Can agricultural insurance guarantee farmer’s income: study on insurance failure and effectiveness based on situational dependence

doi:10.3969/j.issn.1004-1524.2022.10.24

Acta Agriculturae Zhejiangensis ›› 2022, Vol. 34 ›› Issue (10): 2296-2309.DOI: 10.3969/j.issn.1004-1524.2022.10.24

• Agricultural Economy and Development • Previous Articles Next Articles

Can agricultural insurance guarantee farmer’s income: study on insurance failure and effectiveness based on situational dependence

GAO Kang(), HE Puming

Hubei Rural Development Research Center, Yangtze University, Jingzhou 434023, Hubei, China

Received:2021-08-18 Online:2022-10-25 Published:2022-10-26

Abstract

Abstract:

Based on the provincial panel data from 2006 to 2018, the fixed effect model and threshold model were used to explore the effect of agricultural insurance on farmer’s income under disaster impact. It was shown that, under the impact of disasters, agricultural insurance was effective for the guarantee of farmer’s operation revenue, but ineffective for the guarantee of total income. The reason lay in the substitution of traditional risk-averse tools of agricultural insurance on farmer’s total income. The effectiveness of agricultural insurance on farmer’s total income was dependent on the degree of agricultural operation and the conditions of non-agricultural employment. The development level of agricultural insurance could better guarantee farmer’s income than the scale of agricultural insurance, but the threshold effect span was as high as 9.7 times. Marginal prediction results validated the above conclusion, and also showed that in the higher development stage, agricultural insurance might have a positive impact on farmer’s income, but there would not be a macro income increase effect. Therefore, measures should be taken to improve the precision guarantee effect of agricultural insurance in China by clarifying the objective of agricultural insurance policy, optimizing the insurance promotion according to local conditions, and exploring multiple risk avoidance paths.

Key words: agricultural insurance, farmer’s income, risk assurance, moderating effects

CLC Number:

GAO Kang, HE Puming. Can agricultural insurance guarantee farmer’s income: study on insurance failure and effectiveness based on situational dependence[J]. Acta Agriculturae Zhejiangensis, 2022, 34(10): 2296-2309.

Figures/Tables 10

Fig.1 Logical framework of agricultural insurance’s impact on farmer’s income

Table 1 Descriptive statistics of variables

变量类型 Variable type	变量名称 Variable name	变量符号 Variable symbol	样本量 Sample size	均值 Mean	标准差 Standard deviation
被解释变量	总收入Total income/yuan	Y₁	403	8 916.78	5 024.04
Explained variable	经营收入Operation revenue/yuan	Y₂	403	3 489.92	1 532.25
解释变量	受灾面积Damage area/(10³ hm²)	R₁	403	1 030.65	995.23
Explanatory variable	成灾面积Disaster area/(10³ hm²)	R₂	403	518.19	553.45
	绝收面积No harvest area/(10³ hm²)	R₃	403	114.02	146.07
调节变量	保费收入Premium income/(10⁶ yuan)	S₁	403	829.77	948.83
Moderator variable	保险赔付Insurance payout/(10⁶ yuan)	S₂	403	521.35	662.99
	保费收入水平Premium income level/yuan	S₃	403	58.98	72.91
	保险赔付水平Insurance payout level/yuan	S₄	403	38.67	54.30
	工资收入Salary income/yuan	S₅	403	4 351.56	3 903.97
	转移收入Transfer income/yuan	S₆	403	1 553.01	13 99.86
控制变量	城市化水平Urbanization level/%	C₁	403	53.16	14.39
Control variable	产业结构Industrial structure/%	C₂	403	10.70	5.52
	城乡收入比Urban-rural income ratio	C₃	403	2.85	0.54
	财政支农强度Financial support for agriculture	C₄	403	0.108	0.033
	政策虚拟变量Policy dummy variable	C₅	403	0.308	0.462

Fig.2 Fitting plot of relationship between agricultural disaster and farmer’s income a, Impact of agricultural disasters on farmer’s income for all samples; b, Impact of agricultural disasters on farmer’s income at levels below the average of premium income of agricultural insurance; c, Impact of agricultural disasters on farmer’s income at levels above the average of premium income of agricultural insurance.

