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Forecasting non-stationary economic time series /

"In their second book on economic forecasting, Michael P. Clements and David F. Hendry ask why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to economic forecasting, they look at the implications for causal modeli...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Clements, Michael P.
Otros Autores: Hendry, David F.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, MA : MIT Press, 1999.
Colección:Zeuthen lecture book series.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Clements, Michael P. 
245 1 0 |a Forecasting non-stationary economic time series /  |c Michael P. Clements and David F. Hendry. 
260 |a Cambridge, MA :  |b MIT Press,  |c 1999. 
300 |a 1 online resource 
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504 |a Includes bibliographical references and index. 
505 0 |a 1. Economic Forecasting -- 2. Forecast Failure -- 3. Deterministic Shifts -- 4. Other Sources -- 5. Differencing -- 6. Intercept Corrections -- 7. Modeling Consumers' Expenditure -- 8. A Small UK Money Model -- 9. Co-breaking -- 10. Modeling Shifts -- 11. A Wage-Price Model -- 12. Postscript. 
520 1 |a "In their second book on economic forecasting, Michael P. Clements and David F. Hendry ask why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to economic forecasting, they look at the implications for causal modeling, present a taxonomy of forecast errors, and delineate the sources of forecast failure. They show that forecast-period shifts in deterministic factors - interacting with model misspecification, collinearity, and inconsistent estimation - are the dominant source of systematic failure. They then consider various approaches for avoiding systematic forecasting errors, including intercept corrections, differencing, co-breaking, and modeling regime shifts; they emphasize the distinction between equilibrium correction (based on cointegration) and error correction (automatically offsetting past errors). Finally, they present three applications to test the implications of their framework. Their results on forecasting have wider implications for the conduct of empirical econometric research, model formulation, the testing of economic hypotheses, and model-based policy analyses."--Jacket 
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546 |a English. 
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650 0 |a Economic forecasting  |x Statistical methods. 
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650 7 |a BUSINESS & ECONOMICS  |x Statistics.  |2 bisacsh 
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650 7 |a Time-series analysis.  |2 fast  |0 (OCoLC)fst01151190 
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700 1 |a Hendry, David F. 
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