Factors affecting gdp per capita - Apply Bayesian analysis

Abstract

GDP per capita is often used by economists to measure the standard of living of people in each country. This paper analyzes some indicators affecting the level of GDP per capita, including average labor productivity, the percentage of trained workers of working age, the unemployment rate of the labor force in working age, the increase in the level of investment per capita in the whole society. With the application of the Bayesian linear regression analysis method, the analysis results show that the factor of the unemployment rate of the labor force in working age has the highest impact on GDP per capita. The factor of the percentage of trained workers of working age has the second highest impact, and the factor with the least impact in this study is Labor productivity. Except for the factor of the unemployment rate of the labor force in working age, which has a negative impact on GDP per capita, other factors show a positive impact on GDP per capita. The analysis results also suggest that besides maintaining the low unemployment rate, the government needs to pay attention to raising the proportion of trained workers by improving policies and investing more in education and training, thereby improving labor productivity and leading to an improvement in people's living standards.