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The Structural Econometric Time Series Analysis Approach
by Arnold Zellner (Editor), Franz C. Palm (Editor)
This book assembles key texts in the theory and applications of the Structural Econometric Time Series Analysis (SEMTSA) approach. 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 presented and applied. Finally, attention is focused on the effects of disaggregation on forecasting precision.
Book Description
This book assembles previously published texts in the theory and application of the Structural Econometric Time Series Analysis (SEMTSA) approach. It 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.
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List of contributors page ix
Acknowledgments xi
Introduction xiii
Part I The SEMTSA approach
1 Time series analysis and simultaneous equation
econometric models (1974) 3
.
2 Statistical analysis of econometric models (1979) 44
Comment (1979) 79
.
Comment (1979) 82
.
Comment (1979) 84
.
Comment (1979) 87
.
Rejoinder (1979) 91
3 Structural econometric modeling and time series
analysis: an integrated approach (1983) 96
.
Comment (1983) 165
.
Comment (1983) 169
Response to the discussants (1983) 172
.
4 Time series analysis, forecasting, and econometric
modeling: the structural econometric modeling, time
series analysis (SEMTSA) approach (1994) 175
5 Large-sample estimation and testing procedures for
dynamic equation systems (1980) 201
.
Rejoinder (1981) 233
.
Part II Selected applications
6 Time series and structural analysis of monetary models
of the US economy (1975) 243
.
7 Time series versus structural models: a case study of
Canadian manufacturing inventory behavior (1975) 288
.
8 Time series analysis of the German hyperinflation
(1978) 315
9 Atime series analysis of seasonality in econometric
models (1978) 332
.
Comment (1978) 382
.
Comment and implications for policy-makers and model
builders (1978) 388
.
Response to discussants (1978) 394
.
10 The behavior of speculative prices and the consistency of
economic models (1985) 397
11 A comparison of the stochastic processes of structural
and time series exchange rate models (1987) 405
. .
12 Encompassing univariate models in multivariate time
series: a case study (1994) 418
Part III Macroeconomic forecasting and modeling
13 Macroeconomic forecasting using pooled international
data (1987) 457
-, .
, . ,
14 Forecasting international growth rates using Bayesian
shrinkage and other procedures (1989) 485
15 Turning points in economic time series, loss structures,
and Bayesian forecasting (1990) 506
, ,
.
16 Forecasting turning points in international output
growth rates using Bayesian exponentially weighted
autoregression, time-varying parameter, and pooling
techniques (1991) 528
, ,
-
17 Bayesian and non-Bayesian methods for combining
models and forecasts with applications to forecasting
international growth rates (1993) 559
-
18forecasting GDP growth rates (2000) 590
. , . ,
.
19 Forecasting turning points in countries’ output growth
rates: a response to Milton Friedman (1999) 612
Pooling in dynamic panel data models: an application to
Part IV Disaggregation, forecasting, and modeling
20 Using Bayesian techniques for data pooling in regional
payroll forecasting (1990) 619
. .
21 Forecasting turning points in metropolitan employment
growth rates using Bayesian techniques (1990) 637
. .
22 A note on aggregation, disaggregation, and
forecasting performance (2000) 656
23 The Marshallian macroeconomic model (2000) 667
24 Bayesian modeling of economies and data
requirements (2000) 677
Subject index 707
Author index 712
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