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The role of social capital for farmers’ climate change adaptation in Lancang River basin in China

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Abstract

This paper distinguishes between bridging and bonding social capital to assess their roles for individual farmers’ adaptation strategies taken through technology adoption. Based on primary data collected in Langcang River (LCR) basin area in southwestern China, the paper finds: (1) adaptation measures have been widely taken by surveyed households, but non-infrastructure-based measures are more prevalent than infrastructure-based measures and (2) surveyed households have strong social capital while having weak bridging social capital. Their bonding social capital has significantly positive relationship with their adaptation decisions, but bridging social capital does not have such statistically significant relationship. It recommends that the governments contemplate carefully how to help the poor to get a good combination of bonding and bridging social capital when designing policies to help the rural poor to improve their long-term adaptive capacity and achieve sustainable rural development.

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Notes

  1. Zilberman et al. (2012) defines adoption as a change in practice (e.g., farming practice) or technology (e.g., new crop varieties and drip irrigation technology) used by individuals or communities.

  2. Empirical evidence has shown that social networks have positive impact on adoption of weather index insurance (Cai et al. 2011) and an inverse-U-shaped relationship exists between social network and adoption of a new crop (Bandiera and Rasul 2006).

  3. LCR basin lies between latitudes 10° and 34° N and longitudes 94° and 107° E. It is divided into two parts, one in Qinghai-Tibet Plateau and the other in Yunnan Province. In Qinghai-Tibet part of LCR basin, the population is very sparse, so this paper does not survey Qinghai-Tibet part of LCR basin.

  4. Yunnan Province, like other regions in Mekong River basin, is the home to many rural poor. It hosts 73 counties (12%) of 592 national economically deprived counties (also called national-level poverty-stricken counties) listed by the Leading Group Office of Poverty Relief and Development under China’s State Council.

  5. Counties near the River and off the River might have different levels of vulnerability to climate change impacts. For example, counties near to the River may be more vulnerable to floods while those off the River and up to the mountains may be vulnerable to droughts. They may also have quite different livelihood means. Thus, we purposively choose two counties at the different locations, one near the River and the other away from the River.

  6. See Neyman (1934) for method comparison and Ritchie et al. (2003) for the sampling design.

  7. The eight villages are Mangzhuan, Pingzhang, Qiande, Taiping, Sijiaotian, Yanjiang, and Gongyu.

  8. We use an exchange rate of US$1 = RMB 6.91 yuan, the exchange rate in December of 2016.

  9. Villages surveyed are administrative villages. In the context of rural China, one administrative village usually involve several sub-units, called natural villages.

  10. The population density in the surveyed villages is quite consistent with the spatial distribution of population density in Lancang-Mekong River basin area studied by You et al. (2010).

  11. Technology adoption can be measured with discrete adoption choice of a particular technology (or class of technology) or an incremental value (such as the extent of adoption) (Zilberman et al. 2012).

  12. We thank our anonymous reviewer to point out the importance of making some discussions and clarifications on this point.

  13. Grootaert et al. (2004) introduces some integrated tools for measuring social capital in developing countries.

  14. In our case for example, the average distance of two natural villages at the two farthest ends is about 15 km.

  15. Some may argue that the number of fellow villagers’ phone numbers kept in the respondent’s phone directories does not necessarily mean that they have actual communication in the adoption process. However, a higher number of fellow villagers’ phone numbers kept in the respondent’s phone directories at least indicates a higher probability of communicating with their fellow villagers. So it is a reasonable proxy for measuring connections among fellow villagers within the same community.

  16. “Guanxi” refers to the personal network in Chinese culture. It is used as substitutes for formal institutional support. Numerous case studies document that Chinese firms can benefit through their personal connections with government officials to solve the broad range of the problems (e.g., Yan 1996; Park and Luo 2001). It also plays an important role on farmers’ market participation (Lu et al. 2010).

  17. Ideally, we could have divided our samples into four subsamples using 25th, 50th, and 75th percentiles of income as cut-off lines. However, given a total sample size of 96, we use the median (50th percentile) income as the cut-off line to divide our sample into two subsamples.

  18. Readers who are interested in taking a look at OLS results, the results are available upon the request. For the Poisson model specification, we only run the regression with the full set of social capital variables, i.e., two alternative measures of the bonding social capital and one proxy of the bridging social capital.

  19. One reviewer points out that our measure of trust, i.e., whether or not the respondents had frequently lent their farming tools to their fellow villagers in the past, may be determined by their possession of the farming tools. Based on our survey measure that may reflect the respondents’ possession of farming tools, i.e., the family’s expenditure on purchasing farming tools in the year before our surveys (2013), we check whether our measure of trust is strongly correlated with the family’s expenditure on purchasing farming tools in the previous year and find no significant correlation between the two variables. We also conduct two-sample t test and Wilcoxon rank-sum (Mann-Whitney) test, respectively, to check whether the family’s expenditure on purchasing farming tools in the previous year is significantly different between the group who lent the farming tools and that who did not lend the farming tools. Both tests show no statistically significant difference between the two groups. Nonetheless, we still have to admit that our survey measure of trust may not be perfect.

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Authors and Affiliations

  1. School of Environment and Natural Resources, Renmin University of China, Beijing, 100872, China

    Yazhen Gong, Hao Li, Moon Parks, Jun Pang & Charlotte de Fraiture

Authors
  1. Yazhen Gong
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  2. Hao Li
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  3. Moon Parks
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  4. Jun Pang
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  5. Charlotte de Fraiture
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Correspondence to Yazhen Gong or Jun Pang.

Additional information

This article is part of a special issue on “climatic change and development in the Mekong River basin” edited by Jaap Evers and Assela Pathirana

Jun Pang: Facilitating field surveys and working with Yazhen Gong on data encoding and cleaning.

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Gong, Y., Li, H., Parks, M. et al. The role of social capital for farmers’ climate change adaptation in Lancang River basin in China. Climatic Change 149, 75–89 (2018). https://doi.org/10.1007/s10584-017-2057-2

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