Table Of ContentCOMPUTATIONAL TECHNIQUES FOR ECONOMETRICS
AND ECONOMIC ANALYSIS
Advances in Computational Economics
VOLUME 3
SERIES EDITORS
Hans Amman, University ofA msterdam, Amsterdam, The Netherlands
Anna Nagurney, University ofM assachusetts at Amherst, USA
EDITORIAL BOARD
Anantha K. Duraiappah, European University Institute
John Geweke, University of Minnesota
Manfred Gilli, University of Geneva
Kenneth L. Judd, Stanford University
David Kendrick, University of Texas at Austin
Daniel McFadden, University of California at Berkeley
Ellen McGrattan, Duke University
Reinhard Neck, Universitiit Bielefeld
Adrian R. Pagan, Australian National University
John Rust, University of Wisconsin
Berc Rustem, University ofL ondon
Hal R. Varian, University ofM ichigan
The titles published in this series are listed at the end of this volume.
Computational Techniques
for Econometrics
and Economic Analysis
edited by
D. A. Belsley
Boston College, Chestnut Hill, U.S.A.
Springer-Science+Business Media, B.V.
Library of Congress Cataloging-in-Publication Data
Computational techniques for econoletrics and economic analysis I
edited by David A. Belsley.
p. cm. -- (Advances in computational economics; v. 3)
Includes index.
1. Econometric lodels--Data processing. 2. Economics.
Mathelatical--Data processing. I. Belsley. David A. II. Series.
H6141. C625 1993
330' .01'5195--dc20 93-17956
ISBN 978-90-481-4290-3 ISBN 978-94-015-8372-5 (eBook)
DOI 10.1007/978-94-015-8372-5
All Rights Reserved
©1994 Springer Science+Business Media Dordrecht
Originally published by Kluwer Academic Publishers in 1994.
Softcover reprint of the hardcover I st edition 1994
No part of the material protected by this copyright may be reproduced
or utilized in any form or by any means, electronic or mechnical,
including photocopying, recording or by any information storage and
retrieval system, without written permission from the copyright owner.
Table of Contents
Preface vii
Part One:
The Computer and Econometric Methods
Computational Aspects of Nonparametric Simulation Estimation
Ravi Bansal, A. Ronald Gallant, Robert Hussey, and George Tauchen 3
On the Accuracy and Efficiency Of GMM Estimators: A Monte Carlo Study
A. J. Hughes Hallett and Yue Ma 23
A Bootstrap Estimator for Dynamic Optimization Models
Albert J. Reed and Charles Hallahan 45
Computation of Optimum Control Functions by Lagrange Multipliers
Gregory C. Chow 65
Part Two:
The Computer and Economic Analysis
Computational Approaches to Learning with Control Theory
David Kendrick 75
Computability, Complexity and Economics
Alfred Lorn Norman 89
Robust Min-Max Decisions with Rival Models
Ber~ Rustem 109
Part Three:
Computational Techniques for Econometrics
Wavelets in Macroeconomics: An Introduction
William L. Goffe 137
MatClass: A Matrix Class for C++
C. R. Birchenhall 151
Parallel Implementations of Primal and Dual Algorithms for Matrix
Balancing
Ismail Chabini, Omar Drissi-Kartouni and Michael Florian 173
VI Table of Contents
Part Four:
The Computer and Econometric Studies
Variational Inequalities for the Computation of Financial Equilibria in the
Presence of Taxes and Price Controls
Anna Nagurney and June Dong 189
Modeling Dynamic Resource Adjustment Using Iterative Least Squares
Agapi Somwaru, Eldon Ball and Utpal Vasavada 207
Intensity of Takeover Defenses: The Empirical Evidence
Atreya Chakraborty and Christopher F. Baum 219
List of Contributors 233
Index 235
DAVID A. BELSLEY, EDITOR
Preface
It is unlikely that any frontier of economics/econometrics is being pushed faster,
further, and in more directions than that of computational techniques. The computer
has become both a tool for doing and an environment in which to do economics and
econometrics. Computational techniques can take over where theory bogs down,
allowing at least approximate answers to questions that defy closed mathematical or
analytical solutions. Computational techniques can make tasks possible that would
otherwise be beyond human potential. And computational techniques can provide
working environments that allow the investigator to marshal all these forces efficiently
toward achieving desired goals.
