Hello, greenblossom-ga!
You have asked a question which will require many, many hours of
research on your part. I have looked at your question on an off during
this past month, and after exhaustive research on various angles of
your topic, I can honestly say that you are delving into a subject
about which little has been written. Therefore, you may have hit on an
excellent subject for your paper!
A wealth of references exist on forecasting methodology,
inaccuracies, and better systems of analysis, but very little about
the personal influences that go into faulty projections.
The best I can do is provide some references that might provide a
start and help you narrow down your opinions concerning human behavior
in relation to inaccurate economic forecasts. As far as "which aspects
of the causes of inaccurate forecasting are well researched" (from a
behavioral standpoint) - I would have to say that the field appears to
be wide open!
I hope the following excerpts will open up some pathways that might
interest you, and help you to refine your research. These references
have been culled from hundreds of papers I have skimmed, in hopes of
targeting the behavioral/social/psychological influences on
forecasting. You might find an interesting angle that you had not
previously considered.
AND - CONGRATULATIONS ON YOUR NEW DAUGHTER! (I'm afraid you will have
to head for the library to get some peace and quiet, but that is not
much of a drawback when relishing in the blessings of parenthood!)
===
As a general start:
The Institute of Business Forecasting "might" have some articles of
interest, but you need to pay for a download, or join to have full
access. I imagine you may have access to these in your university
library. http://www.ibf.org/index.cfm
Journal
http://www.ibf.org/index.cfm?fuseaction=showObjects&objectTypeID=20
For example, you might want to look at titles under the following
categories to see if any give reference to the role of human
interpretation and error:
http://www.ibf.org/journal.cfm?fuseaction=downloadjbf&s=true
200- Forecast Error
201- Forecast error measures/how to improve forecasts
202- Decomposing forecast error
204- Forecast evaluation
Discussion Group - It might be interesting to pose some of your thesis
questions on this site. It is free to register. You might get a lot of
response if you start a "new topic."
http://www.ibf.org/forums/
ARTICLES THAT TOUCH ON PERSONAL CAUSES OF INNACCURATE BUSINESS FORECASTING
===============================================================================
From "Taking The Frenzy Out Of Forecasting," by Philip Bligh, Darius
Vaskelis, and John Kelleher. Optimize. March 2003, Issue 17
http://www.optimizemag.com/showArticle.jhtml;jsessionid=WVYPMK3IBMWIGQSNDBGCKHSCJUMEKJVN?articleID=17700869
"At the other extreme, many companies rely far too heavily on the
opinions of salespeople and managers in the production of forecasts.
It's been shown that the opinions of these people, no matter how
experienced, can produce inaccurate results. Opinions bias results
because people tend to:
* Confuse targets (hope) with forecasts (reality).
* Assume their personal judgments are more reliable than statistical projections.
* Produce forecasts for their own functions and mistrust forecasts
from other areas.
* Overestimate the effect of marketing campaigns and other
revenue-management actions.
* Use forecasts that differ from those used in other areas of the
company. For example, financial, manufacturing, and sales functions
may produce forecasts independently, but none monitors the changes in
the others' projections nor revises its own to reflect these changes."
==
The impact of personal factors on forecasting:
From "Forecasting Assessment Literature," by Dr. David Donnelly
http://www.hfac.uh.edu/MediaFutures/assessment.html
"Secondly, there are personal factors, factors internal to the
forecaster, that affect and, in some cases, invalidate a forecast.
Martino asserts that if a forecaster is aware of their own human
frailties, and if they take into account the possibility of being
afflicted by them, they have a much better chance of avoiding them and
can thereby increase the usefulness of their forecasts. Lastly, he
concurs with Ascher (1979) and Schnaars (1989) concerning the
importance of core assumptions in forecasting and asserts that they
may exert a greater influence on the outcome than the actual
methodology selected. He suggests that forecasters "recognize that
their core assumptions will dominate the outcome of a forecast" (p.
246). They should, therefore, try to identify and verify these
assumptions through discussions with other experts in order to improve
their accuracy."
