Expert Forecasts Research Articles

Accuracy and reliability of an automated air quality forecast system for ozone in seven Kentucky metropolitan areas

An automated forecast system for ozone in seven Kentucky metropolitan areas has been operational since 2004. The forecast system automatically downloads the required input data twice each day, produces next-day forecasts of metro area peak 8-h average ozone concentration using a computer coded hybrid nonlinear regression (NLR) model, and posts the results on a website. The automated models were similar to previous NLR models, first applied to forecasting ozone in the Louisville metro area. The forecast system operated reliably during the 2004 and 2005 O 3 seasons, producing at least one forecast per day better than 99% of the time. The forecast accuracy of the automated system was good. For all 2004 and 2005 forecasts, the mean absolute error was equal to 8.7 ppb, or 15.6% of the overall mean concentration. The overall detection rate of air quality standard exceedences was 56%, and the overall false alarm rate was 42%. In Louisville, the performance of the automated system was comparable to that of expert forecasters using the NLR model as a forecast tool.

Anchoring Bias in Consensus Forecasts and its Effect on Market Prices

Previous empirical studies that test for the 'rationality' of economic and financial forecasts generally test for generic properties such as bias or autocorrelated errors, and provide limited insight into the behavior behind inefficient forecasts. In this paper we test for a specific behavioral bias--the anchoring bias described by Tversky and Kahneman (1974). In particular, we examine whether expert consensus forecasts of monthly economic releases from Money Market Services surveys from 1990-2006 have a tendency to be systematically biased toward the value of previous months' data releases. We find broadbased and significant evidence for the anchoring hypothesis; consensus forecasts are biased towards the values of previous months' data releases, which in some cases results in sizable predictable forecast errors. Then, to investigate whether the market participants anticipate the bias, we examine the response of interest rates to economic news. We find that bond yields react only to the residual, or unpredictable, component of the surprise and not to the expected piece of the forecast error apparently induced by anchoring. This suggests market participants anticipate the anchoring bias embedded in expert forecasts.

Anchoring Bias in Consensus Forecasts and its Effect on Market Prices

Previous empirical studies that test for the rationality of economic and financial forecasts generally test for generic properties such as bias or autocorrelated errors, and provide limited insight into the behavior behind inefficient forecasts. In this paper we test for a specific behavioral bias -- the anchoring bias described by Tversky and Kahneman (1974). In particular, we examine whether expert consensus forecasts of monthly economic releases from Money Market Services surveys from 1990-2006 have a tendency to be systematically biased toward the value of previous months' data releases. We find broad-based and significant evidence for the anchoring hypothesis; consensus forecasts are biased towards the values of previous months' data releases, which in some cases results in sizable predictable forecast errors. Then, to investigate whether the market participants anticipate the bias, we examine the response of interest rates to economic news. We find that bond yields react only to the residual, or unpredictable, component of the surprise and not to the expected piece of the forecast error apparently induced by anchoring. This suggests market participants anticipate the anchoring bias embedded in expert forecasts.

The psychology of economic forecasting

Is the imprecision of economic forecasts due to the judgements of biased decision makers? This study explores decision making among expert forecasters in Sweden using semistructured interviews. The results indicate that forecasters' decision processes are characterised by intuitive, as well as calculating reasoning, gradually adopting mental models and conflicting goals. This indicates that forecasters are better described as ecologically rational rather than biased decision makers. A consequence is that behavioural forecasting research would benefit from taking into account the specific decision-making environment in which forecasters operate.

