Forecasting :: an essential introduction /
Concise, engaging, and highly intuitive--this accessible guide equips you with an understanding of all the basic principles of forecasting.
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New Haven ; London :
Yale University Press,
[2019]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Concise, engaging, and highly intuitive--this accessible guide equips you with an understanding of all the basic principles of forecasting. |
| Beschreibung: | 1 online resource (xiv, 213 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780300248241 0300248245 |
Internformat
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| 100 | 1 | |a Castle, Jennifer, |d 1979- |e author. |1 https://id.oclc.org/worldcat/entity/E39PBJvt9CKxH6VhcXcdgFgkDq |0 http://id.loc.gov/authorities/names/nr2004013374 | |
| 245 | 1 | 0 | |a Forecasting : |b an essential introduction / |c Jennifer L. Castle, Michael P. Clements, David F. Hendry. |
| 264 | 1 | |a New Haven ; |a London : |b Yale University Press, |c [2019] | |
| 300 | |a 1 online resource (xiv, 213 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed April 11, 2019). | |
| 520 | |a Concise, engaging, and highly intuitive--this accessible guide equips you with an understanding of all the basic principles of forecasting. | ||
| 505 | 0 | |a 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 by; Sources of information; Chapter 3. Where are we before we forecast? | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 wrong; Why does differencing work?; Robustification can help; Chapter 9. How do we automatically detect breaks?; Finding shifts by indicator saturation | |
| 505 | 8 | |a 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 eruption; Chapter 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? | |
| 505 | 8 | |a 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?; Is economic forecasting an oxymoron?; In need of better communication; Can you believe forecasts from 'experts'?; Chapter 15. Further reading; Subject index. | |
| 650 | 0 | |a Economic forecasting. |0 http://id.loc.gov/authorities/subjects/sh85040814 | |
| 650 | 6 | |a Prévision économique. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Economics |x General. |2 bisacsh | |
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| 700 | 1 | |a Clements, Michael P., |e author. |0 http://id.loc.gov/authorities/names/n97124472 | |
| 700 | 1 | |a Hendry, David F., |e author. |0 http://id.loc.gov/authorities/names/n84023190 | |
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| author | Castle, Jennifer, 1979- Clements, Michael P. Hendry, David F. |
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| contents | 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 by; Sources 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 wrong; Why 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 eruption; Chapter 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?; Is economic forecasting an oxymoron?; In need of better communication; Can you believe forecasts from 'experts'?; Chapter 15. Further reading; Subject index. |
| ctrlnum | (OCoLC)1096280255 |
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| dewey-ones | 330 - Economics |
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| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| publisher | Yale University Press, |
| record_format | marc |
| spelling | Castle, Jennifer, 1979- author. https://id.oclc.org/worldcat/entity/E39PBJvt9CKxH6VhcXcdgFgkDq http://id.loc.gov/authorities/names/nr2004013374 Forecasting : an essential introduction / Jennifer L. Castle, Michael P. Clements, David F. Hendry. New Haven ; London : Yale University Press, [2019] 1 online resource (xiv, 213 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references and index. Online resource; title from PDF title page (EBSCO, viewed April 11, 2019). Concise, engaging, and highly intuitive--this accessible guide equips you with an understanding of all the basic principles of forecasting. 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 by; Sources 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 wrong; Why 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 eruption; Chapter 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?; Is economic forecasting an oxymoron?; In need of better communication; Can you believe forecasts from 'experts'?; Chapter 15. Further reading; Subject index. Economic forecasting. http://id.loc.gov/authorities/subjects/sh85040814 Prévision économique. BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh BUSINESS & ECONOMICS Forecasting. bisacsh Economic forecasting fast Clements, Michael P., author. http://id.loc.gov/authorities/names/n97124472 Hendry, David F., author. http://id.loc.gov/authorities/names/n84023190 has work: Forecasting (Text) https://id.oclc.org/worldcat/entity/E39PCFYQYp8xcYQdTYCq6JJmBd https://id.oclc.org/worldcat/ontology/hasWork Print version: Castle, Jennifer, 1979- Forecasting. New Haven [Connecticut] : Yale University Press, [2019] 0300244665 (DLC) 2019934600 (OCoLC)1055260945 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2099754 Volltext |
| spellingShingle | Castle, Jennifer, 1979- Clements, Michael P. Hendry, David F. Forecasting : an essential introduction / 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 by; Sources 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 wrong; Why 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 eruption; Chapter 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?; Is economic forecasting an oxymoron?; In need of better communication; Can you believe forecasts from 'experts'?; Chapter 15. Further reading; Subject index. Economic forecasting. http://id.loc.gov/authorities/subjects/sh85040814 Prévision économique. BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh BUSINESS & ECONOMICS Forecasting. bisacsh Economic forecasting fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85040814 |
| title | Forecasting : an essential introduction / |
| title_auth | Forecasting : an essential introduction / |
| title_exact_search | Forecasting : an essential introduction / |
| title_full | Forecasting : an essential introduction / Jennifer L. Castle, Michael P. Clements, David F. Hendry. |
| title_fullStr | Forecasting : an essential introduction / Jennifer L. Castle, Michael P. Clements, David F. Hendry. |
| title_full_unstemmed | Forecasting : an essential introduction / Jennifer L. Castle, Michael P. Clements, David F. Hendry. |
| title_short | Forecasting : |
| title_sort | forecasting an essential introduction |
| title_sub | an essential introduction / |
| topic | Economic forecasting. http://id.loc.gov/authorities/subjects/sh85040814 Prévision économique. BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh BUSINESS & ECONOMICS Forecasting. bisacsh Economic forecasting fast |
| topic_facet | Economic forecasting. Prévision économique. BUSINESS & ECONOMICS Economics General. BUSINESS & ECONOMICS Reference. BUSINESS & ECONOMICS Forecasting. Economic forecasting |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2099754 |
| work_keys_str_mv | AT castlejennifer forecastinganessentialintroduction AT clementsmichaelp forecastinganessentialintroduction AT hendrydavidf forecastinganessentialintroduction |