==
From "Forecasting with Econometric Methods: Folklore versus Fact." J.
Scott Armstrong. The Wharton School, University of Pennsylvania.
Published in Journal of Business, 51 (4), 1978, 549-564.
http://www-marketing.wharton.upenn.edu/forecast/paperpdf/Econometric%20Methods.pdf
Abstract: "Evidence from social psychology suggests that
econometricians will avoid evidence that disconfirms their beliefs.
Two beliefs of econometricians were examined: (1) Econometric methods
provide more accurate short-term forecasts than do other methods; and
(2) more complex econometric methods yield more accurate forecasts. A
survey of 21 experts in econometrics found that 95% agreed with the
first statement and 72% agreed with the second. A review of the
published empirical evidence yielded little support for either of the
two statements in the 41 studies. The method of multiple hypotheses
was suggested as a research strategy that will lead to more effective
use of disconfirming evidence. Although this strategy was suggested in
1890, it has only recently been used by econometricians."
===
From "Quantifying Cognitive Biases in Analyst Earnings Forecasts."
Geoffrey Friesen, Iowa State University and Paul A. Weller, University
of Iowa. September 2003.
http://207.36.165.114/Denver/Papers/Quantifying%20cognitive%20biases%20in%20analyst%20earnings%20forecasts.pdf
Abstract - "This paper develops a formal model of analyst earnings
forecasts that discriminates between rational behavior and that
induced by cognitive biases. In the model, analysts are Bayesians who
issue sequential forecasts that combine new information with the
information contained in past forecasts. The model offers a number of
testable implications that allow us to detect cognitive biases, and
also to quantify their magnitude. We estimate the model and find
strong evidence that analysts are overconfident about the precision of
their own information and also subject to cognitive dissonance bias.
We examine the influence of the relative amount of private information
as a measure of ambiguity on the magnitude of the biases. The
variation in overconfidence is consistent with the well-established
variations documented in the psychological literature. We also
demonstrate a relationship between cross-country."
Also read "THE PSYCHOLOGY OF ECONOMIC FORECASTING." Under first review
at Global Review of Business and Economics. Karl Wennberg, Center for
Entrepreneurship and Business Creation, Stockholm School of Economics,
and Björn Nykvist, Department of Physical Resource Theory, Chalmers
University of Technology
http://www.hhs.se/NR/rdonlyres/1BF21E2B-529E-4961-B24E-1900E7DAF963/0/Wennberg_psychology_forecasting.pdf
===
"Conservatism and consensus-seeking among economic forecasters."
Batchelor, R; Dua, P. Journal of Forecasting. Vol. 11, no. 2, pp.
169-181. 1992
http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=2693355CI&q=author%3A%5C%22Batchelor%5C%22+intitle%3A%5C%22Conservatism+and+consensus-seeking+among+economic+forecasters.%5C%22&uid=1293456&setcookie=yes
"This paper uses the track records of a panel of US economic forecasts
participating in a concensus forecasting service to test for
conservatism and concensus-seeking behaviour. The tests are based on
particular method-of-moments estimator, designed to allows for the
heteroscedasticity and serial correlation which is inevitably present
in errors from repeated forecasts for fixed target dates. Most
forecasters prove to be conservative. When revising forecasts they
give too much weight to their own past forecasts. Surprisingly,
forecasters are not consensus-seeking but "variety-seeking". When
revising forecasts, they give too little weight to the known forecasts
of other forecasters."
===
How much personal "economic judgment" should the forecaster use in
making projections, and how much can it impact the accuracy of a
forecast?
See "Forecasting and Econometric Models," by Saul H. Hymans. The
Concise Encyclopedia of Economics.
http://www.econlib.org/library/Enc/ForecastingandEconometricModels.html
Excerpt:
"Most econometric forecasters believe that economic judgment can and
should be used not only to determine values for exogenous variables
(an obvious requirement), but also to reduce the likely size of model
error...