Psychiatric Music Therapy in 2016: A Delphi Poll of the Future

ABSTRACT: The future of psychiatric music therapy was investigated using a Delphi poll to garner expert consensual predictions in the areas of theoretical orientations, music therapy interventions, qualifications of psychiatric music therapists, and selected scenarios. Invented by the Rand Corporation and temporarily classified by the U.S. Military, Delphi methodology has been cited as the best available technique for forecasting the future. Psychiatric internship directors at roster AMTA internships participated as the panel of experts. The panel ranked the future probability of 101 music therapy-related events using seven-point Likert scales ranging from great decrease/ very unlikely to great increase/very likely. Content validity was established for the questionnaire in addition to a criterion validity coefficient of .85, which was established for second-round results. What might the future of psychiatric music therapy look like in the year 2016? Professional issues considered as crucial include licensure and restrictive licensure laws (Adamek, 1999; McKinney, 2005; Murphy & Polen, 2005), reimbursement (Adamek, 1999; Hairston, 2003; Wheeler, 2005), and the need for protocols supported by research and outcomebased data (Adamek, 1999; McKinney, 2005; Pfeifer, 2003; Wheeler, 2005). Other issues of concern to related professionals that have import for the music therapy profession are changes in theoretical orientation, therapeutic interventions, and training requirements for therapists (Norcross, Hedges, & Prochaska, 2002). In view of the preceding concerns, it is imperative that we become knowledgeable about how such issues will affect the future of music therapists and our patients. What will be the face of psychiatric music therapy in the year 2016? Delphi Methodology The best available technique for forecasting the future is the Delphi poll (Neimeyer & Diamond, 2001). More than 1000 Delphi polls have been used to forecast the future in diverse areas such as technology (Linstone & Turoff, 1975), accounting (Baldwin-Morgan, 1993), psychotherapy (Norcross et al., 2002), counseling (Neimeyer & Diamond, 2001), and pediatric psychology (Brown & Roberts, 2000). The Rand Corporation invented Delphi methodology in the mid-1950s. The technique was subsequently classified by the U.S. military and used for predicting the effects of a massive nuclear attack. Delphi methodology was declassified by the U.S. Air Force in 1962 (Dalkey & Helmer, 1963; Linston & Turoff, 1975; Neimeyer & Diamond, 2001). The Delphi poll's reliance on expert consensual prediction is a major strength over usual survey methods. Experts achieve this consensus by rating future events and then rating the same events a second time after viewing the ratings of the other experts on the panel (Norcross et al., 2002). Delphi polls are considered economical and time efficient, usually more accurate than other prognostication techniques, to outperform 95% of individual expert forecasts and are useful in moving professions forward (Ascher, 1978; Norcross et al., 2002; Parente, Anderson, Meyers, & O'Brien, 1984). Although Delphi polls have been cited as useful in moving professions forward, they have not yet been used in the music therapy profession. The purpose of this study was to forecast the future of psychiatric music therapy over the next decade. The target date the panel was given for future predictions was the year 2016. The predictions were considered as probabilities rather than absolutes. The panel predicted what probably will happen rather than what will happen. Method Participants Psychiatric internship directors (IDs) at internships approved by The American Music Therapy Association (AMTA) served as the participants. The rationale for restricting the participants to IDs was because as a group, IDs are among the most experienced, if not the most experienced group, of psychiatric clinicians in the music therapy profession. …

Application of Neural Networks for Avalanche Forecasting

Application of neural networks is investigated for the prediction of avalanches on Chowkibal-Tangdhar road axis in Jammu and Kashmir. The networks are developed and trained monthwiseusing the past snow and weather parameters recorded at the Stage-II Observatory on the axisto generate an assessment of avalanche and non-avalanche activities. Two approaches havebeen considered for training the network. In the first approach, only avalanche activities observedin the axis were taken for training, and in the second approach, along with the observed activities,the opinion of expert forecasters were also considered. The performance of the networks variesfrom 67 to 82 per cent for correct predictions. Winter data for 2001-2002 has been used to validatethe network performance.

