-Stolorz and Dmytrów [18] use the CRITIC method to assess SDG 8 and its importance in the European Union’s economy. Their findings show that the annual growth rate of real GDP per employed person is the most vital indicator.

Skvarciany and Vidžiūnaitė [19] uses the Analytic Hierarchy Process method to assign suitable weights to the SDG 8 indicators for the prioritization of BRICS countries. Their findings show that GDP and unemployment indicators dominate decent work assessments, suggesting that economic fundamentals remain paramount in emerging economies. Employing the two-step system generalized method of moments approach and dynamic panel data analysis, Yerrabati [20] find that vulnerable employment exhibits a dual relationship with growth: positive at higher vulnerability levels and negative at lower levels. This finding suggests that policy interventions must be carefully calibrated to avoid unintended consequences. Some prior studies have mentioned that there is a need for a new approach to promote ‘sustained economic growth’ that takes a long-term view and is supported by the diversification of productive activities and DW factors. The most fundamental challenge to current decent work frameworks comes from strong sustainability perspectives. Kreinin and Aigner [21] present a damning assessment, arguing that SDG 8 fundamentally fails to meet strong sustainability criteria. Their proposed alternative indicators focus on welfare provisioning independent of economic growth, representing a radical departure from conventional approaches.

2.2. Research Gap and Hypothesis Development

While numerous studies have explored the link between DW and economic growth, research focusing specifically on the GCC countries remains limited. Prior research such as Navajas-Romero et al. [22] and Lapinskaitė and Vidžiūnaitė [7] has often used aggregate global or OECD data to analyse how employment quality, labour market security, and informality impact national economic output. However, the GCC is characterized by state-dominated labour markets, high public employment, and a large share of expatriate labour.

In this paper, the term DW refers to the opportunity for all individuals to secure work that is both productive and compensates them fairly, as well as the security of the workplace, social protection for families, improved prospects for personal growth, and social integration. Sustained economic growth indicates sustainability in the gross domestic production of the GCC. Human Capital Theory provides the most robust foundation for examining decent work-growth relationships in the GCC context. This framework emphasizes that investments in worker capabilities, skills, and well-being directly enhance productivity and support sustainable economic growth. This hypothesis asserts that advancements in digital literacy strengthen human capital, hence fostering stronger and more inclusive economic growth—a viewpoint consistent with the objectives of SDG 8, while necessitating empirical proof within the context of the GCC nations.

Table 1. Hypotheses to measure the effect of DW.

No.	Hypothesis
H1	There may be a long-run/short-run effect of the decent work on sustained GDP growth in the GCC countries.
H2	GDP per person employed might have a positive impact on sustained GDP growth in the GCC countries.
H3	The unemployment rate might have a negative impact on sustained GDP growth in the GCC countries.
H4	Vulnerable employment might have a negative impact on sustained GDP growth in the GCC countries.
H5	Self-employed might harm sustained GDP growth in the GCC countries.

formulates five hypotheses based on the theoretical framework and review of previous empirical studies.

3. Materials and Methods

Many studies have examined the impact of DW indicators on sustained economic growth in many developed economies. This study employs a panel data analysis using multiple regression techniques to investigate how DW impacts economic growth in the GCC countries. The study focuses on key indicators aligned with SDG 8, which promotes inclusive and sustainable economic growth, employment, and decent work for all [23,24]. The dependent variable is GDP per capita (constant 2015 US$), which serves as a proxy for economic growth. Independent variables include GDP per person employed, unemployment rate, self-employment rate, and vulnerable employment rate—all of which are commonly used proxies for DW and have been validated in prior literature [7,25]. Five targets under SDG 8 are selected based on their relevance and data availability across the GCC region, these include:

Target 8.1: Sustain per capita economic growth in accordance with national circumstances and, in particular, at least 7 percent gross domestic product growth per annum in the least developed countries.

Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading, and innovation, including a focus on high-value-added and labour-intensive sectors. Proxied by GDP per person employed.

Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity, and innovation and encourage the formalization and growth of micro, small, and medium-sized enterprises, including through access to financial services. Captured through the self-employment rate [22,26].

Target 8.5: By 2030, achieve full and productive employment and DW for all women and men, including young people and persons with disabilities, and equal pay for work of equal value, assessed via the unemployment rate.

