The Impact of Tax Policy Uncertainty on Forecasting Summaries of Papers in This Issue
Jennifer L. Brown, K. C. Lin, Jared A. Moore, and Laura A. Wellman
This study examines how tax policy uncertainty impacts analysts and managers as they predict effective tax rates (ETRs). We adopt a news-based measure developed by Baker, Bloom, and Davis (2016) to identify periods of high tax policy uncertainty and show this measure correlates predictability with major tax policymaking activity. Our main analyses show that (1) analysts' implied ETR forecasts are less accurate and more disperse during periods of high tax policy uncertainty, (2) managers' interim ETR estimates are less accurate during periods of high tax policy uncertainty, and (3) more inaccurate management ETR estimates exacerbates the effect of TPU on analysts' ETR forecast inaccuracy and dispersion. Overall, our findings are consistent with the idea that tax policy uncertainty impedes analysts' and managers' ability to predict future tax-related fundamentals.
Our research is timely and relevant to policymakers. Press articles suggest tax policy uncertainty is a serious concern for both managers and market participants (McKinnon, Fields, and Saunders 2010; Block 2012; Reddy and Thurm 2012), yet compared to research on the effects of tax policy, relatively little is known about the effects of tax policy uncertainty. Our study helps fill that gap. In an era of deficits, the tax code has become increasingly temporary in nature. The use of sunset provisions allows legislators to behave myopically (Kysar 2011), as seen in the context of the TCJA. Our study provides evidence that when Congress fails to provide stable tax policy, a resulting cost is impairment of managers' and market participants' ability to assess firms' tax-related fundamentals.
To our knowledge, our study is also among the first in accounting to define tax policy uncertainty and identify and validate a measure to capture time-varying tax policy uncertainty (TPU). We define tax policy uncertainty as uncertainty about the application of existing tax law as well as uncertainty about what future tax laws will be. We adopt a news-based measure developed by Baker, Bloom, and Davis (2016) to identify periods of high tax policy uncertainty and show this measure correlates predictability with hand-collected data on tax legislation, congressional hearings, and congressional research reports. Our validation tests provide assurance that TPU truly captures tax policy uncertainty rather than general (non-tax) economic policy uncertainty. Most prior empirical studies on tax policy uncertainty examine uncertainty related to passage of specific legislation or uncertainty surrounding elections (e.g., Ayers, Cloyd, and Robinson 2005; Bratten and Hulse 2016; Hoopes 2018). By utilizing and validating a new measure of tax policy uncertainty, we are able to provide broad evidence on how tax policy uncertainty influences analysts and managers.
Corporate Social Responsibility and Tax Management: The Moderating Effect of Beliefs about Corporate Tax Duty
Ann Boyd Davis, Rebekah D. Moore, and Timothy J. Rupert
Prior literature (Dowling 2014) suggests that a key question that has yet to be addressed is whether the obligation to pay the corporate income tax is considered to be a fundamental aspect of corporate social responsibility (CSR). Further, if it is considered to be an aspect of CSR, how it relates to other aspects of CSR is an additional question that needs to be addressed. Relying on Avi-Yonah's (2005, 2009, 2014) theories of the corporation, we address the call to determine how paying corporate taxes is viewed in relation to CSR by analyzing investors' perceptions of firm-level CSR performance. More importantly, we also develop a measure to capture individual beliefs about the corporate duty to pay (or minimize) taxes. We then use this measure in a model that explores how an investor's individual beliefs about the corporate duty to pay (or minimize) taxes influences his/her perceptions of managerial quality, and thus his/her willingness to invest.
To investigate these issues, we conduct an experiment with MBA students. We find that the company's tax management is negatively related to participants' assessments of the company's CSR, suggesting that, on average, participants consider paying taxes to be a socially responsible activity. When we measure the extent of participants' individual beliefs about the corporate duty to pay (minimize) taxes, descriptive statistics on this measure confirm that participants adhere more strongly to the belief that corporations should pay a fair share of taxes than to the view that corporations have a duty to minimize taxes.
In additional experimental conditions, we include information about both tax management and the firm's performance in a non-tax CSR issue, and our results suggest both tax management and performance in a non-tax CSR issue affect perceived managerial quality, which in turn impacts the investor's willingness to invest. In this model, the individual beliefs about the corporate tax duty also moderates the relationship between tax management and perceived managerial quality. These results demonstrate that investors' beliefs about the corporate tax duty influence the role of tax management in investing behavior.
