Economic theory suggests a strong link between economic freedom and economic growth. Since the 1980s, economists like Ricardo, Adam Smith, and Hayek have argued that free markets, individual choice, resource allocation, competition, and property rights are fundamental to economic prosperity. The "invisible hand" of the market and the principles of liberalism, including private property and social cooperation, are key aspects of this perspective. Restrictions on trade and capital flow negatively impact economic growth. Empirical evidence largely supports this positive correlation, although studies have used different methodologies and examined various regions and periods. However, the relationship is complex and intertwined with institutional quality, particularly regulatory quality (RQ). Strong RQ preserves economic freedom, promotes stability, and fosters a conducive business environment, thus aiding economic growth. However, some studies have yielded conflicting findings, indicating that the relationship may not always be significant or even positive in certain contexts. This study investigates this complex interplay using a large global sample and Bayesian regression, analyzing countries with high and low RQ separately, with a specific focus on Vietnam to identify unique country-specific factors and policy recommendations.

The literature extensively explores the relationship between economic freedom and economic growth. Early work by Adam Smith highlighted the importance of free markets and competition. Later studies by Islam (1996) and Acemoglu et al. (2005) showed a correlation between income levels and economic freedom. Gwartney and Lawson (2003) linked higher economic freedom to stronger legal frameworks protecting property rights. Friedman (2010) emphasized efficient resource utilization, while Mamun et al. (2020) focused on endogenous factors like capital formation and regulatory quality. Studies examining the impact of economic freedom on economic growth through various avenues such as knowledge transfer and investment climate were also referenced, including Gurgul and Lach (2011), Bayar (2016), and Kacprzyk (2016). Sulasni and Surbakti (2022) and Ciftci and Durusu-Ciftci (2022) affirmed the positive impact of economic freedom and FDI on growth. However, studies also cautioned against a simplistic view, noting cases where the relationship is insignificant or negative (Doucouliagos, 2005; Uzelac et al., 2020). The close relationship between economic freedom and regulatory quality was highlighted, building upon La Porta et al.'s (1997) work on legal variables impacting economic growth. Cebula and Foley (2012) linked high regulatory quality to a more efficient system, reducing business costs and increasing growth. Ogbuabor, Orji, et al. (2020) and others emphasized the role of robust institutions and a conducive political and legal environment for fostering growth. Studies exploring the impact of governance on growth were also included, including those by Beyene (2022) and Mahran (2023). The literature demonstrates the nuanced relationship between economic freedom, regulatory quality, and economic growth, motivating the current study to clarify the correlation through rigorous methodology and a differentiated analysis of countries with different levels of regulatory quality.

The study employs Bayesian linear regression analysis to investigate the relationship between economic freedom and economic growth, considering the moderating role of regulatory quality. The dataset includes 54 countries from 2008 to 2022. Countries were divided into two groups based on their average regulatory quality index (RQ) from the World Bank: a high RQ group and a low RQ group. The dependent variable is the GDP growth rate. The independent variable is the Economic Freedom Index from The Heritage Foundation. Control variables include fixed capital formation, tax revenue, government expenditure, corruption control, government expenditure on education, foreign direct investment, population growth rate, labor force participation, inflation, unemployment rate, and financial development. Bayesian regression was chosen for its ability to handle complex models, small sample sizes, and heterogeneous data. The Metropolis-Hastings (MH) algorithm was used to run the model 10,000 times, yielding a posterior distribution of regression coefficients. The authors performed convergence diagnostics to check the reliability of their results. Separate analyses were conducted for each group and for Vietnam individually. Posterior interval tests were performed to determine the probabilities of parameters' signs.

The Bayesian regression analysis revealed a positive relationship between economic freedom and economic growth in both high and low RQ groups, with probabilities of 0.9984 and 1 respectively. This suggests that economic freedom is a crucial driver of economic growth, irrespective of regulatory quality. Fixed capital formation (FCF), FDI, and Tax Revenue all showed positive effects on economic growth, particularly in countries with low RQ. Government expenditure on education (GEOE), labor force participation (LABOR), inflation (INF), and unemployment rate (UNE) negatively impacted growth in both groups, with the negative effect being more pronounced in high RQ countries. In low RQ countries, corruption control (CC) and financial development (FD) had positive effects on growth, while the opposite was true in high RQ countries. Vietnam's analysis showed a positive impact of economic freedom on growth (probability of 1), consistent with other countries. However, it revealed some contrasting effects compared to the other two groups. GEOE had a positive effect, while INF, FCF, and POP had negative impacts on growth in Vietnam. The authors explained these differences in the context of Vietnam's status as a developing economy and its specific economic policies. The study further highlighted differences in the impact of corruption control (CC) and financial development (FD) between countries with high and low regulatory quality. In countries with low RQ, both factors positively influenced economic growth, whereas in countries with high RQ, the opposite was observed.

The study's findings reinforce the significance of economic freedom in fostering economic growth, irrespective of a country's regulatory quality. The positive relationship between economic freedom and growth is consistent with existing literature. The differential impacts of control variables across the high and low RQ groups suggest that the effectiveness of institutional factors like corruption control and financial development is context-dependent. The contrasting results for Vietnam highlight the importance of considering country-specific factors and policies when analyzing the relationship between economic freedom and growth. The positive impact of education expenditure on Vietnam's growth suggests that investments in human capital may yield greater returns in developing economies. The positive influence of inflation on growth in Vietnam aligns with the use of expansionary monetary policies in developing countries to stimulate growth. The negative effects of FCF and population growth in Vietnam warrant further investigation, possibly linked to the rapid pace of economic development and demographic changes. The study's findings have implications for policymakers in both high and low RQ countries, advising tailored strategies to maximize economic growth.

This research confirms the significant positive relationship between economic freedom and economic growth across countries with varying regulatory quality. The study's findings underscore the importance of tailoring policies to specific national contexts, recognizing the complex interactions between economic freedom, regulatory quality, and various control variables. Future research should explore a broader range of countries and incorporate additional variables to enhance the generalizability and comprehensiveness of the findings.

The study's scope is limited to 54 countries, potentially limiting the generalizability of findings to other regions. The use of data from different organizations may introduce inconsistencies, and the timeliness of the data might affect the accuracy of the results. Future research should expand the geographical scope and utilize real-time data to address these limitations.