Evaluating crop insurance as production risk management strategy
| dc.contributor.advisor | Willemse, B. J. | |
| dc.contributor.advisor | Grové, B. | |
| dc.contributor.author | Maré, Frikkie Alberts | |
| dc.date.accessioned | 2015-10-20T07:29:22Z | |
| dc.date.available | 2015-10-20T07:29:22Z | |
| dc.date.copyright | 2014-01 | |
| dc.date.issued | 2014-01 | |
| dc.date.submitted | 2014-01 | |
| dc.description.abstract | The primary objective of this study was to evaluate the effectiveness of Alternative Risk Transfer (ART) against Short-term Crop Hail Insurance as risk management strategies for crop hail insurance in two regions, Standerton and Lichtenburg. While Short-term Crop Hail Insurance has a fixed premium as percentage of the value of the crop, the decision maker can determine how much the contribution to the ART fund should be. Three different ART contributions had been analysed; ART 25 and ART 50 with respective contributions equal to 25 % and 50 % of the gross margin, and ART PC with a contribution equal to the premium of Short-term Crop Hail Insurance. A farm financial simulation model was developed to simulate the influence of hail damage and the different crop insurance policies on a maize enterprise with variable levels of yields and prices. Since the historical data of hail damage and the data on yields and prices did not match the same time series, the yield and price data were simulated with the procedure for estimating and simulating multivariate empirical (MVE) probability distributions. The risk efficiency of the different crop insurance options was analysed with stochastic efficiency with respect to a function (SERF). SERF expresses the certainty equivalents in monetary values and enables the calculation of the utility weighted risk premiums that are used to determine the benefit between alternatives. The results indicated that hail damage does occur in both the Standerton and Lichtenburg regions, but the impact thereof is not the same in each region. The negative impact of hail damage on the cumulative probability distribution of the Net Present Value (NPV) after interest and tax was larger in the Standerton than in the Lichtenburg. Decision makers in both regions were willing to pay for crop hail insurance options, but much more so in Standerton than in Lichtenburg. The difference between the costs and benefits of a crop hail insurance policy determines the net advantage (or disadvantage) that it will bring to financial position of the enterprise. The insurance options with the largest net benefit to the enterprise were ART PC in Lichtenburg and Short-term Crop Hail Insurance in Standerton. However, in Standerton ART PC emerged as the second-best option, which also makes it an option to consider. The last test for effectiveness on the different crop hail insurance options was the ability of the different options to provide continuous cover against hail risk. The differences between the claim pay-out of Shortterm Crop Hail Insurance and ART PC indicate the instances where the ART PC was too small to provide the necessary cover. While it can be concluded that ART PC is ineffective in Standerton, owing to its inability to provide continuous cover and the large differences in pay-outs, the same conclusion cannot necessarily be made for Lichtenburg. The differences in pay-outs are small enough to be counter for by the decision maker, especially because the enterprise never returns a negative NPV, even without insurance, while the financial impact on the enterprise and the maximum benefit of the policy provides a total financial advantage for the enterprise. In conclusion, it was found that both Short-term Crop Hail Insurance and ART might be effective measures for the mitigation of hail damage, as long as these products are implemented according to findings of proper research for the option that will provide the enterprise with the largest net benefit in the specific area it is situated. Since the model can easily be adapted to be applied not only on other field crops, but also on horticultural crops with different types of risk perils, it is suggested that the model might be applied to other sectors of agriculture to test the effectiveness of insurance on these sectors. | en_ZA |
| dc.description.sponsorship | National Research Foundation (NRF) | en_ZA |
| dc.description.sponsorship | Corporate Guarantee | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11660/1399 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | University of the Free State | en_ZA |
| dc.rights.holder | University of the Free State | en_ZA |
| dc.subject | Dissertation (M.Sc.Agric. (Agricultural Economics))--University of the Free State, 2014 | en_ZA |
| dc.subject | Crop insurance | en_ZA |
| dc.subject | Risk management | en_ZA |
| dc.subject | Agriculture -- Risk management | en_ZA |
| dc.subject | Utility Weighted Risk Premium | en_ZA |
| dc.subject | Certain Equivalent | en_ZA |
| dc.subject | SERF | en_ZA |
| dc.subject | MVE Distributions | en_ZA |
| dc.subject | Simulation Model | en_ZA |
| dc.subject | Alternative Risk Transfer | en_ZA |
| dc.subject | Risk | en_ZA |
| dc.subject | Insurance | en_ZA |
| dc.title | Evaluating crop insurance as production risk management strategy | en_ZA |
| dc.type | Dissertation | en_ZA |