Principles of Forecasting: A Handbook for Researchers and PractitionersJ.S. Armstrong Principles of Forecasting: A Handbook for Researchers and Practitioners summarizes knowledge from experts and from empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. It applies to problems such as those in finance (How much is this company worth?), marketing (Will a new product be successful?), personnel (How can we identify the best job candidates?), and production (What level of inventories should be kept?). The book is edited by Professor J. Scott Armstrong of the Wharton School, University of Pennsylvania. Contributions were written by 40 leading experts in forecasting, and the 30 chapters cover all types of forecasting methods. There are judgmental methods such as Delphi, role-playing, and intentions studies. Quantitative methods include econometric methods, expert systems, and extrapolation. Some methods, such as conjoint analysis, analogies, and rule-based forecasting, integrate quantitative and judgmental procedures. In each area, the authors identify what is known in the form of `if-then principles', and they summarize evidence on these principles. The project, developed over a four-year period, represents the first book to summarize all that is known about forecasting and to present it so that it can be used by researchers and practitioners. To ensure that the principles are correct, the authors reviewed one another's papers. In addition, external reviews were provided by more than 120 experts, some of whom reviewed many of the papers. The book includes the first comprehensive forecasting dictionary. |
Contents
INTRODUCTION | 1 |
ROLE PLAYING | 13 |
A METHOD TO FORECAST DECISIONS | 15 |
INTENTIONS | 31 |
METHODS FOR FORECASTING FROM INTENTIONS DATA | 33 |
EXPERT OPINIONS | 57 |
IMPROVING JUDGMENT IN FORECASTING | 59 |
IMPROVING RELIABILITY OF JUDGMENTAL FORECASTS | 81 |
JUDGMENTAL ADJUSTMENT OF STATISTICAL FORECASTS | 405 |
COMBINING FORECASTS | 417 |
EVALUATING METHODS | 441 |
EVALUATING FORECASTING METHODS | 443 |
ASSESSING UNCERTAINTY | 473 |
PREDICTION INTERVALS FOR TIMESERIES FORECASTING | 475 |
OVERCONFIDENCE IN JUDGMENTAL FORECASTING | 495 |
GAINING ACCEPTANCE | 517 |
DECOMPOSITION FOR JUDGMENTAL FORECASTING AND ESTIMATION | 107 |
THE ROLE OF THE DELPHI TECHNIQUE | 125 |
CONJOINT ANALYSIS | 145 |
FORECASTING WITH CONJOINT ANALYSIS | 147 |
JUDGMENTAL BOOTSTRAPPING | 169 |
INFERRING EXPERTS RULES FOR FORECASTING | 171 |
ANALOGIES | 193 |
TIME SERIES | 195 |
EXTRAPOLATION | 215 |
EXTRAPOLATION FOR TIMESERIES AND CROSSSECTIONAL DATA | 217 |
NEURAL NETWORKS FOR TIMESERIES FORECASTING | 245 |
RULEBASED FORECASTING | 257 |
USING JUDGMENT IN TIMESERIES EXTRAPOLATION | 259 |
EXPERT SYSTEMS | 283 |
EXPERT SYSTEMS FOR FORECASTING | 285 |
ECONOMETRIC FORECASTING | 303 |
SELECTING METHODS | 363 |
SELECTING FORECASTING METHODS | 365 |
INTEGRATING ADJUSTING AND COMBINING | 387 |
JUDGMENTAL TIMESERIES FORECASTING USING DOMAIN KNOWLEDGE | 389 |
SCENARIOS AND ACCEPTANCE OF FORECASTS | 519 |
MONITORING FORECASTS | 541 |
COPING WITH HINDSIGHT BIAS AND AMBIGUITY | 543 |
APPLICATIONS OF PRINCIPLES | 555 |
POPULATION FORECASTING | 557 |
IMPLICATIONS FOR TIMESERIES EXTRAPOLATION | 577 |
ECONOMETRIC MODELS FOR FORECASTING MARKET SHARE | 597 |
FORECASTING TRIAL SALES OF NEW CONSUMER PACKAGED GOODS | 613 |
DIFFUSION OF PRINCIPLES | 631 |
DIFFUSION OF FORECASTING PRINCIPLES THROUGH BOOKS | 633 |
DIFFUSION OF FORECASTING PRINCIPLES THROUGH SOFTWARE | 651 |
SUMMARY | 677 |
STANDARDS AND PRACTICES FOR FORECASTING | 679 |
FORECASTING STANDARDS CHECKLIST | 733 |
EXTERNAL REVIEWERS | 739 |
ABOUT THE AUTHORS | 745 |
THE FORECASTING DICTIONARY | 761 |
| 825 | |
| 843 | |
Other editions - View all
Principles of Forecasting: A Handbook for Researchers and Practitioners J.S. Armstrong Limited preview - 2001 |
Principles of Forecasting: A Handbook for Researchers and Practitioners J.S. Armstrong No preview available - 2002 |
Common terms and phrases
alternative approach assess autocorrelation average Bayesian bias biases bootstrapping models Box-Jenkins causal forces causal variables changes cointegrating Collopy combined forecast compared conjoint analysis correlation decision decomposition Delphi developed domain knowledge econometric models econometricians economic effects empirical equation error measures estimates evaluation ex ante example expert systems explanatory variables exponential smoothing extrapolation factors feedback Fildes fore forecast errors forecast horizon forecasting methods forecasting models forecasting principles hindsight bias improve forecast accuracy intentions International Journal J. S. Armstrong Journal of Forecasting judgmental bootstrapping judgmental forecasting Makridakis MAPE neural networks Norwell outcome outliers overconfidence parameters percent performance prediction intervals Principles of Forecasting problem procedures programs reasons regression reliability respondents role playing sample scenarios Scott Armstrong selection situation Source of evidence Strength of evidence studies time-series tion trend uncertainty unit root validity weights Wittink