Factors That Attract the Population: Empirical Research by Multiple Regression Analysis Using Data by Prefecture in Japan

Abstract

The development of the local economy and correcting the concentration in the capital city have long been the target for many countries. Furthermore, in the wake of the recent COVID-19 pandemic, the momentum for rural migration has been increasing to prevent the risk of infection with the help of the rise of remote work. However, there is not enough debate about what kind of land will attract the population. Therefore, in this paper, we performed correlation and multiple regression analyses, with the inflow rate and the net inflow rate of the population as the dependent variables, using the average values of government statistics for each prefecture in 2010 and 2017. As a result of the analyses, in addition to economic factor variables, variables of climatic, amenity, and human factors correlated with the inflow rate, and it was shown that the model had the greatest explanatory power when multiple factors had been used in addition to specific factors. It indicated that local prefectures were required to take regional promotion measures focusing not only on economic factors but also on multifaceted factors to attract the outside population. In addition, when the dependent variable was replaced with the 2020 population inflow rate, the model in which human factors were used as the independent variable showed the largest improvement in explanatory power. Therefore, it was shown that human factors have become more important in attracting people during the COVID-19 pandemic.