The Interactive Role of Difficulty and Incentives in Explaining the Annual Earnings Forecast Walkdown

2016 ◽  
Vol 91 (4) ◽  
pp. 995-1021 ◽  
Author(s):  
Mark T. Bradshaw ◽  
Lian Fen Lee ◽  
Kyle Peterson
Keyword(s):  
Interactive Effect ◽  
Earnings Forecasts ◽  
Data Availability ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Regression Analyses ◽  
Strategic Incentives ◽  
Psychology Literature ◽  
Annual Earnings

ABSTRACT The within-year walkdown of analysts' earnings forecasts has largely been attributed to analysts' incentives to curry favor with managers. We appeal to cognitive psychology literature on motivated reasoning and propose that forecasting difficulty interacts with such incentives to yield the observed walkdown. Higher forecasting difficulty generates a wider range of outcomes from which analysts can justify optimistically biased forecasts. In regression analyses, we find that the interaction between analysts' incentives for optimism and difficulty exhibits the strongest effect on earnings walkdowns. We also examine revenue forecasts as a benchmark of lower forecasting difficulty and find that revenue walkdowns are relatively diminutive. However, when analysts forecast losses, revenue forecasts are more critical and exhibit markedly steeper walkdowns. Our results suggest that analyst forecast walkdowns are better characterized by an interactive effect between analysts' strategic incentives for optimism and forecasting difficulty. JEL Classifications: G17; M41. Data Availability: Data are available from public sources identified in the text.

scholarly journals The Determinants of Access to Sanitation: The Role of Human Rights and the Challenges of Measurement

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1676
Author(s):  
Rebecca Schiel ◽  
Bruce M. Wilson ◽  
Malcolm Langford
Keyword(s):  
Sustainable Development ◽  
Human Rights ◽  
Field Data ◽  
Data Availability ◽  
Regression Analyses ◽  
Human Right ◽  
Sustainable Development Goal ◽  
Development Goal ◽  
The Sustainable Development

Ten years after the United Nation’s recognition of the human right to water and sanitation (HRtWS), little is understood about how these right impacts access to sanitation. There is limited identification of the mechanisms responsible for improvements in sanitation, including the international and constitutional recognition of rights to sanitation and water. We examine a core reason for the lack of progress in this field: data quality. Examining data availability and quality on measures of access to sanitation, we arrive at three findings: (1) where data are widely available, measures are not in line with the Sustainable Development Goal (SDG) targets, revealing little about changes in sanitation access; (2) data concerning safe sanitation are missing in more country-year observations than not; and (3) data are missing in the largest proportions from the poorest states and those most in need of progress on sanitation. Nonetheless, we present two regression analyses to determine what effect rights recognition has on improvements in sanitation access. First, the available data are too limited to analyze progress toward meeting SDGs related to sanitation globally, and especially in regions most urgently needing improvements. Second, utilizing more widely available data, we find that rights seem to have little impact on access.

Discussion: “Dispersion in Analysts' Earnings Forecasts as a Measure of Uncertainty”

1998 ◽  
Vol 13 (3) ◽  
pp. 271-274 ◽  
Author(s):  
Lawrence D. Brown
Keyword(s):  
Stock Price ◽  
Annual Report ◽  
Earnings Forecasts ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Data Set ◽  
Forecast Dispersion ◽  
Forecast Revision ◽  
Analyst Earnings ◽  
The Impact

This paper tackles an interesting question; namely, whether dispersion in analysts' earnings forecasts reflects uncertainty about firms' future economic performance. It improves on the extant literature in three ways. First, it uses detailed analyst earnings forecast data to estimate analyst forecast dispersion and revision. The contrasting evidence of Morse, Stephan, and Stice (1991) and Brown and Han (1992), who respectively used consensus and detailed analyst data to examine the impact of earnings announcements on forecast dispersion, suggest that detailed data are preferable for determining the data set on which analysts' forecasts are conditioned. Second, it relates forecast dispersion to both analyst earnings forecast revision and stock price reaction to the subsequent earnings announcement. Previous studies related forecast dispersion to either analyst forecast revision (e.g., Stickel 1989) or to subsequent stock price movements (e.g., Daley et al. [1988]), but not to both revision and returns. Third, it includes the interim quarters along with the annual report. In contrast, previous research focused on the annual report, ignoring the interims (Daley et al. [1988]).

