The Path Leading up to the New IFRS 16 Leasing Standard: How was the Restructuring of Lease Accounting Received by Different Advocacy Groups?

Christian Blecher and Stephanie Kruse

Chapter 105 in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning:(In 4 Volumes), 2020, pp 3675-3702 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The due process of the International Financial Reporting Standards (IFRS) enables interested parties to comment on the development of new IFRS. Unsurprisingly, different advocacy groups have very different perspectives and interests. For example, businesses are more likely to be interested in “user-friendly” rules, whereas standard-setters and academics tend to prefer theoretically coherent standards.This paper analyzes the response behavior of different advocacy groups using the example of lease accounting reform whereas leasing seems to be a promising example. First, to analyze the response behavior, five different advocacy groups are defined. The 657 comment letters submitted for the Re-Exposure Draft “Leases” are then assigned to these five advocacy groups. The Re-Exposure Draft formulates questions about different aspects of the new standard and asks for comments regarding these aspects. Next, the response behavior of the different advocacy groups with respect to the most relevant questions is examined quantitatively and qualitatively. The quantitative analysis uses the Kruskal–Wallis test (H-test) and the Mann–Whitney test (U-test) to evaluate the response behavior. The main result of the study is that the response behavior to various questions differs significantly between advocacy groups. In particular, it is shown that the response behavior differs drastically between more “user-oriented” and more “theoretically oriented” advocacy groups.

Keywords: Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data (search for similar items in EconPapers)
JEL-codes: C01 C1 G32 (search for similar items in EconPapers)
Date: 2020
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