TITLE:
Fair Employee Treatment and Financial Characteristics of Firms
AUTHORS:
Himanshu Joshi, Prachi Bhatt
KEYWORDS:
Fair Employee Treatment, Leverage, Binary Logistic Regression, Employee Compensation
JOURNAL NAME:
Theoretical Economics Letters,
Vol.9 No.4,
April
18,
2019
ABSTRACT: Present paper investigates the interactions between
firm’s key financial decisions and its fair employee treatment and welfare
policies. Fair employee treatment has two components—measurable and
unmeasurable. Certain ratios like employee compensation to sales, employee
compensation to total assets, and total employee welfare to sales are computed
to capture the measurable part of fair employee treatment. To envisage the unmeasurable
component, a dummy variable for fair employee treatment is used which is based
on the listing of the firm in India’s Best Companies to Work for 2017: The
complete List prepared by Great Place to Work and published by Economic Times.
Linear multiple regression analysis is conducted using firm’s leverage, price
to book value, and enterprise value to EBDITA as dependent variables, and fair
employee treatment, and employee compensation to sales as independent
variables. Results indicate a negative relationship between employee
compensation and firm valuation, and confirm that high leverage firms are more likely to cut-down
on employee compensation but ensure better and fair treatment of employees. The
result of binary logistic regression model predicts that firm’s dividend
policy, employee stock options, and firm leverage positively impact the
probability of fair employee treatment.