패널자료를 활용한 수도권과 비수도권 지역의 생활만족도 결정요인

Abstract

The purpose of this empirical study is to analyze the difference in life satisfaction and determinants of the metropolitan and the non-metropolitan areas by merging the Korea Welfare Panel Study data (2007~2014). The results of the empirical analysis are as follows. First, life satisfaction was significantly higher in the non-metropolitan areas than in the metropolitan areas, and the difference was the largest in 2010 and 2014. The reason for the difference in life satisfaction between the two regions in 2010 is that the life satisfaction decreased in 2009, but life satisfaction was recovered in both regions in 2010. The increase is larger in non-metropolitan areas than in the metropolitan areas which made for a bigger gap. The reason for the difference in life satisfaction between the two regions in 2014 is that the life satisfaction in the non-metropolitan area showed not much difference but life satisfaction in the metropolitan area was lower than 2013. This seems to be related to the recent decline in leases but increase in monthly rents in the Korean housing market. Second, in order to estimate whether there is a difference in life satisfaction depending on the resident location in the metropolitan areas and the non-metropolitan areas, it is necessary to estimate the life satisfaction determinants by controlling variables affecting life satisfaction such as gender, education, income and health condition. As a result, the non-metropolitan area showed higher life satisfaction than the metropolitan area, but it was not statistically significant. Third, one of the important policies of the central governments as well as the local governments is to improve the local residents’ quality of life. It is necessary to know what variables affect life satisfaction in order to implement effective policies for improvement of the local residents’ quality of life. In addition, the determinants of life satisfaction should be estimated separately for each resident area since the influencing factors are different depending on the resident area. As a result of estimating the life satisfaction using the panel regression analysis (fixed effect model) by dividing the metropolitan areas and the non-metropolitan areas, the age, disposable income, year debt, living cost, and health condition were variables in the metropolitan areas whereas age, disposable income, health condition, monthly rent, and regular employment were the variables in the non-metropolitan areas. Therefore, it is necessary to consider the variables that have significant influence to increase life satisfaction in metropolitan and non-metropolitan areas.