STOCHASTIC DYNAMIC MODELING: AN AID TO AGRICULTURAL LENDER DECISION MAKING
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Factors affecting a lender's decision to grant farmers operating credit in North Dakota are quantified in an intertemporal loan profitability model using stochastic dynamic programming. Experimental data obtained from a panel of lenders demonstrates the sensitivity of an optimal policy to changes in a lender's discount rate, a borrower's repayment status, and patronage. The value of credit scoring models that appraise a borrower's credit worthiness also is determined.