Simulation analysis of risk management for a diversified commercial farm

Abstract

Managing a profitable commercial agricultural business requires morethan effective budgeting and financial bookkeeping. Due to dramatic changes in the agricultural decision-making environment over the past 15 years, farmers have to realise that farming requires effective risk management. A successful farmer is one w ho can identify these risks, match them up with expected returns and make the best decision on future actions. The farmer must be able to look strategically into the future and position the business in a way that ensures long-term sustainability and survivability. To forecast effectively, it is vital for the agribusiness to predict the effects of various risks on the financial position of the business.This research attempts to develop a simulated dairy management model that can be used as a farm management tool. Normal distributions were used to simulate the movement of maize prices under different scenarios. This model was applied to a 2007 case study, and it was found to be a suitable tool for financial analysis and scenario planning. By utilising different sets of input values, the model gives an indication of the possibility of risks involved in different scenarios. However, the model is in a rather crude form, and further development should be undertaken to account for the interaction between variable inputs. The model highlights the importance of a change in strategic direction, w hile it is useful in analysing the scenario outcomes of new strategies.

Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model

“…Bioeconomic models detail biotechnical specifications and simulate producers' decisions assuming that they make their decisions in order to optimize their objective function (Janssen and van Ittersum, 2007). Some dynamic bioeconomic livestock models have been built to assess impacts of weather (Finger et al, 2010) or price risks (Hardaker and Lien, 2010;Malan et al, 2010) on farms. However, few authors have already simulated shock impacts when taking simultaneously into account the possibility of adjusting animal weight, herd size, crop product, and land use, given that livestock production systems are particularly complex (Austin et al, 1998;Pang et al, 1999).…”