Target 8.8: Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular, women migrants, and those in precarious employment, represented by the vulnerable employment rate [20,25].

These variables were selected for two key reasons. First, they are widely recognized in the literature as relevant indicators of DW and are explicitly linked to the targets of SDG 8 [7]. Second, data for all five indicators are consistently available across the GCC countries from reliable sources such as the World Bank and the ILO, ensuring the robustness and comparability of the analysis. Data from 1991 to 2022 for the six GCCs countries were sourced from the World Bank and the ILO, ensuring consistency and reliability as seen in

Table 2. Variables explanation.

Variable	Variable Name	Definition	Unit	Source
PGDP	GDP per capita (constant 2015 US)	The gross domestic product divided by the midyear population	US Dollar	World Bank
GDPPE	GDP per person employed	Calculated by dividing GDP by the total employment in the economy.	US Dollar	World Bank
UNEMP	Unemployment, total (% of total labour force)	Unemployment represents the portion of the labour force actively seeking employment.	Percentage (%)	World Bank and the ILO
VEMP	Vulnerable employment, total (% of total employment)	Vulnerable employment refers to the percentage of family workers and own-account workers that contribute to total employment.	Percentage (%)	World Bank and the ILO
SEMP	Self-employed, total (% of total employment)	Self-employed workers work independently, with partners, or in cooperatives.	Percentage (%)	World Bank and the ILO

. Thus, including all targets would compromise model validity due to data limitations and conceptual misalignment with macroeconomic growth modeling.

The excluded targets, although globally important, are either conceptually peripheral to the GCC context or unsuitable for econometric modelling. For instance, Target 8.4 (resource efficiency) belongs to the environmental dimension rather than labour–productivity dynamics; Target 8.6 (youth NEET) suffers from fragmented time-series data across GCC countries; Target 8.7 (child and forced labour) has limited relevance given strict labour and migration regulations in the region; Target 8.10 (financial inclusion) is not a binding constraint in GCC economies with near-universal banking access; and Target 8.b (youth employment strategies) is policy-oriented and lacks measurable time-series indicators. Excluding such targets avoids compromising model validity and ensures analytical focus on those aspects of SDG 8—productivity, employment quality, and labour rights—that directly influence sustained economic growth in the GCC [27]. See Appendix A.

A descriptive analysis and Pearson correlation matrix were initially employed to evaluate variable distributions and interrelationships. Pearson’s coefficient provides a straightforward, widely used measure of association that allows for comparability with findings from prior empirical studies. This makes it a suitable initial diagnostic tool before applying more advanced econometric techniques, such as the Toda–Yamamoto causality test [28]. A cross-sectional dependence test was conducted to determine appropriate unit root tests. The second-generation panel unit root tests (CADF and CIPS) revealed that all variables are integrated in order one, I (1), necessitating first differencing [29].

Given the non-stationarity, we applied the Westerlund cointegration test to examine potential long-run relationships between DW indicators and economic growth. The test results indicated the absence of cointegration, justifying the use of dynamic models focused on short-run dynamics [30]. Consequently, a Fixed Effects (FE) model was estimated based on the Hausman test, which rejected the Random Effects (RE) specification. To address potential autocorrelation, heterogeneity, and endogeneity, a CS-ARDL model was also estimated [31].

4. Results

To ensure compatibility and interpret the obtained coefficients as elasticities, the targeted variables were subjected to a natural logarithm transformation [32]. Descriptive statistics presented in

Table 3. Statistical description of variables in the model.

Variable	Obs.	Mean	Std. Dev.	Min	Max
Log PGDP	198	10.3444	0.4352	9.6033	11.3097
Log GDPPE	198	11.7399	0.2470	11.1432	12.3020
Log UNEMP	198	0.5862	0.9434	−2.3026	2.0082
Log VEMP	198	0.2545	1.1973	−2.1642	2.4972
Log SEMP	198	1.0710	0.8101	−1.0449	2.6558

Source: Authors’ calculations using EViews software (Version 12).

show that the log-transformed variables display reasonable ranges and dispersion across the dataset. While some variables, such as Log UNEMP and Log VEMP, exhibit relatively large standard deviations compared to their means, the result reflects underlying labor market volatility across GCC countries. Importantly, panel econometric estimators such as FE, RE, and ARDL do not require strict normality of variables; what matters is the integration order and error term properties, both of which were validated in subsequent unit root and robustness tests.

