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Creating the entrepreneur farmers needed  yesterday, today and tomorrow Xiaobing Wang, Jikun Huang, Linxiu Zhang, Scott Rozelle Jan 25, 2011
Percent of Pop’n in Ag. Sector Income per Capita US and other OECD nations Ethiopia, Rwanda, etc. “ Iron Law of Economic Development” Data from the World Bank
Percent of Pop’n in Ag. Sector Income per Capita Development = Industrialization Modernization = Urbanization Zero : there are no high income countries in world with more than 10% of their populations that live in agriculture 10%
Percent of Pop’n in Ag. Sector Income per Capita “ Miracle Development—with Taiwanese Characteristics” Taiwan—1950s Taiwan—1974 Taiwan—today Taiwan—1987
Percent of Pop’n in Ag. Sector Income per Capita ,[object Object],[object Object],[object Object],[object Object],China in 1980s China at the End of Socialism
 
 
 
Is China moving along the Transformation Path,    according to the  Iron Law ?   moving along the Transformation Path, according to the  Iron Law ?hina moving along the Transformation Path, according to the  Iron Law ? ,[object Object],[object Object]
China’s per capita GDP (at PPP) in the last one thousand years Tang  Song  Ming  Ch’ing  Since 1978 1911 – 1970s Source: Angus Maddison Poverty line
Becoming better off … income rising …
Shenzhen in  1980 … …  and 2000
Transformation Path Percent of Pop’n in Ag. Sector Income per Capita So it is clear that as China is growing (moving left to right across the graph), it also is beginning to move “down” the transformation path …  this is “development”
What was the Role of Self-employed (through 2000)? Self-employed Migrant Wage Earners
[object Object],[object Object],[object Object],[object Object],[object Object]
Reason 2: Demand for services high ,[object Object],[object Object],[object Object],Why was there so much SE activity?
Why was there so much SE activity?  ,[object Object],Yuan / hour (real 2000 yuan)
[object Object],[object Object],[object Object],But, China’s labor markets have continued to evolved between 2000 and 2008 …
Question for Rest of Presentation ,[object Object],[object Object],[object Object],speculative
Plan for the rest of the paper ,[object Object],[object Object],[object Object],[object Object],[object Object]
Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Sichuan Hubei Shaanxi Hebei Zhejiang Liaoning 2000  China National Land and Labor Survey (First Wave) -- 6 Provinces -- 5 Counties / Province -- 2 Villages / County -- 20 Households / Village     1200 hh’s
Sichuan Hubei Shaanxi Hebei Zhejiang Liaoning 2008  China National Land and Labor Survey ( Second Wave ) -- 6 Provinces -- 5 Counties / Province -- 2 Villages / County -- 20 Households / Village     1160 hh’s Two villages in one county were almost completely destroyed by the earthquake in Sichuan  Surveyed: May 2009
Contents of Survey ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
In 2008: 62% of rural labor force had jobs off the farm    more than 80% of households had at least 1 person working off the farm In 1980: only 16% worked off the farm Overall Increase in Off-farm Work by Rural Laborers (note 100% is the full rural labor force ≈ 500 million people)
Cohort effect of off-farm participation
During 2000s, SE is stagnant and migrant wage earners keep growing fast Self-employed Migrant Wage Earners
Remember what happened through 2000? Self-employed Migrant Wage Earners
SE and Migrant Wage Earners, 1981 to 2008 Self-employed Migrant Wage Earners
Number of SE Firms Even more dynamic than this … 60% of firms “died” between 2000 and 2008 … 50% of firms are “new” (born between 2000 and 2008 …
Why did this happen? Why did this happen?
Wages in recent years also have risen fast (not surprising—given there are few people who do not have a job in most prime-aged cohorts) ,[object Object],[object Object],Yuan / hour (real 2008 yuan)
Wages and Returns to Self Employment,  2000 and 2008 Predicted wage for the Self Employed Returns to Self Employment
Income gap of being self-employer The income gap declines 2000 2008 Actual hourly earnings 7.2 7.4 Predicted wage 3.1 4.7 Difference  4.1 2.7
Probit estimation of rural laborer’s occupation choice, 2008 Variables If off-farm rural laborers are self-employed  (Self-employer=1; Wage earner=0) Earning gap 0.010** 0.007* (2.22) (1.79) Gender -0.249** -0.187* (-2.53) (-1.80) Training 0.413*** 0.405*** (4.24) (3.86) Marriage 0.508*** 0.471*** (3.32) (2.93) Age 0.084*** 0.085** (2.69) (2.59) Age square -0.0008** -0.0008** (-2.23) (-2.15)
Why? ,[object Object],[object Object],[object Object],[object Object]
So what about self-employed firms in China in the future ,[object Object],[object Object],[object Object],[object Object]

