The Yale Undergraduate Research Journal
Article Title
Applied Statistical Models for Evaluating Firm Operating Performance and Investment Returns
Abstract
This paper investigates the extent to which CEO, industry, firm, year, corporate parent, and business segment effects contribute to variation in the performance of public US companies classified by NAICS industry codes between 2010-2018. Applying several statistical models, the paper finds that 32.9% of segment profit variation is associated with business segment effects with negligible year effects (0.11%), similar to the findings of prior literature. This analysis also finds that corporate parent membership plays a larger role and industry and CEO effects play a smaller role in profit variation than previously suggested. These results have potential implications for the fields of strategic management, financial economics, and others, but several considerations, 1.) comparability and external validity of results, 2.) lack of performance-level mechanisms of causal inference, 3.) reliance on variation as a tool for generalized linear regression, and 4.) autocorrelation, represent key limitations to the interpretation of these results.
Recommended Citation
Chen, Christopher
(2020)
"Applied Statistical Models for Evaluating Firm Operating Performance and Investment Returns,"
The Yale Undergraduate Research Journal: Vol. 1:
Iss.
1, Article 16.
Available at:
https://elischolar.library.yale.edu/yurj/vol1/iss1/16