STOCHASTIC DYNAMIC MODELING: AN AID TO AGRICULTURAL LENDER DECISION MAKING

Abstract

Factors affecting a lenderÂ’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 lenderÂ’s discount rate, a borrowerÂ’s repayment status, and patronage. The value of credit scoring models that appraise a borrowerÂ’s credit worthiness also is determined.Agricultural Finance,