159. "Making Policy for Complex Systems: A Medical Model for
Economics," Journal of Policy Analysis and Management, Vol. 4, No.
3 (1985), pp. 383-395. Reprinted in Ray C. Rist (ed.), Policy Studies
Review Annual, Vol. 8, New Brunswick, NJ: Transaction Books.
Abstract: In recent years, policy analysts have shown a growing
interest in less rationalistic policymaking models. Medical
knowledge may be useful to consider in this regard, since it
combines practical knowledge with the findings of numerous
analytic disciplines, and includes procedures for dealing with
high uncertainty. In contrast, economic policymaking often
applies analysis from a single discipline directly to a
multifaceted problem. A broader "socioeconomic" approach
emulating the medical model would incorporate variables such as
political, social, cultural, psychic, and environmental factors.
RATIONALITY AND POLICYMAKING
Policy science, the effort to build a systematic approach to
policymaking, has burgeoned since 1970. The number of books and
journals devoted to the subject has increased sharply, as well as
the number of policy-related schools, centers, and courses. At
the same time, however, one finds little agreement on the nature
and dimensions of the discipline, on the base of knowledge from
which scholars and policy advisors ought to derive their
formulations. Some scholars lean toward a strict natural science
model. They hope to evolve a mathematically derived set of
procedures for formulating policies, and they seek a high-powered
quantitative testing of propositions to determine the "best"
policy.(1) Others lean toward a "softer" approach, of the kind
prevalent in the humanities. They seek to sensitize a policymaker
to certain considerations by transmitting the lessons of previous
experiences, by calling attention to nonquantitative factors that
otherwise might be overlooked, and by drawing insights from case
Studies of policymaking which assume that the actors are
highly rational have largely followed the natural science model,
often drawing on economics. For decades economics has been
considered the queen of the social sciences, the most successful
policy science, the one that most resembles physics and the one
most inclined to ascribe to man rational faculties. Indeed, in
the early 1960s it was widely assumed that economics of itself
provided a sufficient knowledge base for successful managing of
the economy. Yet today there is much less certainty that
economics can reliably provide such a basis for public policy.(2)
Theorists have also recognized that highly quantitative
approaches such as the one introduced during the Johnson
administration, first in the Defense Department and then in
domestic agencies, known as Planning-Programming-Budgeting
System,(3) may have required more information and a greater
capacity to assess implications than was possible, at least at
the time. Game theory, another type of highly logical and
quantitative approach, has also proven more fallible than its
proponents had hoped. Psychological studies have shown that
peoples' behavior diverges sharply from the key assumptions of
In the realm of public administration, rational decision-making has been challenged by those who maintain that "disjointed
incrementalism" (muddling through) is both the way most decisions
are made and, in the final analysis, the way they are best made.(5)
On the highest level, Herbert Simon's intellectual
breakthrough is widely acknowledged. He pointed out that human
beings do not--and in fact, are unable to conduct themselves with
the full rationality that the economist's view of "optimization"
requires. Rather, "satisficing" describes the pattern typically
followed. People tend to end their search for a solution when
they find an option that seems "good enough."(6)
All this is not to imply that the rationality theorem has
been abandoned. In recent years, for instance, an economic theory
entitled rational expectations" gained a certain following. It
assumes people act as if they are actually conversant with
economic theory.(7) Yet, by and large, there is now a greater
readiness to entertain theorems and approaches that assume a
lesser degree of rationality and to ask how decisions might be
made with less than a high degree of knowledge.
The Medical Model
The search for less rationalistic models for policy science
may benefit from an examination of the medical profession, or,
indeed, other professions that are based on the application of a
body of scientific knowledge. (Engineering, for example, might be
pertinent, but law would not be.) This suggestion assumes, first
of all, that knowledge is organized and applied differently when
the immediate purpose is to provide service rather than to
achieve greater comprehension; the distinction separates
professional knowledge from that of the basic sciences.
Professionals emphasize finding solutions to a problem, whether
or not they fully understand how and why the solution works,
whereas researchers in basic science focus on discovering
explanations for the unknown, not on means of responding to it.
