3.2.2. Determining the relationship between regional disparity and each development policy variable using the rolling regression
In the rolling regression, each parameter was estimated separately for each di¤erent period with a fixed sample size. We regressed regional income inequality for each decentralization and economic development policy variable in logarithmic form. In total, 53 bi-annual data points were included, and for each equation the sample size was fixed at 39 bi-annual data points, so 14 data sets were derived for the estimation of the rolling regression. For example, the first data set covered the period from 1971 to 1990, and that of the final set did the period from 1978 to 1997. This rolling regression model could explain the trend of variation in elasticity for each development variable with respect to regional income inequality over the specified
period.
In terms of the elasticity for regional income equity, shown in Fig. 4,the construction of infrastructure facilities such as roads and water supply facilities was shown to have the most substantial e¤ect on decreasing the income gap among regions. The elasticity for regional disparity gradually diminished with a considerable increase in investments in the transportation
and water supply sectors in the early 1990s. The e¤ect of the spatial distribution of educational services on income distribution increased until 1993, then decreased slowly. This pattern was attributed to expanded opportunities for access to a high level of educational services. In addition, there were no substantial structural changes in the relationship between regional inequality and national economic growth, spatial dispersion of employment
opportunities, or information networks, whereas the elasticity value of each variable stayed fairly stable over the period. These may result from strong restrictions on land use in industrial zones for the largest cities, the provision of financial incentives and price subsidies to producers in the lagging regions, and the expansion of information networks throughout the nation. Finally, the urbanization rate was negatively related to the regional inequality of incomes, because in-migrants into the high-wage regions could reduce the difference in regional incomes. The negative impacts of urbanization on regional income inequality continued to decline during the 1990s.4
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