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Nevertheless the history of economics has
taken its revenge on Koopmans' reductionist agenda.
Had the Cowles Commission implemented their
structural-equation agenda in Walrasian general
equilibrium theory, the reductionist agenda would
have appeared to have been realized. But the macroeconomics that was actually used for
implementation was not a macroeconomics that is just
an extension of Walrasian microeconomics; it was the
Keynesian macroeconomics.
Even before Smith's Wealth
of Nations economists were interested in what
may be called macroeconomics in the sense of a
theory of the overall level of output for a national
economy. With the 1871 marginalist revolution economists had developed
an economic psychology based on the classical
rationality postulate of maximizing behavior, which
enabled economists to use the differential calculus
to express their theory.
And this in turn occasioned the
mathematically elegant Walrasian general equilibrium
theory that affirmed that the rational maximizing
behavior of individual consumers and entrepreneurs
would result in the maximum level of employment and
output for the whole national macroeconomy.
The Great Depression of the 1930's called
this optimism into question, and Keynes'
macroeconomic theory offered an alternative thesis
of the less-than-full-employment equilibrium.
This created a distinctively macroeconomic
perspective, because it made the problem of
determining the level of total output and employment
a different one than the older problem of
determining the most efficient interindustry
resource allocation in response to consumer
preferences.
This new perspective also brought in its
train certain other less obvious novelties. Ostensibly the achievement of Keynes' theory was to explain
the possibility of the less-than-full-employment
equilibrium by the use of the classical economic
psychology, the theory of value that explains
economic behavior in terms of the maximizing
rationality postulate.
But supporters as well as critics of Keynes
knew that there is a problem in deriving a theory in
terms of communities of individuals and groups of
commodities from a basic theory set forth in terms
of individuals and single commodities.
In his Keynesian
Revolution ([1947], 1966) the Keynesian advocate
and 1980 Nobel laureate econometrician, Lawrence
Klein (b. 1920, called this "the problem of
aggregation", and he notes that Keynesians have
never adequately addressed this problem.
Joseph Schumpeter, a Harvard University
economist critical of Keynes, was less charitable. In his review of Keynes' General
Theory in Journal
of the American Statistical Association (1936)
he described Keynes' "Propensity to Consume”
as nothing but a deus
ex machina that is valueless if we do not
understand the "mechanism" of changing
situations in which consumers' expenditures
fluctuate, and he goes on to say that Keynes'
"Inducement to Invest", his
"Multiplier", and his "Liquidity
Preference", are all an Olympus of such
hypotheses which should be replaced by concepts
drawn from the economic processes that lie behind
the surface phenomena.
In other words this brilliant expositor of
the Austrian school of marginalist economics
regarded Keynes' theory as hardly less atheoretical
than if Keynes had used data analysis.
Schumpeter would settle for nothing other
than a marginalist macroeconomic theory in the
Romanticist tradition.
For the next quarter of a century economists
attempted unsuccessfully to reduce macroeconomics to
microeconomics, but econometricians did not wait for
the approval of the likes of Schumpeter.
Keynesian economics became the principal
source of theoretical equation specifications for
macroeconometric modeling.
In 1955 Klein and Goldberger published their
Keynesian macroeconometric model of the U.S.
national economy, which later evolved into the
elaborate WEFA macroeconometric model of several
thousand equations. And this is not the only large Keynesian macroeconometric
model; there are now many others, such as the
DRI-WEFA and the Economy.com models, and they have
spawned important information-consulting industry
marketing to both business and government.
But there are considerable differences among
these large macroeconometric models, and these
differences are not decided by reference to
purported derivations from rationality postulates or
microeconomic theory, even though econometricians
ostensibly subscribe to Haavelmo's
structural-equation programme and include relative
prices in their equations.
The criterion that is effectively operative
in the choice among the many alternative business
cycle models is unabashedly pragmatic; it is their
forecasting performance.
Muth’s
Rationalist Expectations Agenda
After Muth's papers, interest in the rational
expectations hypothesis died, and the rational
expectations literary corpus was entombed in the
tomes of the profession's periodical literature for
almost two decades.
