Stochastic simulation of the economic viability of feedlot finishing steers slaughtered at different weights in southern Brazil

Abstract

The objective of this study was to evaluate the use of stochastic simulations in decision-making regarding the economic viability of feedlot finishing Charolais steers slaughtered at different weights (420, 460 or 500 kg live weight). Monte Carlo simulation was used, with or without Spearman correlation, to evaluate the risk associated with random input variables, and to compare the curves of pairs of slaughter weights by stochastic dominance. The financial indicator net present value (NPV) was the output variable. The expected means and standard deviations for the slaughter weights of 420, 460 and 500 kg were USD 28.77 ± 53.90; USD 36.27 ± 57.22 and USD 54.60 ± 66.74 for simulation with correlation, and USD 28.75 ± 96.15; USD 36.17 ± 103.11 and USD 54.53 ± 111.96 for simulation without correlation. The simulations without correlation were found to overestimate the standard deviation by 75% compared to simulations performed in addition to correlation analysis. The correlation between random input variables should be prioritized, as this resulted in better estimates of risk associated with investment. For all simulated situations, the lowest slaughter weights dominated the largest, according to the first- and second-order stochastic dominance criteria. For the simulation with correlation, the probability of NPV ≥ 0 was 29.4, 24.4 and 19.4% for slaughter weights of 420, 460 and 500 kg, respectively. Interpretation of these simulations allowed classification of feedlot technology as high risk, with a high probability of economic loss.

Keywords

• decision making
• monte carlo simulation
• investment projects
• nonparametric statistics