This volume provides a collection of recent studies that exemplify all the elements
mentioned above. And beyond the intrinsic interest each brings to its respective
subject, they demonstrate by their depth and breadth the amazing power that the
computer brings to the economic analyst. Here we see how modern economic
researchers incorporate the computer in their efforts from the very inception of a
problem straight through to its conclusion.
THE COMPUTER AND ECONOMETRIC METHODS
In "A Nonparametric Simulation Estimator for Nonlinear Structural Models,"
R. Bansal, A.R. Gallant, R. Hussey, and G. Tauchen combine numerical techniques,
the generalized method-of-moments, and non-parametrics to produce an estimator
for structural economic models that is defined by its ability to produce simulated
data that best match the moments of a scoring function based on a non-parametric
estimate of the conditional density of the actual data.
In "On the Accuracy and Efficiency of GMM Estimators: A Monte Carlo Study,"
AJ. Hughes Hallett and Yue Ma provide Monte Carlo evidence that helps to evaluate
the relative small-sample characteristics of several of the more popular generalized
method-of-moments estimators and surprise us by indicating that their own suggested
method seems to work best.
In "A Bootstrap Estimator for Dynamic Optimization Models," A.J. Reed and
C. Hallahan make use of a bootstrapping technique to provide estimates of stochastic,
dynamic programming models that can be made to conform to boundary restrictions
with relative ease.
In "Computation of Optimum Control Functions by Lagrange Multipliers,"
G. Chow explains and illustrates the gain in numerical accuracy that accompanies
D. A. Belsley (ed.), Computational Techniques for Econometrics and Economic Analysis. vii-ix.
viii Preface
his method of Lagrange multipliers for solving the standard optimal control problem
over the more usual method of solving the Bellman equations.
THE COMPUTER AND ECONOMIC ANALYSIS
D. Kendrick in "Computational Approaches to Learning with Control Theory" dis-
cusses the means by which the more realistic assumptions that different economic
agents have different knowledge and different ways of learning can be incorporated
in economic modeling.
In "Computability, Complexity and Economics," AL Norman works to find a
framework within which the mathematical theories of computability and complexity
can be used to analyze and compare the relative merits of various of the optimizing
procedures used in economics.
Ber~ Rustem, in "Robust Min-Max Decisions with Rival Models," provides an
algorithm for solving a constrained min-max problem that can be used to produce a
robust optimal policy when there are rival models to be accounted for.
COMPUTATIONAL TECHNIQUES FOR ECONOMETRICS
Continuing his tradition of seeing what the cutting edge has to offer economic and
econometric analysis, W.L. Goffe, in ''Wavelets in Macroeconomics: An Introduc-
tion," examines the usefulness of wavelets for characterizing macroeconomic time
series.
C.R. Birchenhall, in "MatClass: A Matrix Class for C++," provides an introduc-
tion to object-oriented programming along with an actual C++ object class library
in a context of interest to econometricians: a set of numerical classes that allows the
user ready development of numerous econometric procedures.
In "Parallel Implementations of Primal and Dual Algorithms for Matrix Balanc-
ing," I. Chabini, O. Drissi-Kailouni, and M. Florian exploit the power of parallel
processing (within the accessible and inexpensive "286" MS-DOS world) to bring
the computational task of matrix balancing, both with primal and dual algorithms,
more nearly into line.
THE COMPUTER AND ECONOMETRIC STUDIES
In "Variational Inequalities for the Computation of Financial Equilibria in the Pres-
ence of Taxes and Price Controls," A. Nagurney and 1. Dong develop a computa-
tional procedure that decomposes large-scale problems into a network of specialized,
individually-solvable subproblems on their way toward analyzing a financial model
of competitive sectors beset with tax and pricing policy interventions.
In "Modeling Dynamic Resource Adjustment Using Iterative Least Squares,"
A. Somwaru, V.E. Bell, and U. Vasavada develop and illustrate a computational
Preface IX
procedure for estimating structural dynamic models subject to restrictions such as
the inequalities entailed on profits functions through convexity in prices.
Recognizing that corporate behavior can be greatly affected by qualitative as well
as quantitative elements, A. Chakraborty and c.P. Baum, in "Intensity of Takeover
Defenses: The Empirical Evidence," harness the power of the computer to allow
them to study the qualitative issues surrounding the adoption and success of various
anti-takeover devices.
David A. Belsley
PART ONE
The Computer and Econometric Methods
