Improving machinery investment decisions

Martin Nyongesa Etyang, Purdue University

Abstract

Many farmers in Indiana are currently in the process of changing their machinery complements. The farmers are considering changes in their machinery complements because of the increasing pressure from both the government and the public for them to change from conventional tillage to reduced tillage, in order to reduce soil erosion. The farmers also expect to increase their earnings because variable costs under reduced tillage are lower. In order to help Indiana farmers make machinery selection decisions, the Purdue Crop/Livestock Planner (PC-LP) model was developed in the early 1990s. The PC-LP model, which was developed for conventional tillage practice does not explicitly incorporate randomness in the number of good field days available during the various crop activity periods. Instead, a rule of thumb was developed for determining the number of good field days during the land preparation, planting and harvesting periods. Although this rule appears to have performed reasonably well in the case of conventional tillage, there is concern that il may not be valid for reduced tillage practices. The main objective of this research was therefore to either validate the rule of thumb or develop a new rule to be used for setting good field day resource availability in a farm planning model, and to determine whether this rule is invariant with respect to tillage system and soil type or not. Rules based on the distributional parameters of the good field days by period, and which give similar results for the optimal net revenue levels for both stochastic and deterministic farm planning models for various machinery sizes, were developed. These rules were found not to differ by much across soil types, but they were substantially different by tillage system.

Degree

Ph.D.

Advisors

Preckel, Purdue University.

Subject Area

Agricultural economics

COinS