Impacts and effects of government regulation on farmers’ responses to drought: A case study of North China Plain

doi:10.1007/s11442-017-1448-7

Abstract

Abstract:

Frequent extreme weather events like drought, etc. in the context of climate change present huge challenges to agricultural production. To find out if farmers have taken measures against them and identify governments’ impact on their response measures are the foundation of and key to further improving relevant policies and farmers’ responsiveness. Taking the North China Plain as an example, the study analyzes farmers’ responses to frequent climate change-induced drought, and assesses the impacts of governments’ early- warning, policy support and other factors on farmers’ responses based on questionnaire survey data and an econometric approach. The results show that: (1) Farmers are responsive to drought, and they are more likely to take measures as the degree of drought deepening. (2) Governments’ regulation affects farmers’ responses, although only part of its regulation measures has remarkable effects. Governments’ early-warning messages can increase the possibility of farmers’ responding to drought, however, only when they get the early-warning in all the processes including before, during, and after disasters can the effects be significant. Currently, as the primary channel through which early-warning information is released, television cannot change farmers’ behaviors significantly. Early-warning is most effective when spread via two or more types of channels. In addition, governments’ (especially town and village level institutions’) policy support has certain impacts on farmers’ responses to drought, yet with less prominent effects in disaster years than in normal years; to provide subsidies, as a regulation measure, can encourage farmers’ initiative a lot in adopting response measures, but most of the farmers haven’t got support from any institutions. Both the structure and strength of government regulation need to be improved. (3) Farmers with different conditions respond differently. Farmer households in irrigation areas, those whose farmland is lower fragmented, and those with numerous agricultural family members tend to take response measures. The study can provide scientific reference to the making of relevant regulation policies under the background of acidifications.

Key words: government regulation, drought, farmer households, response behaviors, North China Plain

Xiaoyun LI, Yu YANG, Yi LIU, Hui LIU. Impacts and effects of government regulation on farmers’ responses to drought: A case study of North China Plain[J].Journal of Geographical Sciences, 2017, 27(12): 1481-1498.

Figures/Tables 9

Figure 1

Table 1

Figure 2

Table 2

Figure 3

Table 3

Figure 4

Table 4

Table 5

The regression models of farmer households’ responses (Dependent variable: taking measures=1, not taking measures=0)"

Independent variables	Model 1		Model 2		Model 3
Independent variables	Coefficients	Exp (B)	Coefficients	Exp (B)	Coefficients	Exp (B)
Internal factors
Total number of family members	-0.063	0.939	-0.061	0.941	-0.062	0.940
Age of household head	-0.01	0.99	-0.01	0.99	-0.012	0.988
Education level of household head	0.028	1.028	0.026	1.026	0.018	1.018
Farmland area of the household (mu)	-0.051**	0.951	-0.049**	0.953	-0.040*	0.961
Farmland fragmentation level (mu/piece)	-0.119**	0.888	-0.119**	0.887	-0.082	0.922
Total value of house (ten thousand yuan)	0.004	1.004	0.004	1.004	0.006	1.006
Joined cooperation organization (Yes=1, No=0)	0.221	1.247	0.184	1.202	0.023	1.023
Family member is/are village cadre/s (Yes=1, No=0)	-0.329*	0.719	-0.344*	0.709	-0.523**	0.593
External factors
Topography (plain=1, others=0)	19.523	3.012	19.595	3.236	19.538	3.056
Inirrigation area (Yes=1, No=0)	0.727***	2.07	0.699***	2.012	0.809***	2.246
Average underground water level (m)	0.001	1.001	0.002	1.002	0.003	1.003
Policy factors
Received early-warning information (Yes=1, No=0)	0.412**	1.51
Only received pre-disaster warning			0.076	1.079
Only received post-disaster warning			0.216	1.241
Received both pre- and post-warning			0.615***	1.85
Only received warning via TV					-0.342	0.711
Only received warning via one channel apart from TV					0.499	1.646
Received warning via two or more channels					0.491**	1.633
The village organizes disaster prevention activities (Yes=1, No=0)	0.326*	1.386	0.321*	1.379	0.223	1.250
Received government supports (Yes=1, No=0)	0.374*	1.454
Supported by town-level or lower levels of institutions			0.667**	1.949
Only technical guidance					0.197	1.218
Only financial subsidies					2.057**	7.821
Only material subsidies					0.019	1.019
Only labor supports					0.744	2.105
Two or more types of supports					1.100	3.003
Supported by above-town level institutions			0.308	1.361
Disaster years (Yes=1, No=0)	0.410**	1.507	0.412**	1.51	0.426**	1.532
Constants	1.025	2.786	1.043	2.838	1.400**	4.057
Accuracy of prediction	79.10%		79.20%		78.80%
Degrees of freedom	15		18		21
Number of samples	1070		1070		936