Correlation results reported in

Table 4. Correlation Matrix.

	Per Capita GDP	GDP per Person Employed	Unemployment Rate	Vulnerable Employment Rate	Self-Employed Rate
Log PGDP	1.00000
Log GDPPE	0.5273 0.0000	1.0000
Log UNEMP	−0.5841 0.0000	−0.0822 0.2493	1.0000
Log VEMP	−0.8877 0.0000	−0.2774 0.0001	0.5819 0.0000	1.0000
Log SEMP	−0.7249 0.0000	−0.2139 0.0025	0.7664 0.0000	0.8031 0.0000	1.0000

Source: Authors’ calculations using STATA software (Version 12).

indicate generally low pairwise associations among the variables, except for a relatively strong correlation (r = 0.80) between vulnerable and self-employment rates, which warrants caution in subsequent regression analysis.

Before estimating the Pooled Mean Group (PMG) and ARDL models, cross-sectional dependence tests were performed to determine an appropriate stationary test for the panel data. These tests can help ensure that the estimation strategy accounts for potential bias and efficiency issues [33],

Table 5. Cross-section dependence test.

Test	Statistics	Prob.
Breusch-Pagan LM	82.5537	0.000
Pesaran scaled LM	12.3336	0.000
Pesaran CD	−0.4579	0.647
Log PGDP	−1.847	0.065
Log GDPPE	6.263	0.000
Log UNEMP	−0.826	0.405
Log VEMP	7.533	0.000
Log SEMP	7.348	0.000

displays the test results. The Breusch–Pagan LM and Pesaran scaled LM tests indicate significant cross-sectional dependence (p < 0.01), whereas the Pesaran CD test fails to reject the null hypothesis of cross-sectional independence (p = 0.647). Given these mixed outcomes, and following standard practice in the literature [34,35], second generation panel unit root tests that allow for cross-sectional dependence were applied to all five variables. In addition, first-generation tests, namely Levin–Lin–Chu (LLC) and Im–Pesaran–Shin (IPS), were conducted as robustness checks. The results are presented in

Table 6. Unit root test.

Variable	CADF		CIPS		LLC		IPS
	Level	1st Difference	Level	1st Difference	Level	1st Difference	Level	1st Difference
Log PGDP	−1.870	−2.669 **	−2.163	−4.211 ***	−0.587	−7.070 ***	−1.274	−7.844 ***
Log GDPPE	−1.920	−2.770 ***	−2.196	−4.023 ***	−0.700	−6.321 ***	0.634	−7.240 ***
Log UNEMP	−0.643	−2.790 ***	−0.736	−4.151 ***	−0.538	−8.485 ***	−0.014	−8.622 ***
Log VEMP	−1.288	−3.157 ***	−1.422	−4.153 ***	−0.237	−3.191 ***	1.629	−4.499 ***
Log SEMP	−1.633	−2.888 ***	−1.230	−3.709 ***	−0.295	−1.644 **	0.853	−2.859 ***

Source: Authors’ calculations using STATA software. Note: ** and *** denotes to 5% and 1% level of significance, respectively.

.

As shown in Table 6, none of the variables is stationary at the level, whereas they become stationary at the first difference with a significance level of 1% and 5%. The findings from the cross-sectional unit root tests demonstrate that all variables in this study are non-stationary at levels, I (0), yet achieve stationarity following first differencing, I(1). This suggests that the variables exhibit stochastic trends, which is common in macroeconomic time series data. The necessity of first differencing implies that shocks to these variables have long-lasting effects.

Panel cointegration tests can ascertain whether the variables of interest exhibit a long-term relationship after confirming stationarity features and rejecting the null hypothesis of a unit root. Given cross-sectional dependence, we apply the Westerlund ECM panel co-integration test as seen in

Table 7. Westerlund ECM panel cointegration tests.

