Earnings Implications Research Articles

10‐K complexity, analysts' forecasts, and price discovery in capital markets

AbstractThis paper examines the behaviour of stock prices and analysts' earnings forecasts following firms' increasingly complex 10‐K filings. Our evidence suggests that greater information uncertainty outweighs greater analyst ability, and the net effect drives greater underreaction in analysts' earnings forecasts following the release of more complex 10‐Ks. Further analysis suggests that analyst underreaction mitigates market overreaction to the information in low‐complexity 10‐K filings, and overwhelms market overreaction to the information in high‐complexity 10‐K filings thus compromising price discovery of the earnings implications of more complex 10‐Ks.

Taxes in video games: overview, purposes, relevance

Taxation and video games are intertwined and affect each other: businesses and players are affected by tax legislation while taxes are, in turn, represented in video games and virtual environments. This article addresses the representation and relevance of taxation in the video game environment, its design, and assessment from a tax perspective. Here we show that video game companies often misrepresent taxes in video games, depicting them as unjustified obligatory payments without a fiscal nature. Such misrepresentations entail negative connotations for users devaluing the taxation concept. Thus, video games design should embed taxation in virtual economies in a more accurate manner. Also, the article outlines how in-games taxation may overlap with real-life tax obligations of players. There is no common position on tax implications of earnings in virtual environments among legislators and researchers. Currently, the gaming industry catches up with technological developments very fast and often promotes them. It will cause more tax issues related to activities in the virtual environments in the future. Thus, these issues should be addressed in a timely manner.

Real earnings management and the properties of analysts' forecasts

Prior literature generally finds analysts are able to identify and process complex financial information. However, research suggests that in certain settings, analysts struggle to fully incorporate into their forecasts all available information. We examine analysts' forecast properties in the face of a specific type of complex financial information: real earnings management (REM). First, we investigate the relation between measures of REM and analysts' forecast properties. We find REM measures are associated with greater forecast error and dispersion in the following year. However, REM measures, by definition, capture abnormal operating results, and thus include both firms engaging in manipulative REM as well as firms experiencing firm-specific economic shocks. Thus, we conduct cross-sectional tests of analysts' forecasts for firms with and without incentives to manipulate earnings. We find that firms with low incentives to engage in earnings management (i.e., firms most likely experiencing firm-specific economic shocks) generate the strongest positive relation between REM measures and the following year's analysts' forecast properties, suggesting analysts more fully incorporate the earnings implications of firms with high incentives (i.e., firms most likely engaging in manipulative REM). Our results are consistent across numerous REM proxies and indicators of earnings management incentives.

Can simple advice eliminate the gender gap in willingness to compete?

As a recent literature has demonstrated, men and women differ in their willingness to sort into competitive environments. In particular, men are more willing than women to compete. We investigate whether it is possible to reduce the gender gap in willingness to compete through an information intervention that informs participants of the gap and advises them about the potential earnings implications. We find that this simple information intervention reduced the gender gap, both in a laboratory study at a German university and in a field study with Swedish high school students. Whereas some participants (primarily high-performing women) benefited from the intervention, others lost out. We discuss the implications for efficiency and policy.

A new approach to estimating earnings forecasting models: Robust regression MM-estimation

This study focuses on the impact of model estimation methods on earnings forecast accuracy. Compared with an ordinary least squares (OLS) regression combined with winsorization, robust regression MM-estimation improves the earnings forecast accuracy of all the models examined, especially for those with more variables. My findings indicate that the impact of outliers on the OLS regression increases with the number of variables in the models, alerting researchers who use OLS regressions for forecasting. My findings explain the puzzling negative relationship between earnings forecast accuracy and the number of model variables in prior research. Moreover, I demonstrate the valuation implications of earnings forecasted using robust regression MM-estimation. This study contributes to earnings forecasting, valuation, and influential observation treatment in forecasting.

