The domain of agent-based models

Agent-based modeling is an intriguing new set of tools for computational social science. The techniques permit us to project forward the system-level effects of a set of assumptions about agent behavior and a given environment. What kinds of real social phenomena are amenable to treatment by the techniques of agent-based modeling? David O’Sullivan and his co-authors offer an assessment of this question in their contribution to a valuable recent handbook, Heppenstall et al, Agent-Based Models of Geographical Systems. (Andrew Crooks and Alison Heppenstall provide a valuable and clear introduction to ABM methodology in their contribution to the volume.)

O’Sullivan and colleagues offer a basic taxonomy of different applications of ABM research.

— simple abstract models where the focus is on exploring the collective implications of individual-level decision making.
— more detailed [accounts that] locate virtual model agents in a representation of the real world setting of interest. Typically, such models operate at a regional or landscape scale
— some of the most ambitious models aim at detailed … representations of both the geographical setting and the processes unfolding in that setting (111-112)

This taxonomy depends on the degree of abstraction and realism that the model aspires to.

Here are a handful of research projects that are amenable to these techniques, most of which are illustrated in the Heppenstall volume.

— Land use patterns in peasant agriculture
— Residential patterns — urban and rural
— Patterns of burglaries
— Occurrence of interpersonal violence in civil war
— Traffic patterns — pedestrian and vehicular

What do the clear examples have in common? They are situations where a number of independent individuals react to a social and natural environment with a set of goals; and they are usually situations where individuals influence each other through their actions. These are situations of dynamic interactive choices. O’Sullivan and colleagues put these points this way:

We consider the most fundamental characteristics of agents in spatial models to be goal-direction and autonomy…. However, more specific definitions of the concept may add any of flexibility, ‘intelligence’, communication, learning, adaptation or a host of other features to these two. (115)

(Crooks and Heppenstall provide a similar list: autonomy, heterogeneity, and activity; 87.)

O’Sullivan et al also pose an important question about what the circumstances are where the features of agents makes a difference in the social outcome:

This argument focuses attention on three model features: heterogeneity of the decision-making context of agents, the importance of interaction effects , and the overall size and organization of the system. If agents are the same throughout the system, then, other things being equal, an aggregate approach is likely to capture the same signifi cant features of the system as an agent-based approach.

Essentially the point here is a simple one: if an aggregate outcome results from homogenous individuals making a decision about something on the same basis as everyone else, then we don’t need an agent-based model. ABM techniques become valuable when heterogeneous agents interact with each other to bring about novel outcomes.

There are quite a few social situations that do not fit the terms of these models well. Some social processes are not simply the aggregate outcome of choices by a set of independent autonomous agents. For example, the flow of work through an architectural design studio is determined by the rules of the firm, not the independent choices of the employees, and the behavior of an army is largely determined by its general staff and command structure. O’Sullivan et al put the point this way:

A more important question may be, “what should the agents in an ABM of this system represent?” If the interactions among individual actors in the real world are substantially channelled via institutions or other social or spatial structures, perhaps it is those institutions or social or spatial structures that should be represented as agents in an ABM rather than the individuals of which they are formed. (120)

So a general question for ABM methodology is this: where do structural social factors come into ABM models? Here I am thinking of things like a system of regulation and law; a pattern of racialized behavior; the architecture of the transport system; a tax system; …. We might treat these as parameters in the environment of choice for the agents. They are beyond the control of the agents and are regarded as constraints and opportunities. (This is one place where the framework of “strategic interactive fields” disagrees, since the SIF approach looks at institutions themselves as part of the field of strategic interaction in that individuals strive to modify the rules to their own benefit.)

It seems reasonable to judge that ABM techniques are very useful when we are concerned with phenomena that are aggregates of strategic behavior by individual actors; but they are not pertinent to many of the questions sociologists pose. In particular, they do not seem useful for sociological inquiries that are primarily concerned with the dynamics and effects of large social structures where the behavior of individuals is routine, homogeneous, or largely determined exogenously. These are the circumstances where the premises of the ABM approach — autonomy, heterogeneity, and activity — are not satisfied.

Strategic action fields

Sometimes a rethinking of ontology and social categories results in an important step forward in social theory. This appears to be the case in some recent reflections on the relationships that exist between social movements theory and the sociology of organizations.  The presumption of existing writings on these fields is that they refer to separate but related phenomena.  One is more about social actors and the other is more about stable social structures.  What happens when we consider the possibility that they actually refer to the same kinds of social phenomena?