Westerlund ECM		Pedroni Test
	Statistic		Statistic
Gt	−2.787 **	Modified PP-t	1.4612 *
Ga	−4.777	Phillips–Perron t	−0.6976
Pt	−2.922	Augmented DF-t	−0.7606
Pa	−2.754

Source: Authors’ calculations using STATA software. Note: * and ** denotes to 10% and 5% level of significance, respectively.

. This assessment includes four statistical metrics: two group and two-panel statistics (Gt, Ga, Pt, and Pa, respectively). This method establishes the following four error-correction-based panel non-cointegration test statistics under a null hypothesis of no cointegrating relationship. To ensure robustness, we also applied the Pedroni test.

The results of the Westerlund ECM panel cointegration test, supported by the Pedroni robustness check presented in Table 7, provide only weak and inconsistent evidence of a long-run relationship between decent work and economic growth in the GCC countries. This implies that improvements in decent work indicators do not consistently translate into sustained economic growth over time within the study period. The limited evidence of cointegration may be linked to the structural features of GCC economies, which remain heavily shaped by oil dependence and segmented labor markets. They rely largely on oil earnings, and changes in global oil prices may have a greater impact on economic growth than labour market circumstances [36,37]. Furthermore, many GCC nations rely on a substantial expatriate labour force with different working conditions than natives, which may limit the impact of decent work rules on long-term economic growth [23,38]. Furthermore, while decent work programs are encouraged, their implementation and impact may differ by sector and nationality, resulting in inconsistent effects on economic growth [39]. Decent work initiatives may offer short-term economic benefits, such as increased productivity and consumption, but these impacts may be insufficient to sustain long-term economic growth [40].

It is important to acknowledge that the Pedroni and Westerlund panel cointegration tests provide only weak and inconsistent evidence of a long-run relationship. This raises the question of whether long-run estimations remain meaningful. Following Pesaran et al. [41], the panel ARDL framework and its extensions (CS-ARDL, AMG, CCE-MG) remain valid and informative even in the absence of strict co-integration, provided that the variables are integrated in order one, I(1). These estimators yield consistent and unbiased long-run parameters by exploiting dynamic adjustments and cross-sectional information, without requiring co-integration as a strict precondition. Furthermore, Banerjee and Carrion-i-Silvestre [42] point out that typical panel cointegration tests may have low power in the presence of structural discontinuities and cross-sectional reliance, both of which are extremely relevant to oil-dependent GCC economies. As a result, our long-run coefficients are read as conditional associations that show systematic linkages across time, while acknowledging that they do not represent a strict co-integrating equilibrium.

To examine the relationship between DW indicators and economic growth, both Random Effects (RE) and Fixed Effects (FE) models were estimated. The appropriate model was selected based on the Hausman test, which evaluates whether the unique errors are correlated with the regressors. The test yielded a Chi-square p-value of 0.01, which is less than the 0.05 threshold, leading to the rejection of the null hypothesis in favor of the FE model. Thus, the FE specification was adopted for analysis. The FE model is structured as follows:

$$\mathrm{Log} \mathrm{GDP} = a_0+ a_1\log {GDPE}_{it}+ a_2\log {UNRA}_{it}+ a_3\log {VUEM}_{it}+ a_4\log {SEM}_{it}+ {\epsilon }_{it}$$

(1)

where $i$represents the number of groups (countries) for $t$time (panel data period). $a_1$ to $a_4$ are the regression coefficients used to interpret the explanatory variables and ${\epsilon }_{it}$is the error term. The regression results indicate that from 1991 to 2022, three variables; GDP per person employed, vulnerable employment, and self-employment exerted a statistically significant impact on economic growth. Specifically, the FE model results in

Table 8. The Fixed and Random-Effects Models.

Variables	Fixed Effects		Random Effects
	Coefficient	SE	Coefficient	SE
Log GDPPE	0.6217 ***	0.0268	0.6181 ***	0.0273
Log UNEMP	−0.0097	0.0111	−0.0124	0.0114
Log VEMP	−0.0450 **	0.0222	−0.0568 **	0.0221
Log SEMP	−0.1364 ***	0.0338	−0.1224 ***	0.0337
c	3.2103 ***	0.3030	3.2414 ***	0.3159
Model fit	$R^2$ = 0.73	N = 198	$R^2$ = 0.75	N = 198
Hausman test	13.46	0.0092

Source: Authors’ calculations using STATA software. Note: ** and *** denotes to 5% and 1% level of significance, respectively.

reveal that GDP per person employed significantly and positively affects economic growth, with an elasticity of 0.62 (p < 0.01). Vulnerable employment and self-employment rates are both negatively associated with GDP per capita, at −0.045 (p < 0.05) and −0.136 (p < 0.01), respectively. The unemployment rate was statistically insignificant. The model’s R-squared value of 0.73 indicates that the DW indicators explain a substantial portion of variation in economic growth.

