Open AccessAnalysis of economic viability under risk conditions of a beef cattle feedlot system in São Paulo State, Brazil
Author(s) -
Kaio Expedito Rodrigues Queiroz,
Janderson Damaceno dos Reis,
André Rozemberg Peixoto Simões
Publication year - 2022
Publication title -
revista ambiente contábil
Language(s) - English
Resource type - Journals
ISSN - 2176-9036
DOI - 10.21680/2176-9036.2022v14n1id27710
Subject(s) - feedlot , beef cattle , net present value , agricultural science , cash flow , discounted cash flow , internal rate of return , feeder cattle , sensitivity (control systems) , zoology , economics , mathematics , econometrics , statistics , agricultural economics , production (economics) , environmental science , biology , engineering , finance , electronic engineering , macroeconomics
Purpose: Assess the sensitivity and economic viability of the beef cattle feedlot system using as a reference a farm located in northern São Paulo State, Brazil.
Methodology: A multidimensional approach was used to assess sensitivity. Financial results were analyzed in terms of cash flow using the net present value (NPV) as a viability indicator. Risks were incorporated using Monte Carlo simulations, considering feed, animal purchase, and animal selling prices as discrete random variables. The value measure was NPV, calculated using a minimum attractive rate of return of 7.55% per semester. Probabilities were estimated by relative frequency analysis.
Results: The probability of a feedlot being economically attractive was 30.2%, indicating that the system was not viable in 69.8% of the cases. Sensitivity analysis showed that the feedlot was most vulnerable to fluctuations in selling price (a 1% increase in fed cattle price generated a 46% increase in NPV), followed by feeder cattle price (a 1% increase in feeder cattle price led to a 29% reduction in NPV) and feed price (a 1% increase in feed price produced a 12% reduction in NPV).
Contributions of the Study: The findings of this study may support new evaluations in representative samples, complement previous studies on the topic, and assist decision makers.