On Farmers’ Participation in Decision-making of Ecological Protection of Drinking Water Resources

On Farmers’ Participation in Decision-making of Ecological Protection of Drinking Water Resources

Jie Lin Chao Yu 

School of economics and management, Zhejiang University of Water Resources and Electric Power, Xuelin Street. No.583, Jianggan District, Xiasha University Town, Hangzhou, PR China, 310018

Esc Rennes School of business, 2 Rue Robert d'Arbrissel, 35065, Rennes, France

Corresponding Author Email: 
linjielinjie1@163.com; yc526009040@gmail.com
Page: 
1-25
|
DOI: 
https://doi.org/10.18280/mmc_c.780101
Received: 
15 March 2017
| |
Accepted: 
15 April 2017
| | Citation

OPEN ACCESS

Abstract: 

Farmers’ participation in ecological protection is the ultimate goal of the government's ecological compensation policy, and their willingness is a prerequisite for participation in ecological protection. This study mainly discusses the decision-making motive of farmers’ participation in ecological protection, and seeks for effective measures to prevent non-point source pollution of chemical fertilizer in water source protection area. In a creative manner, the author makes the famers’ willingness to cut back on fertilizer in the compensation scenario as the proxy variable of farmers’ willingness to participate in ecological protection of drinking water environment, and choose the ordered Logit regression model to analyze the causes of farmers’ differed willingness to cut back on fertilizer. The results show that income-related factors have a significant effect on farmers’ willingness to participate in non-point source pollution control, and those with concurrent business, high household income, high personal income, and high production efficiency are more likely to cut back more on fertilizer. Although the farmers’ awareness of fertilizer pollution is generally low, the farmers have a strong awareness of environmental issues and are very willing to participate in water environmental protection. In particular, farmers who have immediate family members living in the water supply areas pay more attention to water quality issues. In contrast, the farmers with higher willingness to receive compensation are more dependent on agricultural income, and their willingness to participate is very low.

Keywords: 

water source, ecological protection, farmers’ participation, farmer’s willingness, the ordered logit regression model

1. Introduction
2. Farmers’ Willingness in Cut Back on Fertilizer
3. Model and Variables
4. Model Estimation Results
5. Conclusion and Implications
Acknowledgments

Support for this research was provided by the Major Program of National Social Science Foundation of China (No. 14ZDA070), National Natural Science Foundation of China (No. 71373238), Specialized Research Fund for the Doctoral Program of Higher Education (No.20123326110004), Zhijiang Young Scholar Program of Social Science Planning of Zhejiang Province (No. 13ZJQN056YB), MOE (Ministry of Education in China) Project of Humanities and Social Sciences(No. 13YJA790047), the Natural Science Foundation of Zhejiang Province (No. LY14G030002), Modern trade research center Project of the key research center of MOE (Ministry of Education in China) Humanities and Social Sciences (No. 12JDSM04Z), the Natural Science Foundation of Zhejiang Province (No. LQ15G030002), Zhejiang philosophy and social science program (No.17NDJC165YB), National Statistical Science Research Project (No.2016LZ10).

  References

1. H.M. LI, J. Yu, Z.H. Fu, J. Wang, The research on environmental status and countermeasures of rural centralized drinking water source in Zhejiang, 2015, Journal of Anhui Agricultural Sciences, vol.43, no.13, pp.190-191.

2. X.J. Feng, C.F. Wei, D.T. Xie, J.N. Shao, P.C. Zhang, Effects of Farm Household's Management Behavior upon Nonpoint Pollution of Agriculture and Model Analysis, 2005, Chinese Agricultural Science Bulletin, vol.21, no.12, pp.354-358

3. J.V. Westra, K.W. Easter, K.D. Olson, Targeting nonpoint source pollution control: phosphorus in the Minnesota river basin, 2002, Journal of American Water Resources Association, no.38, pp.493-506.

4. N. Hanley, S. Banerjee, G.D. Lennox, P.R. Armsworth, How should we incentivize private landowners to "produce" more biodiversity? 2012, Oxford Review of Economic Policy, vol.28, no.1, pp.93-113.

