Analyst revenue forecast reporting and the quality of revenues and expenses

• Date: 01 January 2019
• DOI: http://doi.org/10.1111/jbfa.12355
• Published date: 01 January 2019
• Author: Michael Eames,Pawel Bilinski

DOI: 10.1111/jbfa.12355

Analyst revenue forecast reporting and the quality

of revenues and expenses

Pawel Bilinski1Michael Eames2

1CassBusiness School, City, University of

London,London, UK

2SantaClara University, Santa Clara, CA, USA

Correspondence

MichaelEames, Santa Clara University, Santa

Clara,CA 95053, USA.

Email:meames@scu.edu

Abstract

We decompose earnings quality into revenue and expense qual-

ity and examine their associations with analyst propensity to sup-

plement their earnings forecasts with revenue forecasts. Analysts

report more revenue forecasts to I/B/E/S when expense quality is

low to compensate for the low accuracy of their earnings estimates,

which has a positive association with expense quality.Expense qual-

ity is unassociated with revenue forecast accuracy, thus revenue

forecasts become increasingly useful for valuing firms when expense

qualityis low. Analysts report fewer revenue forecasts when revenue

quality is low because both earnings and revenue forecast accuracy

decline as revenue quality deteriorates. Tocontrol for endogeneity,

we use firm-fixed effects to control for unobserved time-invariant

heterogeneity across firms, instrumental variables regressions and

regression in changes.

KEYWORDS

earnings and revenue forecast accuracy, joint earnings and revenue

forecast issues, price reaction, quality of earnings components

1INTRODUCTION

Analysts routinely report their earnings-per-share (EPS) forecasts to I/B/E/S, but complement only some of these with

revenue forecasts.1This study considers the associations of revenue and expense quality with analysts’ propensity

to report revenue forecasts with their EPS forecasts to I/B/E/S. Our intuition is that low revenue and expensequality

increase earnings forecasting difficulties and reduce the accuracy and value relevance of analysts’ EPS forecasts

(Bradshaw, Richardson, & Sloan, 2001; Hughes, Liu, & Su, 2008). This in turn increases investors’ reliance on and

demand for complementary information.2We argue that low quality expenses increase the investordemand for com-

plementary information in the form of revenue forecasts and analysts respond by reporting more revenue forecasts.

1Toillustrate, in our sample of the 853,789 individual analyst earnings forecasts from I/B/E/S over the period 2000–2013, over 55.1% are supplementedby

revenueestimates.

2Revenueforecasts are useful as they permit investors to supplement earnings based valuations with revenue-based assessments and achieve greater accu-

racy(Beatty, Riffe, & Thompson, 1999; and Yoo, 2006). Furthermore, revenue forecasts providean ex -ante check on the quality of EPS forecasts. Specifically,

revenue forecasts enable investorsto decompose EPS forecasts into forecasts of revenues and expenses and pay particular attention to the contribution of

theformer, more persistent component of the earnings forecast (Ertimur, Livnat, & Martikainen, 2003).

136 c

2018 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/jbfa JBus Fin Acc. 2019;46:136–158.

BILINSKI ANDEAMES 137

We also argue that low quality revenues will reduce the reporting of revenue forecasts as a result of both a decrease

in demand and analysts’ reluctance to report low quality forecasts.

Toexamine the associations of revenue and expense quality with analysts’ decisions to report a revenue forecast

with an earnings forecast, we consider I/B/E/S reported annual EPS and revenue forecasts over the fiscal years

2000–2013. We focus on I/B/E/S reported forecasts, rather than on the revenue forecasts in analysts’ investment

reports, as only the voluntary nature of reporting to I/B/E/S allows us to examine when and how analysts respond to

investor demand for revenue forecasts. Specifically, investmentreports routinely include revenue forecasts as part

of the forecasted income statements. With a standard research report setup, analysts will include revenue forecasts

in their investment reports even if (1) there is no demand for the forecast because the EPS estimate is already of

high quality (e.g., when revenue and expensequality are high), and (2) the revenue forecast is of such low quality that

investors would ignore it. I/B/E/S does not require analysts to report revenue forecasts, hence voluntary revenue

reporting to I/B/E/S is more likely to capture (1) investordemand for the forecast, and (2) analyst inclination to report

a useful revenue forecast.

I/B/E/S is an important medium for analysts to disseminate their forecasts and investors pay close attention to

the type and quality of forecasts supplied to I/B/E/S. Ivkovic and Jegadeesh (2004, p. 434) emphasize that ‘investors

pay millions of dollars every year to purchase forecast and recommendation data from vendors such as First Call,

I/B/E/S, and Zacks’. Furthermore, analysts issue their full reports much less frequently than theyissue forecasts to

I/B/E/S.3Ertimur, Mayew,and Stubben (2011) point out that access to I/B/E/S forecasts reduces information search

and processing costs for investors by standardizing the forecast measures across analysts. I/B/E/S also gives analysts

exposureto vast investor groups, including important institutional investors such as pension and mutual funds. Ertimur

et al. (2011) highlight that analyst ranking services such as StarMine use I/B/E/S to rate analysts and that analyst

rankings matter for analyst career prospects and compensation (Hong & Kubik, 2003; Hong, Kubik, & Solomon, 2000;

Leone & Wu, 2007).

We document that analysts are more likely to report revenue forecasts in association with low earnings quality

and high quality revenues and the effects are economically non-trivial. A one standard deviation reduction in the

log of expense quality leads to a 13.9% increase in the likelihood of issuing a joint EPS and revenue forecast. A one

standard deviation reduction in the log of revenue quality reduces the likelihood of reporting a revenueforecast with

an earnings forecast by 10.3%. Toaddress the concern that our results reflect endogeneity, we perform three tests.

First, we use firm-fixed effects in our regressions to control for unobserved firm characteristics that may correlate

with the analyst revenue reporting decision and revenue and expense quality. Second, we estimate the regression

model with changes in revenue and expensequality as, ‘changes regressions are less susceptible to correlated omitted

variables problems’ (Skinner, 1996, p. 397). Third, we use instrumental variables regressions to address analyst

endogenous coveragechoices. Fourth, we repeat the analysis for the decile of largest Compustat stocks where analyst

coverage choices are constrained.4As a corroborating test, we also examine the association of analyst initiation of

revenueforecast reporting with the subsequent q uality ofr evenueand expenses. If analyst revenue forecast reporting

and revenue and expense quality jointly respond to external factors, we expect revenue and expense quality to

change after analysts start reporting revenue forecasts, but find no evidence to support this claim. Teststhat address

endogeneity produce evidence supporting our predictions.

To build confidence in the validity of our conclusions, we subject the results to a battery of robustness tests.

Sensitivity tests show that our conclusions are not driven by an increase in institutional investor demand for revenue

forecasts or by management revenueguidance. Further, the results remain unchanged when we employ an alternative

revenue quality measure and remove joint issuances of earnings and cash flow forecasts from the sample. Finally,

3Toillustrate, Huang, Zang, andZheng (2014) report that ‘[O]n average, an analyst issues 10.5 reports for our sample firms in 1998, and that number increases

graduallyto 33 by 2008’. Forcomparison, in our I/B/E/S sample, analysts reported on average 38 EPS forecasts for the firms they covered in 1998 and close to

50forecasts in 2013. Bradshaw (2011) mentions that I/B/E/S aggregates information from, among others, analysts’ reports and morning broker notes.

4Brokersroutinely cover large stocks because sell-side research is compensated out of trade commissions, which increase with the size of the covered firm

(Irvine,2004).