Econometric Decision Models: Proceedings of a Conference Held at the University of Hagen, West Germany, June 19–20, 1981

373 Pages·1983·8.636 MB·English

by  Josef Gruber (auth.), Prof. Dr. Josef Gruber Ph.D. (eds.)

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Lectu re Notes
in Economics and
Mathematical Systems
Managing Editors: M. Beckmann and W. Krelle
Econometrics
208
Econometric
Decision Models
Proceedings of a Conference
Held at the University of Hagen, West Germany,
June 19 - 20,1981
Edited by Josef Gruber
Springer-Verlag
Berlin Heidelberg New York Tokyo 1983
Editorial Board
H. Albach A. V. Balakrishnan M. Beckmann (Managing Editor)
p. Ohrymes, J. Green W. Hildenbrand W. Krelle (Managing Editor)
H. P. KOnzi K. Ritter R. Sato U. Schittko P. Schonfeld R. Selten
Managing Editors
Prof. Dr. M. Beckmann
Brown University
Providence, RI 02912, USA
Prof. Dr. W. Krelle
Institut fOr Gesellschafts-und Wirtschaftswissenschaften
der Universitat Bonn
Adenauerallee 24-42, 0-5300 Bonn, FRG
Editor
Prof. Dr. Josef Gruber, Ph.D.
Fernuniversitat Hagen
Fachbereich Wirtschafts-und Rechtswissenschaften
Roggenkamp 6, 0-5800 Hagen, FRG
ISBN-13: 978-3-540-11554-0 e-ISBN-13: 978-3-642-46464-5
001: 10.1007/978-3-642-46464-5
Library of Congress Cataloging in Publication Data.
Main entry under title: Econometric decision models. (Lecture notes in economics and
mathematical systems; 208) 1. Econometrics-Congresses. 2. Economics-Mathematical
models-Congresses. 3. Economic policy-Mathematical models-Congresses. 4. Deci
sion-making-Mathematical models-Congresses. I. Gruber. Josef, 1935-. II. Fernuniversitlit
Hagen. III. Series. HB141.E218 1983 330'.028 82-19706 ISBN 0-387-11554-4 (U.S.)
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© by Springer-Verlag Berlin Heidelberg 1983
2142/3140-543210
PREFACE
This proceedings volume contains papers presented at the conference on
econometric decision models held at the University of Hagen (= Fern
Universitat), June 19-20, 1981. Included are also two papers by authors
from abroad which could not be presented during the conference: one by
E.O. Heady et al. from the USA and one by H. and J. Wallenius from
Finland.
The authors of the 18 papers/extended abstracts included in this
volume are econometricians, economists and operations researchers.
The papers were contributed by scientists from the following coun
tries: West Germany (10 papers), The United States (3 papers), The
Netherlands (2 papers), Finland (1 paper), Switzerland (1 paper)
and Yugoslavia (1 paper).
Although all but one authors come from universities, the audience of
the conference also came from economic agencies at the federal and
state level. This composition of the audience made for a fruitful
exchange of ideas on the possibility and necessity of improving econo
metric decision models so that these models may play a greater role
in practical policy decision making.
Some further remarks on this topic can be found in the introductory
paper of this volume.
For providing financial support of the conference, I wish to thank the
University of Hagen (and the taxpayer in the State of Northrhine-West
falia), the 'Gesellschaft der Freunde der FernUniversitat" (= Society
of the Friends of the University of Hagen), and several banks.:
Commerzbank Hagen, Commerzbank Hohenlimburg, Sparkasse Hagen, Volks
bank Hagen.
I also wish to thank the managing editors of this series of Lecture
Notes for accepting the conference papers in this proceedings volume,
the Springer Verlag for publishing it, and Mrs. E. Greber, my secre
tary, for editorial assistance.
May the reader of this volume find answers to some important questions
concerning econometric decision models. May he be inspired to ask new
questions and/or to take up old questions and problems again in order
to strive for better answers and improved solutions.
