English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The need for qualified decisions in business environment creates demands for the use of mathematical and statistical methods to assist the decisional process. In this context, this article aims to test the applicability of the method of Monte Carlo simulation to predict changes in production costs in a post-privatization period. To perform the experiment Companhia Vale do Rio Doce - CVRD was chosen, considering its privatization that occurred in 1997. The analyzed variables data were extracted from published financial statements between 1990 and 2004. Production costs (CPV) are simulated in two applications of the method: an application that ignores the effects of privatization and implementation that considers the period after privatization, the reduction of variable costs and the income operating increase. In a privatization process, these effects are expected and were estimated by linear regressions in a previous study by Lustosa and Oliveira (2007). To verify the predictive ability of the method comparative analysis are performed, using statistical tests of means between the real samples and the post-privatization period simulated samples. The results show the suitability of the method in predicting the production costs and consequently assisting the decisional process.

revista de contabilidade e organizações

Aplicabilidade do método de simulação de Monte Carlo na previsão dos custos de produção de companhias industriais: o caso da Companhia Vale do Rio Doce