To further probe the short- and long-run dynamics, based on the unit root test results the study applied the CS-ARDL model. The CS-ARDL model was used for this investigation because of its flexibility in applying varying lags to different variables and its ability to address autocorrelation and endogeneity concerns. The model considers the impact of DW on GDP, estimates dynamic panel models to account for both short- and long-term effects, and addresses issues of stationarity and endogeneity in the variables. The CS ARDL model exhibits stationarity.

$${\mathrm{G}\mathrm{D}\mathrm{P}}_{it}={\phi }_i(\log {GDP}_{it-1}-{\beta }_i{X}_{it-1})+\sum _{j=1}^p{\lambda }_{ij}\log {GDP}_{i,t-j}+\sum _{j=0}^q{\delta }_{ij}\log X_{i,t-j}+{\epsilon }_{it}$$

(2)

Here, the lags of the dependent and independent variables are represented by $p$ and $q$, respectively. The dependent variable is the log GDP, and the error part is denoted by ${\epsilon }_{it}$. $X$ is the vector of explanatory variables. In particular, the short-term parameters of the lagged dependent variable are denoted by $\lambda$, the short-term coefficients of the lagged explanatory variables are denoted by $\delta$, and the long-term effect of the explanatory variables is denoted by $\phi$.

Table 9. CS ARDL model.

	Variable	Coefficient	SE
Long-run coefficients	Log GDPPE	0.4272 ***	0.0335
	Log UNEMP	0.0370	0.0080
	Log VEMP	−0.0029	0.0312
	Log SEMP	−0.0306	0.0455
Short-run coefficients		−0.9246 ***	0.0273
	D Log GDPPE	0.8239 ***	0.0681
	D Log UNEMP	−0.0052	0.0154
	D Log VEMP	−0.0577	0.0593
	D Log SEMP	0.0701	0.0862

Source: Authors’ calculations using STATA software. Note: *** denotes to 1% level of significance.

illustrates the outcomes of the CS-ARDL panel model, which was estimated utilizing the PMG [12].

The results of the CS-ARDL model were estimated using the PMG estimator, and they reveal both the short-term responsiveness and long-term equilibria of the modeled relationships. The error correction term is −0.92 (p < 0.01), indicating a strong and rapid convergence to equilibrium after a shock. While relatively large in magnitude, such high adjustment speeds are not uncommon in panel ARDL ap-plications Pesaran, Shin and Smith [41] and may reflect the structural features of GCC economies, where fiscal buffers and oil revenues enable swift stabilization of growth trajectories. In the short run, GDP per person employed significantly contributes to growth (coefficient = 0.82, p < 0.01), underscoring the role of productivity. In contrast, UNEMP, VEMP, and SEMP exhibited statistically insignificant short-run effects, suggesting that their impact on output may not materialize immediately or uniformly across countries.

In the long-run estimates, GDPPE remained statistically significant and positive (coefficient = 0.43, p < 0.01), confirming its sustained importance for economic growth in the GCC. However, the long-run coefficients for UN, VEMP, and SEMP were insignificant, consistent with the findings from the Westerlund test that suggested no cointegrating relationship. These findings highlight that while improvements in productivity directly bolster economic output, broader indicators of DW such as employment security and informality may not have immediate or sustained impacts on growth in the GCC. This may reflect structural characteristics of GCC labour markets, including reliance on migrant labour and public-sector employment dominance [23,43].

It is worth noting that in static FE/RE models, VEMP and SEMP are negatively and significantly related with economic growth, however in the CS-ARDL long-run estimates, these impacts are statistically insignificant. This divergence likely reflects the difference between static correlations and dynamic adjustments: in the short run, informality and self-employment may constrain productivity and output, but these effects dissipate over time in the GCC context, where oil revenues, public-sector dominance, and reliance on expatriate labor reduce the long-term impact of labor market structure on growth.

