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.


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.

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 the theory.(4)

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.


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 flowers.

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 single phenomenon.

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 for policymaking.

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 relationship.)(10)

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)


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 disciplines.(14)

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 to treat.

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 proper term.

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.


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 lacunas.

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 frequently.

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 organization.

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): 498.

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. 186-187.

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 I.

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.

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