Regional Economic Growth and Income Inequality in Indonesia and China
| Project/Area Number |
15530195
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Economic policy
|
|---|
| Research Institution | International University of Japan |
|---|
Principal Investigator |
AKITA Takahiro International University of Japan, Graduate School of International Relations, Professor, 大学院・国際関係学研究科, 教授 (50175791)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
COORAY S.Nawalage International University of Japan, Graduate School of International Relations, Assistant Professor, 助教授 (50350723)
TOKUNAGA Suminori University of Tsukuba, Graduate School of Life and Environmental Sciences, Professor, 農林学系・生命環境科学研究科, 教授 (10150624)
川村 和美 (財)環日本海経済研究所, 研究員
|
|---|
| Project Period (FY) |
2003 – 2005
|
| Project Status |
Completed (Fiscal Year 2005)
|
| Budget Amount *help |
¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 2005: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2004: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2003: ¥1,200,000 (Direct Cost: ¥1,200,000)
|
|---|
| Keywords | Regional Income Inequality / Indonesia / China / Japan / Theil Indices / Weighted Coefficient of Variation / Geographic Concentration / Economies of Scale / 地域の所得格差 / 交通費 / 労働集約度 / 産業連関度 / 地域間産業連関分析 / 地域格差収束分析 / 地域間格差 |
|---|
| Research Abstract |
(1)We estimated regional income inequality in China over the 1995-1998 period using a Theil index based upon district-level GDP and population data, and conducted a two-stage nested inequality decomposition analysis to explore factors determining regional income inequality. We also performed a regression analysis to explore the possible determinants of within-province income inequality. The decomposition analysis showed that the within-province inequality component accounted for 62 percent of overall regional income inequality in 1998, while the between-region component contributed 27 percent. According to the regression analysis, cumulative per capita FDI and a dummy variable designating inland border provinces are found to be significant in explaining within-province inequality. We also found that economic dualism, as denoted by a low ratio of agricultural labor productivity to labor productivity in non-agricultural sectors, was another significant factor contributing to within-provi
… More
nce inequality.
(2)We employed provincial data to measure regional inequalities in per capita GDP and labor productivity in Indonesia from 1993 to 1999 by the weighted coefficient of variation and the Theil T index, and investigated factors determining regional income inequalities by using several inequality decomposition techniques. We also compared Indonesia's pattern of regional inequalities in 1993-1999 with Japan's pattern in the postwar period and predicted the future pattern of regional inequalities in Indonesia.
(3)We investigated the changing geographical pattern of manufacturing industries in Japan between 1985 and 1995 and explored factors of their geographic concentration. A regression analysis was conducted to test some hypotheses that were derived directly from early models of the New Economic Geography (NEG). Regression results indicated that the geographic concentration of Japanese manufacturing industries seems to be determined by some combination of internal economies of scale, transportation costs, and factor intensity. However, inter-industry linkages were found to be an insignificant factor of geographic concentration. As posited by the NEG theories, Japanese manufacturing industries with larger internal economies of scale and smaller unit transportation costs tended to have a higher level of geographic concentration. Japanese manufacturing data also supported the Heckscher-Ohlin theory : labor- or capital-intensive industries tend to have a higher level of geographic concentration.
(4)We measured regional income inequalities in Japan in the postwar period by using the weighted coefficient of variation and the Theil T index and explored factors determining regional income inequalities by using several inequality decomposition techniques. Regional inequality in per capita GDP, as measured by the weighted coefficient of variation, first increased and reached a peak in 1958 at 0.38. It then declined steadily and hit the bottom at 0.25 in 1979. After 1979, it rose again and reached a peak in 1990 at 0.37. There is a declining trend after 1990. To a considerable extent, regional inequality in per capita GDP was determined by regional inequality in labor productivity. Regional inequality in labor participation rate was not significant. A rapid rise in primary sector's inequality in per capita GDP was attributable to a rise in its inequality in employment share. On the other hand, a decrease in secondary sector's inequality in per capita GDP until the middle of the 1970s was due mainly to a fall in its inequality in employment share, while a decrease in tertiary sector's inequality in per capita GDP until the middle of 1960s was attributable to a fall in its inequality in both labor productivity and employment share. Less
|
Report
(4 results)
Research Products
(9 results)