Then unstable national macroeconomic
conditions including the deep recession of 1974
and the high inflation of the later 1970's created
embarrassments for macroeconomic forecasters using
the large structural-equation macroeconometric
models based on Keynes' theory.
These large models had been gratifyingly
successful in the 1960's, but their structural
breakdown in the 1970's occasioned a more critical
attitude toward them and a proliferation of
alternative views.
One consequence was the disinterment and
revitalization of interest in the rational
expectations hypothesis.
Most economists today attribute these
economic events to the large increases in crude oil
prices imposed by the Organization of Petroleum
Exporting Countries or "OPEC.”
These events were also accompanied by large
Federal fiscal deficits and by Federal Reserve
expansionary monetary policies, and these
macroeconomic policy actions became targets of
criticism, in which the structural-equation type of
models containing such policy variables was attacked
using the rational expectations hypothesis.
1995 Nobel laureate economist Robert E. Lucas
(1937-
) criticized the traditional structural-equation
type of econometric model.
He was for a time at Carnegie-Mellon, and
came from University of Chicago, to which he has
since returned.
Lucas' "Econometric Policy Evaluation: A
Critique" in The
Phillips Curve and Labor Markets (1976) states
on the basis of Muth's papers, that any change in
policy will systematically alter the structure of
econometric models, because it changes the optimal
decision rules underlying the statistically
estimated structural parameters in the econometric
models. Haavelmo
had addressed the same type of problem in his
discussion of the irreversibility of economic
relations, and his prescription for all occasions of
structural breakdown is the addition of missing variables.
But Lucas does not even mention this remedy.
Thomas J. Sargent, economist at the University of
Minnesota and also an advisor to the Federal Reserve
Bank of Minneapolis joined Lucas in the rational
expectations critique of structural models in
their jointly written "After Keynesian Macroeconomics"
(1979) reprinted in their Rational
Expectations and Econometric Practice (1981).
They state that the verbal statement of
Keynes' theory set forth by Keynes himself in his General
Theory (1936) does not contain reliable prior
information that certain variables should be
excluded from the right-hand side of the structural
equations of the macroeconometric models based on
Keynes' theory, and furthermore that neoclassical
theory of optimizing behavior almost never implies
either the exclusionary restrictions suggested by
Keynes or those imposed by modern macroeconometric
models. They
maintain that the parameters identified as
structural by current structural-equation macroeconometric
methods are not in fact structural, and that these
models have not isolated structures that remain
invariant. This
criticism of the structural-equation models is
perhaps better described as criticisms of the
structural models based on Keynesian macroeconomic
theory, and they leave open the possibility that
structural-equation business-cycle econometric
models could nevertheless be constructed, which
would not be used for policy analysis, and which are
consistent with the authors' rational expectations
alternative. But
while Lucas and Sargent offer the non-Keynesian
theory that business fluctuations are due to errors
in expectations resulting from unanticipated events,
they do not offer another structural-equation type
of model. Events
took another turn: what happened was the rejection
of the use of expectations measurement data by the
rational expectations advocates, and the consequent
development of a kind of rational expectations
macroeconometric model that is different from
Haavelmo's structural-equation type of model.
Rejection
of Expectations Data and Evolution of VAR Models
The rejection of the use of expectations
measurement data antedates Muth's rational
expectations hypothesis.
In 1957 University of Chicago economist
Milton Friedman set forth his permanent income
hypothesis in his Theory
of the Consumption Function.
This is the thesis for which he was awarded the Noble prize
twenty years later, and in his Nobel Lecture,
published in Journal of Political Economy (1977) he expressed approval of the
rational expectations hypothesis and explicitly
referenced the contributions of Muth, Lucas and
Sargent. In
the third chapter of his book, "The Permanent
Income Hypothesis", he discusses the semantics
of his theory and of measurement data. He states that the magnitudes termed "permanent"
are ex ante
theoretical constructs, and that they cannot be
observed directly for an individual consumer.
