
The Structural Econometric Time Series Analysis Approach
Résumé
Bringing together a collection of previously published work, this book provides a timely 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. Analytical relations between dynamic econometric structural models and empirical time series MVARMA, VAR, transfer function, and univariate ARIMA models are established with important application for model-checking and model construction. The theory and applications of these procedures to a variety of econometric modeling and forecasting problems as well as Bayesian and non-Bayesian testing, shrinkage estimation and forecasting procedures are also presented and applied. Finally, attention is focused on the effects of disaggregation on forecasting precision and the new Marshallian Macroeconomic Model that features demand, supply and entry equations for major sectors of economies is analysed and described. This volume will prove invaluable to professionals, academics and students alike.
Sommaire
- The SEMTSA approach
- Time series analysis and simultaneous equation econometric models (1974)
- Statistical analysis of econometric models (1979)
- Structural econometric modeling and time series analysis: an integrated approach (1983)
- Time series analysis, forecasting, and econometric modeling: the structural econometric modeling, time series analysis (SEMTSA) approach (1994)
- Large-sample estimation and testing procedures for dynamic equation systems (1980)
- Selected applications
- Time series and structural analysis of monetary models of the US economy (1975)
- Time series versus structural models: a case study of Canadian manufacturing inventory behavior (1975)
- Time series analysis of the German hyperinflation (1978)
- A time series analysis of seasonality in econometric models (1978)
- The behavior of speculative prices and the consistency of economic models (1985)
- A comparison of the stochastic processes of structural and time series exchange rate models (1987)
- Encompassing univariate models in multivariate time series: a case study (1994)
- Macroeconomic forecasting and modeling
- Macroeconomic forecasting using pooled international data (1987)
- Forecasting international growth rates using Bayesian shrinkage and other procedures (1989)
- Turning points in economic time series, loss structures, and Bayesian forecasting (1990)
- Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques (1991)
- Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates (1993)
- Pooling in dynamic panel data models: an application to forecasting GDP growth rates (2000)
- Forecasting turning points in countries' output growth rates: a response to Milton Friedman (1999)
- Disaggregation, forecasting, and modeling
- Using Bayesian techniques for data pooling in regional payroll forecasting (1990)
- Forecasting turning points in metropolitan employment growth rates using Bayesian techniques (1990)
- A note on aggregation, disaggregation, and forecasting performance (2000)
- The Marshallian macroeconomic model (2000)
- Bayesian modeling of economies and data requirements (2000)
Caractéristiques techniques
PAPIER | |
Éditeur(s) | Cambridge University Press |
Auteur(s) | Arnold Zellner, Franz C. Palm |
Parution | 07/10/2004 |
Nb. de pages | 718 |
Format | 15,5 x 23,5 |
Couverture | Relié |
Poids | 1284g |
Intérieur | Noir et Blanc |
EAN13 | 9780521814072 |
ISBN13 | 978-0-521-81407-2 |
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