Bayesian Modeling of Innovation Effect on the Human Development Index in Developing Countries

There are 2 general approaches in statistics science to estimation: classical and Bayesian approaches. In addition to using the random sample information in Bayesian approach, the prior information of parameters is also used for estimation. In other words, in Bayesian approach, a combination of random sample information and prior information is used for deduction. Therefore, the aim of this study is to investigate the relationship between the human development index and innovation in the elected developed countries based on Bayesian approach. In order to measure the innovation index in this study, the number of inventions and the number of inventors were used. In addition to innovation factor, the inflation rate and the health and education costs of the government were also considered as control variables. The statistical sample consisted of 22 elected developed countries in the time period 1996-2015. The analysis results showed that innovation and its indicators, as well as inflation and the health and education costs of the government play a significant role in explaining the human development index in Bayesian approach, which was based on theoretical foundations. According to the obtained results, it is suggested that in the future studies and different research areas, Bayesian approach is used and the results are compared with those of the classical approach.