Hagen, October 1982 Josef Gruber
TABLE OF CONTENTS Page
GRUBER, J.:
"Introduction: Towards observed preferences in econometric decision
models"
PROBLEM AREA 1: Econometric decision models in theory and practice:
experiences and problems in large-scale applications,
recent developments in theory and methods (except
those of problem areas 2 and 3 below)
FISCHER, J. and UEBE, G.:
"The "optimal" control of the RWI-model" 10
HElKE, H.D. and ROSSA, H.:
"Optimal stabilization with a quarterly model of the Federal
Republic of Germany" 21
RIESS, H. Ch.:
"Some experiences with the control of a macroeconometric model with
a scalarvalued objective function from the viewpoint of applied
economic research" 48
KIRCHGl\.SSNER, G.: Y
"An application of optimal control to a small model of politico-
economic interaction" 55
BAUM, Ch. F.: ~
"Evaluating macroeconomic policy: Optimal control solutions versus
suboptimal alternatives" 81
KENDRICK, D.:
~
"Adaptive control of macroeconomic models" (abstract) 110
LESERER, M.;
"A fine-tuning scheme for economic decision rules" 111
FROMMHOLZ, H. and WOLTERS, J.:
A control-theoretic analysis for a small econometric model of the
Federal Republic of Germany" 116
FRIEDMANN, R.:
"The asymptotic distribution of optimal policy feedback coeffi-
cients" 131
HAAS, H.:
"Conflict, cooperation and social preference functions" 148
PETKOVSKI, D. B. :
"Decentralized control strategies for large-scale discrete-time
systems" 170
HEADY, E.O., LANGLEY, J .A., and HUANG, W.:
"A recursive adaptive hybrid model for national and interregional
analysis" 183
VI
PROBLEM AREA 2: Methods for obtaining the weights and target Page
vaZues in the saaZarvaZued objeative funation
of (e.g.) the Zinear-quadratia econometria
deaision modeZ
ST5pPLER, S. and STEIN, J.-P.:
-A study of adaptive revision of target values in an econometric
decision model" 221
MERKIES, A.H.Q.M. and NIJMAN, TH.E.:
-The measurement of quadratic p£eference functions with small
samples" 242
ANCOT, J.P. and HUGHES HALLETT,A.J.:
-The determination of collective preferences in economic decision
models: With an application to Soviet economic policy" 263
PROBLEM AREA 3: Methods for avoiding the necessity of expZicitly
specifying and quantifying a scalarvalued objective
function before solving the econometric decision
model
DEISSENBERG, Ch.:
"Interactive solution of multiple objective, dynamic, macroeconomic
stabilization problems: A comparative study" 305
WALLENIUS, H. and WALLENIUS, J.:
"A methodology for solving the multiple criteria macroeconomic
policy problem" 310
STREUFF, H. and GRUBER, J.:
"The interactive multiobjective optimization method by Elemer E.
Rosinger: A computer program and aspects of applications" 334
INTRODUCTION; TOWARDS OBSERVED PREFERENCES IN ECONOMETRIC DECISION
MODELS
Josef Gruber
FernUniversitat Hagen
Lehrgebiet Statistik und Bkonometrie
D-5800 Hagen 1, Federal Republic of Germany
Abstract
This paper contains some of the remarks I made during the opening of
the conference on econometric decision models at the University of
Hagen, June 19-20, 1981. Its main message is concerned with a varia
tion of a theme by W. Leontief (1971), namely: In econometric decision
models, use observed preferences of the decision maker instead of
theoretically assumed (hypothetical, "plausible") preferences.
In recent developments in theory and methods, there are two main lines
along which this can roughly be accomplished:
a) Some methods are directed towards numerically determining the para
meters of the scalar-valued preference function of econometric de
cision models from data (time series observations, cross section
observations from surveys, interviews etc.). Papers of problem area
2 deal with this line of research.
b) Interactive methods of vector optimization avoid the necessity of
explicitly specifying a scalar-valued preference function. They are
more or less well adapted to the needs of decision makers working
with econometric equation systems. For practical decision making,
this approach has important advantages in comparison with control
theoretical decision models in which an explicitly specified scalar
valued preference function is required. Papers of problem area 3
deal with this line of research.
Contents Page:
Econometric decision models as a tool for studying problems
of economic policy 2
2 Econometric decision mode~with an explicitly specified
scalar-valued preference function 3
3 Econometric vector optimization model$ interactive procedures
and observed preferences of decision makers 6
2
Page:
4 Three major problem areas discussed 7
8
References
Econometric decision models as a tool for studying problems of
economic policy
Problems of economic policy and planning have motivated the founders
of econometrics. In his Ragnar Frisch lecture at the Fourth World Con
gress of the Econometric Society at Aix-en-Provence in 1980, E. Malin
vaud stated: "The research program launched by Tinbergen, and taken
over by Lawrence Klein, has led to the current abundance of macroecono
metric models and to the fact that these models have become the main
instrument for studying macroeconomic policy, and this even in coun
tries which, like France, long remained sceptical" (Malinvaud, 1981,
p. 1363).
Whether (macro)econometric models are the main instrument or just one
instrument (among others) can not be of major interest here. May it
suffice to observe that input-output models and activity analysis
models ("programming models") in general are also important tools of
economic analysis and decision making, also or especially at levels
that are disaggregated by sectors, in time and in space. Models for the
statistical analysis of time series which are, in contrast to econome
tric models, not based on economic theory serve a different but also
very important purpose. Problem-oriented economic analysis usually
necessitates the combination of various types of models and methods.
