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Nonfarm Work and Marketization of the Chinese Countryside*

Published online by Cambridge University Press:  12 February 2009

Extract

This article examines the extent to which labour markets are emerging in the Chinese countryside, focusing on nonfarm work, and whether women participate in those new markets. The examination is based on a 1993 survey that provides new detail on types of work, employment channels, migration and income

Type
China, China Studies and The China Quarterly: A Symposium of Editorial Reflections on the Occasion of the 35th Anniversary of The China Quarterly
Copyright
Copyright © The China Quarterly 1995

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References

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7 More precisely, in a cross-sectional earnings function equation, where logged income is the dependent variable, the regression coefficient for years of education is about 0.08, though there is some variation in the exact coefficient from sample to sample and from time to time, e.g. Sakamoto, Arthur and Chen, Meichu D., “Further evidence on returns to schooling by establishment size,” American Sociological Review, Vol. 56 (1991), pp. 765771.CrossRefGoogle Scholar

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10 Based on reanalysis of May labour force survey data from the Directorate General of Budget Accounting and Statistics, Taipei.

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20 Many readers know of this county through articles and a book by Siu, Helen F., Agents and Victims in South China: Accomplices in Rural Revolution (New Haven: Yale University Press, 1989).CrossRefGoogle Scholar

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22 As a main job, nonfarm work averages 303 days per year. As a second job, it averages only 150 days per year, suggesting much more seasonal and other forms of transient work.

23 Tongjiju, Guojia, Zhongguo tongji zhaiyao, 1994 (Statistical Survey of China, 1994) (Beijing: China Statistics Press, 1994), p. 21.Google Scholar

24 Comparisons to a 1988 survey are highly problematic - both because different counties were sampled and because the 1988 survey found too few first jobs in nonfarm work (12%) when compared to official statistics for the same year (21%). Nevertheless, the addition of second jobs caused the percentage of villagers in nonfarm work to increase by only 5 percentage points in 1988 (reanalysis of raw data from Griffin and Zhao, Distribution of Income). In 1993 the increase was 12 percentage points (see average of male and female figures in Table 2). Though methodologically problematic, the larger 1993 increase is consistent with more nonfarm second jobs in 1993.

25 These comparatively high levels of education are unlikely to be a sampling fluke, for compared to other national surveys, our sample is not unusually well educated. For example, among all village labourers (farm and nonfarm), 27% are illiterate or semi-illiterate, whereas in large 1990 and 1991 national surveys, only 17% to 21% are so poorly educated. See Guojia, Tongjiju Nongcun Shehui Jingji Diaocha Zongdui (ed.), ’92 Zhongguo nongcun zhuhu diaocha nianjian (’92 Annual Survey of Chinese Rural Households) (Beijing: China Statistics Press, 1993), p. 3.Google Scholar

26 State Statistical Bureau, China Statistical Yearbook 1993 (Beijing: China Statistics Press, 1993), pp. 113–14, 330.Google Scholar

27 This speculation is based in part on a reanalysis of 1988 survey data, which shows the reported regional concentration. Also, the 1988 data show 18% of first jobs in the private sector, not too different from 1993. In second jobs, 34% were in the private sector, which was less than in 1993. This would be consistent with a growth of the private, informal sector in the following five years. Original data from Griffin and Zhao, Distribution of Income.

28 Comparison to nonfarm job channels in Taiwan provides some perspective on how very special these patterns are. In 1990 Taiwan, 42% used personal connections, 26% started or continued in the family's running of their own business, 20% replied to an advertisement, and only 8% went through government channels (reanalysis of May 1990 official labour force survey). This is a situation of open, and semi-open, competition approached in the China sample only by final “other” group, which includes joint ventures.

29 Unfortunately, we do not know whether these outsiders are in farming or nonfarm activities. However, separate statistics on outmigrants show that only one-tenth of those working outside their home village are in agriculture, which suggests that most migrants are in nonfarm jobs.

30 We want males not females, since females will typically leave the village for marriage reasons alone, while males are more likely to have left for reason of work.

31 Based on aggregate income, urban proximity and migration patterns, we classify our Jiangsu, Guangdong and Sichuan sample sites as core areas with high labour demand.

32 We checked this pattern province by province. Pujian is the only other locale where administrative family connections fail to improve nonfarm work opportunities.

33 Among several alternate specifications of the relationships in Table 9, we also considered the per capita output value of each village as a control for wealth of local environment. The results were similar to those presented here.

34 Griffin and Zhao, Distribution of Income, also report higher income returns for women.

35 A note of caution. Though quite different from American patterns (Mincer, Schooling), the patterns are less distinct when compared to Taiwan. In Taiwan, the initial rise in income is steeper (0.06) than in China (0.04). But the pattern of a long slow increase in income covering an initial period of over 20 years is shared, suggesting that more than simple market/non-market differences are involved. (Taiwan figures based on reanaly sis of private employees in the May 1990 official labour force survey.)

36 Further signs of that equality of pay include a lower dispersion of wages, as measured by a standard deviation, when compared to other sectors. Also, in a reanaly sis of the raw data from Griffin and Zhao, Distribution of Income, education had a somewhat greater, but still limited, effect on income in the rural collective sector. Though the illiterate were less well paid, primary to college graduates all made about the same incomes. The Griffin/Zhao data has too little data on the self-employed sector for reanalysis of that sector.

37 Cf. Nee, “Theory of market transition,” ”Social inequalities.”

38 Cf. Oi, “Fiscal reform.”

39 Cf. Oi, State and Peasant, “Fate of the collective”; Lin and Hao, “Local market socialism.”

40 Wiemer, “State policy.” A cautionary note is that in our data, though rural collective employees make much more than farmers, they make no more or less than private sector workers (see Table 9). Thus, the restraints on free migration could be the more important explanation for slow employment growth in some locales.

41 Cf. Nee, “Theory of market transition,” “Social inequalities.” On some of the shared similarities with Latin America, see Portes, Alejandro, “Industrial development and labor absorption,” Population and Development Review, Vol. 10 (1984), pp. 589612.CrossRefGoogle Scholar