This is the perspective taken by Neil Fligstein and Doug McAdam in a recent contribution to Sociological Theory, “Toward a General Theory of Strategic Action Fields”(link). (They develop these ideas more fully in A Theory of Fields.) In the Sociological Theory article they write:

We assert that scholars of organizations and social movements — and for that matter, students of any institutional actor in modern society — are interested in the same underlying phenomenon: collective strategic action. (2)

Fligstein and McAdam formulate their novel approach in terms of the idea of “strategic action fields.” They put it forward that “strategic action fields … are the fundamental units of collective action in society” (3). Power and advantage play key roles in their construction: “We too see SAFs as socially constructed arenas within which actors with varying resource endowments vie for advantage. Membership in these fields is based far more on subjective ‘standing’ than objective criteria” (3).

Here are types of social items they include in this theory:

  1. strategic action fields 
  2. incumbents, challengers, and governance units 
  3. social skill 
  4. the broader field environment 
  5. exogenous shocks, field ruptures, and the onset of contention 
  6. episodes of contention 
  7. settlement (2) 

This approach is importantly couched at the level of social ontology: what sorts of things should we identify and analyze as explanatory factors in our theories? The move to SAFs is a move against the idea of the fixity of social “structures,” institutions, and organizations. For example, they write against the ontology of new institutionalism: “The general image for most new institutionalists is one of routine social order and reproduction” — or in other words, a static set of rules and constraints within which action takes place. Their ontology, on the other hand, emphasizes the fluidity of the constraints and circumstances of action from the actors’ points of view; so the field shifts as actors undertake one set of strategies or another. “This leaves great latitude for the possibility of piecemeal change in the positions that actors occupy” (5).

So both stability and change are incorporated into a single framework of analysis: actors react strategically to the field of constraints and positions within which they act, with results that sometimes reinforce current positions and other times disrupt those positions.

They account for what looks like institutional rigidity by calling out the power of some actors to maintain their positions in the social order: “Most incumbents are generally well positioned and fortified to withstand these change pressures. For starters they typically enjoy significant resource advantages over field challengers” (9). But institutions should not be expected to maintain their structures indefinitely: “The expectation is that when even a single member of the field begins to act in innovative ways in violation of field rules, others will respond in kind, precipitating an episode of contention” (9).

So what is intended by the idea of “strategic action” in this theory? Here is what they have to say on that subject:

We define strategic action as the attempt by social actors to create and maintain stable social worlds by securing the cooperation of others. Strategic action is about control in a given context. The creation of identities, political coalitions, and interests serves to promote the control of actors vis-a-vis other actors. (7)

Here is one other interesting ontological feature of this approach. Their language suggests some parallels with assemblage theory (link), in the sense that social constructs fit upwards and downwards into strategic action fields at a range of fields. “We conceive of all fields as embedded in complex webs of other fields” (8). This set of ideas seems to suggest an unexpected affinity to “actor-network theory” and the sociological ideas of Bruno Latour (ANT) (link). But at the other end of some obscure spectrum of theory differentiation, their account also seems to rub shoulders with rational-choice theory, where both actions and rules are subject to deliberation and change by prudential actors.


There are several features of this approach that seem promising to me. One is the fact that it directly challenges the tendency towards reification that sometimes blocks sociological thinking — the idea that social “things” like states persist largely independently from the individuals who make them up. This new approach leads to a way of thinking about the social world that emphasizes contingency and plasticity (linklink) rather than rigid and homogeneous social structures. It also seems consistent with the thinking that leads to the idea of “methodological localism” — the idea that social phenomena rest upon “molecules” of socially constructed, socially situated individuals (link). I also like the fact that their analysis is explicitly couched at the meso level — neither macro nor micro.

One concern this approach raises, however, is suggested by the point mentioned above about its apparent proximity to some versions of rational choice theory — the view that all social outcomes and processes are ultimately the consequence of prudential actors pursuing their interests. But this assumption — which McAdam certainly does not share elsewhere in his writing (e.g. Dynamics of Contention) — threatens to push out of consideration social realities like normative systems, social identities, and distributed systems of power that somehow or other seem to demand inclusion in our understanding of social processes.

Finally, we can ask whether this innovation provides a basis for more fruitful empirical research into concrete phenomena like how corporations and revolutionary parties function, how demonstrations against Islamophobia take shape, and how resistance to racial discrimination emerges.  If the theoretical innovation doesn’t lead to richer empirical research, then it is reasonable to be skeptical about why we should adopt the new theoretical tools.

