Forecasting : an essential introduction / Jennifer L. Castle, Michael P. Clements, David F. Hendry
- Bib ID:
- 8052523
- Format:
- Book
- Author:
- Castle, Jennifer, 1979-, author
- Online Access:
- http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2099754
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- Description:
-
- New Haven ; London : Yale University Press, 2019
- 1 online resource.
- ISBN:
-
- 9780300248241 ((electronic bk.))
- 0300248245 ((electronic bk.))
- Invalid ISBN:
- 9780300244663
- Full contents:
-
- Cover page; FORECASTING; Copyright page; Contents; Figures; Preface; Acknowledgments; Chapter 1 Why do we need forecasts?; What is a forecast?; Why do we need forecasts?; A brief history of forecasting; Why are forecasts uncertain?; A motoring analogy; Beware false forecasting; Time, models and the future; The road ahead-literally; Chapter 2 How do we make forecasts?; A galaxy of terms, and ways, for 'seeing into the future'; Making forecasts; Forecasting her journey time; Forecasting in 'normal' times; More uncertainty; Illustrating forecast uncertainty; Adapting to forecast failure
- Updating forecasts as time goes bySources of information; Chapter 3 Where are we before we forecast?; The motorist and the economist; Why are data subject to revision? And why might it matter?; Forecasting data revisions; Inaccurate data do matter; Chapter 4 How do we judge forecasts?; Forecasts are made to inform decisions; Standard forecast evaluation criteria; Everyone wins!; Unequal costs of positive and negative forecast errors; Chapter 5 How uncertain are our forecasts?; Modeling and forecasting uncertainty; Interval forecasts; 'Density' forecasts; Evaluating 'density' forecasts
- Chapter 6 Are some real world events unpredictable?Sudden unanticipated shifts: When the ground moves; Flocks of 'black swans'; Trends and their ilk; Why does the type of trend matter?; Trends can cancel; Location shifts can also cancel; Chapter 7 Why do systematic forecast failures occur?; Some impressive forecast failures; Missing systematically; We don't always fail!; What changes matter most for forecast failure?; Learning from past mistakes; What do forecast failures entail?; Chapter 8 Can we avoid systematic forecast failures?; The bus-stop game; Risks and benefits of 'causal' models
- Adaptation as forecasts go wrongWhy does differencing work?; Robustification can help; Chapter 9 How do we automatically detect breaks?; Finding shifts by indicator saturation; Chapter 10 Can we forecast breaks before they hit?; What would we need to know?; Forecasting the Great Recession; The 2004 Indian Ocean tsunami; Two information sets; Chapter 11 Can we improve forecasts during breaks?; Illustrating forecasting during a break; A possible role for non-linear models; Missing breaks, but adapting quickly; Switching between several 'regimes'; The costs of mis-forecasting hurricanes
- Forecasting climate after a volcanic eruptionChapter 12 Would more information be useful?; Pooling information; Are simple models best?; Pooling forecasts; Using other information; Should we use big or small forecasting models?; If only we could forecast shifts!; Chapter 13 Can econometrics improve forecasting?; Models versus extrapolation (or rules-of-thumb); All models are not born equal; Are 'good' forecasting models useful for policy?; From forecasting to forediction; Federal Open Market Committee members' assessments; Chapter 14 Can you trust economic forecasts?
- Notes:
-
- Includes bibliographical references and index.
- Online resource; title from PDF title page (EBSCO, viewed April 11, 2019).
- Reproduction:
- Electronic reproduction. Ipswich, MA Available via World Wide Web.
- Subject:
- Economic forecasting
- Other authors/contributors:
- Available From:
-
- JSTOR
- OverDrive, Inc.
- Copyright:
-
In Copyright
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Copyright status was determined using the following information:
- Material type:
- Literary Dramatic Musical
- Published status:
- Published
- Publication date:
- 2019
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