5. A.P. Barnes, L. Toma, J. Willock, C. Hall, Comparing a ‘budge’ to a ‘nudge’: Farmer responses to voluntary and compulsory compliance in a water quality management regime, 2013, Journal of Rural Studies, pp.448-459.

6. G. Wiegleb, U. Broring, G. Choi,, Ecological restoration as precaution and not as restitutional compensation, 2013, Biodiversity and Conservation, vol.22, no.9, pp.1931-1948.

7. I.S. Chang, Y.X. Yang, J. Wu, Ecological compensation in China—Progress, problems and prospects, 2013, Advanced Materials Research, vol.726-731, pp.988-991.

8. A. Villarroya, J. Persson, J.G. Puig, Ecological compensation: from general guidance and expertise to specific proposals for road developments, 2014, Environmental Impact Assessment Review, vol.45, pp.54-62. 

9. B. Yu, L.Y. Xu, The Individual WTA Changing Analysis for Eco-Compensation Construction in Water Source Conservation Area, 2013, Advanced Materials Research, vol.779-780,  pp.1437-1440. 

10. P. Cooper, G.L. Poe, I.J. Bateman, The structure of motivation for contingent values: a case study of lake water quality improvement, 2004, Ecological Economics, vol.50, no.1, pp. 69-82.

11. K. Segerson, J. Wu, Nonpoint pollution control: Inducing first-best outcomes through the use of threats, 2006, Journal of Environmental Economics and Management, vol.51, no.2, pp.165-184.

12. R. Home, O. Balmer, I. Jahrl, M. Stolze, L. Pfiffner, Motivations for implementation of ecological compensation areas on Swiss lowland farms, 2014, Journal of Rural Studies, vol.34, no.4 pp.26-36.

13. N. Kumar, A.R. Quisumbing, Access, adoption, and diffusion: understanding the long-term impacts of improved vegetable and fish technologies in Bangladesh, 2011, Journal of Development Effectiveness, vol.3, no.2, pp.193-219.

14. R. Tiffin, K. Balcombe, The determinants of technology adoption by UK farmers using bayesian model averaging: The cases of organic production and computer usage, 2011, Australian Journal of Agricultural and Resource Economics, vol.55, no.4, pp.579-598.

15. A. Ngwira, F.H. Johnsen, J.B. Aune, M. Mekuria, C. Thierfelder, Adoption and extent of conservation agriculture practices among smallholder farmers in Malawi, 2014, Journal of Soil and Water Conservation, vol.69, no.2, pp.107-119.

16. S. Kim, J. Gillespie, K.P. Paudel, K.J. Moon, The effect of socioeconomic factors on the adoption of best management practices in beef cattle production, 2005, Journal of Soil and Water Conservation, vol.60, no.3, pp.111-120.

17. J.M. Cao, R.F. Hu, J.K. Huang, Agricultural technology extension and farmers' modification of new technology: Study on influence factors in farmers’ participating in technologies training and their willingness to adopt, 2005, China soft Science, no.6, pp.61-66. 

18. H.Y. Han, Z.X. Yang, Analysis on farmers' adoptive behavior of soil testing for formulated fertilization: Empirical evidence from the Xuecheng District of Zaozhuang City in Shandong Province, 2011, vol.44, no.23, China Agriculture Science, no.4, pp.4962-4970.

19. Z.G. Wang, C. Wang, X.Y. Xu, The mechanism for farmers'  cognizing and adopting creative agricultural production method:  An investigation based on fruit industry in four rural districts of Beijing City, 2010, China Rural Survey, no.4, pp.33-43.

20. D.J. Pannell, Economics, extension and the adoption of land conservation innovations in agriculture, 2013, International Journal of Social Economics, vol.26, no.7-9, pp.999-1014.

21. L. Pan, Researches on Willingness of Farmers Joining Professional Cooperatives—based on the questionnaire survey of Nanjing, 2011, Journal of Anhui Agricultural Sciences, vol.39, no.14, pp.8660-8663.

22. D.O. Staiger, J.H. Stock, Instrumental variables regression with weak instruments, 1994, Econometrica, vol.65, no.3, pp.557-586.

23. J.M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, 2001, The MIT Press, pp.472-479.