Value of Expertise for Forecasting Decisions in Conflicts

In important conflicts, people typically rely on experts' judgments to predict the decisions that adversaries will make. We compared the accuracy of 106 expert and 169 novice forecasts for eight real conflicts. The forecasts of experts using unaided judgment were little better than those of novices, and neither were much better than simply guessing. The forecasts of experts with more experience were no more accurate than those with less. Speculating that consideration of the relative frequency of decisions might improve accuracy, we obtained 89 forecasts from novices instructed to assume there were 100 similar situations and to ascribe frequencies to decisions. Their forecasts were no more accurate than 96 forecasts from novices asked to pick the most likely decision. We conclude that expert judgment should not be used for predicting decisions that people will make in conflicts. Their use might lead decision makers to overlook other, more useful, approaches.

A systematic comparison of professional exchange rate forecasts with the judgemental forecasts of novices

Professional forecasters in foreign exchange markets are not able to beat naive forecasts. In order to find reasons for this phenomenon we compare the empirical forecasts of experts with the experimentally generated forecasts of novices for the EUR/USD exchange rate in three different forecast horizons. Although the subjects are only provided with the realizations of the exchange rate and are not supported by any statistical procedures they outperform experts in accuracy. Professionals consistently expect a reversal of forgoing exchange rate changes whereas novices extrapolate trends. The judgemental forecasts appear to be unbiased and professionals appear to be biased. We demonstrate that professionals are influenced by the fundamental value—an irrelevant anchor in speculative exchange markets. The poor performance of the experts is not a common failure of human decision-making in market environments but caused by misleading information.

Expert Forecasts and the Emergence of Water Scarcity on Public Agendas

ABSTRACT Expert forecasts of worldwide water scarcity depict conditions that call for proactive, preventive, coordinated water governance, but they have not been matched by public agendas of commensurate scope and urgency in the United States. This disconnect can not be adequately explained without some attention to attributes of forecasts themselves. I propose that the institutional fragmentation of water expertise and prevailing patterns of communication about water scarcity militate against the formulation of a common public definition of the problem and encourage reliance on unambiguous crises to stimulate social and policy agenda setting. I do not argue that expert forecasts should drive public agendas deterministically, but if their purpose is to help prevent water crises (not just predict them), then a greater effort is needed to overcome the barriers to meaningful public scrutiny of expert claims and evaluation of water strategies presently in place.

Forecasting the Laws of Distribution of the Conveyance and Certification Times for Storekeeping

Consideration was given to forecasting the dynamics of the distribution laws of the times of commodity conveyance and certification in the wholesale storekeeping systems. An approach to this problem relying on forecasting the corresponding random processes was proposed. Mathematical models of the dynamics of conveyance and certification times were formulated, and the optimal methods of forecasting were substantiated for them. A method of combined analytical and expert forecasts was presented.

Value of Expertise for Forecasting Decisions in Conflicts

In important conflicts, people typically rely on experts' judgments to predict the decisions that adversaries will make. We compared the accuracy of 106 expert and 169 novice forecasts for eight real conflicts. The forecasts of experts using unaided judgment were little better than those of novices, and neither were much better than simply guessing. The forecasts of experts with more experience were no more accurate than those with less. Speculating that consideration of the relative frequency of decisions might improve accuracy, we obtained 89 forecasts from novices instructed to assume there were 100 similar situations and to ascribe frequencies to decisions. Their forecasts were no more accurate than 96 forecasts from novices asked to pick the most likely decision. We conclude that expert judgment should not be used for predicting decisions that people will make in conflicts. Their use might lead decision makers to overlook other, more useful, approaches.

A Ten-Year Delphi Forecast of the Irish Speciality Food Market

The speciality food sector affords small agri-businesses the opportunity to operate in a growing niche market that satisfies consumer demands for high quality artisan foods. In this research the Delphi Technique was used to forecast growth in the Irish Speciality Food Market five and ten years into the future. The expert panel forecast that the Irish Speciality Food Market would grow by 65 per cent over the next ten years, with the most significant growth in the cured meats, yoghurt and cheese categories. The forecast indicated that sales through delicatessen or speciality food stores would be worth €47 million by 2010. The Irish Speciality Food Market's growth rate between 2000 and 2005 was forecast to be faster than the growth between 2005 and 2010.

