Item

The application of a whole farm business simulator in farm machinery investment analysis

Gamble, D. R.
Date
1978
Type
Thesis
Fields of Research
ANZSRC::140201 Agricultural Economics , ANZSRC::070106 Farm Management, Rural Management and Agribusiness
Abstract
A common approach to the analysis of farm machinery purchase/contract and size problems has been the use of average total cost curves (a partial analysis). This study examines a whole farm approach to machinery investment problems using a simulation model. A whole farm business simulator was built by adapting the Lincoln University College Business Simulator to reflect the 1976/77 Australian income taxation laws and to allow for a more realistic simulation of machinery, loans and income taxation structure of a farm business. A wheat/sheep case study property from the Central West of N.S.W. was used to illustrate the potential of the model in evaluating a range of farm machinery strategies and to test the effect of changes in taxation and credit policy changes on the machinery strategies. Results from the simulation model were contrasted with two average cost curve approaches. The results from the low cost average total cost curve analysis indicated a similar ranking of machinery strategies to the simulation model. However it is suggested that because of the ability of the simulation model to simulate the whole farm business, it can better reflect the actual differences between strategies using a number of criteria (average cost curves normally use only one criterion). The simulation model can also be used to analyse a much wider range of farm machinery problems. Machinery strategy differences from the model were found to be very sensitive to the Income Equalization Deposits option, the elimination of the 40% Investment Allowance and a 2% reduction in loan interest rates. The study demonstrated that the development of the simulation model could have important applications in extension, research and farm management education. However it has revealed serious deficiencies in available machinery data, essential for farm managers to make informed machinery decisions.
Source DOI
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