Abstract
This paper examines farmland investment decisions using a stochastic dynamic programming framework. Consideration is given to the dynamic, stochastic nature of farmland returns, linkages between farmland returns and farmland prices, and the effects of the above dynamic factors on a farm's financial structure. Optimal decisions to purchase or sell farmland are found for a central Illinois farm with high quality farmland. Sizes and debt distributions are then determined, given that the optimal decision rule is followed. Decisions from the dynamic programming model also are compared to a capital budgeting model. Land transactions have significant impacts on a farm's profitability and financial structure. Much research has analyzed various aspects of these impacts with emphasis given to financing firm growth. Using debt capital to finance firm growth requires an increase in leverage position which increases the firm's risk position (Barry, Hopkin, and Baker), alters the time pattern of cash flows (Ellinger, Barry, and Lins; Lee), reduces its liquidity (Barry and Baker), and may affect the optimal production organization (Baker). Alternative strategies for managing debt and equity capital also affect a firm's risk position (Held and Helmers; Hinman and Hutton), consumption patterns, and production decisions (Johnson and Boehlje). These financing issues are important when considering farmland purchase or sale decisions. Other important factors include the stochastic, dynamic nature of farmland returns (Alston; Burt) and linkages between farmland returns and prices (Burt). Most previous studies either assume that future farmland returns and prices are known with certainty or that their distributions are known unconditionally. The authors are, respectively, an assistant professor in the De
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