Two problems arise in considering medical practice as a
possible model for the policy sciences: First, there is
disagreement among medical scholars themselves over the
characteristics of medicine. At one extreme there are those who
see medical science as a basic science. At the opposite extreme
there are those who stress its artlike qualities, the
considerable extent to which physicians draw on intuition and
insight and are unable explicitly to account for their
decisions.(8) Most students of medicine view their profession as
something between these poles, as akin to other science-based
professional bodies of knowledge, which are said to mix
scientific elements with trial and error.(9)
Following this view, I suggest that one can discern three
essential parts to medical knowledge: findings from a variety of
basic sciences, medical knowledge not derived from or directly
reducible to other sciences, and rules of conduct to cope with
circumstances of high uncertainty. I would expect that these
component parts are not unique to medical practice but rather
typify any field that consists of complex but only partially
known systems. Since policymakers deal routinely with such
systems, medical knowledge can in this respect provide a model
for policy science.
The second objection to medical knowledge as an analog to
the policy sciences concerns differences in the nature of the
goals and structure of the two disciplines. The goal of medicine
is relatively clear and straightforward whereas the policy field
encompasses multiple and often conflicting goals. Furthermore,
the structure of decision-making is unitary in the medical
profession while it is pluralistic and contested in policymaking.
These differences suggest, first of all, that policy analysis is
much more difficult than medical analysis. (And may well help
explain why medicine is a relatively more successful endeavor.)
It follows that if medicine requires various "accommodative"
mechanisms and cannot proceed solely from rationalistic
assumptions, then policy analysis would need such mechanisms even
more. "Accommodative" mechanisms allows one to function, "make
do," when faced with an unresolvable difficulty. While such
mechanisms are inevitably "second best," less satisfactory than
resolutions--they are preferable to inaction. In the medical
context, for example, L-Dopa is a medication that suppresses
severe symptoms, enabling patients to function, but it does not
slow the progress of the underlying illness.
The medical model is applicable if one also remembers that
in the formal reasoning process the analogy to policymaking can
be limited to one facet of medicine, setting aside others. We can
learn from the way medical facts, theories, and methods relate to
one another and are used, even if goal-setting and decision-making structures are quite different. Or, to put it differently,
once policymakers set their goals through whatever system they
use to reach their decisions, they will still face knowledge
issues similar to those faced in the practice of medicine.
THE PROBLEM OF SCIENTIFIC FRAGMENTATION
Since economics tends to emulate the basic sciences in key
respects, any discussion of the relevance of medicine to
economics must begin with a look at the nature of those sciences.
It has often been noted that scientific analysis requires
abstraction. Unique features of various incidents of the same
phenomenon are deliberately overlooked in favor of generic
features. It is much less often taken into account that
scientific analysis also proceeds by fragmenting the phenomenon
under study. Instead of all the facets of a phenomenon being
studied, many attributes, including generic ones, are
deliberately and systematically ignored in favor of focusing on a
few selected attributes. A chemist may focus on the process of
photosynthesis of flowers; a geneticist, on the various
chromosomes; an economist, on the changes in their prices; a
social psychologist, on the meaning of giving various kinds of
Scientific work progresses by grouping information, or
findings, about a slice of the phenomenon under study, into an
analytic discipline. Analytic theories are constructed by
grouping together variables of one kind, whether chemical, or
genetic, or economic. Propositions are derived within these
segregated frameworks and are compared with data organized within
the same categorical confines. Scientific knowledge is
accumulated and transmitted within these frameworks.
This system of scientific inquiry successfully serves the
advancement of science, but the application of such a system to
decision-making in the real world of public policy has received
little attention. In many instances, policy decisions require
dealing with all the main elements that are intertwined in a
Under these conditions, when the findings of one analytic
science are applied directly to a multifaceted problem, the
effect is that action is based only on a subset of variables.
