Factors Influencing the Take-Up of Agricultural Insurance and the Entry into the Mutual Fund: A Case Study of the Czech Republic
Abstract
:1. Introduction
- Question 1: Which agricultural risks do farmers believe will become significantly more important in the future?
- Question 2: What incentives influence individual demand for agricultural insurance?
- Question 3: At what acreage does the chance of purchasing agricultural insurance increase?
- Question 4: Does the purchase of agricultural insurance influence farmers’ opinions about the conditions for indemnity from the upcoming fund for non-insurable risks?
2. Data and Methods
- Enterprises with 100% of their revenues from crop production (26.9%);
- Enterprises with more than 75% of their revenue from crop production (16.5%);
- Enterprises with more than 75% of their revenue from livestock production (20.8%);
- Enterprises with 100% of their revenue from livestock production (8%);
- Enterprises with mixed crop and livestock production (27.8%).
- Have you purchased agricultural insurance? (Yes = 1, No = 0);
- How should the indemnity payment be tied to commercial agricultural insurance (check only one option)?
- ○
- No conditions (indemnity from the fund should not be linked to the purchase of commercial agricultural insurance);
- ○
- Agricultural insurance of at least 50% of annual production (otherwise no indemnity);
- ○
- Agricultural insurance of at least 50% of annual production (otherwise indemnity is halved).
3. Results
3.1. Expected Changes in the Importance of Agricultural Risks
3.2. Incentives Influencing the Individual Demand for Agricultural Insurance
- The likelihood of taking out agricultural insurance (ceteris paribus) increases with the farm size;
- With higher distrust towards insurance companies, the likelihood of taking out agricultural insurance decreases (ceteris paribus);
- With a higher probability of suffering a loss of more than 20% of production, the likelihood of purchasing agricultural insurance increases (ceteris paribus);
- With a higher level of agreement with the statement that the decision to take out agricultural insurance is influenced by price, the likelihood of taking it out decreases (ceteris paribus);
- With a higher level of agreement with the statement that risks on the farm are managed according to a developed formal strategy, the likelihood of taking out agricultural insurance decreases (ceteris paribus).
3.3. Farmers’ Views on Upcoming Fund for Non-Insurable Risks (the Fund)
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Appendix B
- The Hosmer–Lemeshow test checks the fit of the model to the data. It tests the null hypothesis of a match between the values of the dependent variable and the expected values based on estimates of the probability that the explained variable takes the value 1. The test follows a chi-squared distribution under the assumption that the null hypothesis of model–data agreement is valid (Hosmer et al. 2013);
- Nagelkerke’s R2 expresses the strength of the association between the dependent variable and the predictors (Nagelkerke 1991);
- A classification table containing information on sensitivity and specificity. Sensitivity represents the proportion of participants who (a) had the characteristic of interest, and (b) were correctly predicted by the logistic regression equation to have the characteristic (correct classification of true positives). On the other hand, specificity represents the proportion of participants who (a) did not have the characteristic, and (b) were correctly predicted to not have that characteristic (correct classification of true negatives). Both sensitivity and specificity are measures of classification accuracy (Hatcher 2013);
- The area under the ROC curve was used to determine how well the predictors (the classification ability of the model) could predict the value of the binary variable. The higher the value, the better the model was, in this sense.
Appendix C
Appendix D
Appendix E
- Age categories: 18–40 years (reference category), 40–50 years, 50–60 years, 60+ years.
- Agricultural land area—intervals: <73 ha (reference category), 73 ha to <312 ha, 312 ha or more (interval boundaries were determined from the original numerical and non-normally distributed variables using the optimal binning procedure in IBM SPSS).
- Type of farming: predominantly crop production (reference category), predominantly livestock production, mixed agricultural production.
- Gender: female (reference category), male.
- Number of years in an executive position (managing director, director, chairman, etc.): up to and including 10 years (reference category), 11–20 years inclusive, more than 20 years.
- Education: primary and secondary (reference category), university graduates.
- Fruit growers: not engaged in fruit production (reference category), engaged in fruit production.
- Distrust of insurance companies: a numerical variable calculated as the average of five sub-statements. All questions had a Likert response scale (1 = Strongly Disagree, 2 = Somewhat Disagree, 3 = Don’t Know, 4 = Somewhat Agree, 5 = Strongly Agree). The reliability of the battery of questions was high (Cronbach’s alpha = 0.858). The higher the score was (arithmetic mean), the higher the respondent’s distrust of insurance companies. The set of statements from which the score was calculated consisted of the following statements:
- ○
- I don’t trust insurance companies for fear of delayed or incomplete indemnities.
- ○
- I don’t trust insurance companies because of complicated contracts or terms and conditions.
- ○
- I don’t trust insurance companies because of bad personal experiences.
- ○
- I don’t trust insurance companies because of my ignorance of insurance products.
- ○
- Insurance premium subsidies are not a direct support to farmers but an indirect support to insurance companies.
