The Structural Econometric Time Series Analysis Approach - Brossura

Brossura

ISBN 10: 0521187435 ISBN 13: 9780521187435

Casa editrice: Cambridge University Press, 2011

Riassunto

This text offers key texts in the theory and application of the Structural Econometric Time Series Analysis (SEMTSA) approach.

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Descrizione del libro

This book assembles previously published texts in the theory and application of the Structural Econometric Time Series Analysis (SEMTSA) approach. It provides a discussion of major considerations relating to the construction of econometric models that work well to explain economic phenomena, predict future outcomes and be useful for policy-making.

Contenuti

Introduction; Part I. The SEMTSA Approach: 1. Time series analysis and simultaneous equation econometric models A. Zellner and F. C. Palm; 2. Statistical analysis of econometric models A. Zellner; 3. Structural econometric modeling and time series analysis: an integrated approach F. C. Palm; 4. Time series analysis, forecasting and econometric modeling: the structural econometric modeling, times series analysis (SEMTSA) approach A. Zellner; 5. Large sample estimation and testing procedures for dynamic equation systems F. Palm and A. Zellner; Part II. Selected Applications: 6. Time series and structural analysis of monetary models of the US economy A. Zellner and F. Palm; 7. Time series versus structural models: a case study of Canadian manufacturing inventory behavior P. K. Trivedi; 8. Time series analysis of the German hyperinflation P. Evans; 9. A time series analysis of seasonality in econometric models C. I. Plosser; 10. The behavior of speculative prices and the consistency of economic models R. I. Webb; 11. A comparison of the stochastic processes of structural and time series exchange rate models F. W. Ahking and S. M. Miller; 12. Encompassing univariate models in multivariate times series: a case study A. Maravall and A. Mathis; Part III. Macroeconomic Forecasting and Modeling: 13. Macroeconomic forecasting using pooled international data A. Garcia-Ferrer, R. A. Highfield, F. Palm and A. Zellner; 14. Forecasting international growth rates using Bayesian shrinkage and other procedures A. Zellner and C. Hong; 15. Turning points in economic time series, loss structures and Bayesian forecasting A. Zellner, C. Hong and G. M. Gulati; 16. Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter and pooling techniques A. Zellner, C. Hong and C. Min; 17. Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates C. Min and A. Zellner; 18. Pooling in dynamic panel data models: an application to forecasting GDP growth rates A. J. Hoogstrate, F. C. Palm and G. A. Pfann; 19. Forecasting turning points in countries' output growth rates: a response to Milton Friedman A. Zellner and C. Min; 20. Using Bayesian techniques for data pooling in regional payroll forecasting J. P. LeSage and M. Magura; 21. Forecasting turning points in metropolitan employment growth rates using Bayesian techniques J. P. LeSage; 22. A note on aggregation, disaggregation and forecasting performance A. Zellner and J. Tobias; 23. The Marshallian macroeconomic model A. Zellner; 24. Bayesian modeling of economies and data requirements A. Zellner and B. Chen.

Dettagli dell?edizione

• Editore: Cambridge University Press
• Data di pubblicazione: 2011
• ISBN 10: 0521187435
• ISBN 13: 9780521187435
• Rilegatura: Copertina flessibile
• Lingua: Inglese
• Numero di pagine: 736
• Redattore: Zellner Arnold
• Contatto del produttore: non disponibile