Benford's law is used in this study to look at how corporations manage their earnings. This is a probability strategy that the investigator use as a hand tool. The study investigates the income statement and balance sheet data in a large sample of Indian public listed firms (34,346 firm-year observations) from 2000 to 2014 to see if the values in the data fit Benford's law distribution. To determine if the numbers in the data follow Benford's law distribution, the data is further segmented depending on ownership concentration, such as business group firms vs. independent firms, and company specific parameters, such as large size vs. small size enterprises. The study examines the conformance of Benford's law using "first digit," "second digit," and "first two digits" analysis. Total assets, receivables, fixed assets, property, plant and equipment, inventory, current assets, current liabilities, sales, selling and distribution expenses, cost of goods sold, cash, earnings before interest and taxes (EBIT), direct tax, and indirect tax are among the financial statement variables considered for the study's analysis. The results show that data has anomalies when distributed according to Benford's law. Further research shows that corporate groups have more data abnormalities than stand-alone companies. In the Indian context, small businesses exhibit more data anomalies than large businesses. Anomalies in data lead to a deeper analysis of the data.
Author(s) Details:
Dr. Ramesh Chandra
Das,
Asst. Professor in Commerce, Bhadrak Autonomous College, Bhadrak, India.
Please see the link here: https://stm.bookpi.org/RDASS-V1/article/view/5720
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