ISSN:0277-6693    

DOI:10.1002/for.3980010102

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractThis paper presents the writer's experience, over a period of 25 years, in analysing organizational systems and, in particular, concentrates on the overall forecasting activity. The paper first looks at the relationship between forecasting and decision taking–with emphasis on the fact that forecasting is ameansto aid decision taking and not anendin itself. It states that there are many types of forecasting problems, each requiring different methods of treatment. The paper then discusses attitudes which are emerging about the relative advantages of different forecasting techniques. It suggests a model building process which requires‘experience’and‘craftsmanship’, extensive practical application, frequent interaction between theory and practice and amethodologythat eventually leads to models that contain no detectable inadequacies. Furthermore, it argues that although models which forecast a time series from its past history have a very important role to play, for effective policy making it is necessary to augment the model by introducing policy variables, again in a systematic not an‘ad hoc’manner. Finally, the paper discusses how forecasting systems can beintroducedinto the management process in the first place and how they should bemonitoredandupdatedwhen

ISSN:0277-6693    

DOI:10.1002/for.3980010103

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractWhile forecasting involves forward/predictive thinking, it depends crucially on prior diagnosis for suggesting a model of the phenomenon, for defining‘relevant’variables, and for evaluating forecast accuracy via the model. The nature of diagnostic thinking is examined with respect to these activities. We first consider the difficulties of evaluating forecast accuracy without a causal model of what generates outcomes. We then discuss the development of models by considering how attention is directed to variables via analogy and metaphor as well as by what is unusual or abnormal. The causal relevance of variables is then assessed by reference to probabilistic signs called‘cues to causality’. These are: temporal order, constant conjunction, contiguity in time and space, number of alternative explanations, similarity, predictive validity, and robustness. The probabilistic nature of the cues is emphasized by discussing the concept of spurious correlation and how causation does not necessarily imply correlation. Implications for improving forecasting are considered with respect to the above

ISSN:0277-6693    

DOI:10.1002/for.3980010104

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractThis article stresses how little is known about the quality, particularly the relative quality, of macroeconometric models. Most economists make a strict distinction between the quality of a modelper seand the accuracy of solutions based on that model. While this distinction is valid, it leaves unanswered how to compare the‘validity’of conditional models. The standard test, the accuracy ofex postsimulations, is not definitive when models with differing degrees of exogeneity are compared. In addition, it is extremely difficult to estimate the relative quantitative importance of conceptual problems of models, such as parameter instability across‘policy regimes’In light of the difficulty in comparisons of conditional macroeconometric models, many model‐builders and users assume that the best models are those that have been used to make the most accurate forecasts are those made with the best models. Forecasting experience indicates that forecasters using macroeconometric models have produced more accurate macroeconomic forecasts than either naive or sophisticated unconditional statistical models. It also suggests that judgementally adjusted forecasts have been more accurate than model‐based forecasts generated mechanically. The influence of econometrically‐based forecasts is now so pervasive that it is difficult to find examples of‘purely judgem

ISSN:0277-6693    

DOI:10.1002/for.3980010105

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractThis paper discusses some problems currently facing forecasters and expresses some of the author's beliefs of how such problems can be handled. It is the author's hope that such discussion will help practitioners to understand and better deal with these problems while, at the same time, stimulate research and influence the thinking of academicians. As with the previous work of this author, the present paper will be practical and brief.

ISSN:0277-6693    

DOI:10.1002/for.3980010106

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractThis paper proposes an Average Recession/Recovery Model (ARRM). It discusses the reasons why such a model is needed and how it can be developed. Major utilities of the model are (1) it is an extremely simple way to display complex forecasts to management graphically, (2) it can be applied to a single time series–with monthly or quarterly data–and is applicable to a large proportion of time series, both macro and micro, (3) it is easy to calculate, to understand, to program and to communicate with it and (4) it employs widely accepted statistical and economic meth

ISSN:0277-6693    

DOI:10.1002/for.3980010107

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractMethods of time series forecasting are proposed which can be applied automatically. However, they are not rote formulae, since they are based on a flexible philosophy which can provide several models for consideration. In addition it provides diverse diagnostics for qualitatively and quantitatively estimating how well one can forecast a series. The models considered are called ARARMA models (or ARAR models) because the model fitted to a long memory time series (t) is based on sophisticated time series analysis of AR (or ARMA) schemes (short memory models) fitted to residualsY(t)obtained by parsimonious‘best lag’non‐stationary autoregression. Both long range and short range forecasts are provided by an ARARMA modelSection 1 explains the philosophy of our approach to time series model identification. Sections 2 and 3 attempt to relate our approach to some standard approaches to forecasting; exponential smoothing methods are developed from the point of view of prediction theory (section 2) and extended (section 3). ARARMA models are introduced (section 4). Methods of ARARMA model fitting are outlined (sections 5,6). Since‘the proof of the pudding is in the eating’, the methods proposed are illustrated (section 7) using the classic example of international airline p

ISSN:0277-6693    

DOI:10.1002/for.3980010108

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

摘要:

AbstractA review of editorial policies of leading journals and of research relevant to scientific journals revealed conflicts between‘science’and‘scientists’. Owing to these conflicts, papers are often weak on objectivity and replicability. Furthermore, papers often fall short on importance, competence, intelligibility, or efficiency. Suggestions were made for editorial policies such as: (1) structured guidelines for referees, (2) open peer review, (3) blind reviews, and (4) full disclosure of data and method. Of major importance, an author's‘Note to Referees’(describing the hypotheses and design, but not the results) was suggested to improve the objectivity of the ratings of importance and competence. Also, recommendations are made to authors for improving contributions to science (such as the use of multiple hypotheses) and for promoting their careers (such as using complex methods and obtu

ISSN:0277-6693    

DOI:10.1002/for.3980010109

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980010110

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980010111

出版商:John Wiley&Sons, Ltd.    

年代:1982

数据来源: WILEY