Flu Fallout: Information Production Constraints and Corporate Disclosure

• Published date: 01 September 2023
• Author: CHEN CHEN,LEONARD LEYE LI,LOUISE YI LU,RENCHENG WANG
• Date: 01 September 2023
• DOI: http://doi.org/10.1111/1475-679X.12486

DOI: 10.1111/1475-679X.12486

Journal of Accounting Research

Vol. 61 No. 4 September 2023

Printed in U.S.A.

Flu Fallout: Information Production

Constraints and Corporate

Disclosure

CHEN CHEN ,∗LEONARD LEYE LI ,†LOUISE YI LU ,‡

AND RENCHENG WANG §

Received 13 January 2020; accepted 26 March 2023

ABSTRACT

Using influenza epidemic data, we examine how constraints on corpo-

rate information production affect disclosure policies. We find that firms

in areas with higher flu activity are less likely to issue short-run earnings

∗Department of Accounting, Monash Business School, Monash University; †School of Ac-

counting, Auditing & Taxation,The UNSW Business School, UNSW Sydney; ‡Research School

of Accounting, Australian National University; §School of Accountancy, Singapore Manage-

ment University

Accepted by Rodrigo Verdi. We are indebted to an anonymous associate editor and an

anonymous reviewer for highly valuable comments and suggestions that helped significantly

improve the paper, and Sonali Walpola for detailed feedback on each revision. We appre-

ciate constructive and insightful suggestions from John Campbell, Xia Chen, Qiang Cheng,

Vivian Fang (discussant), Wayne Guay, Charles Hsu, Ting Jiang, Robert Knechel, Wayne

Landsman, Ningzhong Li, Gerald Lobo, Yun Lou, Xiumin Martin, Gary Monroe, Venky Na-

gar, Jeffrey Ng, Zihang Peng, Jeff Pittman, Greg Shailer, Lakshmanan Shivakumar, Jin Wang

(discussant), Holly Yang, Yangxin Yu, Liandong Zhang, and workshop participants at Fu-

dan University, Hong Kong Polytechnic University, Monash University, University of Sydney,

Wuhan University,the 2020 Accounting and Finance Association of Australia and New Zealand

(AFAANZ) Annual Conference, the 2020 Midyear Meeting of the Financial Accounting and

Reporting Section (FARS), and the 2020 SMU Accounting Symposium. We thank four prac-

titioners in S&P 500 firms for sharing their experiences of the forecasting processes. We ex-

press appreciation to Kathy Xuejun Jiang, Yongtao Jiang, Madhukar Singh, Ben Wang, and

Kathy Dongyue Wang for their excellent research assistance. We also thank our respective

schools for their financial support. Wang acknowledges the support from University of Mel-

bourne with which he was affiliated while part of the work on this paper was done. All er-

rors and omissions are our own. An online appendix to this paper can be downloaded at

https://www.chicagobooth.edu/jar-online-supplements.

1063

© 2023 The Chookaszian Accounting Research Center at the University of Chicago Booth School of

Business.

1064 c. chen, l. l. li, l. y. lu, and r. wang

forecasts and more likely to issue long-run earnings forecasts. These results

are more pronounced when the information production process is more

complex, when managers face a greater reputational loss for issuing low-

quality short-run forecasts, and when firms’ costs of switching the forecast

horizon are lower. Further analysis implies that the effect of flu activity on

these forecast issuance decisions is not driven by firm performance or infor-

mation uncertainty. Our results suggest that managers do not simply avoid

issuing forecasts in response to information production constraints. Instead,

they shift the forecast horizon from short-run to long-run, appearing to bal-

ance the costs of issuing low-quality forecasts with those of not issuing fore-

casts at all.