Meeting Individual Analyst Expectations

2014 ◽  
Vol 89 (6) ◽  
pp. 2203-2231 ◽  
Author(s):  
Marcus P. Kirk ◽  
David A. Reppenhagen ◽  
Jennifer Wu Tucker
Keyword(s):  
Private Information ◽  
Explanatory Power ◽  
Analyst Forecasts ◽  
Data Availability ◽  
Analyst Forecast ◽  
Analyst Expectations ◽  
Management Literature ◽  
Two Measures ◽  
Reported Earnings

ABSTRACT The expectations management literature has so far focused on firms meeting the analyst consensus forecast—the expectations of analysts as a group—at earnings announcements. In this study we argue that investors may use individual analyst forecasts as additional benchmarks in evaluating reported earnings because the consensus forecast underutilizes private information contained in individual analyst forecasts. We predict that measures reflecting such private information have incremental explanatory power over the consensus forecast for the market's reaction to earnings news. We find results consistent with this prediction by examining two measures: (1) the percentage of individual forecasts met and (2) meeting the key analyst forecast. We extend the literature by documenting the role of individual analyst forecasts in investors' evaluations of reported earnings. JEL Classifications: G10; G11; G17; G14; G24. Data Availability: Data are publicly available from the sources identified in the paper.

How Disaggregated Forecasts Influence Investor Response to Subsequent Earnings Announcements

2019 ◽  
Vol 4 (1) ◽  
pp. 157-171
Author(s):  
Shana M. Clor-Proell ◽  
D. Eric Hirst ◽  
Lisa Koonce ◽  
Nicholas Seybert
Keyword(s):  
Earnings Announcements ◽  
Earnings Forecasts ◽  
Data Availability ◽  
Earnings Forecast ◽  
Multiple Points ◽  
Earnings Announcement ◽  
Carry Over

Firms often issue disaggregated earnings forecasts, and prior research reveals benefits to doing so. However, we hypothesize and experimentally find that the benefits of disaggregated forecasts do not necessarily carry over to the time of actual earnings announcements. Rather, disaggregated forecasts create multiple points of possible comparison between the forecast and the subsequent earnings announcement. Thus, when firms disaggregate forecasts and subsequently release disaggregated actual earnings numbers, investors reward firms that beat those multiple benchmarks, but punish firms that miss those multiple benchmarks. Thus, we show that issuing a disaggregated earnings forecast to achieve the associated benefits can backfire after the announcement of actual earnings. Our results have implications for researchers and firm managers. Data Availability: Contact the authors.

Recommendation-Forecast Consistency and Earnings Forecast Quality

2013 ◽  
Vol 27 (3) ◽  
pp. 451-467 ◽  
Author(s):  
Lawrence D. Brown ◽  
Kelly Huang
Keyword(s):  
Earnings Forecasts ◽  
Firm Valuation ◽  
Data Availability ◽  
Earnings Forecast ◽  
Market Reactions ◽  
Stock Recommendations ◽  
Ex Ante ◽  
Forecast Quality

SYNOPSIS: We investigate the implications of recommendation-forecast consistency for the informativeness of stock recommendations and earnings forecasts and the quality of analysts' earnings forecasts. Stock recommendations and earnings forecasts are often issued simultaneously and evaluated jointly by investors. However, the two signals are often inconsistent with each other. Defining a recommendation-forecast pair as consistent if both of them are above or below their existing consensus, we find that 58.3 percent of recommendation-forecast pairs are consistent in our sample. We document that consistent pairs result in much stronger market reactions than inconsistent pairs. We show that analysts making consistent recommendation forecasts make more accurate and timelier forecasts than do analysts making inconsistent recommendation forecasts, suggesting that consistent analysts make higher-quality earnings forecasts. We extend the literature on informativeness of analyst research by showing that recommendation-forecast consistency is an important ex ante signal regarding both firm valuation and earnings forecast quality. Investors and researchers can use consistency as a salient, ex ante signal to identify more informative analyst research and superior earnings forecasts. Data Availability: All data are available from public sources.

scholarly journals Are Analysts Overoptimistic about the Prospects of Sin Firms?

2017 ◽  
Vol 8 (4) ◽  
pp. 99 ◽  
Author(s):  
Jin Zhang ◽  
Haeyoung Shin
Keyword(s):  
Stock Price ◽  
Forecast Accuracy ◽  
Earnings Forecasts ◽  
Positive Association ◽  
Negative Association ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Absolute Value ◽  
Forecast Bias ◽  
The Difference

We investigate the association between the bias and accuracy of consensus analysts’ earnings forecasts and whether a firm is a sin firm or not. We measure analyst forecast bias as the difference between the consensus earnings forecast and the actual earnings, scaled by the stock price. We measure analyst forecast accuracy as the negative of the absolute value of the difference between the firms’ forecasted and actual earnings, scaled by the stock price. We find a positive association between the level of forecast optimism and sin firm membership. We find a negative association between the level of forecast accuracy and sin firm membership. Overall, these results imply that analysts tend to issue over-optimistic and less accurate earnings forecasts on sin firms.

