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The Impact of Outward-Oriented Economic Reform on Income Inequality in China: 1978–2007

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Abstract

China initiated economic reform in various sectors from 1978 and since the early 1990s has drawn a great deal of attention to its outward-oriented economic reforms. The economic transition from a centrally planned to a market-oriented system accompanied fluctuations in income distribution. The main objective of this chapter was to examine the impact of China’s outward orientation (globalisation) on income inequality from 1978 to 2007 by using the cross-sectional and time series approach. The major results show that (1) income inequality was widening in the 1990s, especially in the eastern region, which coincided with the period of all round economic reform and accelerated outward-oriented reforms; (2) the reforms of trade and state owned enterprises lead to income inequality, whereas, FDI and economic growth improved income inequality; (3) the eastern region dominated the inequality-increasing effect of trade and inequality-decreasing effect of FDI; and (4) the reform package introduced in 1992 played an important role in the overall inequality-increasing effect. The policy implication is that FDI and trade policies should be strengthened in those regions and sectors that are less developed and/or concerned.

Dr. Shao-Wei Lee is a Research Fellow at the Taiwan Academy of Banking and Finance, Taipei, Taiwan. This research project is originated and re-written based on her unpublished PhD thesis which was completed in Nov. 2010 at the University of Wollonging in Australia.

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Notes

  1. 1.

    Based on the poverty headcount ratio of $1.25 a day, the aggregate absolute poverty decreased from 60 % of the population in 1990 to 16 % in 2005 in China (World Bank 2009).

  2. 2.

    Fourteen coastal cities are including Shanghai, Tianjin, Dalian (Liaoning province), Qinghuangdao (Heibei province), Yantai (Shandong province), Qingdao (Shandong province), Lianyungang (Jiangsu province), Nantong (Jiangsu province), Ningbo (Zhejiang province), Wenzhou (Zhejiang province), Fuzhou (Fujian province), Guangzhou (Guangdong province), Zhanjiang (Jiangsu province), Beihai (Guangxi province).

  3. 3.

    The three regions are defined officially by the Chinese government. The eastern region contains Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shangdong, Guangdong, Guangxi, and Hainan. The central region contains Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, and Hunan. The western region contains Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaxxi, Gansu, Qinghai, Ninghai, and Xinjiang.

  4. 4.

    For example, Yao 1999; Keng 2004; Zhao 2003; Kanbur and Zhang 2005; Huang et al. 2006; Lin and Liu 2005.

  5. 5.

    Refer to Chapter Five in Lee (2011) for fuller discussions.

  6. 6.

    GDP data for Hainan is incomplete and withdrawn from this analysis.

  7. 7.

    Take FDI for example, regional FDI is calculated as a ratio of FDI in the a region to total GDP.

  8. 8.

    As mentioned earlier, the panel data regression in this chapter controls for time-invariant region-specific characteristics. That is, fixed effects (group dummies) control for the average difference across regions. This will reduce the problem of omitted variable bias. The consequence of using national data for the inflation rate is that regional-specific differences in inflation rates will only be taken into account without omitted variable bias if the differences are constant. If not, then the estimated coefficient on the inflation rate may be biased.

  9. 9.

    For example, the essential component of the regional labour force and unemployed population are not available. As for inflation, the use of an aggregate measure may lead to a biased parameter estimate.

  10. 10.

    The panel LM unit root test assumes Model AA (which allows two breaks in the intercept) only. In this test, all variables were time demeaned, as if including time fixed effects in usual panel models. This can reduce the cross correlation problems, if they exist.

  11. 11.

    The Davidson-Mackinnon test (1993) examines whether potential endogenous regressors are correlated with the error terms. Rejection of the null hypothesis indicates that the regressors are endogenous and instrumental variables techniques are required. Further to this, the test of validity for the possible instrumental variables including the over-identification, weak-identification, and under-identification tests are used. The over-identification test uses the Sargan-Hansen Statistic with a null hypothesis of the instrument is valid and uncorrelated with the error term. The weak-identification test is undertaken using the Cragg-Donald F statistic, which tests the null hypothesis that the endogenous variables are weakly correlated with their instruments. Lastly, the under identification test by Anderson’s canon correlation likelihood ratio (LR) statistic examines the null hypothesis that the endogenous variables are not correlated with the instruments in the equation.

Abbreviations

ADF:

Augmented Dickey-Fuller

FDI:

Foreign Direct Investment

FIEs:

Foreign-Invested Enterprises

GDP:

Gross Domestic Product

HOS:

H-O model and Stolper-Samuelson theorem

IPS:

Im Pesaran, and Shin

LLC:

Levin Lin, and Chu

LM:

Liquidity preference Money supply

SEZs:

Special Economic Zones

SOEs:

State-Owned-Enterprises

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Authors and Affiliations

  1. Taiwan Academy of Banking and Finance, Taipei, Taiwan

    Shao-Wei Lee

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  1. Shao-Wei Lee
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Correspondence to Shao-Wei Lee .

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Editors and Affiliations

  1. School of Economics, The University of Wollongong, Wollongong, New South Wales, Australia

    Zhiming Cheng

  2. Department of Resource Management and Geograph, The University of Melbourne, Melbourne, Victoria, Australia

    Mark Wang

  3. School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China

    Junhua Chen

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Lee, SW. (2014). The Impact of Outward-Oriented Economic Reform on Income Inequality in China: 1978–2007. In: Cheng, Z., Wang, M., Chen, J. (eds) Urban China in the New Era. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54227-5_1

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