This suggests that policies enhancing productivity are more effective for sustaining growth than those targeting informality, unless accompanied by deeper structural reforms. To validate the reliability of the CS-ARDL model results, two alternative panel estimators were used: Driscoll-Kraay standard errors (DK-SEs) with fixed effects and two types of mean group estimators that account for cross-sectional dependence: The Augmented Mean Group (AMG) and the Common Correlated Effects Mean Group (CCE-MG) estimators [44,45,46].

The fixed effects regression with DK-SEs in

Table 10. Robustness Tests results: DK Fixed Effects, AMG and CCE-MG.

Variables	DK Fixed Effects		AMG		CCE-MG
	Coefficient	Drisc/Kraay SE	Coefficient	SE	Coefficient	SE
Log GDPPE	0.6217 ***	0.0721	0.8868 ***	0.0642	0.8784 ***	0.0608
Log UNEMP	−0.0097	0.0141	0.0141	0.0156	−0.0072	0.0147
Log VEMP	−0.0450	0.0365	−0.1511	0.1781	−0.0599	0.0847
Log SEMP	−0.1364 *	0.0727	0.1765	0.2084	0.0842	0.1139
c	3.2103 ***	0.7962	−0.3732	0.6490	0.6740	0.7165
Model fit	$R^2$ = 0.82	N = 198	chi2 = 606.08 (0.000)	N = 198	chi2 = 822.01 (0.000)	N = 198

Source: Authors’ calculations using STATA software. Note: *** and * denotes to 1% and 10% level of significance.

confirms a positive and significant relationship between GDPPE and economic growth (coefficient = 0.622, p < 0.01), while UNEMP and VEMP remain statistically insignificant. SEMP is marginally significant at the 10% level (p < 0.10), suggesting only weak evidence of a negative association with growth. The AMG estimator, which accounts for unobserved common factors through a common dynamic process, yields an even stronger positive impact of GDPPE (coefficient = 0.887, p < 0.01), with other variables remaining insignificant. Similarly, the CCE-MG estimator supports a robust positive effect of GDPPE (coefficient = 0.878, p < 0.01) and confirms the insignificance of UN, VEMP, and SEMP. These consistent results across estimation techniques affirm the central role of labour productivity in driving economic growth in the GCC while suggesting limited long-run influence of other DW indicators.

These robustness assessments corroborate the CS-ARDL model’s main findings: economic productivity, as measured by GDP per employee, is the most consistent and significant predictor of economic growth across all models. In contrast, other elements of decent work, such as unemployment, vulnerable employment, and self-employment, do not exhibit statistically significant long-run effects in the GCC.

5. Discussion

The objective of this paper was to find out the impact of DW on accelerating sustained economic growth in GCC countries during the 1991–2022 period using a set of explanatory variables to measure DW, including GDPE, UNEMP, VEMP, and SEMP. Panel data analysis was employed to investigate the correlation between long-term economic growth and several variables of DW. The summary statistics indicate that the log-transformed variables exhibit consistent means and ranges, suggesting that the dataset is suitable for regression analysis. The Pearson correlation matrix indicates that the correlation is rather low in all instances, as the coefficients are below 0.80. Therefore, it is show relatively low pairwise associations among the explanatory variables. The cross-section dependence test results reveal that Breusch–Pagan LM and scaled LM suggest dependence (p < 0.01), whereas Pesaran CD does not. Given mixed results, we conservatively used second-generation tests. The findings suggest that all the variables display stationarity at the first difference at the 1% and 5% significance levels. While Pedroni and Westerlund tests provided only weak evidence of cointegration, the use of panel ARDL-type estimators (CS-ARDL, AMG, CCE-MG) remains appropriate, as they yield consistent long-run parameters without requiring strict cointegration [41]. Accordingly, our long-run results should be viewed as conditional associations that capture systematic linkages over time rather than strict equilibrium relationships.