"Imposing such constant adjustments on forecasts used to be disparaged
as entirely unscientific. In recent years, however, researchers have
begun to regard such behavior as inevitable in the social science of
economic forecasting and have begun to study how best - from a
scientific perspective - to incorporate such outside information."
"Much of the motivation behind trying to specify the most accurately
descriptive economic model, trying to determine parameter values that
most closely represent economic behavior, and combining these with the
best available outside information arises from the desire to produce
accurate forecasts."
Also see "Five Ways to Achieve Better Forecasts," by Pat LaPointe.
MarketingProfs. March 23, 2004
http://www.marketingprofs.com/4/lapointe1.asp
(provides some reference to getting rid of personal bias)
===
From "An Overview of Forecasting Methodology," by David S. Walonick,
Ph.D. StatPac. http://www.statpac.com/research-papers/forecasting.htm
Excerpt:
"Difficulties in Forecasting Technology:
"Clarke describes our inability to forecast technological futures as a
failure of nerve. When a major technological breakthrough does occur,
it takes conviction and courage to accept the implications of the
finding. Even when the truth is starring us in the face, we often have
difficulty accepting its implications."
"Clark refers to this resistance to change as cowardice, however, it
may be much deeper. Cognitive dissonance theory in psychology has
helped us understand that resistance to change is a natural human
characteristic. It is extremely difficult to venture beyond our
latitudes of acceptance in forecasting new technologies."
"Clarke states that knowledge can sometimes clog the wheels of
imagination. He embodied this belief in his self-proclaimed law:
"When a distinguished but elderly scientist states that something is
possible, he is almost certainly right. When he states that something
is impossible, he is very probably wrong."
"Nearly all futurists describe the past as unchangeable, consisting as
a collection of knowable facts. We generally perceive the existence of
only one past. When two people give conflicting stories of the past,
we tend to believe that one of them must be lying or mistaken."
"This widely accepted view of the past might not be correct.
Historians often interject their own beliefs and biases when they
write about the past. Facts become distorted and altered over time. It
may be that past is a reflection of our current conceptual reference.
In the most extreme viewpoint, the concept of time itself comes into
question."
"The future, on the other hand, is filled will uncertainty. Facts give
way to opinions. As de Jouvenel points out, the facts of the past
provide the raw materials from which the mind makes estimates of the
future. All forecasts are opinions of the future (some more carefully
formulated than others). The act of making a forecast is the
expression of an opinion. The future, as described by de Jouvenel,
consists of a range of possible future phenomena or events. These
futuribles are those things that might happen."
===
From "C H A P T E R O N E - An Overview of Economic Forecasting," by
Michael P. Clements and David F. Hendry.
http://www.blackwellpublishing.com/content/BPL_Images/Content_store/Sample_chapter/0631215697/02Chap01.pdf
A reference to "judgmental forecasting" and personal ideas:
"As one might anticipate, a wide variety of models and methods are
used. In contrast to the statistical, model-based approaches surveyed
by Pedregal and Young, and Proietti, Dilek Önkal-Atay, Mary Thomson,
and Andrew Pollock discuss judgmental forecasting. They note that
judgment may enter the forecasting exercise at many levels, from the
choice of the variables to include, to the adjustment of model
predictions for new information. The term judgmental forecasting
refers to "the incorporation of forecasters? opinions and experience
into the prediction process," and so covers a wide variety of
situations. They review the factors that affect the accuracy of
judgmental forecasts, studies that have sought to compare the accuracy
of judgmental and model-based forecasts, and judgmental adjustments
and the combination of the two types of forecast. They discuss why
forecast users sometimes prefer judgmental forecasts, irrespective of
their accuracy."
===
You might want to get access to the following journal article I found
referenced in the following syllabus for a Political Psychology
course. I could find no abstract online, unfortunately.
