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Prior Information and ARIMA Forecasting
Author(s) -
Cholette Pierre A.
Publication year - 1982
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980010405
Subject(s) - autoregressive integrated moving average , judgement , econometrics , pessimism , computer science , consensus forecast , operations research , economics , time series , mathematics , machine learning , philosophy , epistemology , political science , law
Abstract Using the method of ARIMA forecasting with benchmarks developed in this paper, it is possible to obtain forecasts which take into account the historical information of a series, captured by an ARIMA model (Box and Jenkins, 1970), as well as partial prior information about the forecasts. Prior information takes the form of benchmarks. These originate from the advice of experts, from forecasts of an annual econometric model or simply from pessimistic, realistic or optimistic scenarios contemplated by the analyst of the current economic situation. The benchmarks may represent annual levels to be achieved, neighbourhoods to be reached for a given time period, movements to be displayed or more generally any linear criteria to be satisfied by the forecasted values. The forecaster may then exercise his current economic evaluation and judgement to the fullest extent in deriving forecasts, since the laboriousness experienced without a systematic method is avoided.