Table 2 Baseline regression result

变量 Variable	模型1 Model 1	模型2 Model 2	模型3 Model 3	模型4 Model 4	模型5 Model 5	模型6 Model 6
R₁	-0.023 1^** (0.011 8)	-0.013 8^** (0.005 7)	-0.017 4^** (0.007 8)	-0.019 5 (0.012 4)	-0.002 7 (0.002 7)	-0.003 4 (0.003 6)
S₁	0.026 5^*** (0.007 6)	-0.001 6 (0.010 3)	-0.009 8 (0.013 0)	0.047 4^*** (0.010 5)	0.000 5 (0.002 3)	-0.000 3 (0.004 0)
R₁×S₁	—	—	0.011 0^*** (0.003 2)	—	—	-0.000 6 (0.001 3)
C₁	0.570 2 (1.200 4)	4.114 2^** (2.023 2)	5.596 4^*** (1.159 2)	-4.752 8^** (1.753 9)	1.233 4^*** (0.288 6)	0.539 5 (0.462 4)
C₂	-0.354 7^*** (0.068 6)	-0.107 8 (0.127 0)	-0.166 0^** (0.069 1)	-0.447 6^** (0.188 4)	-0.007 8 (0.017 9)	-0.055 5^* (0.031 1)
C₃	-1.365 9^*** (0.180 3)	-0.715 1^** (0.306 0)	-0.792 0^*** (0.173 1)	-1.646 0^*** (0.390 3)	-0.653 3^*** (0.046 0)	-0.665 1^*** (0.073 3)
C₄	3.452 0^*** (0.516 0)	1.555 2^* (0.856 0)	1.596 6^*** (0.565 4)	4.155 9^*** (0.907 8)	0.353 9** (0.151 7)	0.421 6^* (0.228 4)
C₅	0.088 6^*** (0.020 2)	0.705 7^*** (0.196 1)	0.765 7^*** (0.076 7)	0.111 1^*** (0.037 0)	1.169 5^*** (0.020 0)	1.120 2^*** (0.035 3)
$C 12$	-0.031 0 (0.162 4)	-0.506 3 (0.311 1)	-0.732 3^*** (0.161 7)	0.809 8^*** (0.249 7)	-0.107 8^*** (0.039 6)	-0.003 7 (0.064 7)
常数项Constant	7.566 6^*** (2.267 4)	0.505 5 (3.186 8)	-1.698 1 (2.129 6)	17.635 8^*** (3.025 1)	5.990 3^*** (0.546 2)	7.227 4^*** (0.803 4)
Hausman检验 Hausman test	87.49^***	210.76^***	327.44^***	124.54^***	50.24^***	51.62^***
校正决定系数Adjusted R²	0.879 1	0.912 3	0.915 1	0.947 3	0.996 7	0.996 6