- Please indicate on a five-point scale how likely it is that a loss equal to or greater than 20% of average annual production will occur from a company-wide perspective (please check only one option): 1 = Almost impossible or very unlikely (1 to 20%), 2 = Extremely likely (21 to 40%), 3 = Ordinarily likely (41 to 60%), 4 = Very likely (61 to 80%), 5 = Highly likely to border on certain (81 to 100%).
- Who is actively involved in risk management in your company?
- ○
- Owner/shareholder/shareholders/shareholders (Yes = 1, No = 0).
- ○
- Director or CEO (Yes = 1, No/Function in the company independently does not exist = 0).
- ○
- Financial director, chief economist or accountant (Yes = 1, No/Function in the company alone does not exist = 0).
- ○
- Risk Management Specialist (Yes = 1, No/Function in the company alone does not exist = 0).
- ○
- Chief agronomist, head of the crop production center (Yes = 1, No/Function in the enterprise independently does not exist = 0).
- ○
- Chief zootechnician, head of the livestock production center (Yes = 1, No/Function on the holding alone does not exist = 0).
- ○
- Official employees (Yes = 1, No = 0).
- In addition to farm insurance, what risk management tools do you use on your farm? (Yes = 1, No = 0)
- ○
- Diversification within agricultural production (on-farm diversification).
- ○
- Diversification into associated production or secondary production (on-farm diversification).
- ○
- Off-farm income.
- ○
- Ad-hoc compensation of damages from the state budget in the event of a crisis.
- ○
- Use of the operating loan.
- ○
- Technological prevention tools.
- ○
- Anti-hail nets or other mechanical safeguard against weather hazards.
- ○
- Price hedging through contractual agreements.
- ○
- Price hedging through futures contracts on a commodity exchange.
- ○
- The safety net of a group of companies or a holding company.
- ○
- Creation of own financial reserves.
- ○
- Subsidy program to support recovery of arable and specialty crops.
- ○
- Marketing organization services.
- ○
- Cooperation with other farmers outside the marketing organization.
- ○
- Disease Fund Grant Programme.
- Please indicate on a point scale the extent to which you agree or disagree with the following statements. All questions have a Likert scale response (1 = Strongly Disagree, 2 = Somewhat Disagree, 3 = Don’t Know, 4 = Somewhat Agree, 5 = Strongly Agree). Rated statements:
- ○
- Risks are managed within the company according to a formal strategy.
- ○
- We actively cooperate with farmers’ associations/NGOs.
- ○
- The cost of insurance is high for our company due to potential insurance claims.
- ○
- Farmers need to anticipate and prepare for risks that are difficult to insure.
- ○
- The fund for non-insurable risks should guarantee the return of the invested money in case of crisis.
- ○
- Compensation by the mutual fund in case of higher average loss is fair.
- ○
- A significant reduction in compensation for uninsured farmers is fair.
- Please indicate what influences your decision to take out agricultural insurance. All questions have a Likert scale response (1 = Strongly Disagree, 2 = Somewhat Disagree, 3 = Don’t Know, 4 = Somewhat Agree, 5 = Strongly Agree). Rated statements:
- ○
- Price (premium).
- ○
- Average company loss ratio (the ratio between the indemnity and the premiums paid in the policy period).
- ○
- Prompt indemnity from the insurance company.
- ○
- Financial advisory services or insurance broker.
- ○
- The amount of the premium subsidy from the Ministry of Agriculture.
- ○
- Administrative burden of premium subsidy from the Ministry of Agriculture.
- ○
- Recommendations from friends or experience of other farmers.
- ○
- The portfolio of covered risks.
- ○
- Competitors’ offers.
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Risk | Average | SD 1 | SE 2 | t | p-Value |
---|---|---|---|---|---|
Hailstorm (present) | 1.28 | 1.392 | 0.099 | 7.489 | 0.000 |
Hailstorm (future) | 1.97 | 1.277 | 0.091 | ||
Fire (present) | 0.51 | 1.086 | 0.077 | 8.013 | 0.000 |
Fire (future) | 1.22 | 1.217 | 0.087 | ||
Windstorm (present) | 1.09 | 1.236 | 0.088 | 6.758 | 0.000 |
Windstorm (future) | 1.66 | 1.174 | 0.084 | ||
Flood (present) | 0.72 | 1.115 | 0.079 | 6.061 | 0.000 |
Flood (future) | 1.13 | 1.226 | 0.087 | ||
