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Abstract
This study examines the interaction between insurance, credit and liquidity
constraints using a stochastic dynamic model. A risk averse farmer whose
objective is to manage both production and market risk is assumed to
maximize the expected utility of life-time consumption by using both area
revenue (AR) insurance and consumption smoothing subject to a credit
constraint. The dynamic programming is coded in MATLAB using
DDPSOLVE algorithm (Appendix a). DSSAT crop simulation model is used
to determine optimal irrigation strategy and to simulate farm level yield. A
Bayesian Model is used to estimate expected county-level revenue. The
approach and results are illustrated via a numerical example using county
level data from Mitchell County in Georgia. Results support the hypothesis
that liquidity constraints can have a large impact on optimal insurance
decisions, and that different levels of premium load, risk aversion level, and
time-preferences can also affect optimal insurance decisions under liquidity
constraints.