Article analysis for Revenue Recognition Timing and Attributes of Reported Revenue: The Case of Software Industry’s Adoption of SOP 91-1 by Yuan Zhang
Timing of revenue recognition is a crucial part in revenue recognition. According to US GAAP, revenue should be recognized when it is realized/realizable and earned (FASB, 1984, Para. 83). However, a number of software firms recognized revenue prior to product delivery or service performance in the past, which potentially violated one or both of the conditions of the revenue recognition principle.
The AICPA responded to this by issuing Statement of Position (SOP) 91-1 in December 1991. SOP 91-1 stated that if the probability of collectability exists, revenue from licenses should be recognized upon delivery, while revenue from services should be recognized evenly over the duration of the service arrangement. This article investigates how the timing of revenue recognition impacts the characteristics of reported revenue.
The importance of revenue recognition timing in financial reporting and the attention given by standard setters makes this question interesting. However, there has been limited empirical research on revenue recognition timing. Additionally, software revenue recognition is unique because it is achieved through license rather than immediate product sale. The main hypotheses for this article assert that early revenue recognition enhances the timeliness of reported revenue.
The intuition behind early revenue recognition is that it provides more timely information, which can better influence decisions. However, this approach also leads to greater uncertainty in reported revenue because changes may not be foreseen at the time of contract signing. Additionally, the time-series predictability of revenue is lower under early revenue recognition due to higher estimation error, which reduces its predictability.
The author selected a sample of 122 firms for analysis based on three criteria. Firstly, the firms had to be engaged in the software business. Secondly, their financial statements had to be available for each fiscal year from 1991 to 1993. Lastly, the firms had to directly report the time, nature, and/or effect of adopting the SOP. The sample period chosen for the analysis was from 1987 to 1997. This period was selected because the analysis required information from the statement of cash flows, which became available in 1987. Additionally, it was important to stop at 1997 in order to ensure consistent definition of revenues for post-SOP firm-quarters. The author then classified the 122 firms into two groups: 29 EARLY firms and 93 CONTROL firms.
The EARLY group consisted of firms that reported a negative cumulative adjustment, indicating that they had previously used early revenue recognition and had to change their policies upon adopting the SOP. The CONTROL group did not see any significant impact from adopting the SOP. None of the firms in the sample reported positive cumulative effects. The author also presented descriptive statistics for three sets of constructs – size, growth, and performance – as these constructs were expected to influence the attributes of reported revenue and help mitigate bias.
The author compared EARLY firms and CONTROL firms for various variables. They found that, in most cases, there were no significant differences between the two groups. In this section, the author discussed the analysis of the data and explained the procedure for regression analysis. The objective of accrual accounting is to record the impact of transactions and other events in the periods they occur. This statement shows that standard setters prioritize both the relevance and reliability of accounting information.
There is a trade-off between relevance and reliability in accounting. Changing an accounting method to gain more reliability may result in a decrease in relevance. In the software industry, recognizing revenue early has the potential to influence decisions by providing more timely information, making it expected to increase the timeliness and relevance of reported revenue. Thus, the author hypothesizes that reported revenue under early revenue recognition is more timely in providing economic information than SOP 91-1.
The author conducted research on the relationship between reported revenue and stock return using reverse regression methodology, aiming to demonstrate the efficiency of stock markets in incorporating value-relevant economic transaction information efficiently and impartially. The analysis of the data led to the conclusion that early revenue recognition enhances timeliness. Additionally, in section 5, the author proposed the hypothesis that accounts receivable accruals have a lesser impact on cash flow realizations compared to those governed by SOP 91-1.
The author discusses how the timing of recognition affects the likelihood of customer payment. Factors such as acceptance, commitment to pay, and need for customization can change before or during the delivery of software or services. These changes are often unforeseen when the contract is signed or before SOP 91-1 guidelines are applied. To test this hypothesis, the author utilized the Dechow and Dichev (2002) method, which examines the standard deviations of residuals from a regression analysis of accounts receivable accruals and corresponding cash flow realizations.
The model examines several factors including accounts receivable, sales cash collected, and errors in accounts receivable accruals (sresid). The author analyzes both pre- and post-SOP firms and considers their size. The findings reveal that sresid is greater for early firms compared to control firms before SOP 91-1, but this trend reverses after SOP. Moreover, early revenue recognition affects the relationship between accounts receivable accruals and cash flow realizations, as well as the reliability of revenue-related accounting information.
Section 6 of the paper analyzed the predictability of future revenue based on reported revenue in financial statements. The author noted in section 5 that recognizing revenue early led to higher estimation error in accounts receivables accruals. Additionally, the author anticipated that increased estimation error would decrease time-series predictability. To investigate this, the author utilized the Foster (1977) model to examine absolute forecast error and its impact on the predictability of reported revenue during the pre- and post-SOP period.
The author’s hypothesis was that the size and revenue volatility of a firm could impact the study’s findings. To ensure an unbiased result, she controlled for these variables. The findings revealed that firms that recognized revenue early generally had higher absolute forecast errors during the pre-SOP period. This confirmed the author’s hypothesis that early revenue recognition reduces the predictability of reported revenue.