Table 5

References 38

[1]	Carter M R, Little P D, Mogues Tet al., 2007. Poverty traps and natural disasters in Ethiopia and Honduras.World Development, 35(5): 835-856. doi: 10.1016/j.worlddev.2006.09.010
[2]	Chen H, Wang J X, Huang J K, 2014. Policy support, social capital, and farmers’ adaptation to drought in China.Global Environmental Change, 24: 193-202. doi: 10.1016/j.gloenvcha.2013.11.010
[3]	Cui Shenghui, Li Xuanqi, Li Yanget al., 2011. Review on adaptation in the perspective of global change.Progress in Geography, 30(9): 1088-1098. (in Chinese) doi: 10.11820/dlkxjz.2011.09.003
[4]	Dai A G, 2011. Drought under global warming: A review.Wiley Interdisciplinary Reviews Climate Change, 2(1): 45-65. doi: 10.1002/wcc.81
[5]	Deressa T T, Hassan R M, Ringler Cet al., 2009. Determinants of farmers’ choice of adaptation methods to climate change in the Nile Basin of Ethiopia.Global Environmental Change, 19(2): 248-255. doi: 10.1016/j.gloenvcha.2009.01.002
[6]	Falco S D, Veronesi M, Yesuf M, 2011. Does adaptation provide food security? A micro-perspective from Ethiopia.American Journal of Agricultural Economics, 93(3): 825-842. doi: 10.1093/ajae/aar006
[7]	Fei Yuhong, Zhang Zhaoji, Zhang Fengeet al., 2007. An analysis of the influence of human activity and climate change on water resources of the North China Plain.Acta Geoscientica Sinica, 28(6): 567-571. (in Chinese) doi: 10.1002/jrs.1570
[8]	He Bin, Wu Jianjun, Lv Aifeng, 2010. New advances on agricultural drought risk study.Progress in Geography, 29(5): 557-564. (in Chinese) doi: 10.11820/dlkxjz.2010.05.007
[9]	Holden S, Shiferaw B, 2004. Land degradation, drought and food security in a less-favored area in the Ethiopian highlands: A bio-economic model with market imperfections.Agricultural Economics, 30(1): 31-49. doi: 10.1016/j.agecon.2002.09.001
[10]	Huang Qingxu, Shi Peijun, He Chunyanget al., 2006. Modeling land use change dynamics under different aridification scenarios in Northern China.Acta Geographica Sinica, 61(12): 1299-1310. (in Chinese) doi: 10.1007/s11442-006-0415-5
[11]	IPCC (Intergovernmental Panel on Climate Change), 2007. Summary for policy-makers. In: Climate Change 2007: synthesis report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. London: Cambridge University Press.
[12]	IPCC (Intergovernmental Panel on Climate Change), 2012. Summary for policy makers. Food security and food production systems. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. London: Cambridge University Press.
[13]	Li Maosong, Li Sen, Li Yuhui, 2003. Studies on drought in the past 50 years in China.Chinese Journal of Agrometeorology, 24(1): 6-9. (in Chinese)
[14]	Li Xinzhou, Liu Xiaodong, Ma Zhuguo, 2004. Analysis on the drought characteristic in the main arid regions in the world since recent hundred-odd years.Arid Zone Research, 21(2): 97-103. (in Chinese) doi: 10.1007/BF02873097
[15]	Liu Huamin, Wang Lixin, Yang Jieet al., 2012. Influence of climate change on farming and grazing households and its adaptation: A case study in Uxin Banner in Inner Mongolia.Resources Sciences, 34(2): 248-255. (in Chinese) doi: 10.1007/s11783-011-0280-z
[16]	Liu Xiaoying, Lin Erda, 2004. Impact of climate change on water requirement of main crops in North China.Journal of Hydraulic Engineering, (2): 77-87. (in Chinese) doi: 10.3321/j.issn:0559-9350.2004.02.013
[17]	Liu Yansui, Liu Yu, Guo Liying, 2010. Impact of climatic change on agricultural production and response strategies in China. Chinese Journal of Eco-Agriculture, 18(4): 905-910. (in Chinese) doi: 10.3724/SP.J.1011.2010.00905
[18]	Lu Hongjian, Mo Xingguo, Hu Shi, 2010. Spatiotemporal variation characteristics of meteorological droughts in North China Plain during 1960-2009. Journal of Natural Disasters, 21(6): 72-82. (in Chinese) doi: 10.1007/s11783-011-0280-z
