were exposed to an enthusiastic review of the first edition [Corbin (1982)], which cited its summaries of rigorous research while retaining a conversational style and inclusion of ‘thought experiments’ _ using ‘the readers basic intuitive judgment as its raw material’ (p. 219). In one example, Hogarth gives the reader a false outcome to an event, later demonstrating how the reader became convinced of the inevitability of the (false) outcome. The second edition retains these features and if anything, improves upon them. The treatment of judgmeent and choice involves forecasting because choice is seen as reflecting two types of judgement: predictive judgements (forecasts) and evaluative judgements. The quality of choice depends on the extent to which the forecasts are accurate and the evaluations faithfully reflect values. The forecasts of concern to Prof. Hogarth are subjective, intuitive forecasts. His discussion of choice is also relevant because forecasters are frequently called upon to predict choices: how many consumers will choose to pay a particular price for a product or service; how many people will apply for a particular job, or choose an early retirement option; investor choices, voter choices, etc. The first three-chapters of the book (and later, Chapter 6) concentrate on predictive judgements. His review of the psychological literature reads like a catalog of human judgmental fallibilities, including: misattribution of causes to random occurrences; incorrect (causal) interpretations of regression towards the mean, producing overly extreme forecasts for previously extreme observations; failure to appropriately incorporate base rate information into forecasts: inferring the probability of a future event on the basis of how easy it Randall J. Jones, Jr. is to imagine the event happening; the lingering Central State ~n~ve~~ity, Oklahoma, USA zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFED impact of whatever initial forecast value was considered, simply because it was the first considered, and adjustments from it are insufficient; use Reference of only a few cues for prediction; use of redundant pieces of information in a forecast as if these Janis, Irving L., Victims of Groupthink (Houghton Mifflin Company, Boston, 1972). were independent of other cues; and failure to seek potentially disconfirming evidence. Not unRobin M. Hogarth, Judgment and Choice: The surprisingly, the degree of confidence felt by peoPsychology ofDecision, Second edition (Wiley, New ple in such forecasts is misplaced. The reader’s York, 1987) $24.95, 217.50, pp. 311. resistance to accepting the validity of the research findings is lessened through Prof. Hogarth’s inThis second edition of Judgment and Choice builds volvement of the reader in mental exercises where upon the success of its predecessor. Forecasters one finds oneself acting in just the way that rewhen forecasts are the basis of important policy decisions, and when forecasters are employees of organizations having vested interests in the results. However, merely because the task is difficult is no reason that the goal should be abandoned. Perhaps it was the editors’ stance on this point that precluded the logical sequel to the descriptive case studies, namely an exploration of ways to improve the objectivity of energy forecasts. The authors of the country essays seem to have been ideally suited for making such proposals, given their knowledge of the country environments within which the forecasts are made. The above criticism does not di~nish the book’s principal achievement of documenting advocacy and bias in energy forecasting, which complex statistical models can easily mask. The editors were successful in attracting contributors having intimate knowledge of forecasting practices in the eight case-study countries and at IIASA. The book is remarkably well integrated to have had thirteen p~ti~ipating writers, which undoubtedly is a result of the continuing guidance the editors provided to the contributors. The editors’ two introductory chapters set the stage well, and their two concluding chapters provide useful summaries of the contributors’ main findings. The book will be useful to a diverse audience, including not only forecasters, but also students of the energy industry, of interest group behavior, and of bureaucratic politics. Many forecasters will identify with the issues raised here and should be reassured in knowing that similar dilemmas they face are not unique, but are commonly shared by colleagues. 136 Book reviews search has demonstrated. Such experiences help lessen dismissive responses of the ‘I’m not like that’ sort. Prof. Hogarth explains the psychological mechanisms that produce these forecasts, and includes a wide range of examples including sales forecasts, forecasts for personnel decisions, medical decisions, and stock purchases. Chapters 4 and 5 discuss choice: choice under certainty (Chapter 4) and risky decision making (Chapter 5). The latter represents a change from the previous edition which only discussed risky decision making briefly. In both chapters, rational choice models are first presented, and the discussion proceeds to the processes through which intuitive choices are actually reached, emphasizing how these differ from the rational choice models. Hogarth explains the substantial impacts of the context in which the choices are presented and the language used to describe identical choices, as well as exploring the psychological basis of such effects. The title of Chapter 7, ‘The Role of Memory in may appear forbiddingly academic, Judgement’, and the reader may be tempted to skip it. That would be a pity. In essence, this chapter looks at the difficulties encountered when one tries to improve one’s intuitive forecasts and choices. In order to improve them, one must look back into one’s memory of past forecasts and choices, and learn from any mistakes. Unfortunately, memory is a slippery thing: research shows that original memory inputs are not retrieved from human memories in the way that they are from computers. Instead, memories are more like reconstructions than anything else, and therefore are only approximately the same as the original. Reconstructed (remembered) forecasts are found to be prone to the ‘hindsight bias’ such that one ‘remembers’ forecasting, in hindsight, whatever transpired, leading one to feel that ‘I knew it all the time’. Such ‘memories’ inhibit identifying flaws in ones forecasting strategy, yielding little incentive to improve. Congruent with one of Hogarth’s major themes, that subjective forecasts frequently derive from causal explanatory models, Chapter 8 looks at the question of how to encourage people to make more accurate causal models and scenarios for the future. A sort of ‘if you can’t beat them, join them’ approach seems to be taken here, which accepts the pervasiveness of causal thinking, even when it is inappropriate. The version