Sometimes, as economists have found, this limited input is
sufficient for successful policy analysis. But the following
conditions must apply: The dynamics of the phenomena in question
must be governed by a limited number of variables, all of which
are members of the same analytic subset, such as, for example,
one that includes physics or biology or chemistry. The second key
requirement is that the phenomena involved be relatively isolated
from all others so that changes in the variables that
characterize phenomenon X can range considerably without causing
or reacting to changes in variables that characterize other
phenomena. For example, the movement of the planets is a
phenomenon independent of radioactive decay on earth.
Limited analytic input may also be sufficient when a high
degree of precision is not sought (the "imprecision" is the
variance accounted for by the other factors not encompassed), or
when the other variables affecting the phenomena change very
slowly, are temporarily set or dormant, or when the time studied
is very short. However, under all other conditions, analysis
based on one discipline will lead to an erroneous knowledge base
To put it conversely, the greater the precision sought, the
more complex the set of variables that must be encompassed, the
less segregated the phenomena, the longer the time span and the
more rapid the pace of change, the lower the ability to move
directly from an analytic discipline to dealing with the
phenomenon. For the sake of brevity these phenomena will be
termed "complex" and the others "simple," although obviously this
is a continuum composed of varying degrees of complexity. We face
a high degree of complexity when we deal with a human body (in
medicine), personality (in psychology), or society (in public
policy), all of which are systems in which numerous factors from
various analytic disciplines affect one another. (The term
semiorganic is sometimes used to characterize this system
Policymakers clearly need to deal with all the relevant
factors that account for a significant portion of the variance,
as well as with the result of their interactions. Otherwise, the
variables ignored will come to haunt them, as is the case when
the psychic implications, or social, cultural, and political
prerequisites of economic policy are ignored. This is the result,
for example, when international organizations such as the IMF,
without regard to the stability of the national governments
involved, urge austerity programs based on monetarist theories on
developing countries, causing the government to be overthrown and
the policy to be rejected along with the policymakers.(11)
RESYNTHESIS: THE ELUSIVE SOLUTION
When one seeks to apply the knowledge of basic sciences to
complex phenomena, the prescribed way to overcome the problem
posed by fragmentation is as easy to depict as it is difficult to
realize. The proper way is said to be to resynthesize the
findings of the various relevant analytic disciplines before one
seeks to act in the concrete world.
For example, the resynthesized flower would contain all the
relevant information bearing on the flower and the variables
that. account for changes in the observed data. It would include
the relationships and interaction among these variables, not
merely within one discipline but also across disciplines. For
example, it would record that excessive plasmolysis of cellular
fluids will result in wilting, decreasing the flower's price, and
reversing its symbolic meaning.
Why not, then, combine relevant findings of several analytic
disciplines, say mainstream economics,(12) experimental psychology,
public administration, and quantitative sociology and political
science? For two reasons resynthesis is infrequently attempted
and rarely accomplished successfully (for complex systems).
First, applying such a process to complex phenomena requires of
the analyst a Renaissance breadth of mind; all the variables must
be ascertained and data about the role and effect of each
integrated. Combining the data of even two disciplines, such as
chemistry and biology, often proves quite taxing. An encompassing
resynthesis is typically overwhelming. (Computers may aid in
dealing with the data, but so far seem to have been unhelpful in
the conceptual integration required.)
One might ask whether it is necessary to include all the
variables. Do we not seek here an "overidentifying" model,(13) one
whose complexity is close to that of the phenomenon under study
and hence thwarts science's search for generalization and for
parsimony? My answer is that we should indeed avoid
overidentification and should include only major relevant
variables. Major may be defined as those that account for a set
proportion of the variance, such as 5% or more. This may often
entail as many as 15 variables or more, from several
Moreover, while in some situations variables X Y,
and Z may account for much of the variance of a phenomenon,
variables A, B, and C will account for it in another instance,
and so on. It may require scores of variables to account for
most--not all!--of the variance of phenomena that a policy, such
as economic policy, seeks to address.
The second reason that the synthesis is rarely successful is
that cash discipline is based on particular assumptions about the
nature of the world and the processes that govern it. These
assumptions are often incompatible with those made by other
disciplines.(15) For instance, much of economic theory tends to
assume that people are basically rational and will act to advance
their own self-interest. In contrast, major segments of
psychology, sociology, and social anthropology assume that people
are largely governed by nonrational forces, such as values and
sentiments, and will act to advance the common good quite
readily. Moreover, physiology's approach to people typically
assumes neither capacity.