A New Approach to Estimate Earnings Forecasting Models: MM-estimation

This study focuses on the impact of model estimation methods on earnings forecast accuracy. Compared with an ordinary least squares (OLS) regression combined with winsorization, robust regression MM-estimation improves the earnings forecast accuracy of all the models examined, especially for those with more variables. My findings indicate that the impact of outliers on the OLS regression increases with the number of variables in the models, alerting researchers who use OLS regressions for forecasting. My findings explain the puzzling negative relationship between earnings forecast accuracy and the number of model variables in prior research. Moreover, I demonstrate the valuation implications of earnings forecasted using robust regression MM-estimation. This study contributes to earnings forecasting, valuation, and influential observation treatment in forecasting. Forthcoming in the International Journal of Forecasting

Hedging, Hedge Accounting, and Earnings Predictability

Studies suggest that, pursuant to the implementation of SFAS 133, even sophisticated users of financial statements find it difficult to comprehend earnings implications of hedging derivatives. Moreover, due to stringent hedge accounting requirements under these standards, many economic hedges do not qualify for hedge accounting and are deemed “ineffective” for financial reporting purposes. Motivated by these considerations, we investigate the impact of hedging on earnings predictability by analyzing hand-collected hedging data from two industries that extensively use derivatives to manage price risks: the oil-and-gas exploration and production industry and the airline industry. In contrast to extant evidence, we find that overall hedging derivatives improve income predictability and increase (decrease) analysts’ forecast accuracy (dispersion). We also show hedges deemed ineffective for hedge accounting can increase earnings volatility and significantly impair earnings predictability. This finding lends support to concerns expressed by some corporate managers and industry experts against stringent hedge accounting requirements.

Implications of Non-GAAP earnings for real activities and accounting choices

Managers almost always define non-GAAP earnings to exclude the effects of acquisition and restructuring expenses, the amortization of intangibles, and impairments. I find that managers with a history of reporting non-GAAP earnings act as if they place lower weight on these excluded expenses when making real activities and accounting choices. They pursue more and larger acquisitions, have higher total capital investment, are more likely to restructure, and are more likely to recognize discretionary impairments. In a difference-in-differences setting, I find that non-GAAP reporting firms are less likely to alter their restructuring activities following a significant change in accounting rules for restructuring expense recognition. Finally, in supplementary analyses, I find that non-GAAP-reporting firms tend to repeat these real activities and accounting choices year-after-year, resulting in more persistent special-item expenses.

CEO Turnover and Accounting Earnings: The Role of Earnings Persistence

Although earnings persistence should have a nontrivial impact on chief executive officer (CEO) turnover decisions, prior studies have paid little attention to the role of earnings persistence in CEO turnover decisions. This study examines the effect of earnings persistence on the sensitivity (i.e., the negative relation) of CEO turnover to earnings performance. First, we find that the sensitivity of forced CEO turnovers to earnings performance is greater when earnings are more persistent. We also show that among numerous earnings attributes, earnings persistence is the most direct and dominant attribute in explaining CEO turnover-earnings sensitivity. Further, when the effect of earnings persistence on CEO compensation-earnings sensitivity is weak, the effect of earnings persistence on CEO turnover-earnings sensitivity is stronger, suggesting that the executive discipline system substitutes for the compensation system when earnings persistence is neglected by compensation policies. Overall, our findings suggest that earnings persistence plays a crucial role in CEO turnover decisions by elevating the board’s knowledge on the future performance implications of current earnings. Finally, the role of persistence is even more crucial when it is neglected by executive compensation policies. This paper was accepted by Shiva Rajgopal, accounting.

Investor Overreaction to Earnings Surprises and Post‐Earnings‐Announcement Reversals

ABSTRACTPrior literature suggests that the market underreacts to the positive correlation in a typical firm's seasonal earnings changes, which leads to a post‐earnings‐announcement drift (PEAD) in prices. We examine the market reaction for a distinct set of firms whose seasonal earnings changes are uncorrelated and show that the market incorrectly assumes that the earnings changes of these firms are positively correlated. We also document that positive (negative) seasonal earnings changes in the current quarter are associated with negative (positive) abnormal returns in the next quarter. Thus, we observe a reversal of abnormal returns, consistent with a systematic overreaction to earnings, rather than the previously documented PEAD. Additional analysis indicates that financial analysts similarly overestimate the autocorrelation of these firms, although to a lesser extent. We also find that the magnitude of overestimation and the subsequent price reversal are inversely related to the richness of the information environment. Our results challenge the notion that investors recognize but consistently underestimate earnings correlation and provide a new perspective on the inability of prices to fully reflect the implications of current earnings for future earnings. That is, we show that investors predictably overestimate correlation when it is lacking, but underestimate it when it is present.

