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  4. A COMPARISON BETWEEN PERT DISTRIBUTION AND SEASONAL ARIMA MODEL TO FORECAST RAINFALL PATTERN

A COMPARISON BETWEEN PERT DISTRIBUTION AND SEASONAL ARIMA MODEL TO FORECAST RAINFALL PATTERN

File(s)
Li_cornell_0058O_10285.pdf (1.91 MB)
Permanent Link(s)
https://doi.org/10.7298/X4ZC8140
https://hdl.handle.net/1813/59471
Collections
Cornell Theses and Dissertations
Applied Economics and Management MS Theses
Author
Li, Yan
Abstract

Weather is becoming more and more unpredictable for farmers, and the frequency of extreme weather events is also increasing. Small households in Kenya are vulnerable to these extreme weather shocks, and failures in effective hedging will make sustainable production extremely difficult for them. The goal of this thesis is to use historical rainfall record in Kenya to forecast rainfall and take quantile of the rainfall distribution to get a trigger for a put-option embedded innovative financial instrument. There are two methods to develop this lower 20% band trigger, which are pert distribution and time series method. Finally, I get two sets of results from two methods. With the help of the simulation results, insurance companies will be able to design a weather-index insurance for small households in Kenya. For farmers, they will use this flexible insurance as an effective substitute for traditional deposit, which requires productive assets as collateral.

Date Issued
2018-05-30
Keywords
SARIMA
•
time series
•
weather-index insurance
•
Risk Contingent Credit
•
Agriculture economics
Committee Chair
Turvey, Calum G.
Committee Member
Woodard, Joshua D.
Shee, Apurba
Degree Discipline
Applied Economics and Management
Degree Name
M.S., Applied Economics and Management
Degree Level
Master of Science
Type
dissertation or thesis

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