These findings make several contributions to the developing literature that investigates the interplay between taxes and CSR. First, we contribute to this literature by examining a different perspective, the investor perspective, that so far has received limited attention in the literature. Most of the prior literature has focused on managerial actions and the association between CSR and tax management by examining the actions and decisions of the firm. Second, by investigating the decisions of individual investors, we contribute to the CSR literature by showing that the investor's view of the corporation's tax duty moderates the relation between tax management and perceptions of managerial quality, which ultimately impacts investors' willingness to invest.
Master Limited Partnership Research in Accounting, Economics, and Finance
Aaron J. Mandell
Master limited partnerships (“MLPs”) are limited partnerships or limited liability companies with ownership units that are traded on public exchanges. MLPs have long been of interest to researchers in accounting, economics, and finance, both because of the MLP's status as an economically significant organizational form in its own right, and because MLPs provide a unique and fruitful setting for examining questions of broad interest in financial economics. In the former case, researchers have examined an array of topics related to the formation and operation of MLPs, including the valuation effects of MLP formation and their determinants (tax versus non-tax benefits, for example), the determinants of divestiture form choice (spin-off versus carve-out), and the operating performance of MLPs and their corporate parents. In the latter case, researchers have exploited the MLP's status as a publicly-traded partnership with pass-through tax treatment as a means of testing predictions on the role of taxes in the choice of organizational form, in determining capital structure, and in the valuation effects of payout policy, among others.
In this paper, I review the research on master limited partnerships in the accounting, economics, and finance literature. I begin by providing institutional background on the structure, taxation, ownership, and governance of master limited partnerships. Next, I describe the various sources from which MLP data are derived and the challenges associated with studying MLPs. I then review the extant research on MLPs, organizing it into four broad categories: (1) taxes and organizational form; (2) taxes, capital structure, and payout policy; (3) valuation; and (4) governance research. Within each section, I present possible avenues for future research and, where applicable, highlight non-MLP research which may bring additional color to the subject matter.
Such a review is timely for several reasons. First, the recent passage of the Tax Cuts and Jobs Act of 2017 renders the MLP a useful setting for the renewed study of the effects of tax changes on organizational form and capital structure choice. Next, the study of MLP governance provisions could provide a window into the consequences of their recent spread into other organizational forms (e.g., REITs, venture capital backed start-ups, and tech corporations like Snapchat and Facebook). Finally, the recent wave of MLP reversions to the corporate form provides a new opportunity for researchers to examine the value relevance of restructuring decisions related to master limited partnerships.
Investor Taxes and Option Prices
Paul D. Mason and Steven Utke
We examine whether tax-sensitive investors play a significant role in options markets by examining whether option prices reflect investor taxes. Existing empirical option pricing literature ignores taxes. Whether option prices reflect investor taxes is an open empirical question due to the fact that options markets fundamentally differ from equity markets, where research generally finds evidence of investor tax effects, because the vast majority of options market participants are dealers who should not consider taxes (Scholes 1976).
We exploit a unique setting where “index” options on the S&P 500 Index (SPX) and nearly identical “non-index” options on the exchange traded fund (ETF) tracking the S&P 500 Index (SPY) face different tax treatments. We find that higher investor taxes reduce option prices, indicating tax capitalization in options. We find consistent results when analyzing options around the investor tax changes enacted by the American Taxpayer Relief Act (ATRA) of 2012, and for options on stock indices other than the S&P 500 (e.g., Russell 2000). Altogether, our findings provide new evidence of an additional item—investor taxes—influencing option prices, suggesting that tax-sensitive investors play a non-trivial role in options markets and that taxes warrant consideration in broader options research. We also highlight several areas where overlooking taxes could lead to incorrect or incomplete conclusions in existing options research.
Big Data Analytics in IRS Audit Procedures and Its Effects on Tax Compliance: A Moderated Mediation Analysis
Erica L. Neuman and Robert J. Sheu
This study investigates taxpayer response to the IRS' use of Big Data analytics in audit procedures. The use of Big Data to supplement traditional data collected for IRS audit selection has dual benefits—the opportunity to better capture noncompliance, and the ability to do so by use of artificial intelligence (AI) and machine learning, requiring fewer costly manpower hours.