Inventory Policy Choice and Cost of Debt: A Private Debtholders’ Perspective

Prior research suggests that last-in-first-out (LIFO) inventory policy produces higher accruals quality than first-in-first-out (FIFO), leading to lower information risk for LIFO firms. Equity investors, in turn, price lower information risk by giving a premium to LIFO firms. Prior research also suggests that LIFO inventory policy, by understating aggregate earnings and net assets, creates hidden reserves that can be released to produce higher future earnings. Prior research, however, is silent on how debtholders price inventory policy choice. Focusing on private debtholders, we explore three research questions: (a) Do private debtholders price LIFO differently from FIFO? (b) If so, how does downside risk affect the pricing of LIFO? and (c) What is the underlying reason for the pricing effect, accounting quality, or hidden reserves? First, we find that LIFO is associated with a lower loan spread than FIFO. Not surprisingly, the pricing effect of LIFO is larger in high-inflation years than in other years. Second, we find that the pricing effect of LIFO is much larger for unrated firms than for rated firms. Third, we find that the negative association between LIFO and loan spread is driven primarily by hidden LIFO reserves rather than accounting quality. Overall, our evidence shows that inventory policy choice affects private debtholders’ pricing decisions, and this effect is primarily due to future earnings implications of hidden LIFO reserves.

The market pricing of negative special items through time: an unintended consequence of regulation change?

Prior research concludes that the implications of negative special items (NSIs) for future earnings are more fully reflected than earnings before NSIs. Our evidence suggests that US regulatory changes resulted in dramatic increases (decreases) in NSI reporting frequency (magnitude). We find that the advantage in pricing NSIs relative to other components of earnings disappears for the average firm post-regulation and for high frequency NSI reporters regardless of time period. Our evidence suggests that regulations governing the financial reporting of NSIs resulted in unintended consequences by impairing the ability of market participants to understand the future earnings implications of these items.

Research and Development Expense and Analyst Forecast Errors: An Underestimation of Sales or Overestimation of Expenses?

We test whether analysts adequately incorporate the implications of research and development (R&D) activities into their forecasts by observing the relation between R&D expense and future forecast errors for earnings, sales, and expenses. We find that analysts systematically underestimate the future earnings implications of R&D, and that this underestimation of earnings is attributable to an overestimation of future expenses rather than an underestimation of future sales. We further find that our results are driven by firms with high fixed costs and high sales growth, which suggests that analysts, on average, assume that costs vary proportionally with sales in high R&D firms perhaps due to the difficulties in separating fixed and variable costs in most financial statements.

Do Financial Analysts Fully Incorporate the Future Earnings Implications of Really Dirty Surplus into Their Earnings Forecasts?

This paper investigates whether sell-side equity analysts fully incorporate the future earnings implications of really dirty surplus (RDS) into their earnings forecasts. RDS refers to gains or losses from contingent equity transactions settled at prices other than the fair value. We find that analysts’ earnings forecasts are over-optimistic for firms with large RDS losses, RDS over-optimism is lower for firms with higher analyst following, and the over-optimism carries over to stock recommendations. Our findings suggest that the lack of fair value information in accounting records about the off-market settlement drives the RDS-related analyst over-optimism.

Do analysts understand the economic and reporting complexities of derivatives?

We investigate whether and how the complexity of derivatives influences analysts׳ earnings forecast properties. Using a difference-in-differences design, we find that, relative to a matched control sample of non-users, analysts׳ earnings forecasts for new derivatives users are less accurate and more dispersed after derivatives initiation. These results do not appear to be driven by the economic complexity of derivatives, but rather the financial reporting of such economic complexity. Overall, despite their financial expertise, analysts routinely misjudge the earnings implications of firms׳ derivatives activity. However, we find evidence that a series of derivatives accounting standards has helped analysts improve their forecasts over time.

