Mark Thomas Bradshaw

Ownership Structure and Tax Avoidance: Evidence from Agency Costs of State Ownership in China

In state owned enterprises (SOEs), taxes are a dividend to the controlling shareholder, the state, but a cost to other shareholders. We examine publicly traded firms in China and find significantly lower tax avoidance by SOEs relative to non-SOEs. The differences are pronounced for locally versus centrally-owned SOEs and during the year of SOE term performance evaluations. We link our results to managerial incentives through promotion tests, finding that higher SOE tax rates are associated with higher promotion frequencies of SOE managers. Our results suggest managerial incentives and tax reporting are conditional on the ownership structure of the firm.

Financial Analysts and Their Contribution to Well-Functioning Capital Markets

Well-functioning capital markets rely on a complex set of institutions and participants that ensure capital is allocated to its best possible use, and that information flows between firms receiving capital and the investors who provide it. In this manuscript, we endeavor to understand whether, how, and under what circumstances sell-side research contributes to the functioning of capital markets. We review major findings in the literature, address significant regulatory and technological changes, and offer suggestions for future research.

The Effects of Analyst-Country Institutions on Biased Research: Evidence from Target Prices

Prior research demonstrates that a strong institutional infrastructure in a country moderates self‐serving behavior of market participants. Cross‐country economic activities have increased significantly, presenting a research opportunity to examine the relative influence of local versus foreign institutional infrastructure on individual market participants. We utilize variation in analyst‐country location relative to covered firm location to examine institutional determinants of optimism in analyst research. Focusing on target prices, where persistent optimism is well documented, we find that analysts domiciled in countries with stronger institutional infrastructures exhibit significantly attenuated target price optimism and more value‐relevant target prices. Our results demonstrate the importance of domestic country‐level institutional factors in moderating self‐serving behavior of market participants engaged in cross‐country activities.

Investor Preference and Manager Motivation for Non-GAAP Earnings: Correcting for Measurement Error in Empirical Research

We examine analysts’ GAAP earnings forecasts and illustrate their usefulness in two prominent research settings. First, we find that the availability of GAAP forecasts has increased dramatically since 2003, and they are now available for most I/B/E/S-covered firms. Next, we utilize GAAP forecasts to solve important measurement error problems in prior research that attempts to examine GAAP forecast errors without an explicit GAAP forecast. We begin with research exploring investors’ preferences for GAAP versus non-GAAP earnings. We find that traditionally-identified GAAP forecast errors are subject to 37% measurement error. Nevertheless, in contrast to the pervasive caveats in the non-GAAP literature, evidence of an investor preference for non-GAAP earnings relative to GAAP earnings is robust after correcting for this measurement error. Second, we revisit the literature identifying firms that use non-GAAP exclusions to meet or beat analysts’ forecasts when GAAP earnings fall short of expectations. We find that 34% of the traditionally-identified meet-or-beat firms are misidentified due to measurement error and this misidentification masks the inference that firms more frequently exclude transitory expenses rather than recurring expenses for meet-or-beat purposes.This study examines how measurement error in earnings expectations affects prior evidence regarding (1) investors’ preferences for GAAP versus non-GAAP earnings and (2) the quality of non-GAAP reporting in meet-or-beat settings. Prior research on non-GAAP reporting computes earnings surprises for both GAAP and non-GAAP earnings relative to analysts’ non-GAAP earnings forecasts. As a result, GAAP earnings surprises are subject to measurement error due to the use of a misaligned earnings expectation. Many studies highlight this measurement error problem and caution that evidence of an investor preference for non-GAAP earnings might simply be due to the mechanical error in GAAP surprises, which creates statistical bias in favor of non-GAAP earnings. Utilizing newly available GAAP forecasts, we find that the traditional GAAP earnings surprise is comprised of 60% measurement error, on average. Nevertheless, we find that the impact of this form of measurement error on inferences regarding investors’ preferred earnings metric is small, and provide evidence that the reason the impact is small is that the components measured with error have low persistence. Next, we examine how measurement error influences inferences regarding the use of non-GAAP exclusions to meet-or-beat analysts’ forecasts. Contrary to prior evidence, after we correct for measurement error, we find that the non-GAAP disclosures of benchmark-beating firms are of lower quality than those of other non-GAAP reporters.

Analyst Dividend Forecasts and Their Usefulness to Investors: International Evidence

Recent finance and accounting studies indicate that dividends are ‘sticky’ and declining in economic importance. If so, there should be little investor demand for analyst dividend estimates and analyst dividend forecasts should simply mirror time-series estimates. We examine firms from 16 countries spanning 2000-2013 and find that only 25% of firms exhibit sticky dividends, while the majority either increase (54%) or decrease (21%) their annual dividends. In contrast to the disappearing dividends view, we predict that this high variability in dividend payments across stocks actually increases investor demand for dividend information. Accordingly, analysts respond to this demand by producing informative dividend forecasts. Our analysis indicates that analysts’ dividend estimates are indeed useful to investors because they (i) are more accurate and better aligned with market dividend expectations than other estimates, such as standard time-series modelling approaches, (ii) convey incremental information to the market beyond that contained in other fundamentals, and (iii) help investors interpret the persistence of earnings news.