Contents
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