He says that the most that can be observed
are actual income expenditures and receipts during
some definite period, and that these observed
measurements are ex
post empirical data, although they may be
supplemented by verbal statements by the consumer
about his future expenditures. Friedman explains that the theoretical concept of permanent
income is understood to reflect the effect of
factors which the income earner regards as
determining his capital value, his subjective
estimate of a discounted future income stream.
Friedman does not explain why the permanent
income cannot be directly observed, why ex
ante empirical reports of expectations cannot
function as observations of the permanent income
signified by the theoretical concept, nor does he
describe the "supplementary" role of
empirical ex
ante measurements.
Instead he poses a problem of establishing a
correspondence between the theoretical constructs
and the observed data.
Thus Friedman poses an even more radical
semantical dualism between theory and observational
description than did Haavelmo.
Friedman's strategy for resolving his
correspondence problem is to use the statistician's
idea of "expected value" of a probability
distribution to isolate a permanent income component
in the ex post
measurement data.
He calls the concept of permanent income an
"analogy" to the statistical concept of
expected value.
The outcome of his semantical dualism is that
empirical ex
ante or reported expectations data are excluded
from any consideration in his empirical analyses
based on his theory.
Muth does not follow Friedman's
neo-Positivist dichotomizing of the semantics of
theory and observation.
In his rational expectations hypothesis he
simply ignores the idea of establishing any
correspondence by analogy between the purportedly
unobservable theoretical concept and the
statistical concept of expected value, and makes the
statistical concept of expected value the literal
meaning of "expectations.”
Friedman subdivides total measured income
into a permanent part and a transitory part.
He says that in a large group the empirical
data tend to average out, so that their mean average
or expected value is the permanent part, and the
residual transitory part has a mean average of zero.
In another statement he says that permanent
income for the whole community can be regarded as a
weighted average of current and past incomes
adjusted by a secular trend, with the weights
declining as one goes back further in time.
When this type of relationship is expressed
as an empirical model, it is a type known as an
autoregressive model, and it is the type that is
very strategic for representation of the rational
expectations hypothesis in contrast to the structural-equation
type of econometric model.
In 1960 Muth published "Optimal
Properties of Exponentially Weighted
Forecasts" in American Statistical Association Journal.
Muth referenced this paper in his
"Rational Expectations" paper, but this
paper contains no reference to empirically gathered
expectations data.
Muth says that Friedman's determination of
permanent income is vague, and he proposes instead
that an exponentially weighted average of past
observations of income can be interpreted as the
expected value of the time series.
He develops such an autoregressive model, and
shows that it produces the minimum-variance forecast
for the period immediately ahead for any future time
period, because it gives an estimate of the
permanent part of measured income. The exponentially weighted average type of model had been
used instrumentally for forecasting for production
planning and inventory planning, but economists had
not thought that such autoregressive models have any
economic significance.
Muth's identification of the statistical
concept of expected value with subjective
expectations in the minds of the population gave the
autoregressive forecasting models a new economic
relevance, but the forecasting success or failure of
these models does not test the rational expectations
hypothesis, because they have no relation to the
neoclassical theory and its maximizing postulate
with or without expectations.
Nearly two decades later there occurred the
development of a more elaborate type of
autoregressive model called the "vector
autoregression" or "VAR" model set forth by Thomas J. Sargent in his "Rational
Expectations, Econometric Exogeniety, and
Consumption" in Journal
of Political Economy (1978).
Building on the work of Friedman, Muth and
Lucas, Sargent developed a two-equation linear
autoregressive model for consumption and income, in
which each dependent variable is determined by
multiple lagged values of both variables.
This is called the "unrestricted vector
autoregression" model. It
implements Muth's thesis that expectations depend on
the structure of the entire economic system; it says
that all factors in the model enter into
consideration by all economic actors in all their
economic roles.
The
VAR model does not have Haavelmo's semantical
property of autonomy, because there is no attempt to
identify the factors considered in determining the
preferences of any particular economic group, since
each individual considers everything.
