Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction
Abstract
:1. Introduction
2. Theoretical Analyses
2.1. Ecological Cognitive Bias
2.2. Farmers’ Satisfaction with Price Insurance
3. Research Area and Data Sources
4. Model Construction and Variables
4.1. Model Construction
4.1.1. Logit Model
4.1.2. Moderating Model
4.1.3. Double Machine Learning
4.2. Variables
4.2.1. Dependent Variable
4.2.2. Independent Variable
4.2.3. Moderating Variables
4.2.4. Control Variables
5. Results
5.1. Baseline Regression
5.2. Moderating Effect
5.3. Robustness Test
5.4. Heterogeneity Analysis
6. Discussion
7. Conclusions and Implications
7.1. Conclusions
7.2. Implications
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Items | Levels | Obs. | Frequency |
---|---|---|---|
Gender | Female | 54 | 15.65% |
Male | 291 | 84.35% | |
Age (years) | <40 | 46 | 13.34% |
41~50 | 96 | 27.84% | |
51~60 | 143 | 41.47% | |
>65 | 60 | 17.40% | |
Education | Elementary and below | 118 | 34.20% |
Junior high school | 145 | 42.03% | |
High school | 72 | 20.87% | |
University and above | 10 | 2.90% | |
Income (unit: 10,000 yuan) | 0~2 | 77 | 22.33% |
2~4 | 121 | 35.09% | |
4~6 | 62 | 17.98% | |
6~8 | 40 | 11.60% | |
>8 | 45 | 13.05% |
Variables | Definition | Min | Max | Mean |
---|---|---|---|---|
Dependent Variable | ||||
Pesticide reduction | Do natural rubber farmers reduce the use of pesticides? 0 = No; 1 = Yes | 0 | 1 | 0.713 |
Independent variable | ||||
Ecological cognitive bias | What impact do you think replacing forests with rubber trees has on the environment? 0 = negative; 1 = no impact, 2 = positive | 0 | 2 | 0.968 |
Moderating Variables | ||||
Satisfaction with the insurance coverage levels | How satisfied are you with the coverage levels of rubber price insurance? 1 = Very dissatisfied; 2 = Dissatisfied; 3 = Neutral; 4 = Satisfied; 5 = Very satisfied | 1 | 5 | 3.971 |
Satisfaction with the insurance service processes | How satisfied are you with the service process of rubber price insurance? 1 = Very dissatisfied; 2 = Dissatisfied; 3 = Neutral; 4 = Satisfied; 5 = Very satisfied | 1 | 5 | 4.017 |
Satisfaction with the insurance compensation outcomes | How satisfied are you with the compensation outcomes of rubber price insurance? 1 = Very dissatisfied; 2 = Dissatisfied; 3 = Neutral; 4 = Satisfied; 5 = Very satisfied | 1 | 5 | 3.942 |
Control variables | ||||
Gender | 1 = Male, 0 = female | 0 | 1 | 0.843 |
Age | Age (years) | 25 | 76 | 51.481 |
Education | Years of education | 1 | 4 | 1.925 |
Internet use | Do you use mobile apps such as TikTok? 0 = No; 1 = Yes | 0 | 1 | 0.217 |
Income | Respondent’s Household Income (unit: 10,000 Yuan) | 0 | 70 | 7.100 |
Party membership | Does the respondent’s family have a Communist Party member? 0 = No; 1 = Yes | 0 | 1 | 0.397 |
Years of production | Years the respondent has been involved in rubber production | 0 | 48 | 22.270 |
Proportion of the labor force | The proportion of family members involved in rubber production. | 0.167 | 1 | 0.612 |
Planted area | Area of rubber planted (unit: mu) | 3 | 150 | 28.732 |
Cultivation structural adjustments | To what extent have you adjusted your crop planting structure? 1 = Very little; 2 = Somewhat little; 3 = Neutral; 4 = Somewhat much; 5 = Very much | 1 | 5 | 1.786 |
Distance | Distance to the city government | 5 | 53 | 21.452 |
Management change | How has the daily management of your rubber plantation changed compared to before? 1 = Much worse than before; 2 = Worse than before; 3 = About the same; 4 = Better than before; 5 = Much better than before | 1 | 5 | 2.780 |
Rubber Tapping Chemicals | Average amount of rubber tapping chemicals used per mu | 0 | 0.893 | 0.036 |
