Comparison of the Effect of Social Progress and Economic Freedom on Gross Domestic Product (GDP) using the Panel Data Method (2014-2018)

The goal of development is accessing the different types of freedom. Any deprivation and constraint somehow disturbs freedom, so the field of production as the acting of development and progress will be lost. Actually, achieving the economic freedom and consequently, social progress can be so important and they can also affect GDP in every country. The relationship between freedom and achievement to social progress is beyond a structural relationship, and it has a high level of importance. What is positively gained by people is affected by economic freedom and opportunities, social powers, healthcare, primary education, and encouragement of innovations. Institutional orders for such opportunities are affected by freedoms that result from their free participation in social selection and free decision making for improving the opportunities.

In this research, data of 144 countries of the world has been used. According to the classification of the World Bank, countries are divided into four groups including countries with low income, countries with lower than average income, countries with higher than average income, and countries with high income. Regarding the theoretical and experimental foundations, three variables have been used in this research: GDP per capita (purchasing power parity) as a dependent variable of research, and independent variables were economic freedom index and social progress indicator. The Economic Freedom Index (EFI) combines the factors of the rule of law (property rights, judicial effectiveness, and government integrity), government size (tax burden, government spending, and fiscal health), legal efficiency (business freedom, labor freedom, and monetary freedom), market openness (trade freedom, investment freedom, and financial freedom); the social progress indicator is a combination of the factors of the basic human needs (nutrition and basic medical care, water and sanitation, shelter, and personal safety), foundations of wellbeing (access to basic knowledge, access to information and communication, health and well-being, and environmental quality) and opportunity (personal rights, personal freedom and choice, tolerance and inclusion, and access to advanced education). Economic Freedom Index is derived from the data banks of Heritage Institution and social progress is derived from Social Progress Index website, and the data of GDP per capita is derived from the World Bank. Data collection required for the test was extracted and analyzed based on the maximum available information over the years 2014-2018. Eviews10 software package was used for data processing and model estimation. In order to estimate the effect of social progress index and economic freedom index on GDP per capita in the four groups of countries, an equation was estimated for each of the groups. In this equation, the effect of social progress and economic freedom on GDP per capita is estimated. By estimating this equation one can say that how many percentage of GDP per capita of each group is explained by social progress and economic freedom.

Having the GDP per capita as the dependant variable and social progress index and economic freedom as independent variables, for estimating the model, first reliability of the research variables was checked by Hardi Unit Root Test. The results of these indicators in the mentioned test and comparison with the critical value at the level of 5%, the null hypothesis considering the existence of a unit root for all the variables is reliable and it was observed that static variables were of zero degree I(0), and there was no need for differentiation. Also, the results of likelihood ratio test, F Limer and Hausman test showed that in likelihood ratio test, the likelihood value is less than 0.05 in all the four groups. So, ordinary least squares cannot be used for estimating the model. As a result, estimators of weighted least squares or generalized least squares were used for assessing the model in order to prevent bias of estimation. The results of F Limer in all the four groups indicated that the value of this statistics was more than the critical point. Therefore, the null hypothesis suggesting using Pool was rejected. Therefore, panel data was used for estimating the model. The results of Hausman test were also observed in all groups. As regards the test statistics is more than the critical point and p-value was obtained less than 0.05, as result, the null hypothesis based on being identical of intercepts was rejected. Accordingly, constant effect method was used for estimating the model. Finally, the results of constant effect of variables for the four income groups of the studied countries showed that social progress index has an increasing and significant effect on GDP per capita in the countries with low income, countries with lower than average income, countries with higher than average income, and countries with high income. The effect of economic freedom index on GDP per capita is increasing and significant in low income countries; insignificant in countries with lower than average income; insignificant in countries with higher than average income; increasing and significant in countries with high income. At last, the share of social progress increases by income enhances in the countries, but the share of economic freedom does not increase.

The important point to be taken into account is that the share of social progress increases with the income boost in countries. Based on the coefficients obtained from the estimation, it should be considered that the effect of social progress index on GDP per capita has a direct relationship with the income increase in countries, and this effect is stronger in high income counties than that of the other three groups of countries. Thus, it can be claimed that a part of the income gap between and among the four groups of countries can be explained by the gap between their social progress levels. Also, the share of economic freedom decreases by income increase in low income and below average income countries. It can be due to environmental and political challenges that are created by increased income of countries and will not lead to economic freedom of countries. Therefore, according to North’s theory of institutions, existence of a stable institutional structure that is the requisite of human interactions provides the opportunity of social progress. However, this condition requires an environment in which free economic management is realized, and it will be achieved through economic freedom. In this regard, paying attention to the effect of institutions on GDP is necessary. Also, acording to the Solow, Lucas, and Barro models, the reason for the differences in countries’ GDP per capita is that wealthy countries have invested more in raising social and economic freedom, creating human and physical capital, and developing education and research and technology.Ethical ConsiderationsAuthors’ contributionsAll authors contributed in producing of the research.FundingIn the present study, all expenses were borne by the author and he did not have any sponsors.Conflicts of interestThe authors declared no conflict of interest.AcknowledgmentsIn this article, all rights relating to references are cited and resources are carefully listed.