Serial Correlation in Management Earnings Forecast Errors

Guojin Gong, Laura Y. Li, Jeff J. Wang

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs shouldnotexhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long-horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self-selection does not seem to drive this phenomenon. Further analyses suggest that managers' unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.

Original languageEnglish (US)
Pages (from-to)677-720
Number of pages44
JournalJournal of Accounting Research
Volume49
Issue number3
DOIs
StatePublished - Jun 1 2011

Fingerprint

Management forecasts
Forecast error
Serial correlation
Management earnings forecasts
Analysts
Persistence
Managers
Self-selection
Information processing
Managerial decision making

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics

Cite this

Gong, Guojin ; Li, Laura Y. ; Wang, Jeff J. / Serial Correlation in Management Earnings Forecast Errors. In: Journal of Accounting Research. 2011 ; Vol. 49, No. 3. pp. 677-720.
@article{9591a4c3b9c84469bacf52c4142ba784,
title = "Serial Correlation in Management Earnings Forecast Errors",
abstract = "We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs shouldnotexhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long-horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self-selection does not seem to drive this phenomenon. Further analyses suggest that managers' unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.",
author = "Guojin Gong and Li, {Laura Y.} and Wang, {Jeff J.}",
year = "2011",
month = "6",
day = "1",
doi = "10.1111/j.1475-679X.2011.00407.x",
language = "English (US)",
volume = "49",
pages = "677--720",
journal = "Journal of Accounting Research",
issn = "0021-8456",
publisher = "Wiley-Blackwell",
number = "3",

}

Serial Correlation in Management Earnings Forecast Errors. / Gong, Guojin; Li, Laura Y.; Wang, Jeff J.

In: Journal of Accounting Research, Vol. 49, No. 3, 01.06.2011, p. 677-720.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Serial Correlation in Management Earnings Forecast Errors

AU - Gong, Guojin

AU - Li, Laura Y.

AU - Wang, Jeff J.

PY - 2011/6/1

Y1 - 2011/6/1

N2 - We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs shouldnotexhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long-horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self-selection does not seem to drive this phenomenon. Further analyses suggest that managers' unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.

AB - We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs shouldnotexhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long-horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self-selection does not seem to drive this phenomenon. Further analyses suggest that managers' unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.

UR - http://www.scopus.com/inward/record.url?scp=79955520456&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79955520456&partnerID=8YFLogxK

U2 - 10.1111/j.1475-679X.2011.00407.x

DO - 10.1111/j.1475-679X.2011.00407.x

M3 - Article

AN - SCOPUS:79955520456

VL - 49

SP - 677

EP - 720

JO - Journal of Accounting Research

JF - Journal of Accounting Research

SN - 0021-8456

IS - 3

ER -