In short, at least in the near future--possibly in the
longer run--resynthesis will remain elusive, and practical
alternatives will have to be found.
The Eclectic Medical Approach
How does the special structure of medical knowledge enable
physicians to compensate for the inability to resynthesized
First, medicine draws on several analytic disciplines
simultaneously without seeking to truly integrate their findings
or assumptions--in what might be referred to as a mechanical,
rather than a chemical, combination. For instance, when faced
with patients who report severe and persistent headaches,
established medical procedure requires the physician to test
first for organic causes and only after the search for those is
exhausted are patients to be referred to psychiatrists. This
combination of two radically different approaches to the
diagnosis of severe headaches is based on the practical
consideration that the organic causes may require urgent
attention while as a rule psychic causes can wait. Such pragmatic
sequential diagnosis will suffice for treatment purposes. In
contrast, comprehension of the headache phenomenon requires a
much higher level of knowledge than is often available to
physicians. For example, what, if any, are the interaction
effects between organic and psychic factors in causing headache?
Are there headaches caused by psychic factors alone? Can those be
distinguished from others caused by organic factors? This is but
one of many examples in which medical knowledge pieces together
various kinds of analytic knowledge, sufficient for service
purposes but not for compehension.
The example also illustrates the reason medicine draws on
several analytic disciplines. The causes of an illness may be
genetic, chemical, physiological, or psychic. Medical diagnoses
based on one analytic discipline are likely to prove
unsatisfactory in a high proportion of the cases medicine seeks
A second factor that enables medical practice to proceed
without a full resynthesizing process is its reliance on past
experience, case studies, statistical relationships, and other
sources of practical information. For example, a physician can
draw definite clinical implications from studies that show a
strong correlation between smoking and lung cancer, even though
science has not yet established how smoking causes cancer.
According to some estimates, a substantial part of current
medical knowledge is of this practical variety.(16)
Finally, to cope with complex and only partially known
systems, physicians formulate, as an integral part of their
discipline, certain procedures for dealing with decision-making
in circumstances of high uncertainty. The high uncertainty is a
direct result of the complex systems, the body or the
personality, with which the physicians deal. Such complex systems
often can be only partially known.
"Partial" knowledge is to be distinguished from the often
used "imperfect" knowledge, a term which implies that the actor
knows most of what is necessary to carry out rational analysis.
The imprecision that may result from less than perfect knowledge
is seen as quite insignificant. Such assumptions are not
appropriate in numerous, if not most medical interventions. To be
sure, medical knowledge as a rule is not so deficient as to
advocate procedures on the basis of little or no knowledge, that
is, to instigate random interventions. Typically, knowledge is
somewhere between "little" and "imperfect"; "partial" seems the
Some of the procedures for coping with high uncertainty are
standard logical processes applied in a medical context. Probably
the most widely used are those that entail what might be called
focused trial-and-error. This approach assumes the physician has
sufficient information to identify the area where the search for
accurate treatment ought to begin. Then, as treatment is applied,
results are checked at predetermined intervals and adjustments
are made in the interventions. Such a "feedback" process is a
method of accommodating the unknown. This approach differs
significantly from both outright trial-and-error, in which no
prior knowledge is assumed, and fine-tuning searches are
undertaken, which are appropriate when knowledge is high.
Other coping procedures are unique to medicine. For example,
the physician relies on as many senses as possible,'including
smell and touch, not merely on the information attainable from
various tests and measurements.
ECONOMICS AND THE MEDICAL MODEL: The Differences
How does economics compare with the model that medical
knowledge offers? Mainstream American economics as a discipline
is highly analytic. It either disregards political, social,
cultural, psychic, and environmental factors or treats them as
exogenous variables which do not change rapidly (and hence may be
treated as constants), or as random events that need not be
incorporated into the model.