An Empirical Comparison of Methods for Eliciting and Modeling Expert Knowledge

The goal of this project in Human-Centered Computing was to apply a variety of methods of Cognitive Task Analysis (CTA) and Cognitive Field Research (CFR) to support a complete process going all the way from knowledge elicitation to leverage point identification and then to system prototyping, and also use this as an opportunity to empirically compare and evaluate the methods. The research relied upon the participation of expert, journeyman, and apprentice weather forecasters at the Naval Training Meteorology and Oceanography Facility at Pensacola Naval Air Station. Methods included Protocol Analysis, a number of types of structured interviews, workspace and work patterns analysis, the Critical Decision Method, the Knowledge Audit, Concept Mapping, and the Cognitive Modeling Procedure. The methods were compared in terms of (1) their yield of information that was useful in modeling expert knowledge, (2) their yield in terms of identification of leverage points (where the application of new technology might bring about positive change), and (3) their efficiency. Efficiency was gauged in terms of total effort (time to prepare to run a procedure, plus time to run the procedure, plus time to analyze the data) relative to the yield (number of leverage points identified, number of propositions suitable for use in a model of domain knowledge). CTA/CFR methods supported the identification of dozens of leverage points and also yielded behaviorally- validated models of the reasoning of expert forecasters. Knowledge modeling using Concept-Mapping resulted in over a thousand propositions covering domain knowledge. The Critical Decision Method yielded a number of richly-populated case studies with associated Decision Requirements Tables. Results speak to the relative efficiency of various methods of CTA/CFR, and also the strengths of each of the methods. In addition to extending our empirical base on the comparison of knowledge elicitation methods, a deliverable from the project was a knowledge model that illustrates human-centered computing in that it integrates training support and performance aiding.

Storm-LK: A Human-Centered Knowledge Model for Weather Forecasting

STORM-LK (System To Organize Representations in Meteorology-Local Knowledge) is a Human-Centered system that used the CMap Tools© software to represent the knowledge and reasoning of expert forecasters. It demonstrates the feasibility of using Concept-Mapping to generate large-scale multi-media knowledge models. STORM-LK can support knowledge preservation, distance learning and collaboration, and navigation through the data that are used in weather forecasting.

