Discussion of “biases in multi-year management financial forecasts: Evidence from private venture-backed U.S. companies”

Discussion of “biases in multi-year management financial forecasts: Evidence from private... Armstrong, Dávila, Foster, and Hand (“ADFH”) use a proprietary venture capital database of revenue and profit projections submitted by young firms seeking financing to attempt to address a number of questions related to forecasts by managers of early stage, venture-backed, private entrepreneurial firms. The proprietary dataset together with the creative use of a “historically-grounded conditional projections” methodology are the most interesting features of ADFH’s study. However, these same aspects give rise to empirical design constraints that the study does not fully overcome. In addition, there are numerous leaps of logic required to arrive at some of ADFH’s conclusions and there are alternative explanations for ADFH’s findings that have not been entirely refuted. This leaves the reader with some doubt as to whether all of ADFH’s conclusions are fully substantiated. Nevertheless, the evidence presented makes an interesting contribution to our understanding of the forecasting behavior of young, private, rapidly growing, VCbacked firms, and provides some natural economic and methodological leads into further studies of these issues. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Accounting Studies Springer Journals

Discussion of “biases in multi-year management financial forecasts: Evidence from private venture-backed U.S. companies”

Loading next page...
 
/lp/springer_journal/discussion-of-biases-in-multi-year-management-financial-forecasts-2fK3N3HAKJ
Publisher
Kluwer Academic Publishers-Plenum Publishers
Copyright
Copyright © 2007 by Springer Science+Business Media, LLC
Subject
Business and Management; Accounting/Auditing; Corporate Finance; Public Finance
ISSN
1380-6653
eISSN
1573-7136
D.O.I.
10.1007/s11142-007-9027-2
Publisher site
See Article on Publisher Site

Abstract

Armstrong, Dávila, Foster, and Hand (“ADFH”) use a proprietary venture capital database of revenue and profit projections submitted by young firms seeking financing to attempt to address a number of questions related to forecasts by managers of early stage, venture-backed, private entrepreneurial firms. The proprietary dataset together with the creative use of a “historically-grounded conditional projections” methodology are the most interesting features of ADFH’s study. However, these same aspects give rise to empirical design constraints that the study does not fully overcome. In addition, there are numerous leaps of logic required to arrive at some of ADFH’s conclusions and there are alternative explanations for ADFH’s findings that have not been entirely refuted. This leaves the reader with some doubt as to whether all of ADFH’s conclusions are fully substantiated. Nevertheless, the evidence presented makes an interesting contribution to our understanding of the forecasting behavior of young, private, rapidly growing, VCbacked firms, and provides some natural economic and methodological leads into further studies of these issues.

Journal

Review of Accounting StudiesSpringer Journals

Published: Mar 8, 2007

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off