Armstrong, J.

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Professor of Marketing
Professor Armstrong is internationally known for his pioneering work on forecasting methods. He is author of Long-Range Forecasting, the most frequently cited book on forecasting methods, and Principles of Forecasting, voted the "Favorite Book – First 25 Years" by researchers and practitioners associated with the International Institute of Forecasters. He is a co-founder of the Journal of Forecasting, the International Journal of Forecasting, the International Symposium on Forecasting, and He is a co-developer of new methods including rule-based forecasting, causal forces for extrapolation, simulated interaction, and structured analogies.
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Now showing 1 - 10 of 227
  • Publication
    Evidence-Based Forecasting for Climate Change
    (2013-02-01) Green, Kesten C; Armstrong, J. Scott; Armstrong, J. Scott
    Following Green, Armstrong and Soon’s (IJF 2009) (GAS) naïve extrapolation, Fildes and Kourentzes (IJF 2011) (F&K) found that each of six more-sophisticated, but inexpensive, extrapolation models provided forecasts of global mean temperature for the 20 years to 2007 that were more accurate than the “business as usual” projections provided by the complex and expensive “General Circulation Models” used by the U.N.’s Intergovernmental Panel on Climate Change (IPCC). Their average trend forecast was .007°C per year, and diminishing; less than a quarter of the IPCC’s .030°C projection. F&K extended previous research by combining forecasts from evidence-based short-term forecasting methods. To further extend this work, we suggest researchers: (1) reconsider causal forces; (2) validate with more and longer-term forecasts; (3) adjust validation data for known biases and use alternative data; and (4) damp forecasted trends to compensate for the complexity and uncertainty of the situation. We have made a start in following these suggestions and found that: (1) uncertainty about causal forces is such that they should be avoided in climate forecasting models; (2) long term forecasts should be validated using all available data and much longer series that include representative variations in trend; (3) when tested against temperature data collected by satellite, naïve forecasts are more accurate than F&K’s longer-term (11-20 year) forecasts; and (4) progressive damping improves the accuracy of F&K’s forecasts. In sum, while forecasting a trend may improve the accuracy of forecasts for a few years into the future, improvements rapidly disappear as the forecast horizon lengthens beyond ten years. We conclude that predictions of dangerous manmade global warming and of benefits from climate policies fail to meet the standards of evidence-based forecasting and are not a proper basis for policy decisions.
  • Publication
    Natural Learning in Higher Education
    (2011-01-01) Armstrong, J. Scott; Armstrong, J. Scott
  • Publication
    Identification of Asymmetric Prediction Intervals through Causal Forces
    (2001-07-01) Armstrong, J. Scott; Armstrong, J. Scott; Collopy, Fred
    When causal forces are specified, the expected direction of the trend can be compared with the trend based on extrapolation. Series in which the expected trend conflicts with the extrapolated trend are called contrary series. We hypothesized that contrary series would have asymmetric forecast errors, with larger errors in the direction of the expected trend. Using annual series that contained minimal information about causality, we examined 671 contrary forecasts. As expected, most (81%) of the errors were in the direction of the causal forces. Also as expected, the asymmetries were more likely for longer forecast horizons; for six-year-ahead forecasts, 89% of the forecasts were in the expected direction. The asymmetries were often substantial. Contrary series should be flagged and treated separately when prediction intervals are estimated, perhaps by shifting the interval in the direction of the causal forces.
  • Publication
    Brief vs. comprehensive descriptions in measuring intentions to purchase
    (1971-02-01) Armstrong, J. Scott; Armstrong, J. Scott; Overton, Terry
    Introduction: In forecasting demand for expensive consumer goods, direct questioning of potential consumers about their future purchasing plans has had considerable predictive success [1, 2, 4]. Any attempt to apply such "intention to purchase" methods to forecast demand for proposed products or services must determine some way to convey product information to the potential consumer [3]. Indeed, all the prospective consumer knows about the product or service is what he may infer from the information given to him by the researcher. This paper presents a study of the effect upon intention to purchase of this seemingly crucial element—the extent and type of description of the new service. How extensive must the description of the new service be in order to measure intention to purchase?