In his "Estimating Vector
Autoregressions Using Methods Not Based On Explicit
Economic Theories" in Federal
Reserve Bank of Minneapolis Quarterly Review
(Summer, 1979), Sargent explains that the VAR
model is not constructed with the same procedural
limitations that must be respected for construction
of the structural-equation model.
Construction of the structural model requires
firstly that the relevant economic theory be
referenced as prior information, and assumes that no
variables may be included in a particular equation
other than those variables for which there is a
theoretical justification.
This follows from Haavelmo's premise that the
probability approach in econometrics is the
application of Neyman-Pearson statistical inference
technique to equations having their specifications
determined a priori by economic theory. But
when the rational expectations hypothesis is
implemented with the VAR
model, the situation changes because
expectations are viewed as conditioned on past
values of all variables in the system and may enter
all the decision functions.
This makes the opposite assumption more
appropriate, namely that in general it is likely
that movements of all variables affect behavior of
all other variables, and all the econometrician's
decisions in constructing the model are guided by
the statistical properties and performance characteristics
of the model rather than by a
priori theory.
He also notes in this article that VAR
models are vulnerable to Lucas' critique, and that
these models cannot be used for policy analyses.
The objective of the VAR model is good forecasting with small mean squared errors.
Criticisms of structural-equation models
similar to those of Lucas and Sargent were set forth
by Christopher A. Sims, a colleague of Sargent then
at the University of Minnesota and now at Yale
University, in his "Macroeconomics and
Reality" in Econometrica
(1980), and Sims advocates the rational
expectations hypothesis and the development of VAR
models. He also states that the coefficients of the VAR models are not easily interpreted for their economic meaning,
and he proposes that economic information be
developed from these models by simulating the
occurrence of random shocks and then observing the
consequences described by the reaction of the model.
Sims thus inverts the relation between
economic interpretation and model construction
advanced by Haavelmo: instead of beginning with the
theoretical understanding and then imposing its
structural restrictions on data in the process of
constructing the equations of the empirical model,
Sims firstly constructs the VAR
model from the data, and then develops an
understanding of economic structure from simulation
analyses with the model.
In the Federal
Reserve Bank of Minneapolis Quarterly Review
(Winter, 1986) Sims states that users of
VAR models have been using these models for
policy analysis in spite of caveats about the
practice. Not
surprisingly this policy advisor to a Federal
Reserve Bank does not dismiss such efforts. He says that use of any models for policy analysis
involves making economic interpretations of the
models, and that predicting the effects of policy
actions thus involves making assumptions for
identifying a structure from the VAR
model. But
his technique of using shock simulations admits to
more than one structural form for the same VAR model, and he offers no procedure for choosing among alternative
structures. His
approach is judgmental.
Litterman's
BVAR Models and Discovery System
In his "Forecasting with Bayesian Vector
Autoregression: Four Years of Experience" in
the 1984
Proceedings of the American Statistical Association,
also written as a Federal
Reserve Bank of Minneapolis Working Paper,
Robert Litterman, at the time a staff economist for
the Federal Reserve Bank of Minneapolis and who
has since moved into the private sector, says that
the original idea to use a VAR
model for macroeconometric forecasting at the
Minneapolis Federal Reserve Bank came from Thomas
Sargent. Litterman's
own involvement, which began as a research assistant
at the Bank, was to write a computer program to
estimate VAR
models and to forecast with them.
He reports that the initial forecasting
results with this unrestricted VAR model were so disappointing, that a simple univariate
autoregressive time series model could have done a
better job, and it was evident that the unrestricted
VAR is
not successful. In
his "Are Forecasting Models Usable for Policy
Analysis?" Litterman noted that the failure
of the unrestricted VAR
model was the attempt to fit too many variables to
too few observations.
This failure led to the development of the
Bayesian VAR
model, and the Bayesian technique became the basis
for Litterman's doctoral thesis titled Techniques
for Forecasting Using Vector Autoregression (University
of Minnesota, 1980).
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