[19]	Ma Z G, Fu C B, 2006. Some evidence of drying trend over northern China from 1951 to 2004.Chinese Science Bulletin, 51(23): 2913-2925. doi: 10.1007/s11434-006-2159-0
[20]	Ministry of Water Resources (MWR), P.R. China, 2010. Bulletin of Flood and Drought Disaster in China. (in Chinese)
[21]	Pan Jiahua, Zheng Yan, 2010. Analytical framework and policy implications on adapting to climate change.China Population Resources and Environment, 20(10): 1-5. (in Chinese) doi: 10.1177/0956247807076726
[22]	Qin Dahe, 2014. Climate change science and sustainable development.Progress in Geography, 33(7): 874-883. (in Chinese)
[23]	Tian Z, Zhong H L, Sun L Xet al., 2014. Improving performance of agro-ecological zone (AEZ) modeling by cross-scale model coupling: An application to japonica rice production in Northeast China.Ecological Modelling, 290: 155-164. doi: 10.1016/j.ecolmodel.2013.11.020
[24]	Tu Qipu, Deng Ziwang, Zhou Xiaolan, 1999. Study of regional characteristics on mean annual temperature variation of near 117 years in China.Journal of Applied Meteorological Science, 10(Suppl.): 34-42. (in Chinese)
[25]	UNDP (United Nations Development Programme), 2004. A global report: Reducing disaster risk: A challenge for development, New York. Available at www.undp.org/cpr/bcpr.
[26]	Wang Y J, Huang J K, Wang J X, 2014. Household and community assets and farmers’ adaptation to extreme weather event: The case of drought in China.Journal of Integrative Agriculture, 13(4): 687-697. doi: 10.1016/S2095-3119(13)60697-8
[27]	Wang J X, Huang J K, Yang J, 2014. Overview of impacts of climate change and adaptation in China’s agriculture.Journal of Integrative Agriculture, 13(1): 1-17. doi: 10.1016/S2095-3119(13)60588-2
[28]	Wang J X, Mendelsohn R, Dinar Aet al., 2010. How Chinese farmers change crop choice to adapt to climate change.Climate Change Economics, 1(3): 167-185. doi: 10.1142/S2010007810000145
[29]	Wang J X, Yang Y, Huang J Ket al., 2015. Information provision, policy support, and farmers’ adaptive responses against drought: An empirical study in the North China Plain.Ecological Modelling, 318: 275-282. doi: 10.1016/j.ecolmodel.2014.12.013
[30]	Weng Zhenlin, 2008. The application research advance and review of the farmer theory. Issues in Agricultural Economy, (8): 93-99. (in Chinese)
[31]	World Bank, 2010. Economics of Adaptation to Climate Change: Synthesis Report..
[32]	Xiao D P, Tao F L, 2014. Contributions of cultivars, management and climate change to winter wheat yield in the North China Plain in the past three decades.European Journal of Agronomy, 52(1): 112-122. doi: 10.1016/j.eja.2013.09.020
[33]	Xiong Wei, Xu Yinlong, Lin Erda, 2005. The simulation of yield variability of winter wheat and its corresponding adaptation options under climate change.Chinese Agricultural Science Bulletin, 21(5): 380-385. (in Chinese)
[34]	Yang Jianying, Mei Xurong, Yan Changronget al., 2010. Study on spatial pattern of climatic resources in North China.Chinese Journal of Agrometeorology, 31(Suppl. 1): 1-5. (in Chinese)
[35]	Ye L M, Xiong W, Li Z Get al., 2013. Climate change impact on China food security in 2050.Agronomy for Sustainable Development, 33(2): 363-374. doi: 10.1007/s13593-012-0102-0
[36]	Zhang Guanghui, Lian Yingli, Liu Chunhuaet al., 2011. Situation and origin of water resources in short supply in North China Plain.Journal of Earth Sciences and Environment, 33(2): 172-176. (in Chinese) doi: 10.3969/j.issn.1672-6561.2011.02.012
[37]	Zhou Li, Zhou Shudong, 2012. Post-disaster adaptability to extreme weather events.China Population Resources and Environment, 22(4): 167-174. (in Chinese)
[38]	Zou Xukai, Ren Guoyu, Zhang Qiang, 2010. Droughts variations in China based on a compound index of meteorological drought.Climatic and Environmental Research, 15(4): 371-378. (in Chinese) doi: 10.3788/gzxb20103906.0998

