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A spatial Bayesian approach to weather derivatives
Nicholas D. Paulson
, Chad E. Hart
, Dermot J. Hayes
Agricultural and Consumer Economics
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peer-review
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Keyphrases
Iowa
100%
Bayesian Approach
100%
Weather Derivatives
100%
Historical Analysis
66%
Historical Data
66%
Rainfall Model
66%
Monte Carlo Method
33%
Competing Models
33%
Estimation Method
33%
Design Methodology
33%
Rainfall
33%
Markov Chain Monte Carlo Methods
33%
Data Availability
33%
Insurance Policy
33%
Climatic Factors
33%
Kriging
33%
Homogeneous Regions
33%
Developing Regions
33%
Weather Risk
33%
Forage Production
33%
Agricultural Insurance
33%
Spatial Markov
33%
Spatial Kriging
33%
Weathering Indices
33%
Drought Insurance
33%
Policy Performance
33%
Mathematics
Bayesian Approach
100%
Kriging
100%
Historical Data
100%
Monte Carlo
50%
Estimation Method
50%
Bayesian
50%
Monte Carlo Technique
50%
Markov Chain Monte Carlo
50%
Economics, Econometrics and Finance
Bayesian
100%
Historical Analysis
100%
Monte Carlo Simulation
50%
Estimation Theory
50%
Markov Chain Monte Carlo
50%
Engineering
Bayesian Approach
100%
Historical Data
100%
Applicability
50%