A non-parametric approach to determine an efficient premium for drought insurance

Insurance to deal with prolonged drought periods in rural Africa requires a practical method to estimate accurate premium values that minimize economic losses. We use non-parametric methods to determine the risk non-neutral insurer’s premium for drought insurance on rain-fed crops. Premium values a...

Full description

Bibliographic Details
Main Authors: Manitra A. Rakotoarisoa, Harry P. Mapp
Format: Article
Language:English
Published: The Academic Research and Publishing UG (i. G.) (AR&P) LLC 2023-03-01
Series:SocioEconomic Challenges
Subjects:
Online Access:https://armgpublishing.com/wp-content/uploads/2023/04/1_SEC_1_2023-2.pdf
_version_ 1797696101631918080
author Manitra A. Rakotoarisoa
Harry P. Mapp
author_facet Manitra A. Rakotoarisoa
Harry P. Mapp
author_sort Manitra A. Rakotoarisoa
collection DOAJ
description Insurance to deal with prolonged drought periods in rural Africa requires a practical method to estimate accurate premium values that minimize economic losses. We use non-parametric methods to determine the risk non-neutral insurer’s premium for drought insurance on rain-fed crops. Premium values are estimated on the basis of percentage of the expected yield losses over the potential yields. Expected yield losses are estimated based on data on the levels of rainfall, potential evapotranspiration and water-holding capacity of the soil, and water requirement of the crop. Maize crop in West Kenya, and rice crop in the Central High Plains of Madagascar are taken as case studies. To check if farmer’s choice of starting seasons affects the expected yields and the values of premium, we employ forecasted yields for two different sowing dates (October vs. November) for maize, and two different transplantation dates (November vs. December) for rice. The mean-variance (E-V), the First-Degree Stochastic Dominance (FSD), and the Second-Degree Stochastic Dominance (SSD) efficiency criteria are used to rank each pair of distributions. Results show that an insurer for maize production in Western Kenya would require a premium value between 43 and 55% of the potential yields to fully cover the loss caused by lack of rainfall. Under E-V and FSD, the two yield distributions cannot be ranked, but under SSD the yield distribution of the October-sown maize dominates that of November. For lowland rice in the Central High Plains of Madagascar, all three efficiency criteria indicate that the yield distribution of the December-transplanted rice dominates that of November and the premium values are less than 4 % of the potential yields.
first_indexed 2024-03-12T03:22:11Z
format Article
id doaj.art-1772dc9ce994444296d52805f4d5bb1a
institution Directory Open Access Journal
issn 2520-6621
2520-6214
language English
last_indexed 2024-03-12T03:22:11Z
publishDate 2023-03-01
publisher The Academic Research and Publishing UG (i. G.) (AR&P) LLC
record_format Article
series SocioEconomic Challenges
spelling doaj.art-1772dc9ce994444296d52805f4d5bb1a2023-09-03T13:52:34ZengThe Academic Research and Publishing UG (i. G.) (AR&P) LLCSocioEconomic Challenges2520-66212520-62142023-03-017111410.21272/sec.7(1).1-14.2023A non-parametric approach to determine an efficient premium for drought insuranceManitra A. Rakotoarisoa0https://orcid.org/0000-0002-5312-7350Harry P. Mapp1Economist, International Economics, Infinite-Sum Modeling LLC, USAProfessor (late), Department of Agricultural Economics, Oklahoma State University, USAInsurance to deal with prolonged drought periods in rural Africa requires a practical method to estimate accurate premium values that minimize economic losses. We use non-parametric methods to determine the risk non-neutral insurer’s premium for drought insurance on rain-fed crops. Premium values are estimated on the basis of percentage of the expected yield losses over the potential yields. Expected yield losses are estimated based on data on the levels of rainfall, potential evapotranspiration and water-holding capacity of the soil, and water requirement of the crop. Maize crop in West Kenya, and rice crop in the Central High Plains of Madagascar are taken as case studies. To check if farmer’s choice of starting seasons affects the expected yields and the values of premium, we employ forecasted yields for two different sowing dates (October vs. November) for maize, and two different transplantation dates (November vs. December) for rice. The mean-variance (E-V), the First-Degree Stochastic Dominance (FSD), and the Second-Degree Stochastic Dominance (SSD) efficiency criteria are used to rank each pair of distributions. Results show that an insurer for maize production in Western Kenya would require a premium value between 43 and 55% of the potential yields to fully cover the loss caused by lack of rainfall. Under E-V and FSD, the two yield distributions cannot be ranked, but under SSD the yield distribution of the October-sown maize dominates that of November. For lowland rice in the Central High Plains of Madagascar, all three efficiency criteria indicate that the yield distribution of the December-transplanted rice dominates that of November and the premium values are less than 4 % of the potential yields.https://armgpublishing.com/wp-content/uploads/2023/04/1_SEC_1_2023-2.pdfdrought insurancenon-parametric methodsstochastic dominanceafrica
spellingShingle Manitra A. Rakotoarisoa
Harry P. Mapp
A non-parametric approach to determine an efficient premium for drought insurance
SocioEconomic Challenges
drought insurance
non-parametric methods
stochastic dominance
africa
title A non-parametric approach to determine an efficient premium for drought insurance
title_full A non-parametric approach to determine an efficient premium for drought insurance
title_fullStr A non-parametric approach to determine an efficient premium for drought insurance
title_full_unstemmed A non-parametric approach to determine an efficient premium for drought insurance
title_short A non-parametric approach to determine an efficient premium for drought insurance
title_sort non parametric approach to determine an efficient premium for drought insurance
topic drought insurance
non-parametric methods
stochastic dominance
africa
url https://armgpublishing.com/wp-content/uploads/2023/04/1_SEC_1_2023-2.pdf
work_keys_str_mv AT manitraarakotoarisoa anonparametricapproachtodetermineanefficientpremiumfordroughtinsurance
AT harrypmapp anonparametricapproachtodetermineanefficientpremiumfordroughtinsurance
AT manitraarakotoarisoa nonparametricapproachtodetermineanefficientpremiumfordroughtinsurance
AT harrypmapp nonparametricapproachtodetermineanefficientpremiumfordroughtinsurance