In recent years many economists have come to believe that
the highly analytic character of the discipline poses a central
difficulty for the policymaker. Many consider the assumptions of
economics too unrealistic and the quest for mathematical elegance
a hindrance in the search for empirically valid theorems.(17)
Although these criticisms may be valid, the medical model
suggests yet another difficulty in developing sound policy on the
basis of economics and that difficulty is the tendency to rely on
a single analytic discipline. It seems evident that economic
policy, which seeks to affect economic phenomena, must take into
account all the major factors that influence these phenomena,
including noneconomic elements such as political, social, and
psychic factors. It follows that even if the assumptions of
economics were modified, if the discipline used a less demanding
mathematics, and so on, it would still, by itself, not provide an
adequate base for the formation of economic policy.
Obviously, economists have not been oblivious to the impact
of noneconomic factors, but they have dealt with them in a
fashion that does not resemble the medical model. One approach
has been to try to incorporate noneconomic factors into economic
theories as if they were economic in nature. This approach
assumes that people are propelled by self-interest and act
rationally not only in economic matters but also in their
political, social, and familial actions. Certain "public choice"
theoreticians promulgate this view, arguing that elected
officials, for example, act solely to maximize their reelection
chances while in office.(18) "Rational expectations" theory, as
well, assumes that people's expectations are not driven by
anxiety, hopes, and aspirations, but are guided by information
they assimilate and analyze quite like economists.(19) Finally,
there are the ideas of "balance-sheet" theoreticians of the
family who treat the decision to have children as analogous to
the decision to purchase a durable consumer good, such as a
refrigerator.(20) The usefulness of these theories is considerably disputed. They are referred to, at best, as interesting and worth
exploring, but not, so far, as a sufficient basis for economic
policy.(21) Few observers believe that the relevant noneconomic
factors can be converted to economic elements.
The second approach seeks to avoid the dilemma of multiple
influences by reverting to a much less analytic science, to the
way political economics was,(22) and history as well as large
segments of anthropology and sociology, often still is. This
tradition relies on relatively descriptive, close-to-the-phenomenon terms; concepts and theorems tend to be broad and to refer to multifaceted phenomena with relatively little
fragmentation. Thus, for instance, the term "class" is used
widely not to denote a mode of ownership, a rank in society, a
shared social perspective, or a political group, but some kind of
a unspecified mix of all of these attributes. The result is often
gratifying to those who seek global, Toynbean, "meaningful"
explanations of the world, but the accounts also lack empirical
specificity. Others who shun the analytic perspective for a more
descriptive one see each situation as unique, endlessly rich in
detail, defying any scientific generalizations. Neither of these
approaches provides a scientific basis for policymaking.
A third approach is to supplement the information from
analytic economics with the practical knowledge of the area to
which it is applied, such as labor economics or developmental
economics. This endeavor is closer to the medical model.(23)
The Use of Principles
What is often missing in any of these approaches that would
complete the development of an economics modeled on the practice
of medicine is the formulation and application of guidance
principles. These are principles that help policy analysts and
policymakers to cope with high uncertainty resulting from partial
knowledge of complex systems. Such principles are of little
interest to an analytic science that seeks a high degree of
determination, even if this can be achieved only for the
relationship among the variables covered in its models. They are,
on the other hand, of great value to those who must act with
partial knowledge even after they piece together inputs from
several analytic disciplines and augment it with practical
knowledge. The principles fill the very considerable remaining
Although some of these principles are elementary, a
distillation of commonsense and experience, their importance is
underscored by the consequences that ensue when they are ignored.
Other principles are more complex and based on counterintuitive
assumptions and on logical or mathematical models.
Among the first kind is a principle that states that because
models are insufficient, all policies are very likely to require
significant adjustment as time goes on; implementation calls
attention to factors not modeled and to changes in circumstances
that have not been anticipated. For instance, one reason Social
Security found itself facing large deficits in the early 1980s
was that assumptions concerning birth rates were built into its
actuarial tables and were not modified for years even after it
became evident that fertility was declining sharply.(24) (Over time such a decline results in fewer people contributing to the system
in proportion to those who draw benefits.) One could attempt to
anticipate such changes from now on, but experience shows that
the actual demographics tend to fall outside the range of
forecasts made.(25) Hence, a good policy principle is to assume
that actuarial tables based on such forecasts must be revised
Another simple rule that is often disregarded is the need to
maintain a "strategic reserve" of funds as a cushion against
unforeseen demands. Many small businesses ultimately fail because
they have been launched without adequate capital; they lack the
means to deal with unforeseen emergencies once they have
committed all their reserves to the initial investment.