Types of disasters | How many types of disasters (typhoons, cold waves, droughts, pests, etc.) did your rubber forest suffer from in 2020? | 0 | 4 | 0.649 |
Northern region | Northern region (Danzhou, Chengmai, and Baisha) = 1, other regions = 0 | 0 | 1 | 0.843 |
Variable | (1) | (2) |
---|---|---|
Ecological cognitive bias | −1.058 *** | −0.871 ** |
(0.30) | (0.36) | |
Gender | −0.373 | |
(0.39) | ||
Age | −0.007 | |
(0.02) | ||
Education | 0.317 * | |
(0.18) | ||
Internet use | −0.257 | |
(0.34) | ||
Income | 0.028 | |
(0.03) | ||
Party membership | −0.145 | |
(0.28) | ||
Years of production | 0.003 | |
(0.01) | ||
Proportion of the labor force | 1.045 * | |
(0.60) | ||
Planted area | −0.009 * | |
(0.00) | ||
Cultivation structural adjustments | 0.215 | |
(0.14) | ||
Rubber Tapping Chemicals | −8.013 *** | |
(2.03) | ||
Distance | 0.018 | |
(0.01) | ||
Management change | −0.309 * | |
(0.17) | ||
Types of disasters | −0.114 | |
(0.16) | ||
Northern region | 0.678 ** | |
(0.30) | ||
Constants | 1.973 *** | 1.757 |
(0.33) | (1.22) | |
N | 345 | 345 |
Pseudo R2 | 0.030 | 0.154 |
Variable | (1) | (2) | (3) |
---|---|---|---|
Ecological cognitive bias | −4.925 ** | −4.969 ** | −4.913 *** |
(1.97) | (1.96) | (1.84) | |
Satisfaction with the insurance coverage levels | −0.848 * | ||
(0.51) | |||
Ecological cognitive bias satisfaction with the insurance coverage levels | 0.988 ** | ||
(0.46) | |||
Satisfaction with the insurance service process | −0.907 * | ||
(0.51) | |||
Ecological cognitive bias satisfaction with the insurance service process | 0.998 ** | ||
(0.46) | |||
Satisfaction with the insurance compensation outcomes | −0.836 * | ||
(0.47) | |||
Ecological cognitive bias satisfaction with the insurance compensation outcomes | 0.989 ** | ||
(0.43) | |||
Control | Yes | Yes | Yes |
Constants | 5.532 *** | 5.769 *** | 5.569 *** |
(2.45) | (2.44) | (2.28) | |
N | 345 | 345 | 345 |
Pseudo R2 | 0.171 | 0.169 | 0.172 |
Variable | Double Machine Learning | OLS | ||
---|---|---|---|---|
Lasso Regression | Ridge Regression | Gradient Boosting | ||
(1) | (2) | (3) | (4) | |
Ecological cognitive bias | −0.160 *** | −0.169 *** | −0.100 ** | −0.133 ** |
(0.05) | (0.05) | (0.05) | (0.05) | |
Constants | 0.003 | −0.002 | 0.002 | 0.820 *** |
(0.02) | (0.02) | (0.02) | (0.20) | |
Control | Yes | Yes | Yes | Yes |
N | 345 | 345 | 345 | 345 |
R2 | —— | —— | —— | 0.174 |
Variable | Smaller Production Areas | Larger Production Areas | Fewer Types of Disaster | Multiple Types of Disaster | Few Experienced Farmers | Experienced Farmers |
---|---|---|---|---|---|---|
Ecological cognitive bias | −1.495 *** | 0.239 | −0.823 | −1.415 ** | −1.161 ** | −0.181 |
(0.51) | (0.62) | (0.59) | (0.59) | (0.51) | (0.63) | |
Constants | 2.496 | 0.148 | 3.461 | 0.213 | 1.059 | 1.445 |
(1.65) | (1.86) | (2.12) | (1.67) | (1.56) | (2.20) | |
Control | Yes | Yes | Yes | Yes | Yes | Yes |
N | 211 | 134 | 173 | 172 | 177 | 168 |
Pseudo R2 | 0.221 | 0.166 | 0.242 | 0.275 | 0.203 | 0.186 |
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Chen, D.; Liu, J.; Zhang, D.; Dong, Z.; Xu, T. Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction. Agriculture 2024, 14, 1633. https://doi.org/10.3390/agriculture14091633
Chen D, Liu J, Zhang D, Dong Z, Xu T. Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction. Agriculture. 2024; 14(9):1633. https://doi.org/10.3390/agriculture14091633
Chicago/Turabian StyleChen, Donghui, Jiyao Liu, Desheng Zhang, Zhixu Dong, and Tao Xu. 2024. "Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction" Agriculture 14, no. 9: 1633. https://doi.org/10.3390/agriculture14091633