Abstract
The resilience and profitability of livestock production in many countries can be impacted by shocks, such as drought and market shifts, especially under high debt levels. For farmers to remain profitable through such uncertainty, there is a need to understand and predict a farming business’s ability to withstand and recover from such shocks. This research demonstrates the use of biophysical modelling linked with copula and Monte Carlo simulation techniques to predict the risks faced by a typical wool and meat lamb enterprise in South-Eastern Australia, given the financial impacts of different debt levels on a farming business’s profitability and growth in net wealth. The study tested five starting gearing scenarios, i.e., debt to equity (D:E) ratios to define a farm’s financial risk profiles, given weather and price variations over time. Farms with higher gearing are increasingly worse off, highlighting the implications of debt accumulating over time due to drought shocks. In addition to business risk, financial risk should be included in the analyses and planning of farm production to identify optimal management strategies better. The methods described in this paper enable the extension of production simulation to include the farmer’s management information to determine financial risk profiles and guide decision making for improved business resilience.
Highlights
Due to the uncertainties and variabilities in international prices and exchange rates, Australian farmers are considered to face high production and output price risks, according to the Organisation for Economic Co-operation and Development (OECD) [1,2]
Previous studies [7] have analysed risk through gross margins or risk methodology [8] without taking into account the relationship between production and prices and the impact of farm debt. These methods are likely to lead to inaccurate conclusions and sub-optimal decision making when considering strategies based on historical data
Distributions were fitted on these inputs that were correlated using copula
Summary
Due to the uncertainties and variabilities in international prices and exchange rates, Australian farmers are considered to face high production and output price risks, according to the Organisation for Economic Co-operation and Development (OECD) [1,2]. According to Frilay et al [5], typical sheep and lamb businesses in Australia have incurred average debts of A$688,000 over the past ten years, potentially impacting the long-term viability of a farm’s capacity to service debt. Previous studies [7] have analysed risk through gross margins or risk methodology [8] without taking into account the relationship between production and prices and the impact of farm debt. These methods are likely to lead to inaccurate conclusions and sub-optimal decision making when considering strategies based on historical data. We make use of historical data and its relationships using copulas to advance these past studies
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