Regarding the study hypotheses, three of the explanatory variables incorporated in the model—GDPE, VEMP, and SEM—indicate that the assumptions related to these variables are valid and are associated with economic growth, while the assumption related to UNRA is not. The ARDL model includes both long-run and short-run coefficients for all variables covering the 1991–2022 period. The ARDL panel model, estimated using PMG estimation, yields statistically significant results for GDPE, while it yields non-significant results for the variables UNEMP, VEMP, and SEMP in both the short and long terms. The effect of the three variables on economic growth in the long term are significant, while a non-significant relationship is found for all variables in the short term. The findings of this study offer precise views of the short- and long-term dynamics of DW indicators on economic growth in the GCC countries. These results are in line with prior studies indicating that indicators of DW, particularly productivity measures, have a significant influence on economic growth [18,21].The fixed effects model highlights that GDP per person employed significantly and positively influences economic growth. This outcome is intuitive, as productivity gains—often associated with higher capital investment and technological enhancement—are direct contributors to GDP increases. In contrast, both vulnerable employment and self-employment have a negative impact on growth, highlighting structural challenges in the GCC labour markets related to informality, limited social protection, and the dominance of non-standard employment arrangements. This aligns with findings from Yerrabati [20], who report that vulnerable employment exhibits a dual relationship with growth—positive at higher vulnerability levels and negative at lower levels—suggesting that the context and composition of vulnerable work can alter its effect on economic performance. The negative and statistically significant coefficient of the error correction term indicates the speed of adjustment to long-run equilibrium after a short-run shock. The observed high error correction speed of −0.92 is plausible, as GCC economies possess significant fiscal buffers through sovereign wealth funds and oil revenues, facilitating swift stabilization. The absence of a long-run link between decent-work indicators and GDP in the GCC reflects the region’s structural context. However, economic growth is dominated by oil revenues and price cycles, while labour markets are segmented and heavily reliant on expatriate workers under migration and sponsorship systems. These features weaken the conventional channels through which decent work affects long-term output [38].

The estimation results suggest the influence of several DW metrics in fostering sustained economic growth. However, the unemployment rate did not exhibit a significant impact on GDP in either the short or long run. This may reflect the structural segmentation of GCC labour markets, where public-sector employment absorbs a significant portion of the national workforce, and unemployment is often hidden or understudied among national populations [23]. Expatriate labour, which constitutes a large portion of the workforce in the private sector, often works in informal or less secure employment conditions, which may weaken the expected economic impact of improving DW indicators. These findings suggest that GCC economies derive more economic benefit from enhancing productivity than from improving general labour market conditions. This insight is particularly relevant for policymakers aiming to diversify GCC economies away from oil dependence while maintaining social protection. Empirical and policy evidence indicates that GCC countries differ substantially in their economic structure and reform courses. Some members continue to exhibit strong capital-intensive production, while others have adopted economic diversification policies, an example Saudi Arabia, expanding finance, tourism and high-value services—sectors in which DW improvements may more directly raise labour productivity and spillovers to non-tradable sectors [47]. These structural differences alter both the exposure of the workforce to DW interventions and the expected growth elasticity of improved job quality.

The findings of the current study support the theoretical propositions underpinning SDG 8. Recent studies corroborate the current results. Goel et al. [48] and Zeb-Obipi and Kpurunee [49] suggest that enhancing DW conditions can be a catalyst for economic growth. The positive impact of GDPE is aligned with the results of Skvarciany and Vidžiūnaitė [19] and Skvarciany and Astike [10]. Blustein, Lysova and Duffy [3] support the findings about the negative implications of UNRA on economic growth. The findings related to VEMP are consistent with those of Yerrabati [20]. The findings on SEM align with global trends and theoretical predictions. They are also supported by Sagar et al. [50] study, which reveals that entrepreneurship significantly promotes economic growth and development by creating jobs, fostering innovation, increasing productivity, and promoting social mobility, thereby reducing economic inequality. Collectively, these studies validate the findings of the present study and highlight the importance of promoting sustainable economic growth in the GCC countries through enhanced employment quality, decreased vulnerability and self-employment, and efficient use of the labour force. The equivalence of these results with global studies emphasizes the global significance of DW as an engine of economic growth.

