JOURNAL ARTICLE
U.S. Multinational Companies' Payout and Investment Decisions in Response to International Tax Provisions of the Tax Cuts and Jobs Act of 2017.
Published In: Journal of the American Taxation Association, 2023, v. 45, n. 1. P. 35 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Beyer, Brooke D.; Downes, Jimmy F.; Mathis, Mollie E.; Rapley, Eric T. 3 of 3
Abstract
The Tax Cuts and Jobs Act of 2017 (TCJA) dramatically changed U.S. taxation of foreign earnings for U.S. multinational companies (MNCs). Specifically, the TCJA required taxation of existing unremitted foreign earnings through a deemed repatriation and effectively eliminated future repatriation taxes through a 100 percent dividends received deduction. Additionally, the bill introduced the global intangible low-taxed income (GILTI) regime. We examine MNCs' responses to the TCJA and find that spending and investment behavior depends on liquidity, investment opportunities, and borrowing costs. Domestic capital expenditures and share repurchases increased for MNCs with low domestic liquidity and high domestic investment opportunities. In contrast, MNCs with low domestic liquidity (high cost of debt) and low domestic investment opportunities increased dividends (decreased debt). Finally, we find that MNCs with high foreign cash and most vulnerable to the GILTI regime increased their foreign but not domestic capital expenditures—a potential unintended consequence. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: F23; G31; G38; H25; M40; M48. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of the American Taxation Association. 2023/03, Vol. 45, Issue 1, p35
- Document Type:Article
- Subject Area:Law
- Publication Date:2023
- ISSN:0198-9073
- DOI:10.2308/JATA-2020-037
- Accession Number:162899850
- Copyright Statement:Copyright of Journal of the American Taxation Association is the property of American Accounting Association 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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