Making Progress in Forecasting

  title={Making Progress in Forecasting},
  author={J. Scott Armstrong and Robert Fildes},
  journal={Econometrics eJournal},
Forecasting and uncertainty: A survey
This paper argues for a new, pragmatic approach where the emphasis must shift from forecasting to assessing uncertainty, as realistically as possible, evaluating its implications to risk and exploring ways to prepare to face it.
FORTHCOMING: Risk and Decision Analysis Journal Forecasting and Uncertainty: A Survey
The origins of forecasting can be traced back to the beginning of human civilization with attempts to predict the weather, although forecasting as a field first appeared in the 1940s and attracted
Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective
This paper introduces a novel and completely automated profit-driven approach that takes into account the expected profit that a technique can create during both the model building and evaluation process and shows that simple seasonal time series models consistently outperform other methodologies.
The Use of Forecast Accuracy Indicators to Improve Planning Quality: Insights from a Case Study
This study particularly explores the practical challenges that might emerge when firms use a performance measure for forecast accuracy, and illustrates how organizational actors experienced these challenges and how they adapted their approach to forecast accuracy in response to them.
Time series forecasting : advances on Theta method
The study’s primary approach, the Dynamic Optimised Theta Model, outperformed all benchmarks methods, constituting, in all likelihood, the highest-performing method for this data set available in the literature.
Validation and forecasting accuracy in models of climate change
Asking the Oracle: Introducing Forecasting Principles into Agent-Based Modelling
A set of guidelines, imported from the field of forecasting, that can help social simulation and agent-based modelling practitioners to improve the predictive performance and the robustness of their models are presented.
Assessment of forecasting management in international pharmaceutical companies : a grounded theory study
Despite the improvements in mathematical forecasts and teh creation of new formulas in forecasting, the increase in the accuracy forecasts is not yet significant, thus, leading to an increase in the


Findings from Evidence-Based Forecasting: Methods for Reducing Forecast Error
Combining forecasts: A review and annotated bibliography
The accuracy of extrapolation (time series) methods: Results of a forecasting competition
The results of a forecasting competition are presented to provide empirical evidence about differences found to exist among the various extrapolative (time series) methods used in the competition.
The Ombudsman: Reaping Benefits from Management Research: Lessons from the Forecasting Principles Project
Results from the forecasting principles project found that journals have provided 89 percent of the useful knowledge, however, journal papers relevant to practice are difficult to find because fewer than three percent of papers on forecasting contain useful findings.
Diffusion of Forecasting Principles through Books
It is found that none of the 18 forecasting books incorporated very many of the 139 forecasting principles, and the highest rated book mentions only 47 principles.
The design features of forecasting support systems and their effectiveness
Diffusion of Forecasting Principles through Software
This work evaluates the effectiveness of forecasting software in implementing relevant principles of forecasting in four market categories: spreadsheet add-ins, forecasting modules of general statistical programs, neural network programs, and dedicated business-forecasting programs.
Commentary on the Makridakis Time Series Competition (M-Competition)
In 1982, the Journal of Forecasting published the results of a forecasting competition organized by Spyros Makridakis, where the ex ante forecast errors of 21 methods were compared for forecasts of a variety of economic time series, generally using 1001 time series.