Financial Risk Modelling with Long-Run Weather & Price Variations

Future Farm Industries CRC Technical Report No. 14

44 Pages Posted: 21 Sep 2014

See all articles by Tim Hutchings

Tim Hutchings

Charles Sturt University - Graham Centre for Agricultural Innovation

Thomas L. Nordblom

Graham Centre for Agricultural Innovation (Charles Sturt University & NSW DPI)

Richard Hayes

Government of New South Wales - Department of Primary Industries

Guangdi Li

Government of New South Wales - Department of Primary Industries

Date Written: June 30, 2014

Abstract

Australian farmers face between three and ten times the level of production risk faced by farmers in competing countries worldwide (OECD-FAO, 2011). Consequently, in Australia, identical management plans may result in sharply contrasting distributions of financial outcomes. These differences provide more complete management information than those based on single-point estimates of average outcomes in the average year, which cannot account for the accumulation of financial impacts.

This study initially uses data of average monthly rainfalls, average crop, pasture and sheep production, and average input costs and output prices for a representative farm in the Coolamon area of southern NSW (Lat -34.817, Long 147.198, Alt 247m). It compares the profitability of several farming system options involving mixtures of annual dryland crops in rotation with annual and perennial pastures. These data are presented in the documentation of a linear programming (LP) model by Bathgate et al. (2010), we call the ‘Coolamon LP’.

A parallel simulation based on the same average-year Coolamon data and performance assumptions, but with long-run series of rainfall data and price variations, a Sequential Multivariate Analysis (SMA) (Hutchings, 2013) was specified with the aim of comparisons with results of the Coolamon LP. The SMA approach simulates multiple 10-year cash balances for the subject farm, after interest and taxes, describing the financial pressures acting upon the business. Results for the SMA model demonstrate the overwhelming importance of downside risk in determining the financial outcomes of farming systems in such dryland farming regions. This demonstrates why an average-season LP model can be a poor, and often incorrect, basis for extension advice on crop and pasture systems or stocking rates.

Keywords: Farm Management, Rainfed, Crop-Livestock systems, Perennial pastures, Weather variations, Price variations, Financial risk, Indebtedness

JEL Classification: G32, Q12, Q14

Suggested Citation

Hutchings, Timothy and Nordblom, Thomas L. and Hayes, Richard and Li, Guangdi, Financial Risk Modelling with Long-Run Weather & Price Variations (June 30, 2014). Future Farm Industries CRC Technical Report No. 14. Available at SSRN: https://ssrn.com/abstract=2495186

Timothy Hutchings

Charles Sturt University - Graham Centre for Agricultural Innovation ( email )

EH Graham Centre (CSU+NSW DPI)
Pine Gully Road
Wagga Wagga, 2650
Australia

Thomas L. Nordblom (Contact Author)

Graham Centre for Agricultural Innovation (Charles Sturt University & NSW DPI) ( email )

Albert Pugsley Place
Wagga Wagga, NSW 2650
Australia
+61419290428 (Phone)

HOME PAGE: http://www.csu.edu.au/research/grahamcentre/our-people/members2/tom-nordblom

Richard Hayes

Government of New South Wales - Department of Primary Industries ( email )

Wagga Wagga Agric Institute
Pine Gully Road
Wagga Wagga, NSW, New South Wales 2650
Australia
+(614) 48231704 (Phone)
+(614) 48231809 (Fax)

Guangdi Li

Government of New South Wales - Department of Primary Industries ( email )

WWAI
Pine Gully Road
Wagga Wagga, NSW, New Sout Wales 2650
Australia
+(612) 6938 1930 (Phone)
+(612) 6938 1809 (Fax)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
83
Abstract Views
705
rank
318,378
PlumX Metrics