Recent Acquisitions

RECENT ACQUISITIONS 'Bibliographies, cArchival Inventories, Indexes SHEILA TUReON Ready Division / McMaster University Library Hamilton, ON, Canada L8s 4L6 TURCON@MCMASTER.CA Allan, Eikan L. from BR, 17 Feb. 1947. Purchase. Added to Rec. Acq. 5°7· Allen, Anthony 2 Is. from BR, 1953. Courtesy of Sheila V. Grant. Re George Grant's "muddle-headed" "Pursuit of an Illusion", Dalhousie Review. 32 (1952): 97-109. Rec. Acq. 1,349· CORRESPONDENCE Berka, Karel L. from BR, 27 July 1966. P., courtesy of Karel Berka via John Shosky. Rec. Acq. 1,340. Berlin, Isaiah Postscript from BR added to letter from Patricia Russdl to Berlin, [April 1944]. P., courtesy of Henry Hardy via Kenneth Blackwell. Rec. Acq. 1,350. British Broadcasting Corp. (Talks Dept., T he previous general update of correspondence acquisitions appeared in Russell, n.S. 16 (1996): 173-6, although in n.s. 18 (1998): 145-59, the acquisition of the Anton Felton Papers was described. There are 18 entries in the listing below covering c. 406 items. Some were received from other institutions, to whom McMaster Library is very grateful. The latest acquisition reported is number 1,351; the latest arrived in August 1999. The following abbreviations are used: L(s). or I(s). =letter(s); P(s). or p(s). = photocopy(ies); p.c(s). = post card(s); and "Ts." = typescript. My previous update of manuscript acquisitions appeared in Russell, n.s. 16 (1996): 171-3. These entries bring the total to 560 entries of manuscript-related acquisitions since the Archives' arrival at McMaster in 1968. See the "25-Year Index" in n.s. 15 (1995) for citations of previous updates. The latest acquisition arrived in August 1999. Bold references are to Blackwell and Ruja's Bibliography ofBertrand Russell russell: the Journal of Bertrand Russell Studies McMaster University Press n.s. 19 (wimer 1999-2000): 183-91 ISSN 0036-01631 184 SHEILA TURCON Recent Acquisitions: Correspondence, Manuscripts and Archives 185 INTRODUCTION OFFICIAL ARCHIVAL ENTRIES IN MORRIS Far Eastern Service, General Over~ seas Dept., London Calling Asia, North American Service, German Service) 36 Is. from BR, 3 Is. from his secretaries; 92 Is. to BR, 1950-52. Rec. Acq. 1,35Ia. 78 Is. from BR, I telegram from BR, 1 from BR's secretary; 114 letters to BR, 1953-57. Rec. Acq. 1,35Ib. 20 Is. from BR, 2 Is. from BR's secretary, 9 Is. from Christopher Farley, 1958-68. Rec. Acq. I,351C. (Copyright Dept.) I I. from Farley, 2 Is. to BR, 1964-66. Rec. Acq. 1,35Id. Ps., courtesy of BBC Written Archives. Rec. Acq. 1,351· Campaign for Nuclear Disarmament BR's letter of resignation, 21 Oct. 1960. Purchase. Also ps. of letters from BR to Canon Collins, 15 May 1961, and Austin Underwood, 4 Feb. 1961. Rec. Acq. 1,323. Falk, J. 2 Is. from BR, 1905. P., courtesy of Ivor Grattan-Guinness. Re editing Boole's mss. Rec. Acq. 1,326. Felton, Anton See "The Bertrand Russell Papers of Anton Felton", Russell, n.s. 18 (1998): 145-59. ' Glynn, Joseph M., Jr. L. from BR, 5 Sept. 1959. Courtesy of Joseph M. Glynn Jr. Rec. Acq. 1,339. John, Augustus 5 Is. from BR, 193660 . Ps., courtesy of National Library of Wales. Re portraits; nudearprotest . Rec. Acq. 1,328. Keler, Vladimir R. (Editorial House Znanie) 2 Is. from BR, 1962-63. Ps., courtesy of Gennady Gorelek. Re publishing in Russian trans. in [Science and HumankindJ BR's unpublished "Nuclear War: an American Expert's Forecast" (see below). Rec. Acq. 1,331. Krassner, Paul L. from BR, 20 April 1959. P., courtesy of Paul Krassner via Bernd Frohmann. Rec. Acq. 1,322. Micheson, Mrs. 1. from BR, 14 Oct. 1924. Purchase. Rec. Acq. 1,345. Neville, Eric L. to BR, 22 Nov. 1923. From Russell's library, Hermann Weyl, Space-Time--Matter. Rec. Acq.I,344· Newman, M. H. A. (Milton) 8 Is. from BR, 1926-66. Ps., courtesy of Dr. William Newman. Re philosophy of matter; Turing; Godel. Rec. Acq. 1,320. Perkins, Elizabeth 15 Is. from BR, 191519 . Purchase. Re WWI and placing BR's mss. Rec. Acq. 1,330. Unknown recipient L. from BR, 14 June 1927, addressed "Dear sir" and...