Institutional heterogeneity also influences the results, as the GCC countries implement DW reforms differently. The disparities in national capacities for social security, collective bargaining, labor inspection, and the rate and extent of DW implementation imply different time lags and effect sizes for any DW-growth dividend. However, this leads to steady fluctuations in unobserved growth factors (e.g., fiscal space, reform sequencing, or exposure to commodity prices). There is a risk that combining all six-member states will confuse various procedures and obscure national pathways via which improvements in employment quality lead to higher productivity and overall growth [51]. While there has been a significant amount of research conducted on the relationship between DW and economic growth, there is currently a lack of studies that specifically examine GCC economies in this context. However, the findings offer a more profound understanding of the significance of DW in GCC countries’ attainment of economic growth and sustainability. In addition, this study examined key indicators of DW using the SDG 8 targets and employed econometric regression approaches. Further investigation is necessary to establish the correlation between DW and economic growth in the GCC, addressing the remaining targets and focusing on DW from different perspectives.

6. Conclusions

This paper examined how DW accelerated sustained economic growth in GCC countries. DW indicators were extracted from the goals of SDG 8 [17]. The study examined the potential the impact of Decent Work indicators on economic growth in GCC countries using advanced panel data techniques, including the CS-ARDL model and robust estimators. While GDP per employee consistently showed a significant positive association with economic growth, other Decent Work dimensions, including unemployment, vulnerable employment, and self-employment, did not exhibit statistically significant long-run effects. These findings suggest that productivity-related aspects of decent work may be more influential than employment structure alone in driving growth in GCC nations. The absence of cointegration further indicates that improvements in decent work do not necessarily translate into long-term economic gains within the GCC context.

This outcome may reflect the structural characteristics of GCC labour markets rather than analytical shortcomings. The GCC economies’ dependence on hydrocarbon revenues, together with their segmented labour markets and reliance on imported labour, creates conditions that diverge from the contexts in which the ILO’s Decent Work framework was originally developed [27,52]. The normative relevance of decent work remains important, particularly in the context of long-term economic diversification strategies and human capital development in the region. The promotion of decent work can be viewed as an investment in inclusive growth and labour market sustainability. To reflect this balance, Baldwin-Edwards [38] and Forstenlechner and Rutledge [53] emphasize the structural constraints and the potential longer-term role of decent work in supporting economic transitions. To foster sustainable growth, policymakers should prioritize productivity-enhancing strategies while ensuring that Decent Work initiatives are effectively implemented and tailored to the unique labour market dynamics of the region.

The primary constraint of this study is the availability of important indicators that reflect the remaining six objectives of SDG 8. The implementation of macroeconomic indicators as proxies for these targets can help move towards long-term economic growth and the adoption of DW strategies. Future studies are suggested to overcome this limitation by providing appropriate indicators and conquering the data availability challenge in GCC countries. Hence, future studies must integrate these variables into the study to attain a more thorough comprehension of DW in GCC nations and emerging economies. Furthermore, examining various data sources can enhance DW research in these economies. Engaging in comparative research across other countries can enhance our comprehension and advancement of DW. Expanding the use of comparison models to include a wider range of countries can enhance the accuracy and precision of this subject.

The current study excluded certain structural variables pertinent to GCC economies, including oil price volatility, contributions from the hydrocarbon industry, and proportions of expatriate workers. These exclusions stem from data limitations and the study’s focus on Decent Work indicators under SDG 8. As such, the results should be interpreted with caution, recognizing that the identified relationships may interact with these broader structural dynamics. Future research is encouraged to incorporate such variables to provide a more comprehensive understanding of the drivers of sustainable growth in GCC economies.

The study’s novelty comes in its utilization of panel data in the econometric analysis of GCC to determine the relationship between DW and economic growth. All GCC countries possess a DW attitude and strive to attain both economic growth and sustainability. The empirical findings of this study reveal that GCC nations are transitioning towards adopting DW standards, as outlined by the United Nations agenda. The findings of this study are valuable for governments and politicians in crafting strategies for economic expansion and development, as well as for achieving DW targets. The findings underscore the imperative for governments to consider implementing long-term strategies and programs to enhance DW and thus promote sustained economic growth in GCC countries. Eventually, the findings provide significant knowledge that guides policy choices based on DW policies and efforts in GCC countries. By focusing on the promotion of rights at work, employment, and social protection and providing economic incentives, policymakers can effectively address the challenges of DW and achieve sustainable economic growth.