Soil flooding (present) | 0.64 | 1.057 | 0.075 | 6.171 | 0.000 |
Soil flooding (future) | 1.04 | 1.145 | 0.082 | ||
Freezing out (present) | 0.92 | 1.090 | 0.078 | 5.109 | 0.000 |
Freezing out (future) | 1.30 | 1.123 | 0.080 | ||
Spring frost (present) | 1.29 | 1.247 | 0.089 | 4.809 | 0.000 |
Spring frost (future) | 1.60 | 1.264 | 0.090 | ||
Frost on the vine (present) | 0.16 | 0.642 | 0.046 | 0.925 | 0.356 |
Frost on the vine (future) | 0.19 | 0.717 | 0.051 | ||
Drought (present) | 2.95 | 1.218 | 0.087 | −0.706 | 0.481 |
Drought (future) | 2.91 | 1.160 | 0.083 | ||
Grain sprouting (present) | 0.95 | 1.137 | 0.081 | 3.033 | 0.003 |
Grain sprouting (future) | 1.14 | 1.141 | 0.081 | ||
Harvest rainfall (present) | 1.92 | 1.297 | 0.092 | 5.006 | 0.000 |
Harvest rainfall (future) | 2.26 | 1.170 | 0.083 | ||
Diseases and pests (present) | 1.55 | 1.307 | 0.093 | 5.452 | 0.000 |
Diseases and pests (future) | 1.87 | 1.305 | 0.093 | ||
Voles (present) | 1.46 | 1.353 | 0.096 | 1.963 | 0.051 |
Voles (future) | 1.59 | 1.316 | 0.094 | ||
Animal disease (present) | 0.50 | 1.053 | 0.093 | 10.251 | 0.000 |
Animal disease (future) | 1.58 | 1.218 | 0.108 | ||
Acute poisoning (present) | 0.37 | 0.855 | 0.077 | 7.439 | 0.000 |
Acute poisoning (future) | 1.02 | 1.028 | 0.093 | ||
Natural disaster—animals (present) | 0.33 | 0.852 | 0.078 | 9.517 | 0.000 |
Natural disaster—animals (future) | 1.28 | 1.154 | 0.105 | ||
Overheating of animals (present) | 0.41 | 0.860 | 0.079 | 5.100 | 0.000 |
Overheating of animals (future) | 0.85 | 0.921 | 0.085 | ||
Non-infectious disease (present) | 0.72 | 1.052 | 0.094 | 7.144 | 0.000 |
Non-infectious disease (future) | 1.38 | 1.083 | 0.097 | ||
Animal injury (present) | 1.02 | 1.015 | 0.088 | 4.606 | 0.000 |
Animal injury (future) | 1.46 | 1.077 | 0.093 |
Model Variable | B | SE 1 | Wald | df | p-Value | Exp(B) 2 | 95% CI 3 for Exp(B) | |
---|---|---|---|---|---|---|---|---|
Area of agricultural land (farm size) | 29.411 | 2 | 0.000 | |||||
Area of agricultural land—interval (1) | 2.064 | 0.518 | 15.904 | 1 | 0.000 | 7.876 | 2.856 | 21.717 |
Area of agricultural land—interval (2) | 5.844 | 1.220 | 22.958 | 1 | 0.000 | 345.276 | 31.616 | 3770.723 |
Distrust of insurance companies | −0.569 | 0.239 | 5.658 | 1 | 0.017 | 0.566 | 0.354 | 0.905 |
Probability of losses exceeding 20% of production | 0.569 | 0.241 | 5.555 | 1 | 0.018 | 1.766 | 1.101 | 2.835 |
The price (premium) influences the probability of taking out an insurance policy | −0.628 | 0.237 | 7.020 | 1 | 0.008 | 0.534 | 0.335 | 0.849 |
Risks are managed in the company according to a formal strategy | −0.480 | 0.239 | 4.036 | 1 | 0.045 | 0.619 | 0.387 | 0.988 |
Intercept | 1.903 | 1.181 | 2.596 | 1 | 0.107 | 6.704 |
Have You Purchased Agricultural Insurance? | ||||
---|---|---|---|---|
How Should the Indemnity Payment Be Tied to Commercial Agricultural Insurance? | No | Yes | Total | |
No conditions (indemnity from the fund should not be linked to the purchase of commercial agricultural insurance) | Count | 83 | 44 | 127 |
% | 65.4% | 34.6% | 100% | |
Adjusted residual | 4.1 | −4.1 | ||
Agricultural insurance of at least 50% of annual production (otherwise no indemnity) | Count | 12 | 27 | 39 |
% | 30.8% | 69.2% | 100% | |
Adjusted residual | −3.3 | 3.3 | ||
Agricultural insurance of at least 50% of annual production (otherwise indemnity is halved) | Count | 15 | 22 | 37 |
% | 40.5% | 59.5% | 100% | |
Adjusted residual | −1.8 | 1.8 | ||
Total | Count | 110 | 93 | 203 |
% | 54.2% | 45.8% | 100% |
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Kislingerová, S.; Špička, J. Factors Influencing the Take-Up of Agricultural Insurance and the Entry into the Mutual Fund: A Case Study of the Czech Republic. J. Risk Financial Manag. 2022, 15, 366. https://doi.org/10.3390/jrfm15080366
Kislingerová S, Špička J. Factors Influencing the Take-Up of Agricultural Insurance and the Entry into the Mutual Fund: A Case Study of the Czech Republic. Journal of Risk and Financial Management. 2022; 15(8):366. https://doi.org/10.3390/jrfm15080366
Chicago/Turabian StyleKislingerová, Sofia, and Jindřich Špička. 2022. "Factors Influencing the Take-Up of Agricultural Insurance and the Entry into the Mutual Fund: A Case Study of the Czech Republic" Journal of Risk and Financial Management 15, no. 8: 366. https://doi.org/10.3390/jrfm15080366