Conover, Pamela and Stanley Feldman, and Kathleen Knight. 1987. "The
personal and political underpinnings of economic forecasts." AJPS 31:
559-83.
http://www.polisci.wisc.edu/users/sapiro/ps823/ps823.htm
===
Reliance on predicting software without any human evaluation can lead to failure:
Excerpt from comment in CIO magazine:
"Forecasting Software Cannot Solely Be Blamed." Anish Jain, Director,
Institute of Business Forecasting. CIO Magazine. July 15, 2003
http://comment.cio.com/comments/13895.html?action=print
"In many cases the faults lie in the people using the system. The Nike
fiasco was a great case in point. It appears they relied on software
as a black box. In other words, they believed that whatever the system
produced as a forecast was accurate and that no additional work was
necessary before and after."
==
From "Why Are Professional Forecasters Biased? Agency versus
Behavioral Explanations." Ehrbeck, Tilman & Waldmann, Robert, 1996.
The Quarterly Journal of Economics, MIT Press, vol. 111(1), pages
21-40. http://ideas.repec.org/a/tpr/qjecon/v111y1996i1p21-40.html
"Professional forecasters may not simply aim to minimize expected
squared forecast errors. In models with repeated forecasts, the
pattern of forecasts reveals valuable information about the
forecasters even before the outcome is realized. Rational forecasters
will compromise between minimizing errors and mimicking prediction
patterns typical of able forecasters. Simple models based on this
argument imply that forecasts are biased in the direction of forecasts
typical of able forecasters. The authors' models of strategic bias are
rejected empirically as forecasts are biased in directions typical of
forecasters with large mean squared forecast errors. This observation
is consistent with behavioral explanations of forecast bias."
==
From "The Strategy of Professional Forecasting," Marco Ottaviani &
Peter Norman Sorensen, 2001. Discussion Papers 01-09, University of
Copenhagen. Department of Economics (formerly Institute of Economics.
http://ideas.repec.org/p/kud/kuiedp/0109.html
"This paper develops and compares two theories of strategic behavior
of professional forecasters. The first theory posits that forecasters
compete in a forecasting contest with pre-specified rules. In
equilibrium of a winner-take-all contest, forecasts are excessively
differentiated. According to the alternative reputational cheap talk
theory, forecasters aim at convincing the market that they are well
informed. The market evaluates their forecasting talent on the basis
of the forecasts and the realized state. If the market has naive views
on forecasters' behavior, forecasts are biased toward the prior mean.
Otherwise, equilibrium forecasts are unbiased but imprecise."
==
Do expected wages influence human behavior in forecasting?
From "Rational bias in macroeconomic forecasts." David Laster, Paul
Bennett, In Sun Geoum. Federal Reserve Bank of New York. March 1997.
Number 21
http://www.newyorkfed.org/research/staff_reports/sr21.html
"This paper develops a model of macroeconomic forecasting in which the
wages firms pay their forecasters are a function of their accuracy as
well as the publicity they generate for their employers by being
correct. In the resulting Nash equilibrium, forecasters with identical
models, information, and incentives nevertheless produce a variety of
predictions in order to maximize their expected wages. In the case of
heterogeneous incentives, the forecasters whose wages are most closely
tied to publicity, as opposed to accuracy, produce the forecasts that
deviate most from the consensus. We find empirical support for our
model using a twenty-year panel of real GNP/GDP forecast data from the
survey Blue Chip Economic Indicators. Although the consensus
outperforms virtually every forecaster, many forecasters choose to
deviate from it substantially and regularly. Moreover, the extent of
this deviation varies by industry in a manner consistent with our
model."
Complete report
http://www.newyorkfed.org/research/staff_reports/sr21.pdf
Papers from the Principles of Forecasting Project
==================================================
You might find some ideas for further research into human behavior and
forecasting by looking at some reviews of papers from the Principles
of Forecasting Project. Not all focus on economic forecasting, but
they do present some interesting pathways for you to pursue.
Unfortunately, the complete papers are not available on the site.
See "Reviews of Important Papers on Forecasting Before 1985."