Tax-Motivated Loss Shifting

2013 ◽  
Vol 88 (5) ◽  
pp. 1657-1682 ◽  
Author(s):  
Merle M. Erickson ◽  
Shane M. Heitzman ◽  
X. Frank Zhang
Keyword(s):  
Earnings Forecasts ◽  
Data Availability ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Corporate Reporting ◽  
Earnings Surprises ◽  
Reporting Decisions ◽  
Tax Payments ◽  
Tax Loss ◽  
Do So

ABSTRACT: This paper examines the implications of tax loss carryback incentives for corporate reporting decisions and capital market behavior. During the 1981 through 2010 sample period, we find that firms increase losses in order to claim a cash refund of recent tax payments before the option to do so expires, and we estimate that firms with tax refund-based incentives accelerate about $64.7 billion in losses. Tax-motivated loss shifting is reflected in both recurring and nonrecurring items and is more evident for financially constrained firms. Analysts do not generally incorporate tax-motivated loss shifting into their earnings forecasts, resulting in more negative analyst forecast errors for firms with tax-based incentives than for firms without. Holding earnings surprises constant, however, investors react less negatively to losses reported by firms with tax loss carryback incentives. Data Availability: Data are available from sources identified in the paper.

The Influence of Corporate Governance Ratings on Buy-Side Analysts' Earnings Forecast Certainty: Evidence from the United States and the United Kingdom (Retracted)

2011 ◽  
Vol 23 (2) ◽  
pp. 1-25 ◽  
Author(s):  
Kwadwo N. Asare ◽  
Mohammad J. Abdolmohammadi ◽  
James E. Hunton
Keyword(s):  
United States ◽  
Corporate Governance ◽  
United Kingdom ◽  
Earnings Forecasts ◽  
The United States ◽  
Data Availability ◽  
Earnings Forecast ◽  
Seamless Integration ◽  
Average Rating ◽  
The United Kingdom

ABSTRACT The current study investigates how corporate governance ratings affect the certainty of buy-side analysts' earnings forecasts. Nineteen financial analysts from the United States (U.S.) and 17 from the United Kingdom (U.K.) participated in a 1 × 2 (corporate governance ratings: below or above industry average) within-participant experiment. We find that, on average, analysts exhibit more certainty in their range forecasts when the corporate governance rating is above average, relative to below average. We also observe a significant interaction between the corporate governance ratings and country, indicating that U.K. analysts exhibit stronger responses to a below average rating than U.S. analysts, while responses to an above average rating are not significantly different between the two countries. These results suggest a need to investigate cultural or other factors that can impede the seamless integration of national capital markets into a unified global financial network. Data Availability: Available upon request.

scholarly journals The Role of Analysts in Intra-Industry Information Transfer

2013 ◽  
Vol 88 (4) ◽  
pp. 1265-1287 ◽  
Author(s):  
Gilles Hilary ◽  
Rui Shen
Keyword(s):  
Information Transfer ◽  
Earnings Forecasts ◽  
Data Availability ◽  
Forecast Revisions ◽  
Management Forecast

ABSTRACT When a firm issues a management forecast, analysts who have observed more forecasts from this firm since covering it (i.e., have more MF-Experience) subsequently improve their own accuracy more and provide timelier earnings forecasts for other (non-issuing) firms in the same industry. We also find that, subsequent to a management forecast, investors are more responsive to forecast revisions for non-issuing firms made by analysts with more MF-Experience. Further tests suggest that our results are not explained by endogeneity in firm coverage. Data Availability: Data are commercially available.

Types of politically connected firms and analysts' earnings forecast

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khairul Anuar Kamarudin ◽  
Wan Adibah Wan Ismail ◽  
Iman Harymawan ◽  
Rohami Shafie
Keyword(s):  
Information Asymmetry ◽  
Boards Of Directors ◽  
Forecast Accuracy ◽  
Earnings Forecasts ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Content Type ◽  
Thomson Reuters ◽  
Different Types ◽  
The Impact

PurposeThis study examined the effect of different types of politically connected (PCON) Malaysian firms on analysts' forecast accuracy and dispersion.Design/methodology/approachThe study identified different types of PCON firms according to Wong and Hooy's (2018) classification, which divided political connections into government-linked companies (GLCs), boards of directors, business owners and family members of government leaders. The sample covered the period 2007–2016, for which earnings forecast data were obtained from the Institutional Brokers' Estimate System (IBES) database and financial data were extracted from Thomson Reuters Fundamentals. We deleted any market consensus estimates made by less than three analysts and/or firms with less than three years of analyst forecast information to control for the impact of individual analysts' personal attributes.FindingsThe study found that PCON firms were associated with lower analyst forecast accuracy and higher forecast dispersion. The effect was more salient in GLCs than in other PCON firms, either through families, business ties or boards of directors. Further analyses showed that PCON firms—in particular GLCs—were associated with more aggressive reporting of earnings and poorer quality of accruals, hence providing inadequate information for analysts to produce accurate and less dispersed earnings forecasts. The results were robust even after addressing endogeneity issues.Research limitations/implicationsThis study found new evidence of the impact of different types of PCON firms in exacerbating information asymmetry, which was not addressed in prior studies.Practical implicationsThis study has a significant practical implication for investors that they should be mindful of high information asymmetry in politically connected firms, particularly government-linked companies.Originality/valueThis is the first study to provide evidence of the impact of different types of PCON firms on analysts' earnings forecasts.

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