Abstract
This chapter discusses the impact of the Grain for Green on the sources and level of income of farmers. While in many places agricultural incomes tended to dominate before the Grain for Green was introduced, by relieving farmers from agricultural work, the Grain for Green has had a considerable impacts on the economic structure and potential sources of income. With the Grain for Green the income structure diversified, to include agriculture, Grain for Green subsidies, the sale of Grain for Green-sponsored forest products, off-farm work in the villages of residence, and migration. In terms of the incomes from Grain for Green-induced land use changes, a distinction has to be made between economic trees, ecological trees, and grassland. Researchers agree that economic trees bring higher profits to the farmers, but even among economic trees, not all trees bring profits comparable to crops, once the subsidies are excluded from the calculation. Most researchers have looked at the benefits per hectare rather than the benefits per person-day.
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Notes
- 1.
The researchers collected information on households’ on-farm production activities on a plot by plot basis. For each plot, respondents reported the crop(s) grown, yield, total output and inputs in 1999 before the program started. The survey also asked for detailed information on each household’s total asset holdings and other income-earning activities from both on- and off-farm enterprises after the program began (Uchida et al. 2005).
- 2.
The survey was carried out in 2004 and included 313 randomly selected households from 13 villages.
- 3.
Liu and Zhang (2006) use data obtained from a unique panel survey conducted by the MOF in 17 counties of North China from 1998 to 2003, supplemented with village and county-level survey data. The 17 counties were randomly selected from 68 program-targeted counties in Hebei, Shanxi, and Inner Mongolia. A total of 188 households were sampled from the selected villages with a total of 927 observations.
- 4.
The data come from a household and village-level survey completed in 2003 by the Center for Chinese Agricultural Policy (CCAP), Chinese Academy of Sciences. The survey was conducted in the three provinces in which the GfG was first implemented, located at the upper reaches of the Yellow River Basin and the Yangtze River Basin: Shaanxi, Gansu, and Sichuan. Two counties per province, three townships per county, two participating villages per township, and 10 households per village were randomly selected, for a total of 36 village surveys and 360 household surveys (Xu et al. 2010).
- 5.
A questionnaire survey was adopted to investigate farm households in 2010. Villages were randomly chosen from each district in proportion to its area size. In total there were 33 valid samples. The study also employed other approaches to obtain data, including face-to-face interviews and informal discussions with local leaders/officials, group debate with local people and comments in official records about environmental policy. Based on Bossel (1999) social sustainability indicators, the social impact of the GfG project was assessed using the coordination coefficient in systems.
- 6.
Dunhua County covers an area of 11,957 km2 and has a total population of 480,000. According to the land use map of Dunhua County for the year 2000, forest lands covered 76.6 % of the territory, and farmlands 15.6 %. Slopes less than 5° accounted for 87 % of the total cropland area. Dunhua County has been the pilot site for several nationwide forest protection projects, including the NFPP (SFA 2005e). In 2000, the county was selected as a demonstration site for the GfG, and all of its 16 townships participate in the GfG program. Since 2000, 230,000 ha of land have been converted to forests (Wang and Maclaren 2011).
- 7.
Wang and Maclaren (2011) selected townships randomly. In each township, two villages were selected and within the two villages 20 respondents were chosen at random. The primary data came from 156 questionnaires and obtained information about income and changes in economic structure of the family before (1999) and after (2003) participating in the program, especially about economic crops, livestock raising and off-farm work. Besides the household survey, interviews with government officials of the Dunhua Forestry Bureau and other agencies were conducted to understand the historical and geographical context of society and the economy in Dunhua, and gain an overview of the progress of the program. Social and economic data of afforestation in Dunhua County were derived from statistical yearbooks, development reports by Dunhua governments, publications on local agriculture, soil, forest and historical development (Wang and Maclaren 2011).
- 8.
Incidentally, families who experienced a decrease in income were more likely to claim that the land conversion had been forced on them by government action. Peasant families with higher incomes and more economic resources to cope with change were associated with more positive perceptions of land use conversion (Wang and Maclaren 2011).
- 9.
Uchida et al. (2007) is based on surveys carried out in 2003, and commissioned by China’s MOF as part of their effort to evaluate the nation’s GfG program after the third year of implementation. By that time, this was the only existing dataset that included both participating and non-participating households. From the three provinces that had been participating in the GFG since 2000 (Sichuan, Shaanxi and Gansu provinces), two counties in each province and three townships in each County were randomly selected. In each township, two participating villages were selected, and within each village, ten households were randomly selected. There was at least one household participating in the program in every village. A total of 359 households were interviewed (Uchida et al. 2007). In two of the 36 villages, all of the households interviewed were participating households. In total, 75 % of the households interviewed participated in the GfG program. The household survey employed a sampling strategy designed to collect data on a random sample of households in the program area. Enumerators collected information on the household’s production activities on a plot-by-plot basis, as well as detailed information on each household’s total asset holdings, its demographic make-up, and other income earning activities from both on- and off-farm (Uchida et al. 2007).
- 10.
It is worth mentioning that, while the sample provinces in Uchida et al. (2005) and Xu et al. (2004) overlap, they studied different counties.
- 11.
Off-farm employment includes (a) employment in local non-agricultural activities and (b) off-village employment as migratory workers.
- 12.
At the household level, cluster sampling was used for the questionnaire survey in 20 villages from the four selected towns. 1,078 questionnaires were completed, covering both participating and non-participating households with a variety of detailed information on demographic characteristics, production and consumption activities, income and other livelihood, as well as some basic information on each family member. In particular, the questionnaire addressed households’ assets that did not change much even after participation in the program (Liang et al. 2012).
- 13.
The lower the Gini coefficient, the more equality there is. A Gini coefficient of 0 means that everybody has exactly the same income. A Gini coefficient of 1 means that all income is concentrated in one person.
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Delang, C.O., Yuan, Z. (2015). Participants’ Income Levels. In: China’s Grain for Green Program. Springer, Cham. https://doi.org/10.1007/978-3-319-11505-4_11
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