Abstract
ABSTRACT Management accounting tools are based on the idea that total costs are composed of fixed and variable components. Textbooks usually teach five methods to identify fixed and variables costs, including two that are outdated (scatterplot and high-low). Account analysis and industrial engineering are sometimes useful, but regression is best for its objectivity. Despite its importance, few cases address cost estimation using regression. This case requires students to use regression analysis to estimate a cost function from 108 monthly observations of unit-level data from a hotel chain. Although the case is intended for use with R or Python, instructors can also use Excel. Students learn how to address important data and model specification issues, including outliers, autocorrelation, and inflation. Students are excited to acquire relevant tools and skills they can apply to future work projects.
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