JOURNAL ARTICLE
Preparer Opposition and Strategic Implementation of Governmental Accounting Standards: Evidence from Public Pension Accounting Reform.
Published In: Management Science (INFORMS), 2023, v. 69, n. 7. P. 4259 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Allen, Abigail; Petacchi, Reining C. 3 of 3
Abstract
This article examines the development, stakeholder lobbying, and implementation of Governmental Accounting Standards Board (GASB) Statements 67 and 68, which significantly changed the accounting for defined benefit public pensions by requiring recognition of previously undisclosed unfunded pension liabilities and introducing a blended discount rate incorporating a market-based component. The study analyzes lobbying positions from 113 state governments and pension funds ("preparers") and 175 users (including internal users such as public employees and unions, and external users such as investors and oversight bodies), finding that preparers generally opposed the liability-increasing proposals due to financial, economic, and political incentives, while users—especially external users—supported greater transparency, revealing a misalignment of interests. Empirical evidence shows that states opposing the market-based discount rate maintained higher discount rates after GASB 67/68's adoption, not by shifting pension investments toward riskier assets or cutting benefits, but primarily by increasing employee contribution rates, indicating strategic implementation to mitigate the impact of the new standards. The findings highlight how lobbying influenced the final standard's compromise on discount rates and demonstrate that accounting changes can have real fiscal effects on public pension funding decisions.
Additional Information
- Source:Management Science (INFORMS). 2023/07, Vol. 69, Issue 7, p4259
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2023
- ISSN:0025-1909
- DOI:10.1287/mnsc.2022.4515
- Accession Number:165047933
- Copyright Statement:Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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