Table 2 Baseline regression result

变量 Variable	模型1 Model 1	模型2 Model 2	模型3 Model 3	模型4 Model 4	模型5 Model 5	模型6 Model 6
R₁	-0.023 1^** (0.011 8)	-0.013 8^** (0.005 7)	-0.017 4^** (0.007 8)	-0.019 5 (0.012 4)	-0.002 7 (0.002 7)	-0.003 4 (0.003 6)
S₁	0.026 5^*** (0.007 6)	-0.001 6 (0.010 3)	-0.009 8 (0.013 0)	0.047 4^*** (0.010 5)	0.000 5 (0.002 3)	-0.000 3 (0.004 0)
R₁×S₁	—	—	0.011 0^*** (0.003 2)	—	—	-0.000 6 (0.001 3)
C₁	0.570 2 (1.200 4)	4.114 2^** (2.023 2)	5.596 4^*** (1.159 2)	-4.752 8^** (1.753 9)	1.233 4^*** (0.288 6)	0.539 5 (0.462 4)
C₂	-0.354 7^*** (0.068 6)	-0.107 8 (0.127 0)	-0.166 0^** (0.069 1)	-0.447 6^** (0.188 4)	-0.007 8 (0.017 9)	-0.055 5^* (0.031 1)
C₃	-1.365 9^*** (0.180 3)	-0.715 1^** (0.306 0)	-0.792 0^*** (0.173 1)	-1.646 0^*** (0.390 3)	-0.653 3^*** (0.046 0)	-0.665 1^*** (0.073 3)
C₄	3.452 0^*** (0.516 0)	1.555 2^* (0.856 0)	1.596 6^*** (0.565 4)	4.155 9^*** (0.907 8)	0.353 9** (0.151 7)	0.421 6^* (0.228 4)
C₅	0.088 6^*** (0.020 2)	0.705 7^*** (0.196 1)	0.765 7^*** (0.076 7)	0.111 1^*** (0.037 0)	1.169 5^*** (0.020 0)	1.120 2^*** (0.035 3)
$C 12$	-0.031 0 (0.162 4)	-0.506 3 (0.311 1)	-0.732 3^*** (0.161 7)	0.809 8^*** (0.249 7)	-0.107 8^*** (0.039 6)	-0.003 7 (0.064 7)
常数项Constant	7.566 6^*** (2.267 4)	0.505 5 (3.186 8)	-1.698 1 (2.129 6)	17.635 8^*** (3.025 1)	5.990 3^*** (0.546 2)	7.227 4^*** (0.803 4)
Hausman检验 Hausman test	87.49^***	210.76^***	327.44^***	124.54^***	50.24^***	51.62^***
校正决定系数Adjusted R²	0.879 1	0.912 3	0.915 1	0.947 3	0.996 7	0.996 6

Table 3 Robustness test result based on substitution of explanatory variables

变量Variable	Y₂	Y₂	Y₂	Y₁	Y₁	Y₁
R₂	-0.011 7^* (0.006 1)	-0.012 0 (0.009 6)	—	-0.002 1 (0.002 5)	-0.002 1 (0.003 0)	—
R₃	-0.014 6^** (0.006 0)	—	-0.013 5^* (0.008 0)	-0.003 0 (0.002 1)	—	-0.002 9 (0.002 5)
S₁	—	-0.007 3 (0.008 9)	-0.007 7^** (0.008 7)	—	0.000 2 (0.003 4)	0.000 2 (0.003 3)
R₂×S₁	—	0.008 4^*** (0.002 9)	—	—	0.000 4 (0.001 3)	—
R₃×S₁	—	—	0.010 2^*** (0.002 7)	—	—	0.000 5 (0.001 2)

Table 4 Robustness test result based on substitution of moderator variables

变量Variable	Y₂	Y₂	Y₂	Y₁	Y₁	Y₁
R₁	-0.016 5^** (0.007 6)	-0.023 7^** (0.009 2)	-0.022 1^** (0.008 5)	-0.002 5 (0.003 0)	-0.003 2 (0.003 3)	-0.006 0^* (0.003 3)
S₂	-0.007 4 (0.011 6)	—	—	-0.000 3 (0.003 2)	—	—
S₃	—	-0.009 9 (0.071 5)	—	—	0.044 6 (0.020 7)	—
S₄	—	—	-0.018 4^** (0.099 4)	—	—	0.057 8^** (0.026 0)
R₁×S₂	0.010 0^*** (0.002 9)	—	—	-0.000 4 (0.001 3)	—	—
R₁×S₃	—	0.059 1^** (0.024 1)	—	—	0.002 2 (0.004 9)	—
R₁×S₄	—	—	0.073 6^** (0.030 5)	—	—	0.003 8 (0.005 3)