  • Publication
    Class of Mail Does Affect Response Rates to Mailed Questionnaires: Evidence from Meta-analysis
    (1990) Armstrong, J. Scott; Armstrong, J. Scott
    In contrast to the conclusions from traditional reviews, meta-analysis shows that certain types of postage have an important effect on return rates to mail surveys. In particular, US business reply postage should not be used in survey research.
  • Publication
    Does an Academic Research Paper Contain Useful Knowledge? No. (p<.05)
    (2004-01-01) Armstrong, J. Scott; Armstrong, J. Scott
  • Publication
    How to avoid exploratory research
    (1970-08-01) Armstrong, J. Scott; Armstrong, J. Scott
    Introduction: Studies in marketing research often start with data rather than with a theory. This exploratory or inductive approach is at odds with the more preferred scientific method where the theory precedes the data in any single research study. (See, for example, the discussion by Francis, 1957) Because exploratory research is common, however, one might argue that it is of some value. A number of researchers have claimed that the exploratory approach leads to new and useful theories. But there is also the danger that the research will produce false leads or useless theories. An attempt is made in this paper to illustrate the dangers inherent in the exploratory approach. The question of whether the potential benefits are large enough to outweigh the dangers is left to the reader.
  • Publication
    Review of Paul Bloomberg, The Predatory Society: Deception in the American Marketplace
    (1990-10-01) Jaworski, Bernard J; Armstrong, J. Scott; Armstrong, J. Scott
    The Predatory Society examines the inadequacies of marketing and the free market system. It is written by a sociologist. I think that, in general, sociologists are biased against marketing people. The bias runs like this: Sociologists believe that consenting adults should be allowed to enter into agreements without state interference. However, if those agreements involve legal transactions with money, the freedom of the consenting adults should be abridged for the protection of those adults. An elite should decide how much freedom is in the interests of these people. Translated into marketers' terms, the argument is that the state should regulate the behavior of adult buyers and sellers because the former are honest but incompetent and the latter are often dishonest. Blumberg lives up to some of my expectations, but he is also aware of the arguments favoring the free market.
  • Publication
    An application of econometric models to international marketing
    (1970-05-01) Armstrong, J. Scott; Armstrong, J. Scott
    Introduction: With more and more firms contemplating expansion in the international market, the question of how a firm estimates its sales potential in a given country takes on increasing importance. Certainly one vital piece of information in estimating sales potential would be the size of the total current market in that country. This article considers the various ways in which firms might estimate market size by country, with particular consideration given to the use of econometric models. The article aims at three related questions. First, what has happened over the past thirty years in the use of econometric models for measuring geographical markets? Second, is it possible to demonstrate that currently available econometric techniques lead to “improved” measurement of geographical markets—and, in particular, for international markets? Finally, have advances in applied econometric analysis over the past thirty years led to any demonstrable progress in measuring geographical markets?
  • Publication
    The Accuracy of Alternative Extrapolation Models: Analysis of a Forecasting Competition Through Open Peer Review
    (1983) Armstrong, J. Scott; Armstrong, J. Scott; Lusk, Edward J
    In 1982, the Journal of Forecasting published the results of a forecasting competition organized by Spyros Makridakis (Makridakis et al., 1982). In this, the ex ante forecast errors of 21 methods were compared for forecasts of a variety of economic time series, generally using 1001 time series. Only extrapolative methods were used, as no data were available on causal variables. The accuracies of methods were compared using a variety of accuracy measures for different types of data and for varying forecast horizons. The original paper did not contain much interpretation or discussion. Partly this was by design, to be unbiased in the presentation. A more important factor, however, was the difficulty in gaining consensus on interpretation and presentation among the diverse group of authors, many of whom have a vested interest in certain methods. In the belief that this study was of major importance, we decided to obtain a more complete discussion of the results. We do not believe that "the data speak for themselves."