Studying the role of specific fields of education on country's social and economic performance

This study tries to investigate the effect of stem education and stem workforce and several social and economic indicators with the objective to understand how they affect these indicators for a country and also overall. It is a general consensus that fields of science, engineering and mathematics are beneficial for competitiveness in the global economy. It is a long-standing topic that there are benefits and as such is a very important area for education and labour force policies and in determining the government expenditure on these. The goal of this paper is not to make predictions for the social and economic indicators but to understand the hidden and spillover effects of STEM in the economic region (which in my case are individual European countries). As with any inferential analysis, drawing inferences are often with a risk as the assumptions for the same are hard to establish in real life. Numerous research has been carried out in this topic but all of them fail to address the social effects of education in STEM fields. The aim of my paper is to build on existing studies and expand the array of returns to education in terms of social development as well as economic growth. Innovation is considered to be the most important tool in solving the problems faced by societies today. It can be confidently stated that innovation and STEM fields cannot be separated from each other. Even the individual components of STEM (Science, Technical, Engineering, Mathematics) cannot be separated from each other for analysis due to the simple reason that they are not located in nature separately (Moomaw 2013). Further, the main idea of this research is to look into the lagged effects of STEM graduates on social and economic development - that is to say, a person graduating in STEM fields may not immediately start contributing to such development but probably after a few years as they enter the workforce and bring around innovation. Therefore, it is essential to use lagged variables of STEM education from before the period of study to understand their effect on the dependent indicators. For this study I employ panel data regression models with fixed effects for each longitudinal section cross country effects in addition to the lagged independent variables. The framework of this study is based on traditional growth models enhanced to include the effect of STEM education. All the data used in this study is obtained from Eurostat sources using a publicly available library. The data ranges over 13 European countries over a period of 10 years. Estimates are obtained using regression analysis over panels as well as cross sectional data. The results indicate some positive, unambiguous effects on these indicators and calls for further research in this topic and policy changes for promoting STEM programs and tertiary graduates and higher levels. The analysis revealed that a 1% increase in STEM workforce is associated with a 0.203% increase in GDP per worker, demonstrating the significant economic impact of STEM education. In addition to economic productivity, STEM concentration contributes to reductions in inequality, severe material deprivation, and crime rates. The findings are limited to European countries, and further global studies are needed to generalize the results.