2006
DOI: 10.1016/j.ijforecast.2006.04.007
|View full text |Cite
|
Sign up to set email alerts
|

Making progress in forecasting

Abstract: Twenty-five years ago, the International Institute of Forecasters was established "to bridge the gap between theory and practice. " Its primary vehicle was the Journal of Forecasting and is now the International Journal of Forecasting. The Institute emphasizes empirical comparisons of reasonable forecasting approaches. Such studies can be used to identify the best forecasting procedures to use under given conditions, a process we call evidence-based forecasting. Unfortunately, evidence-based forecasting meets … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
19
0
3

Year Published

2008
2008
2020
2020

Publication Types

Select...
9

Relationship

1
8

Authors

Journals

citations
Cited by 34 publications
(22 citation statements)
references
References 27 publications
0
19
0
3
Order By: Relevance
“…Many methods have been developed to model and forecast time series, making the choice of an appropriate method an important task. Extensive research conducted by forecasters indicates that there is no universally superior forecasting method and that theoretical arguments can be made in favor of multiple methods given the same set of data 4,22,23 . Therefore, good forecasting practice suggests that multiple forecasting methods should be compared and evaluated based on their ability to forecast postsample observations 23 .…”
Section: Methodsmentioning
confidence: 99%
“…Many methods have been developed to model and forecast time series, making the choice of an appropriate method an important task. Extensive research conducted by forecasters indicates that there is no universally superior forecasting method and that theoretical arguments can be made in favor of multiple methods given the same set of data 4,22,23 . Therefore, good forecasting practice suggests that multiple forecasting methods should be compared and evaluated based on their ability to forecast postsample observations 23 .…”
Section: Methodsmentioning
confidence: 99%
“…One fundamental contribution of forecasting research is its emphasis on the requirement that a method (or forecasting process) demonstrates its superiority by beating some plausible competing benchmark. In so far as researchers know how to select a good forecasting method ex ante, perhaps the primary requirement is that it must have been shown to work previously in circumstances similar to those which are expected to apply in the future, outperforming the alternatives, and in particular a benchmark (Armstrong & Fildes, 2006). Of course, it is expected that in small samples, the noise may well overwhelm the signal (in the GCMs derived from increasing CO 2 emissions and concentration levels), and therefore a large sample of forecasts may need to be considered.…”
Section: Forecast (Output) Validationmentioning
confidence: 99%
“…Wang et al [4] proposed residual modification models to improve the precision of seasonal ARIMA for electricity demand forecasting. The forecasting based on hybrid methodology that combines both autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models for predicting was presented in [5][6][7][8]. Kavasseri and Seetharaman [9] examined the use of fractional-ARIMA or f-ARIMA models to model, and forecast wind speeds.…”
Section: Introductionmentioning
confidence: 99%