Value relevance and market valuation of assets measured using IFRS and US GAAP in the US equity market

Abstract

Purpose Studies show firms reporting using Generally Accepted Accounting Principles in the United States (US GAAP) and International Financial Reporting Standards (IFRS) are similarly valued in the market, however, these studies are limited due to the noise present in international studies from regulatory differences. This study aims to eliminate much of this noise by using a cleaner sample of all listings with the Securities Exchange Commission (SEC). This paper also looks at more detailed book value figures. Design/methodology/approach There have been previous studies on the differences in market valuation of firms reporting using IFRS vs US GAAP. Most of this research is confounded with difficulties due to different regulatory environments and volatile time periods. The study uses cleaner data following the SEC’s acceptance of IFRS financials without a 20-F Reconciliation. The authors use a large sample of non-US firms trading on US exchanges choosing to use either US GAAP or IFRS for SEC reporting purposes. The sample period starts two years after the SEC’s acceptance of IFRS financials without a 20-F reconciliation and is larger than earlier samples. Findings The authors show that there is no difference between IFRS and US GAAP firms’ overall value relevance, however, earnings are more value relevant when measured using IFRS and book value is more value relevant when measured using US GAAP. The authors find that the difference between US GAAP and IFRS can be explained, at least in part, by greater market multiples being placed on inventories and goodwill using US GAAP. This is offset in part by greater multiples being placed on other assets under IFRS. Originality/value The authors replicate earlier studies but also extend with a better sample and more detailed finings.

The Value‐relevance of Fair Value Measurement for Inventories

“…All variables, apart from Size, MTB and Neg, are scaled by number of shares outstanding, which has been shown to most reliably compensate for scale effects when using accounting data (Barth and Clinch 2009;Aledo Martínez et al 2020). To mitigate against the impact of outlying observations, we winsorise all variables, other than Neg, by year, at the 5% and 95% levels, similar to prior research (Barth et al 2012;Cipriano et al 2022).…”