Principles of Forecasting Project.
http://hops.wharton.upenn.edu/forecast/reviews2.html
Interesting examples:
From "Review of: Craig A. Anderson (1983), "Imagination and
expectation: the effect of imagining behavioral scripts on personal
intentions," Journal of Personality and Social Psychology, 45,
293-305.
http://hops.wharton.upenn.edu/forecast/summary/anderson83.html
"Some questions remain unanswered. Would the changes in intentions
lead to changes in behavior? Could these results be applied to a
business executive writing scenarios about possible strategic actions
he or she might take for the organization?"
=
From "Review of: Craig A. Anderson (1983), "Abstract and concrete data
in the perseverance of social theories: when weak data lead to
unshakeable beliefs," Journal of Experimental Social Psychology, 19,
93-108." http://hops.wharton.upenn.edu/forecast/summary/anderson83-2.html
"An interesting extension of Anderson?s study would be to see whether
the effect holds if the subjects are told in advance (as we do in
scenarios) that the predictions are hypothetical."
=
Review of: Asher Koriat, Sarah Lichtenstein, and Barauch Fischoff
(1980), "Reasons for confidence," Journal of Experimental Psychology:
Human Learning and Memory, 6, 107-118.
http://hops.wharton.upenn.edu/forecast/summary/koriat80.html
"People tend to think of the reasons to support a given decision or
forecast: this leads to overconfidence. In this study, an explicit
list of the reasons contradicting their answers in a test of knowledge
led to a more realistic estimate of confidence in their answers.
Perhaps this conclusion can be generalized to forecasts."
====
For newer papers, see "Reviews of Important Papers on Forecasting,
1985 and on." Principles of Forecasting Project.
http://hops.wharton.upenn.edu/forecast/reviews.html
Examples of further paths of research you might follow:
From "Review of: Hoch, Stephen J. (1985), "Counterfactual reasoning
and accuracy in predicting personal events," Journal of Experimental
Psychology: Memory and Cognition II, 719-731."
http://hops.wharton.upenn.edu/forecast/summary/hoch85.html
"The study has a practical implication: prior to making judgmental
forecasts, the forecasters should write about the reasons why a
favorable forecast might be wrong. It is not known to what extent it
would help to produce such reasons after the judgmental forecast has
been made."
=
More reference to how personal judgment my impact forecasting:
From "Review of: Nada Sanders and Karl B. Manrodt (1994), Forecasting
practices in US corporations: Survey results, Interfaces, 24, 92-100."
http://hops.wharton.upenn.edu/forecast/summary/sanders94.html
"Sanders and Manrodt also provided information about issues that were
not addressed by Mentzer and Cox. Of particular interest, they
examined judgmental revisions of forecasts. Only 9% of the respondents
said that they never made judgmental revisions, while 45% said that
they always adjusted the forecasts. The respondents claimed that this
gave them an opportunity to incorporate their knowledge of the
environment (39%), their product knowledge (30%), or their experience
(26%). I believe that it is better to use subjective information as
inputs to models rather than to revise forecasts."
"One intent of subjective adjustments is to introduce biases. Most of
these respondents wanted to underforecast (70%), although 10% said
that they preferred to overforecast. As with the Mentzer and Cox
(1984) and Dalrymple (1987) surveys, this paper by Sanders and Manrodt
should be a widely cited paper."
===
You might want to look at "For Researchers in Forecasting" and click
on various links to get an idea of what research is currently out
there:
http://www-marketing.wharton.upenn.edu/forecast/researchers.html#Research%20Needs
===
The Society for Judgment and Decision Making "might" have some
resources of interest, but you will need to perform your own searches.
"The Society for Judgment and Decision Making is an interdisciplinary
academic organization dedicated to the study of normative,
descriptive, and prescriptive theories of decision. Its members
include psychologists, economists, organizational researchers,
decision analysts, and other decision researchers."
http://www.sjdm.org/index.shtml
Newsletter archives (laborious searching)
http://www.sjdm.org/newsletters/index.html
Excerpts from Book Reviews
===========================
"Robert Evans, Macroeconomic Forecasting: A Sociological Appraisal,
Routledge Studies in the Modern World Economy: Routledge, 1999."