More complex rules are illustrated by the James Tobin
"portfolio theory." He drew on the mathematical probability
theory of Pascal, Fermat, Laplace, and Kolmogorov to determine
what proportion of one's investment ought to be put into stocks
and bonds instead of being kept in cash which yields no return.(26)
The policy science that would emerge if practitioners
adhered to these various principles could be called
"socioeconomics" to distinguish it from economics as an analytic
science.,Socioeconomics would combine contributions from other
disciplines whose subjects are political, cultural, and psychic.
The term would also serve as a reminder that there is no one
policy science applicable to all policy areas. For instance,
educational policy needs a different policy science, one which
draws more heavily on psychology and sociology and less on
economics. And, of course, the practical knowledge component
would differ from one policy science to another just as it does,
say, between medicine and engineering.
In the practice of medicine the need to rely on sources of
knowledge other than that provided by one analytic discipline
varies greatly from one subfield to another. For instance,
genetic counseling and hematology require a less eclectic base
than do the areas of psychosomatic illness, public health, or
preventive medicine. Similarly, in economic policy analytic
economics per se may be relatively more "serviceable" in price
theory (especially for those sections of the market which
approximate perfect competition) than, say, industrial
The explanation for the variation may lie in the fact that
the subfields that are less dependent on information from other
disciplines and concern subsystems of the body or the economy
that are relatively segregated from the whole system and hence
relatively less complex by the definition introduced above. While
there is no study or count of how many subfields are largely of
one kind or the other, an informal overview suggests that those
that require multiple inputs, practical knowledge, and guidance
rules are quite numerous.
Certain working and teaching practices already exist in the
field of economy that somewhat approximate aspects of the medical
model; these deserve brief attention. In one type of situation
individual economists, especially those who work for public
policy agencies, informally acquire knowledge of other social
sciences and "cycle" it into their deliberations. Or similarly,
some economists work as members of teams comprised of both
economists and other social scientists. Both situations provide
informal analogs to the medical model but do not offer the
systematic grounding in multiple sources of knowledge that a
policy science discipline would. One observer has noted that
graduates of public policy schools are often considered less
effective than those economists who informally acquire knowledge
in other social sciences. The fact is many public policy schools
tend not to follow the medical model but to teach mainly basic
and applied economics, and rather little of the other social
sciences. More important, many public policy schools provide only
a short curriculum with relatively little preparation for the
specialty in which the graduate will practice. It is as if a
medical trainee were to do an internship in no particular
specialty. Business schools also produce graduates lacking in
broad exposure to other disciplines. However, to do full justice
to the point, a detailed analysis of both types of institutions
would be required. Nevertheless, it seems safe to suggest that
the medical model is often approximated in varying degrees, but,
so far, it is rarely explicitly adopted or fully emulated.
The medical model suggests that an economic policy science
or socioeconomics would require the following: Policy analysts
would recognize that analytic economics is distinct from economic
policy science; analytic economics might be altered in its
approaches and theories, but such changes cannot make the
discipline per se a sufficient base for a policy science;
additional analytic insights from other social sciences are
crucial; practical knowledge must be used systematically to
supplement analytic knowledge; guidance principles must be
distilled and transmitted as part of the policy science.
Pivotal to the preceding discussion is the assumption that
under many circumstances, in dealing with complex systems, one
cannot move directly from analytic economics to providing a
knowledge base for economic policy without the said additions.
Unsatisfactory experiences with economic policy may be due to
numerous factors, including political unwillingness to do what
economics prescribes, unique events, and the difficulties in
reconciling democratic goals with a rational policy. However,
there are indications that part of the trouble lies in the
knowledge base on which policymakers base their analyses, and
hence alternative approaches, such as that suggested by the model
of medical practice, deserve close attention.