Une comparaison des prévisions des experts à celles issues des modèles B VAR

A Comparison of Expert Forecasts with BVAR Model Forecasts by Sandrine Lardic and Auguste Mpacko-Priso This paper checks whether economic and financial experts forecast macroeconomic and financial variables «better» than alternative techniques and in particular the Bayesian method. The BVAR methodology, presented in detail in Lardic and Mpacko-Priso (1996) and summarised in this paper, is used to generate six-month and twelve-month forecasts of the Consumer Price Index, Industrial Production Index, Standard and Poors 425, and Standard and Poors 500 for two samples. These forecasts are then compared with economic and financial expert predictions as well as with forecasts derived from traditional techniques for the same periods of time. Statistical and economic criteria are used to gauge the different forecasts. We show that the BVAR forecasts are generally better than the individual expert forecasts. We conclude that the BVAR methodology merits being used more than it is at present.

Cocoa crop protection: an expert forecast on future progress, research priorities and policy with the help of the Delphi survey

Disease and pest attack on cocoa ( Theobroma cacao) causes significant yield losses which are difficult and costly to control. A discussion of the prospects of techniques and strategies in cocoa crop protection for the next 25 years is based on a detailed survey. Combining various traditional techniques (for instance, traditional resistance breeding) with modern tools (for instance, methods of molecular biology) improves prospects for a future reduction of yield losses. A complementary application of various research tools may achieve a significant reduction of yield losses caused by Phytophthora pod rot, vascular streak dieback, witches' broom, and the cocoa pod borer.

Implications of Herding Behavior for Earnings Estimation, Risk Assessment, and Stock Returns

Experts' earnings predictions exhibit positive bias and disappointing accuracy. These shortcomings are usually attributed to some combination of incomplete knowledge, incompetence, and/or misrepresentation. This article suggests that the human desire for consensus leads to herding behavior among earnings forecasters. Herding results in a reduction in the dispersion and an increase in the mean of the distribution of expert forecasts, creating positive bias and inaccuracy in published earnings estimates. Investors mistake reduced dispersion for reduced risk and positive bias for high future returns. These misperceptions lead to abnormally low returns from stocks with unpredictable earning streams.

An experimental examination of subjective forecast combination

Little is known about how individuals subjectively combine forecasts. This study uses two experiments to investigate how subjective forecast combination is influenced by both features of the decision context and characteristics of expert forecasters (financial analysts) who provide the individual forecasts. Experimental results indicate that individuals often are conservative in their combined forecasts; this conservatism is related to both the intended purpose of the forecast and individuals' beliefs that analysts' forecasts typically are optimistic. Other results show that individuals' combined forecasts on average reflect the relative historical accuracy of forecasters but not the relative historical dependence between forecasters. Although some subjects used dependence correctly in their combined forecasts, others either used it incorrectly or indicated that they did not know how it should be used. These results suggest that subjectively combined forecasts are likely to differ from those based on theoretical forecast combination models.

Forecasting severe ozone episodes in the Baltimore metropolitan area

In order to protect sensitive individuals and support possible episodic emissions control efforts, a pilot program was undertaken to forecast episodes of high ozone concentrations for 24–72 h in the Baltimore metropolitan area. This program utilized Classification and Regression Tree (CART) algorithms as well as standard regression analysis and expert forecasts. All approaches tend to underpredict peak O 3 concentrations at 24 h. The low bias varied from 5 ppbv for the expert forecast to 7 ppbv for the CART forecast. The standard error for forecast O 3 varied from 17 ppbv for the regression forecast to 23 for the CART forecast. For high O 3 (> 120 ppbv) events, the expert forecast has the best success with a detection rate of 50%, and skill scores varying from 0.40 to 0.50. For expert forecasts of greater than 115 ppbv, verifying against observations of greater than 120 ppbv, the detection rate rises to 75% with skill scores of 0.60–0.66. One of the principal sources of forecast error was underprediction of mid-day surface temperature by the standard meteorological models during extremely warm episodes. When perfect forecasts of meteorological parameters are utilized, the forecast skill of the objective measures increases to approximately the skill of the expert forecasts. Improvements can be made by utilizing more recent data for initialization of the ozone regression equations and the use of local forecasts to supplement temperature forecasts during warm periods.