Reviewed by: Anca Porojan, University of Derby; published in the
International Journal of Forecasting, 16 (200), 423-425.
http://hops.wharton.upenn.edu/forecast/reviews/EvansbyPorojan.pdf
"Economics remains a policy science and, for that reason, as Blaug
(1992) puts it, "the attempt to separate positive from normative
propositions in economics, and clearly specify the conditions for
submitting positive propositions to the test of experience, remains a
task which is as important to the progress of economics today as it
ever was."
"A revealing exploration of this positive normative debate comes, with
this book, not from an economist, but from a sociologist with a keen
interest in the ways in which the skills and expertise of
macro-economists contribute, alongside their social practices, to the
shaping of macroeconomic policy in the UK. The book aims to provide a
sociological account of the models, methods and forecasts produced by
forecasters advising governments on matters of policy."
==
The following book reviews offer some insight into personal failures
in relation to economic forecasting:
See Book Review - "Principles of Forecasting: A Handbook for
Researchers and Practitioners" - J. Scott Armstrong, The Wharton
School, Univ. of Pennsylvania. FUTURECASTS online magazine. Vol. 5,
No. 2, 2/1/03. http://www.futurecasts.com/Book%20review%205-2.htm
Excerpt:
"As an example of the tendency of even the most authoritative experts
to base forecasts on methods that rest on mere opinion with no
supporting empirical evidence, Armstrong cites the dubious expertise
of Nobel Laureate economist Paul Samuelson...."
=
Excerpt:
From Book Review - Improving Judgment in Forecasting" - by Nigel
Harvey, Univ. College of London - discusses methods of reducing the
impact of inconsistency and bias in forecasts based on expert
judgment.
"By definition - those with experience, learning and a proven track
record in the relevant field - the "experts" - are a good source of
reliable forecasts. However, there are reasons why experts fail - and
there are techniques to counter those reasons..
*** "Bias may arise from the self interest of the expert, or may be
inherent in the judgmental or statistical methods applied.."
==
Also see the following sections from "CONCLUSION: ECONOMICS AND PUBLIC
POLICY." Man, Economy & State.
http://66.102.7.104/search?q=cache:6_u00SXNS6sJ:www.mises.org/rothbard/mes/chap19.asp+reasons+for+human+failure+in+economic+forecasting&hl=en
Read sections on:
2. "Implicit Moralizing: The Failures of Welfare Economics"
3. "Economics and Social Ethics"
===
Finally, the following book might offer some fun, and enlightening reading:
"The Fortune Sellers : The Big Business of Buying and Selling
Predictions," by William A. Sherden. Wiley; 1 edition (October 14,
1997)
http://www.amazon.com/exec/obidos/tg/detail/-/0471181781/102-4121418-3511322?v=glance
"Sherden, a business consultant, explores seven of the major fields
involving prediction?meteorology, economics, investments, technology
assessment, demography, futurology, and organizational planning. He
describes each field, examines its track record, and concludes that
none can make accurate forecasts. Meteorology at least, he says, has a
sound scientific basis, though it may never be able to make accurate,
long-term predictions because of the chaotic nature of weather. The
author says the impediment for the other fields is that they must deal
with complex systems involving too many variables to devise workable
laws on which to base predictions. He writes in a very readable
academic style and documents his sources, while providing numerous
charts and examples. Highly recommended for all academic and public
libraries as both an overview of the seven fields covered and a
palliative to the many popular works that purport to be able to
predict the future."
==
Again - I hope these references prove helpful and provide some food
for thought as you pursue your research!
Sincerely,
umiat
Search Strategy
sociological reasons for failure in economic forecasting
reasons for human failure in economic forecasting
bias in economic forecasting
human failure in business forecasting
human error in business forecasting
human behavior and economic forecasting
peer pressure AND economic OR business forecasting
personal bias AND economic OR business forecasting
psychology AND economic predictions OR forecasting
personal influence AND economic forecasting
personal factors influencing economic forecasts
relation of cognitive psychology to economic forecasts
Survey of Professional Forecasters
are economic forecasters influenced by personal opinions? |