Comments by Joseph J. Cordes and Lucy Ferguson are gratefully
acknowledged. Research assistance by Virginia A. Haufler and
Elizabeth R. Massen. This is a publication of the socioeconomic
project supported by The George Washington University and the
Center for Policy Research.
AMITAI ETZIONI is a university professor at The George Washington
University and director of the Center for Policy Research.
1. Raiffa, H., Decision Analysis (Reading, MA: Addison-Wesley,
1968); Axelrod, R., Structure of Decision: The Cognitive Map of
Political Elites (Princeton: Princeton University Press, 1976).
2. Stein, H., Presidential Economics: The Making of Economic
Policy from Roosevelt to Reagan and Beyond (New York: Simon and
Schuster, 1984), p. 110.
3. Quade, E. S., Analysis for Public Decision (New York:
Elsevier, 1975), pp.248-250.
4. Maital, S., Minds, Markets, and Money (New York: Basic Books,
1982), pp. 124-125. Some studies that show the assumptions of
game theory are incorrect: Bonacich, P., Shure, G., Kahan, J.,
and Meeker, R., Journal of Conflict Resolution, 20 (1976): 687;
and Lindskold, S., McElwain, D., and Wayner, Y., Journal of
Conflict Resolution, 21 (1977): 531.
5. See Braybrooke, D., and Lindblom, C. E., A Strategy of
Decision (New York: Free Press, 1963), pp. 48-50, 111-143. For a
critical review see, Etzioni, A., Public Administration Review,
27 (1967): 5.
6. Simon, H., Models of Man (New York: Wiley, 1957), pp.
204,250,261; and The American Economic Review, 69 (4) (1979):
7. Muth, J., quoted by Sheffrin, S., in Rational Expectations
(Cambridge, MA: Cambridge University Press, 1983), pp. 5, 9.
8. See, for a reductionist stance, Bernard, C., An Introduction
to the Study of Experimental Medicine (New York: Schuman, 1949).
For the opposite view see Carlson, R., The End of Medicine (New
York: Wiley-Interscience, 1975).
9. For examples of philosophers of medicine who argue for the
nonreducibility of medical knowledge to the basic sciences, see
Feinstein, A., Clinical Judgment (Baltimore: William and Wilkins,
1967); Schaffner, K., Logic, Laws, and Life, R. Colodny, Ed.
(Pittsburgh: University of Pittsburgh Press, 1977). Those who
consider medicine to be itself a basic science are Gorovitz, S.,
and McIntyre, A., "Toward a Theory of Medical Fallibility,"
Journal of Medicine and Philosophy, 1 (1976): 51.
10. On the special nature of semiorganic systems, see Nagel,
Ernest, The Structure of Science (Indianapolis: Hackett
Publishing Co., 1979), Chap. 12.
11. How often this occurs and which instances qualify is a
subject of much controversy. See Diaz-Alejandro, Carlos F.,
"Southern Cone Stability Plans," Economic Stabilization in
Developing Countries, W. Cline and S. Weintraub, Eds.
(Washington, DC: Brookings Institution, 1981). For an overview
see Nelson, Joan N., "The Political Economy of Stabilization in
Small, Low Income, Trade-Dependent Nations," unpublished paper.
12. I use the term to refer to the main works currently dominant
in American economics, excluding institutional, developmental,
and political economics.
13. Turner, M. E., and Stevens, C. D., Causal Models in Social
Sciences, H. M. Blalock, Jr., Ed. (Chicago: Aldine Publishing
Co., 1971), pp. 86-87; Mason, R., and Halter, A. N., op. cit., p.
202; Pindyck, R., and Rubinfeld, D. L., Econometric Models and
Economic Forecasts, 2nd ed. (New York: McGraw-Hill, 1981), pp.
14. It has been suggested that economic models include
hundreds of variables without difficulties. As I see it, these
are often not variables in the sense of concepts, members of a
theory, whose relationships are accounted for, but are
measurements, many of which measure the same basic variable, or
none at all, and whose relations are statistically but not
conceptually accounted for.