The IRS already uses advanced technologies to plot relationships among participants in business deals, create heat maps identifying concentrations of non-filers, and test which combinations of contacts are most likely to procure payment. The IRS collects both publicly available data from social media sites such as Facebook and Twitter and holds contracts with data-mining firms to provide the agency with data necessary to functionalize these technologies (Houser and Sanders 2017; Rubin 2020). Though new technologies and data help the IRS to collect revenue more efficiently, the IRS has been criticized on lack of notice to taxpayers, lack of transparency in the algorithms, and privacy concerns (Houser and Sanders 2017).
This study experimentally examines individual taxpayer compliance in response to the IRS' use of Big Data analytics in audit procedures. Deterrence theory suggests that the improvement in audit effectiveness will increase compliance but does not recognize in its model the behavioral factors of compliance and, specific to this context, taxpayer perceptions of procedural fairness at the IRS. We test a moderated mediation model examining the mediating role of procedural fairness on the relationship between IRS audit procedures and tax compliance at varying levels of participatory monitoring, which captures how effects vary when participants willingly increase traceability of their income by advertising online. We manipulate IRS audit procedures at two levels: basic technologies, including traditional audit procedures such as document matching, and advanced technologies, including the use of AI and machine learning to analyze new sources of Big Data. Further, we examine how individuals may comply and assess the fairness of the IRS' use of Big Data analytics in their audit procedures differently corresponding to whether participants engage in participatory monitoring. We manipulate how contract income is earned by the taxpayer at two levels: non-participatory, where income was advertised word-of-mouth and thus taxpayers did not increase traceability of their income, and participatory, where income was advertised by publishing on various social media platforms and thus taxpayers did increase the traceability of their income.
We find evidence supporting a moderated mediation model where procedural fairness mediates the relationship between audit procedures and tax compliance, moderated by participatory monitoring, which captures how effects vary when taxpayers willingly increase traceability of their income by advertising online. When taxpayers advertise business online, use of advanced technologies in audit selection significantly increases compliance with no significant effect on perceived fairness; when they do not, use of advanced technologies has no effect on compliance, but significantly decreases perceived fairness. Though an increase in tax compliance and tax collections is clearly the goal of the IRS' use of Big Data analytics, the IRS should be aware of the unintended consequences of such procedures on tax morale, particularly as research has documented a negative association between perceptions of fairness and tax compliance (Niesiobędzka 2014). We also contribute to the literature on tax compliance by identifying how fairness can moderate the effectiveness of deterrence efforts.
Market and Firm Reaction to Targeted Tax Benefits: Evidence from the Tax Reform Act of 1986
Jennifer Luchs-Nuñz, George A. Plesko, and Steven Utke
This paper extends the literature on targeted tax benefits by examining market and firm reactions to a rifle-shot transition rule (RSTR) in the Tax Reform Act of 1986 (TRA86) that provided a tax refund to large, but poorly performing, steel firms. This refund, granted only to certain qualifying firms in the steel industry, averaged 15 percent of recipient firms' market value. Overall, we find that tax benefits granted to significant but struggling firms generate limited economic benefits to those firms, underscoring the importance of firms' specific circumstances on the economic effects of targeted tax benefits.
We first test the market response to the steel RSTR around key dates in the TRA86 legislative process using the multivariate regression model from Schipper and Thompson (1983). Relative to steel firms not receiving the refund, we find a negative market reaction around (1) the first public mention of the steel RSTR, and (2) approval of the conference committee bill. We find no significant response when the bill's text, including the complete details of the steel RSTR, became publicly available shortly before the bill's final passage. Although the RSTR provided a significant cash infusion for qualifying firms, the market response findings suggest that investors did not view the refund as meaningfully improving these firms' chance of success.
We next examine how qualifying firms used the proceeds from the refund. Using a difference-in-differences analysis, we test whether qualifying steel firms adjust their capital expenditures, cash holdings, debt, shareholder payout, acquisitions, or employment following the RSTR, compared to steel firms not receiving the refund. We find that qualifying firms use the proceeds to pay down debt, but we do not find reliable evidence that firms used the refund for other tested uses. This result is consistent with the financial distress of the qualifying firms, in particular, and the downward trends in the overall U.S. steel industry at the time.
While prior studies on targeted tax benefits often implicitly focus on provisions for successful or growing firms, the steel RSTR setting allows us to examine the effects of a targeted tax benefit for large but poorly performing firms. The negative or muted market reactions, together with qualifying firms' use of the refund to pay down debt, highlight the importance of considering specific economic circumstances when evaluating the economic effects of a targeted tax benefit.