The Impact of empirical accuracy studies on time series analysis and forecasting
Author: Fildes, Robert ; Makridakis, SpyrosINSEAD Area: Technology and Operations Management Series: Working Paper ; 93/29/TM Publisher: Fontainebleau : INSEAD, 1993.Language: EnglishDescription: 26 p.Type of document: INSEAD Working Paper Online Access: Click here Abstract: This paper examines a specific area of social science, time series forecasting, which, through empirical studies using real-life data, allows for objectivity and replicability and offers the possibility of controlled experimentation. Yet its findings are ignored and its conclusions to advance the field of forecasting are disputed. The paper describes what has been learnt from forecasting competitions and compares the results with expectations base on stastistical theory. It demonstrates that considerable anomalies exist which have been neglected by academic statisticians who have focussed their attention on topics/directions of little practical value, and no relevance for real-life applications. The paper concludes with a challenge to theoretical statisticians and empirical researchers alike : working together they can learn from each other and advance their field to better serve the business and economic communities and make their area more useful and relevant to policy and decision makersItem type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Digital Library | Available | BC000732 |
This paper examines a specific area of social science, time series forecasting, which, through empirical studies using real-life data, allows for objectivity and replicability and offers the possibility of controlled experimentation. Yet its findings are ignored and its conclusions to advance the field of forecasting are disputed. The paper describes what has been learnt from forecasting competitions and compares the results with expectations base on stastistical theory. It demonstrates that considerable anomalies exist which have been neglected by academic statisticians who have focussed their attention on topics/directions of little practical value, and no relevance for real-life applications. The paper concludes with a challenge to theoretical statisticians and empirical researchers alike : working together they can learn from each other and advance their field to better serve the business and economic communities and make their area more useful and relevant to policy and decision makers
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