| Subject |
Economic forecasting.
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| Descript |
1 online resource. |
| Content |
text txt |
| Media |
computer c |
| Carrier |
online resource cr |
| 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 |
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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 |
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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 |
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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 |
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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? |
| Note |
Unlimited number of concurrent users. UkHlHU |
| Alt author |
Clements, Michael P.,
|
|
Hendry, David F.,
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| ISBN |
9780300248241 (electronic bk.) |
|
0300248245 (electronic bk.) |
|
9780300244663 |
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