Do Analysts Understand the Economic and Reporting Complexities of Derivatives?

We investigate whether and how the complexity of derivatives influences analysts’ earnings forecast properties. Using a difference-in-differences design, we find that, relative to a matched control sample of non-users, analysts’ earnings forecasts for new derivatives users are less accurate and more dispersed after derivatives initiation. These results do not appear to be driven by the economic complexity of derivatives, but rather the financial reporting of such economic complexity. Overall, despite their financial expertise, analysts routinely misjudge the earnings implications of firms’ derivatives activity. However, we find evidence that a series of derivatives accounting standards has helped analysts improve their forecasts over time.

Aggregate earnings and why they matter

The accounting literature has traditionally focused on firm-level studies to examine the capital market implications of earnings and other accounting variables. We first develop the arguments for studying capital market implications at the aggregate level as well. A central issue is that diversification makes equity investors at least partially and potentially almost completely immune to several firm-level properties of earnings by holding diversified portfolios. Diversification is particularly important when assessing the welfare consequences of random errors in accounting measurement (imperfect accruals) and, to the extent it is independent across firms, of deliberate manipulation (earnings management). Consequently, some firm-level metrics of association, timeliness, value relevance, conservatism and other earnings properties do not map easily into investor welfare. Similarly, earnings-related risk manifests itself to equity investors largely through systematic earnings risk (covariation with aggregate earnings and/or other macroeconomic indicators). We conclude that the design and evaluation of financial reporting must adopt at least in part an aggregate perspective. We then summarize the literature in accounting, economics and finance on aggregate earnings and stock prices. Our review highlights the importance of studying earnings at the aggregate level.

EBITDA Disclosure and Overinvestment in Capital

This paper investigates the association between firms’ EBITDA reporting practices in earnings announcements and their capital investment decisions. I find that firms that include EBITDA in their earnings announcements over-invest in capital, are smaller, and have lower market-to-book ratios and lower profitability than non-EBITDA-reporting firms. These results are not explained by opportunistic disclosure behavior. Specifically, the results provide little evidence that firms report EBITDA specifically when the EBITDA metric shows superior performance. The paper contributes to the prior literature in various ways. First, these results suggest that managers’ reliance on EBITDA leads them to overinvest, which is a form of real earnings management that – to the extent that it exists – is sustainable in a steady state as long as EBITDA is considered an appropriate performance measure. In addition, this paper provides new evidence on the inferior characteristics and implications of non-GAAP earnings. Lastly, the paper provides evidence that in contrast with prior literature, which claims that managements report opportunistically.

The drivers, consequences and policy implications of non-GAAP earnings reporting

Non-generally accepted accounting principles (GAAP) (pro forma) earnings form an increasingly important part of firms’ performance reporting narrative. This paper reviews the academic and professional debate surrounding non-GAAP earnings reporting by management. I argue that the demand for customised performance reporting is a natural response to constraints imposed by a one-size-fits-all reporting system and that the non-GAAP phenomenon forms part of a long-standing debate over the definition and presentation of periodic performance. A review of extant research suggests non-GAAP disclosures are driven by informative reporting and opportunistic motives. Opaque presentation of non-GAAP earnings is associated with earnings mispricing, particularly among unsophisticated investor groups. Regulations and governance systems designed to ensure transparency are associated with higher quality disclosures and less mispricing. While customised reporting behaviour is evident in many settings, I argue that such disclosures create particular risks in a financial reporting context because they threaten the integrity of the underlying reporting system. Prevailing regulatory approaches are reviewed and factors limiting disclosure transparency are highlighted. The paper concludes with suggestions for further research.

Discussion of ‘The drivers, consequences and policy implications of non-GAAP earnings reporting’ by Steven Young (2014)

Discussion of ‘The drivers, consequences and policy implications of non-GAAP earnings reporting’ by Steven Young (2014)