According to the topic of this conference, we are mainly concerned
with the following question: How can the usefulness of econometric mo
dels as tools for decision making be increased?
One way of increasing the usefulness of econometric forecasting models
is to use these models as a part of econometric decision models (= opti
mization models): In an econometric decision model, an objective func
tion (or functional) is optimized subject to constraints derived from
(among other components) an econometric equation system.
During this conference, mainly two types of econometric decision models
were dealt with:
1. the econometric decision model with an explicitly specified scalar
valued preference function and
2. the econometric decision model in which no scalar-valued preference
3
function is specified explicitly. Instead, in an interactive algo
rithm for vector optimization, the decision maker communicates with
the computer. He supplies in each iteration pieces of information
on his local preferences. An optimal solution of the decision pro
blem is reached in a finite number of iterations. Let me briefly
call this type of model "econometric vector optimization model".
Let me make a few remarks on these two types of econometric decision
models.
2 Econometric decision mode~with an explicitly specified scalar-valued
preference function
The particular version of this type of model which is most often used,
especially for deriving optimal stabilization policies, is the linear
quadratic model: The explicitly specified preference function to be op
timized is quadratic in the target and instrument variables, and the
constraints are linear in these variables. This type of model is also
known as the control theoretical (econometric) decision model.
Optimization models of this type were explained in detail and in the
terminology familiar to economists first of all in the textbooks by
Theil, 1964, and by Fox, Sengupta and Thorbecke, 1966. Especially in
the latter book, this type of decision model was integrated into the
theory of quantitative economic policy. It also contains a chapter on
control theory. ~ortunately, as a graduate student I had the opportu
nity to attend the seminar series on quantitative economic policy at
Iowa State University - probably the first advanced course of this type
in the USA - in the academic year 1962/63,when Karl A. Fox, Jati K. Sen
gupta und Erik Thorbecke began to develop a set of lecture notes which
finally resulted in the textbook published in 1966 (second edition 1973).)
If the econometric decision model contains dynamic restrictions (i.e.
a dynamic econometric equation system), the economic policy model be
comes very similar to the optimal control model: The solutions of both
models define an optimal time path of the state vector. Therefore,
additional insight into the properties of optimal economic policies may
be gained when these are interpreted in terms of optimal control
theory.
However, it cannot be denied that models and methods from optimal con
trol are not yet sufficiently adapted to the peculiarities of quanti
tative economic policy. For example, in economic policy it does matter
4
whether the target variable "number of unemployed persons" is larger
or smaller than a given desired value; but in controlling a chemical
production process, a positive deviation from a desired value of a tar
get variable may be as disadvantageous as a negative deviation.
Also, after an exogenous disturbance the decrease of oscillatory move
ments of target and control variables to a tolerable size in (say)
20 periods may be acceptable to the decision maker in the chemical
production process, where the length of the observation period may e.g.
be one second. But such oscillatory movements of target and instrument
variables may be completely unacceptable to the economic policy maker
who e.g. has to work with quarterly data.
An impressive amount of research has resulted in a better adaptation
of models of optimal control to the needs of quantitative economic poli
cy, but often at the expence of disadvantages with respect to other
properties. For example, the replacement of the quadratic criterion
function by a piecewise quadratic function permits the decision maker
to "weight" positive deviations of an instrument variable from the
corresponding desired value different than negative deviations. But
this advantage of the piecewise quadratic preference function cannot
be gained without loss of the first-period certainty equivalence
result (see e.g. Friedman, 1972, 1975).
For recent reviews of control theory in economics see, e.g., Pau,
1979, and Szego, 1982. With its applicability are especially con
cerned e.g. Johansen, 1979, and Shupp, 1979. See also several papers
in this proceedings volume, section "problem area 1".
A major (perhaps the major) problem in constructing an econometric de
cision model with an explicitly specified scalar-valued preference
function is the development of this preference function. Some research
on solving this problem has been done (see e.g. Johansen, 1974, and
Frisch, 1981). But most practitioners today still work, it seems to me,
like I did in 1965 - 1967 in a pilot study on market stabilization (see
Gruber, 1967):
A quadratic objective function is chosen (mainly because it is easy
to handle; it leads to linear decision rules in the case of linear
equality constraints) ;
- trend values of target and instrument variables are taken as desired
values (e.g. values free of cyclical fluctuations);
- the weighting matrices ("penalty matrices") are assumed to be diago
nal (as a rule, only then there is a chance of getting these matrices