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Creating the entrepreneur farmers needed yesterday, today and tomorrow

  • 1. Creating the entrepreneur farmers needed yesterday, today and tomorrow Xiaobing Wang, Jikun Huang, Linxiu Zhang, Scott Rozelle Jan 25, 2011
  • 2. Percent of Pop’n in Ag. Sector Income per Capita US and other OECD nations Ethiopia, Rwanda, etc. “ Iron Law of Economic Development” Data from the World Bank
  • 3. Percent of Pop’n in Ag. Sector Income per Capita Development = Industrialization Modernization = Urbanization Zero : there are no high income countries in world with more than 10% of their populations that live in agriculture 10%
  • 4. Percent of Pop’n in Ag. Sector Income per Capita “ Miracle Development—with Taiwanese Characteristics” Taiwan—1950s Taiwan—1974 Taiwan—today Taiwan—1987
  • 5.
  • 6.  
  • 7.  
  • 8.  
  • 9.
  • 10. China’s per capita GDP (at PPP) in the last one thousand years Tang Song Ming Ch’ing Since 1978 1911 – 1970s Source: Angus Maddison Poverty line
  • 11. Becoming better off … income rising …
  • 12. Shenzhen in 1980 … … and 2000
  • 13. Transformation Path Percent of Pop’n in Ag. Sector Income per Capita So it is clear that as China is growing (moving left to right across the graph), it also is beginning to move “down” the transformation path … this is “development”
  • 14. What was the Role of Self-employed (through 2000)? Self-employed Migrant Wage Earners
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22. Sichuan Hubei Shaanxi Hebei Zhejiang Liaoning 2000 China National Land and Labor Survey (First Wave) -- 6 Provinces -- 5 Counties / Province -- 2 Villages / County -- 20 Households / Village  1200 hh’s
  • 23. Sichuan Hubei Shaanxi Hebei Zhejiang Liaoning 2008 China National Land and Labor Survey ( Second Wave ) -- 6 Provinces -- 5 Counties / Province -- 2 Villages / County -- 20 Households / Village  1160 hh’s Two villages in one county were almost completely destroyed by the earthquake in Sichuan Surveyed: May 2009
  • 24.
  • 25. In 2008: 62% of rural labor force had jobs off the farm  more than 80% of households had at least 1 person working off the farm In 1980: only 16% worked off the farm Overall Increase in Off-farm Work by Rural Laborers (note 100% is the full rural labor force ≈ 500 million people)
  • 26. Cohort effect of off-farm participation
  • 27. During 2000s, SE is stagnant and migrant wage earners keep growing fast Self-employed Migrant Wage Earners
  • 28. Remember what happened through 2000? Self-employed Migrant Wage Earners
  • 29. SE and Migrant Wage Earners, 1981 to 2008 Self-employed Migrant Wage Earners
  • 30. Number of SE Firms Even more dynamic than this … 60% of firms “died” between 2000 and 2008 … 50% of firms are “new” (born between 2000 and 2008 …
  • 31. Why did this happen? Why did this happen?
  • 32.
  • 33. Wages and Returns to Self Employment, 2000 and 2008 Predicted wage for the Self Employed Returns to Self Employment
  • 34. Income gap of being self-employer The income gap declines 2000 2008 Actual hourly earnings 7.2 7.4 Predicted wage 3.1 4.7 Difference 4.1 2.7
  • 35. Probit estimation of rural laborer’s occupation choice, 2008 Variables If off-farm rural laborers are self-employed (Self-employer=1; Wage earner=0) Earning gap 0.010** 0.007* (2.22) (1.79) Gender -0.249** -0.187* (-2.53) (-1.80) Training 0.413*** 0.405*** (4.24) (3.86) Marriage 0.508*** 0.471*** (3.32) (2.93) Age 0.084*** 0.085** (2.69) (2.59) Age square -0.0008** -0.0008** (-2.23) (-2.15)
  • 36.
  • 37.