RAINFALL-INDEX INSURANCE AND TECHNOLOGY ADOPTION: EVIDENCE FROM FIELD EXPERIMENT IN TUNISIA

2013 ◽  
Vol 25 (5) ◽  
pp. 660-673 ◽  
Author(s):  
Noujeima Ragoubi ◽  
Lotfi Belkacem ◽  
Anouar Ben Mimoun
Keyword(s):  
Technology Adoption ◽  
Field Experiment ◽  
Index Insurance ◽  
Rainfall Index

The impact of weather index insurance on agricultural technology adoption evidence from field economic experiment in China

2019 ◽  
Vol 11 (4) ◽  
pp. 622-641
Author(s):  
Yingmei Tang ◽  
Yue Yang ◽  
Jihong Ge ◽  
Jian Chen
Keyword(s):  
Technology Adoption ◽  
Field Experiment ◽  
Rural China ◽  
Rural Households ◽  
Agricultural Technology ◽  
Index Insurance ◽  
Weather Index ◽  
Content Type ◽  
Weather Index Insurance ◽  
The Impact

Purpose The purpose of this paper is to empirically investigate the impact of weather index insurance on agricultural technology adoption in rural China. Design/methodology/approach A field experiment was conducted with 344 rural households/farmers in Heilongjiang and Jiangsu Provinces, China. DID model was used to evaluate farmers’ technology adoption with and without index insurance. Findings The results show that weather index insurance has a significant effect on the technology adoption of rural households; there is a regional difference in this effect between Heilongjiang and Jiangsu. Weather index insurance promotes technology adoption of rural households in Heilongjiang, while has limited impact on those in Jiangsu. Weather, planting scale and risk preference are also important factors influencing the technology adoption of rural households. Research limitations/implications This research is subject to some limitations. First, the experimental parameters are designed according to the actual situation to simulate reality, but the willingness in the experiment does not mean it will be put into action in reality. Second, due to the diversity of China’s climate, geography and economic environment, rural households are heterogeneous in rural China. Whether the conclusion can be generalized beyond the study area is naturally questionable. A study with more diverse samples is needed to gain a fuller understanding of index insurance’s effects on farmers in China. Originality/value This research provides a rigorous empirical analysis on the impact of weather index insurance on farmers’ agricultural technology adoption through a carefully designed field experiment.

scholarly journals Dynamics of Demand for Index Insurance: Evidence from a Long-Run Field Experiment

2014 ◽  
Vol 104 (5) ◽  
pp. 284-290 ◽  
Author(s):  
Shawn Cole ◽  
Daniel Stein ◽  
Jeremy Tobacman
Keyword(s):  
Risk Management ◽  
Field Experiment ◽  
Spillover Effect ◽  
Small Samples ◽  
Index Insurance ◽  
Recent Experience ◽  
Insurance Demand ◽  
Rainfall Index ◽  
Long Run ◽  
Management Technology

This paper estimates how experimentally-manipulated experiences with a novel financial product, rainfall index insurance, affect subsequent insurance demand. Using a seven-year panel, we develop three main findings. First, recent experience matters for demand, consistent with overinference from small samples. Second, spillovers also matter, in the sense that the recent payout experience of village co-residents affects insurance demand about as much as one's own recent payout experience. Third, the spillover effect decays as time passes while the effect of one's own experience does not. We discuss implications of this analysis for commercial sustainability of this complicated but promising risk management technology.

scholarly journals Designing Rainfall Index Insurance for Rubber Plantation in Balikpapan

2021 ◽  
Vol 1863 (1) ◽  
pp. 012018
Author(s):  
Muhammad Azka ◽  
Fauziyyah ◽  
Primadina Hasanah ◽  
Syalam Ali Wira Dinata
Keyword(s):  
Index Insurance ◽  
Rubber Plantation ◽  
Rainfall Index

Evaluating effectiveness of rainfall index insurance

2018 ◽  
Vol 78 (5) ◽  
pp. 611-625 ◽  
Author(s):  
Rui Zhou ◽  
Johnny Siu-Hang Li ◽  
Jeffrey Pai
Keyword(s):  
Crop Yield ◽  
Variance Reduction ◽  
Index Insurance ◽  
Corn Yield ◽  
Basis Risk ◽  
Content Type ◽  
Optimal Insurance ◽  
Rainfall Index ◽  
Temperature And Precipitation ◽  
Insurance Portfolio

Purpose The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer. Design/methodology/approach Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined. Findings The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent. Originality/value By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

scholarly journals The Impact of Commercial Rainfall Index Insurance: Experimental Evidence from Ethiopia

2020 ◽  
Vol 102 (4) ◽  
pp. 1154-1176
Author(s):  
Shukri Ahmed ◽  
Craig McIntosh ◽  
Alexandros Sarris
Keyword(s):  
Experimental Evidence ◽  
Index Insurance ◽  
Rainfall Index ◽  
The Impact
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