Globalization and Regional Income Inequality in China

Abstract

China’s recent accession to the WTO is expected to accelerate its integration into the world economy, which aggravates concerns over the impact of globalization on the already rising inter-region income inequality in China. This chapter discusses China’s globalization process and estimates an income generating function, incorporating trade and FDI variables.

Data Appendix

• 1. Unless indicated otherwise, data for the period 1987–1998 are all from Comprehensive Statistical Data and Materials for 50 Years of New China (NBS 1999). Data for years 1999–2001, unless indicated otherwise, are from China Statistical Yearbook, 2000, 2001 and 2002 (NBS various years).

• 2. Income: Regional income is the weighted average of urban and rural per capita incomes, with non-agricultural and agricultural population shares as weights. Both urban and rural incomes are deflated by regional urban and rural CPIs. For Shanghai, Beijing and Tianjin, urban and rural CPIs are the same.

• 3. Capital: Using perpetual stock method, Zhang et al. (2004) constructed capital stock data at the 1952 price. They provide estimates for 1952–2000, and the authors extend the data to 2001. Capital stock in 1952 is given by

  $$K_{0} = \frac{{I_{0} }}{\delta + r}$$

  where K ₀ is the capital stock in 1952, I ₀ investment in the same year, $\delta$ depreciation rate, and r average growth rate of real investment before 1952.

• 4. Dependency: Dependency ratio is computed as:

  $$Dependency = \frac{total\;population - employment}{employment} \times 100\,\%$$

• 5. Education (edu): China Population Yearbooks report regional population by education attainment as from 1987. Unfortunately, such data were not published for 1989, 1991 and 1992, and data for 1987 and 1988 are incomplete as illiterate population are not reported. Also, unlike data for other years, the 1994 data did not consider population below the age of 15. To estimate data for these years, we compute average years of schooling using data for the other years and then fit the model:

  $$\ln (edu) = f( \cdot ) + \mu ,$$

  where $edu$ is per capita years of schooling, $f( \cdot )$ is simply a linear function of time trend and regional dummies, $\mu$ the error term. This model is estimated by GLS technique, allowing for heteroskedasticity in the panel data. The R² of the estimated equation is 0.966. Denote the predicted value by ^, we have:

  $$\widehat{edu} = \exp \left[ {\ln \left( {\widehat{edu}} \right)} \right]\,{ \exp }\left( {0. 5\,\hat{\sigma }^{2} } \right),$$

  where $\ln \widehat{{\left( {edu} \right)}}$ denotes the predicted values of ln ($edu$) and $\hat{\sigma }^{2}$ is the estimated variance of $\mu$. Data for 1987–1989, 1991, 1992 and 1994 are estimated by the above model.

• 6. FDI: FDI is defined as per capita FDI. The 1987–1989 data for Sichuan are from China Statistical Yearbook. The Qinghai data for 1988 and 2000 are the average of the neighboring two years. FDI data are converted into RMB, using medium exchange rate available in China Statistical Yearbooks.

• 7. Trade: Trade is computed as the trade/GDP ratio. Trade data are converted into RMB.

• 8. Reform: Reform is computed as the proportion of workers and staff in non-state-owned entities.

• 9. Urbanization: Urbanization is defined as the proportion of non-agricultural population in the total. Except for Hebei, Heilongjiang and Gansu, 1999–2001 data of agricultural and non-agricultural population are from provincial statistical yearbooks. Total population of Hebei, Heilongjiang and Gansu in 2000 are from China Statistical Yearbook, 2001. For these three regions, the 1999 population data are the averages of the neighboring two years, and the 2001 data are forecast based on data in 2000 and the growth rate during 1999–2000.

• 10. Gov: This is per capita government expenditure excluding administration fees, deflated by regional CPI (see Tables 4.5, 4.6, 4.7, 4.8 and 4.9).

Table 4.5 Results of χ ² test with H₀: Model 1 = Each of Models 2–17

Table 4.6 Inequality decomposition results, GE₀

Table 4.7 Inequality decomposition results, GE₁

Table 4.8 Inequality decomposition results, Atkinson index (e = 0)

Table 4.9 Inequality decomposition results, Squared CV