The Structural Econometric Time Series Analysis Approach

Front Cover
Arnold Zellner, Franz C. Palm
Cambridge University Press, Oct 21, 2004 - Business & Economics
Bringing together a collection of previously published work, this book 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. 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 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.
 

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Contents

Time series analysis and simultaneous equation
3
Statistical analysis of econometric models 1979
44
Comment 1979
79
Comment 1979
87
Structural econometric modeling and time series
96
Comment 1983 1 65
165
Time series analysis forecasting and econometric
175
Largesample estimation and testing procedures
201
and time series exchange rate models 1987
405
Encompassing univariate models in multivariate time
418
Macroeconomic forecasting using pooled international
457
Forecasting international growth rates using Bayesian
485
Turning points in economic time series loss structures
506
Forecasting turning points in international output
528
Bayesian and nonBayesian methods for combining
559
an application
590

Rejoinder 1981
233
Time series and structural analysis of monetary models
243
a case study
288
Time series analysis of the German hyperinflation
315
A time series analysis of seasonality in econometric
332
Comment 1978
382
Comment and implications for policymakers and model
388
Response to discussants 1978
394
Forecasting turning points in countries output growth
612
Using Bayesian techniques for data pooling in regional
619
growth rates using Bayesian techniques 1990
637
A note on aggregation disaggregation
656
The Marshallian macroeconomic model 2000
667
Bayesian modeling of economies and data
677
Subject index
707
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Page 7 - The equation system in (2.15), where each endogenous variable depends only on its own lagged values and on the exogenous variables, with or without lags, has been called the "separated form...
Page xi - Published by the Kansai Economic Federation with the collaboration of the Wharton School of Finance and Commerce, University of Pennsylvania, and the Institute of Social and Economic Research, Osaka University.
Page 15 - ... is dominated by a mixture of exponentials and damped sine waves after the first p — q lags.

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