Number of measures taken		Normal years		Disaster years
Number of measures taken		Number of farmer households taking measures	Percentage (%)	Number of farmer households taking measures	Percentage (%)
Number of farmer households not taking measures		133	24.63	93	17.22
Number of farmer households taking measures, among whom:		407	75.37	447	82.78
	1 measure	263	48.70	185	34.26
	2 measures	112	20.74	112	20.74
	3 measures	29	5.37	95	17.59
	4 measures	3	0.56	42	7.78
	5 measures	0	0.00	13	2.41
Total		540	100.00	540	100.00
Variance analysis	F value	9.011
Variance analysis	Sig.	0.003

Got information or not		Pre-disaster				Amid- and post-disaster
		Normal years		Disaster years		Normal years		Disaster years
		Number of farmer households	Percentage (%)	Number of farmer households	Percentage (%)	Number of farmer households	Percentage (%)	Number of farmer households	Percentage (%)
No		292	65.32	291	56.84	282	63.66	286	55.75
Yes		155	34.68	221	43.16	161	36.34	227	44.25
Number of channels	1	132	29.53	185	36.13	140	31.60	188	36.65
	2	21	4.70	33	6.45	19	4.29	34	6.63
	3	1	0.22	2	0.39	1	0.23	4	0.78
	4	1	0.22	1	0.20	1	0.23	1	0.19
Total		447	100	512	100	443	100	513	100

Being supported	Normal years		Disaster years
Being supported	Number of samples	Proportion (%)	Number of samples	Proportion (%)
No	406	76	403	75
Yes, by:	129	24	131	25
Village	32	23.40	37	26.60
Town	39	28.50	37	26.60
Upper-level institutions	63	46.00	62	44.60
Others	3	2.20	3	2.20
Total number of supports	137	100	139	100
Total number of samples	535	100	534	100

Being supported	Share of farmer households taking actions (%)
Being supported	Normal years	Disaster years
No	72.17	81.39
Yes	85.07	86.86
Technical guidance	100.00	87.50
Financial subsidies	85.29	86.96
Material subsidies	83.02	88.00
Labor support	100.00	100.00