This paper presents a theoretical framework for incorporating the following sources of risk into the determination of optimal fertilization rates: (a) the influence of weather and other stochastic factors on the marginal product of fertilizer, and (b) uncertainty about the coefficients of the...

A framework for combining extraneous information with an econometric model to evaluate the economic impacts of pesticide withdrawals is presented in this paper. The extraneous information, which can be a best guess or experimental data, is used to shift an econometrically estimated supply...

This note demonstrates that a certain class of stochastic problems for determination of optimal fertilizer application rates in the presence of fertilizer carry-over can be simplified to static, certainly equivalent problems. Conditions required for certainty equivalence to hold are: (1)...

This article graphically illustrates the one-to-one duality mapping among the production function, the product supply equation, the derived factor demand equation, and the indirect profit function for the classical profit maximization problem. This pedagogical framework is then used to...

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 farmÂ’s...

Statistical procedures are developed for reducing the number of autonomous state variables in stochastic dynamic optimization models when these variables follow a stationary process over time. These methods essentially delete part of the information upon which decisions are based while...

This paper presents a hyperbolic trigonometric (HT) transformation procedure for empirically estimating a cumulative probability distribution function (cdf), from which the probability density function (pdf) can be obtained by differentiation. Maximum likelihood (ML) is the appropriate...