JEL codes: D8, I10, I18, J10, J32, M41

Keywords: information production constraints; flu epidemic; management

forecast; corporate disclosure

1. Introduction

Previous studies find that investors’ capacity to process information is con-

strained by their need to allocate time and effort across various activities

(Blankespoor, deHaan, and Marinovic [2020]). Survey evidence suggests

that firms may face similar constraints on the production of high-quality

information due to the demands on employees in terms of time and effort

(Hsieh, Koller, and Rajan [2006], Ernst and Young [2015]). However, em-

pirical evidence of the impact of these constraints on firms’ information

production is limited. We help fill this gap in the literature by examining

how firms’ constraints on information production affect managers’ forecast

issuance policies.

Theoretical work and empirical evidence suggest that managers have

strong incentives to issue credible forecasts and maintain a transparent in-

formation environment (e.g., Trueman [1986], Healy and Palepu [2001],

Graham, Harvey, and Rajgopal [2005]). We argue that managers have

two potential disclosure choices when firms face constraints on generat-

ing high-quality information. The first choice, as previous researchers sug-

gest, is to cease issuing forecasts (e.g., Feng, Li, and McVay [2009], Do-

rantes et al. [2013], Call et al. [2017], Chen et al. [2018]). Managers make

this decision because such constraints tend to increase information pro-

duction costs and decrease the accuracy of forecasts. This exposes man-

agers to reputational loss should a forecast later prove inaccurate. However,

this strategy of silence may also be costly because it violates firms’ commit-

ment to following transparent disclosure policies and contributes to infor-

mation asymmetry (e.g., Grossman [1981], Milgrom [1981], Houston, Lev,

and Tucker [2010], Chen, Matsumoto, and Rajgopal [2011], Baginski and

Rakow [2012]).

These concerns may lead to the pursuit of the second choice, in which

managers may take a middle position between nonissuance and issuing

dubious forecasts by issuing long-run instead of short-run forecasts. This

information production constraints and corporate disclosure 1065

“Information

Production

Window”

Bundled

Forecasts

FQEi,t EAi,t FQEi,t+1

Fig 1.—Event window of flu activity.This figure illustrates the information production window.

We define this window for calculating flu activity as the weeks between the end of fiscal quarter

tfor firm i(FQEi,t) and its EA date for quarter t’s performance (EAi,t). The bundled short- or

long-run forecasts are those issued within the window [˗1, +1] of the EA date (EAi,t). The

short-run forecasts are for fiscal quarter t+1’s performance, and the long-run forecasts are

for the performance associated with fiscal periods beyond quarter t+1.

tradeoff strategy allows managers to continue to provide forecasts, thereby

reducing the costs of cutting all forecasts. It can also address managers’ rep-

utational concerns about issuing low-quality forecasts, as the ex post costs of

issuing inaccurate forecasts for managers are lower for long-run forecasts.

Specifically, the mistakes in long-run forecasts can be more easily attributed

to “unavoidable errors” than those in short-run forecasts (Gong, Li, and Xie

[2009, p. 502]). As managers have more opportunities to revise and correct

errors in long-run forecasts, investors may view such corrections as informa-

tive updates (e.g., Trueman [1986]).

To investigate this issue, we use flu activity in the area surrounding a

firm’s headquarters during a period of intensive information production

to measure the information production constraints on a firm. The flu im-

poses staffing constraints on firms when employees take sick leave or work

while ill, care for infected family members, or cover sick colleagues. There-

fore, infectious illness is a major cause of lost work time and effort (for a

review, see Keech and Beardsworth [2008]). Considering that information

production is labor intensive and requires coordination and collaboration

among employees, the flu imposes severe constraints on this activity.

We analyze a sample of 86,483 firm-quarter observations from 2003 to

2018. We define the period between the end of the fiscal period and the

earnings announcement (EA) date as a firm’s “information production win-

dow” (see figure 1). We then measure flu activity using the average weekly

data for outpatient visits to healthcare providers for influenza-like illness

(ILI) in a U.S. state where a firm’s headquarters is located during its in-

formation production window. First, as a validation test, we demonstrate

that firms experience longer reporting lags and are more likely to produce

financial statements with errors when the level of flu activity is higher. A

one-standard-deviation increase in flu activity corresponds to a one-day in-

crease in reporting lag and 6% more financial statement errors compared