of the ‘joining ‘em’ strategy involves creativity in the generation of scenarios and causal models. Techniques for increasing creativity are discussed. The difficulties of implementing such techniques - and implementing creative solutions - are also addressed. Resistance by others to such innovations is to be expected. Hogarth’s quote from zyxwvutsrqponmlk The Prince about such resistance is apt, where Machiavelli explains the difficulties in introducing a new order of things, since it ‘has for enemies, all those who have done well under the old’ yet but ‘lukewarm defenders in those who may do well under the new’ (p. 163). In Chapter 9, Hogarth looks at decision aids for improving intuitive forecasts and choices. He offers procedures and practices that could be implemented to help address limitations in human judgement, including a particularly useful table listing eight key points for probabilistic thinking and prediction. The final chapter (Chapter 10) offers an overview of human judgement, which summarizes and synthesizes much of the work presented earlier. In addition, it includes what Hogarth refers to as a ‘speculative’ section on the origins of judgmental bias. It is not only a discussion of origins. It also argues that these biases were, and remain, adaptive in many situations. It therefore raises the question of how problematic these judgmental fallibilities actually are. I am afraid that some readers may conclude that the significance of these judgmental liabilities is more limited than was demonstrated earlier. My own reading of the literature is that these judgmental failings are most apt to spell trouble when there is little opportunity for trial and error learning, and ‘midcourse corrections’ are difficult or costly: in short, when it is important to do it right the first time. These situations are not just rare cases involving new or complex technologies. Anyone who has experienced the effects of a disastrous hiring (or promotion) decision is personally familiar with the liabilities of a poor forecast of an individual’s performance. Or, for a more homely instance, one’s experience with marital disruptions among friends and family give distressingly familiar examples of the limitations of subjective forecasts in marital choice, and emphasizes the importance of the issues discussed. The book concludes with a quote from Francis Bacon. ‘We do ill to exalt the powers Book reviews 137 tion of multiple time series modeling procedures. There are many other additions throughout the book with plenty of references to recent work (including some from 1986). In fact, the references alone are a very valuable part of this book. For example, a tool in model selection proposed by Hannan and Rissanen in 1982 is included in the sections on single time series and on multiple time series, and estimation techniques that have been Bernard J. Goitein developed since the writing of the first edition are Bradley University, Peoria, Illinois, USA zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJ presented. The approach of the entire book is to present, in a coherent fashion, topics in forecasting that Reference have practical value to forecasters of economic and business data. The authors begin by introducCorbin, R.M., 1982, “Judgement and choice: A review for ing basic theoretical concepts for ARIMA models, forecasters and futurists” [review of R.M. Hogarth, Judgesuch as the autocorrelation structure. The second ment and Choice: The Psychology of Decisions], Journal of chapter is on spectral analysis. While this chapter Forecasting, 1, 219-221. contains material that a forecaster should know, it is not necessary to read this chapter before readC.W.J. Granger and Paul Newbold, Forecasting ing the rest of the book. Chapter Three explains Economic Time Series, Second edition (Harcourt how to build univariate ARIMA models with Brace Jovanovich, New York, 1986) hard cover several examples and practical suggestions for both $49.50/paperback $24.95, E37.50 pp. 337. nonseasonal and seasonal time series. Some theoretical aspects of forecasting and presented in This small book contains an enormous amount of Chapter Four. Chapter Five is aptly called ‘Practimaterial that is presented in an extremely inforcal Methods for Univariate Time Series Forecastmative manner. In the preface to the first edition, ing.’ Along with the Box-Jenkins methods, one is the authors state that the research projects which shown smoothing methods (including simple, resulted in that book were motivated by the lack Holt-Winters, and Brown’s general exponential of connection in the literature between the theosmoothing) and stepwise autoregression. Forecastretical aspects of forecasting and the applied ing results are compared, and some relationships aspects. The second editions continues to relate these two aspects. The theoretical concepts of between the methods are shown. In Chapter Five, regression models for forecastforecasting are presented in precise mathematical terms which are followed by intuitive explanations ing are introduced. The authors discuss extensively, with examples, the problems of autocorof the mathematical formulas. The authors give related error and model misspecification. The preclear interpretations and simple examples that only sentation in Chapter Five should strongly motia person with a thorough understanding of the vate the reader to want to understand the material underlying theory could possibly give. in the following two chapters, which are on the Although this book does not contain detailed theory with extensive proofs, it does require some theory and applications of multiple time series modeling and forecasting. Modeling with transfer mathematical maturity on the part of the reader. A minimum level would be the ability that one functions is not explained in enough depth for a achieves by completing a sequence in mathematipractitioner to understand how to identify models. cal statistics or probability. For example, the On the other hand, more space is devoted to authors use generating functions (which they devector ARIMA models, and several examples are fine and explain) very heavily. Furthermore, a given. In addition, three tests for causal direction reader should be comfortable with matrix notation are explained and compared. and have a familiarity with regression analysis. Chapter Nine contains an informative presentaThe authors state that the major changes for tion on the combination and evaluation of forethe second edition are in the theory and applicacasts. There are some very interesting points raised of the human mind, when we should seek out its proper helps’. Forecasters especially should be concerned with such ‘proper helps’. The temptation to reject the unflattering picture of human reasoning painted by researchers is great. It is better to seek means to cope with the problems than to deny them, and this book marks a significant step toward that end.