Table 5 Robustness test result based on threshold estimation

变量与指标 Variables and indexes	模型7 Model 7	模型8 Model 8	模型9 Model 9	模型10 Model 10
R₁(S≤ϕ₁)	-0.068^***(0.012)	-0.069^***(0.011)	-0.079^***(0.010)	-0.080^***(0.011)
R₁(ϕ₁<S≤ϕ₁)	-0.047^***(0.011)	-0.050^***(0.011)	-0.058^***(0.010)	-0.063^***(0.012)
R₁(S>ϕ₂)	-0.031^**(0.012)	-0.040^***(0.012)	-0.046^***(0.011)	-0.051^***(0.011)
校正决定系数Adjusted R²	0.861 1	0.860 0	0.858 5	0.860 8
门槛范围Threshold range	[0.55,8.48]	[0.05,8.37]	[0.01,5.98]	[0.01,6.11]
ϕ₁	4.07[3.99,4.08]	3.45[3.27,3.47]	0.56[0.45,0.63]	0.44[0.37,0.45]
ϕ₂	6.68[6.66,6.69]	6.79[6.76,6.82]	4.19[4.15,4.19]	4.27[4.22,4.28]
单一门限Single threshold	35.86^**	28.25^**	32.10^**	31.13^*
双重门限Double threshold	29.63^**	32.27^***	26.08^*	31.92^**
三重门限Triple threshold	14.00	10.23	14.56	11.34

Table 6 Estimation result of instrumental variable method

变量	Y₂				Y₁
变量	模型11 Model 11	模型12 Model 12	模型13 Model 13	模型14 Model 14	模型15 Model 15	模型16 Model 16
R₁×S₁	0.050 5^***	0.049 1^***	0.031 9^***	0.029 9^***	-0.027 0	-0.026 4
	(0.008 2)	(0.008 1)	(0.008 9)	(0.008 9)	(0.016 4)	(0.016 5)
R₁	-0.037 6^**	-0.035 7^**	-0.014 2	-0.014 3	-0.019 7^*	-0.021 1^*
	(0.014 7)	(0.014 5)	(0.014 0)	(0.013 8)	(0.011 4)	(0.011 4)
S₁	-0.000 9	0.000 1	0.011 8	0.014 0	0.028 8	0.028 5
	(0.016 0)	(0.016 0)	(0.012 5)	(0.012 4)	(0.049 6)	(0.042 0)
F	32.74	32.74	52.92	52.92	32.74	52.92
Hansen	0.576 6	0.576 6	0.415 3	0.415 3	0.206 1	0.609 4

Table 7 Estimation of heterogeneous effect of agricultural insurance on farmers’ income

变量 Variable	Y₂	Y₁
变量 Variable	Y₂	全样本 All samples	全样本 All samples	西部地区 West area	粮食主产区 Main grain-pro areas	高作物播种区 H-crop planting area
R₁×S₅	—	0.0043^**	—	-0.0027	—	—
		(0.0021)		(0.0029)
R₁×S₆	—	—	0.0013	—	—	—
			(0.0013)
R₁×S₁	—	—	—	—	0.0054^**	0.0063^**
					(0.0024)	(0.0026)
R₁	—	-0.0420^**	-0.0242^*	-0.0058^*	-0.0404^**	-0.0110^**
		(0.0179)	(0.0146)	(0.0035)	(0.0179)	(0.0052)
S₅	-0.1072^**	0.0807^***	—	0.0681^***	—	—
	(0.0452)	(0.0169)		(0.0138)
S₆	—	—	0.0640^***	—	—	—
			(0.0175)
S₁	—	—	—	—	-0.0462^**	-0.0158^***
					(0.0193)	(0.0050)

Fig.3 Marginal prediction of moderating effect of agricultural insurance The mean value and its 95% confidence interval were shown in the above figures. a, Marginal effect of disasters on operation revenue under different premium income; b, Marginal effect of disasters on operation revenue under different premium income level; c, Marginal effect of disasters on total income under different premium income; d, Marginal effect of disasters on total income under different salary income; e, In the main grain-pro areas, marginal effect of disasters on total income under different premium income; f, In the H-crop planting area, marginal effect of disasters on total income under different premium income. The main grain-pro areas consisted of Heilongjiang, Henan, Shandong, Sichuan, Jiangsu, Hebei, Jilin, Anhui, Hunan, Hubei, Inner Mongolia, Jiangxi and Liaoning. H-crop planting area referred to the areas with higher crop sown areas than the average crop sown area of all samples.

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Can agricultural insurance guarantee farmer’s income: study on insurance failure and effectiveness based on situational dependence

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