Date of Completion

2020

Document Type

Honors College Thesis

Department

Grossman School of Business

Thesis Type

College of Arts and Science Honors, Honors College

First Advisor

Akshay Mutha

Keywords

management-accounting interface, retailing, regression analysis, trade policy

Abstract

This paper attempts to recreate the regression model originally presented in Kesavan and Mani (2013) to analyze the relationship between abnormal inventory growth (AIG) and one-year-ahead earnings per share (EPS) for U.S. public retailers. In addition, this paper aims to build upon Kesavan and Mani (2013)’s findings by applying the model to recent data in order to test whether results vary as a function of different macroeconomic conditions. Unlike Kesavan and Mani (2013), I do not find a statistically significant relationship between AIG and future EPS for the years 2004-2009. However, when applying the same model to data from 2013 to 2018, I find a significant, inverted-U relationship between the two variables. These findings suggest that abnormal inventory growth is impacted by macroeconomic factors that encourage retailers to accumulate excess inventory. Furthermore, I find that excess inventories have a larger negative impact on future earnings than insufficient inventories, implying that retailers should prioritize strategies that prevent bloated inventory levels above those that lead to decreased service level.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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