15. Hammond, R., McClelland, G. H., and Mumpower, J., Human
Judgement and Decision Making: Theories, Methods, and Procedures
(New York: Praeger, 1980). On four incompatible theoretical
perspectives, each seeking to explain the role of labor and the
economy, see Thurow, op. cit., p. 183. On incompatible
assumptions about crime between sociologists and economists, see
a collection of essays, Andreano, R., and Siegfried, J. J., Eds.,
The Economics of Crime (New York: Wiley, 1980), especially Part
16. "Much" of medicine is not scientifically supported.
Inglefinger, R., Erlman, A., and Findland, M., Controversy in
Internal Medicine (Philadelphia: W. B. Saunder, 1966). "85
percent of the problems a doctor sees in his office are not in
the book." Quoted from a physician, in Schon, D., The Reflective
Practitioner (New York: Basic Books, 1983), p. 16.
17. See Allvine, F. C., and Tarpley, F. A., Jr., The New State of
the Economy (Cambridge, MA: Winthrop Publishing, 1977), pp. 132-150; Thurow, L.C., Dangerous Currents: The State of Economics
(New York: Random House, 1983); Wilder, C. K., and Jameson, K.
P., An Inquiry into the Poverty of Economics (Notre Dame:
University of Notre Dame Press, 1983); and Balogh, T., The
Irrelevance of Conventional Economics (New York: LiveRight
Publishers, 1982); Lekachman, R., Economists at Bay: Why the
Experts Will Never Solve Your Problems (New York: McGraw-Hill,
1976); and a special issue of The Public Interest (1980) devoted
to the problems of economic theory.
18. Sears, D., Lau, R., Tyler, T., and Allen, H., "Self Interest
vs. Symbolic Politics in Policy Attitudes and Presidential
Voting," American Political Science Review, 74 (1980): 670;
Mayhew, D., Congress: The Electoral Connection (New Haven: Yale
University Press, 1974); Aldrich, J., Before the Convention: A
Theory of Presidential Nomination Campaigns (Chicago: University
of Chicago Press, 1980).
19. For an overview see Sheffrin, S., Rational Expectations
(Cambridge: Cambridge University Press, 1983).
20. Becker, G., The Economic Approach to Human Behavior (Chicago:
University of Chicago Press, 1976), pp. 170-179.
21. Indeed many observations are much harsher. Sheffrin, S.,
Rational Expectations (Cambridge: Cambridge University Press,
1983). See Craggs, J.G., and Malkel, B. G., Expectation and the
Structure of Share Prices (Chicago: University of Chicago Press,
1982). See Also Klamer, A., Conversations with Economists: New
Classical Economists and Opponents Speak Out on the Current
Controversy in Macroeconomics (Totowa, NJ: Rowman and Allanheld,
1984), pp. 106-113.
22. On modern Marxist interpretation of political economy, see
McLellan, D., Marxism After Marx: An Introduction (New York:
Harper and Row, 1980).
23. J. Dunlop advocates improving economic policy analysis by
incorporating history and the evolution of institutions,
organizational decision-making, interdependence of domestic and
international problems, and structural economic change in
Industrial and Labor Relations Review, 30 (1977): 281.
24. Derthick, M., Policy Making for Social Security (Washington,
DC: Brookings Institution, 1979), pp. 383-384; and Myers, R. J.,
"Social Security's Hidden Hazards," Wall Street Journal, July 28,
1972. On demographic surprises, see Morrison, P. A., "Demographic
Certainties and Uncertainties in the Future of Social Security,"
RAND Note, July 1981.
25. A comparison of the actual number of families in the USA to
those projected a few years earlier by the Bureau of the Census
(in 1966 cf to 1975 and in 1974 cf to 1980) shows that the actual
number fell significantly outside a range of projections
provided. Details on request from author.
26. Tobin, J., Essays in Economics, Volume I: Macroeconomics
(Chicago: Markhan Publishing Company, 1971), pp. 242-271.