Actor-centered sociology and agent-based models

Actor-centered sociology (ACS) begins in the intuition that social processes begin in the interactions of socially constructed individuals, and it takes seriously the idea that actors have complex and socially inflected mental schemes of action and representation. So actor-centered sociologists are keen not to over-simplify the persons who constitute the social domain of interest. And this means that they are generally not content with sparse abstract schemata of actors like those proposed by most versions of rational choice theory. 

Agent-based modeling (ABM) is a collection of aggregative techniques aimed at working out the aggregate consequences of the hypothetical choices of a number of individuals interacting in a series of social environments. ABM models generally represent the actors’ motivations and decision rules very abstractly — sometimes as economic actors, sometimes as local optimizers, sometimes as heuristically driven decision makers. An ABM model may postulate several groups of actors whose decision rules are different — predators and prey, landlords and tenants, bandits and generals. The goal is to embody a set of behavioral assumptions at the actor level and then to aggregate the results of the actions and interactions of these actors at a macro level. (Stephen Railsback’s Agent-Based and Individual-Based Modeling: A Practical Introduction provides an accessible introduction.)

My question here is a focused one: do these apparently similar approaches to explaining social outcomes actually have as much in common as they appear to at first glance? And the answer I’ll suggest is — not yet, and not enough. (Here are earlier discussions of the two frameworks; linklink.)

The sticking point between them is the issue of abstraction and granularity concerning the nature of the actors. ACS researchers are critical of the methodological move towards abstraction in the description of the actor. They believe that the socially embedded and rather specific features of deliberation and action that they investigate in various historical and cultural settings are crucial and are lost when we move to a more abstract DBO approach. ABM theorists argue that abstraction about the agent is necessary if a social situation is supposed to be tractable — to model the behavior of a population of agents we need to be able to represent their decision rules in a reasonably compact and mathematically representable way. So if we take the view that each individual is a unique bundle of mental frameworks and action-practices, we will have to give up the enterprise of modeling their collective behavior.

However, some efforts to apply ABM techniques to real contemporary and historical problems — for example, land use patterns in contemporary African agriculture — have had disappointing results. The patterns predicted by the simulation diverge fairly significantly from the observed patterns on the ground. And some of these researchers believe that the problem lies not with the model but with the assumptions made about the actor. Those assumptions are basically Chicago-style rational choice assumptions, and researchers are coming to see that the actors — farmers, herders, traders — are operating on the basis of rules that are more nuanced. The actors are prudential and they make deliberative choices; but their reasoning doesn’t reduce to an application of expected-utility calculation. So the researchers themselves are asking whether it would be better to incorporate more realistic assumptions about actors’ motivations and reasoning frameworks.

This suggests that there is perhaps more fertile ground between the ACS and ABM frameworks than has yet been exploited. ACS focuses its attention on the question of refining our understanding of how actors are constituted, and ABM provides a rich set of techniques for transporting from assumptions about individual actors to the simulated result of aggregating these actors’ behaviors onto a collective pattern. 

The hybrid approach still requires abstraction about actors. But perhaps it is worth considering adjusting the focus, from “farmers in an environment” to “Kenyan farmers with X, Y, Z features of goals and reasoning schemes”. Perhaps the disaggregation of types of actors needs to go even further. And perhaps the question of “what kinds of actors are involved in land use in Kenyan agriculture?” needs to be driven by empirical investigation rather than methodological fiat or computational convenience.

So maybe the great centers for complexity studies around the country would be well advised to begin including anthropologists and cultural sociologists within their research teams. And maybe the result will be a fertile marriage of modeling with greater cultural specificity.

Mental illness, big pharma, and agent-based simulation


The New York Review of Books has an absorbing two-part piece by Marcia Angell on mental illness, psychiatry, and big pharma (linklink). (The NYRB Facebook page provides a good way of following the NYRB.)  Angell provides an in-depth discussion of books by Irving Kirsch, Robert Whitaker, and Daniel Carlat. There has been an explosion in the numbers of patients diagnosed with a list of mental disorders, and there has been an explosion in the profits associated with the drugs prescribed in treatment of these disorders as well.

It seems that Americans are in the midst of a raging epidemic of mental illness, at least as judged by the increase in the numbers treated for it. The tally of those who are so disabled by mental disorders that they qualify for Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI) increased nearly two and a half times between 1987 and 2007—from one in 184 Americans to one in seventy-six. For children, the rise is even more startling—a thirty-five-fold increase in the same two decades. Mental illness is now the leading cause of disability in children, well ahead of physical disabilities like cerebral palsy or Down syndrome, for which the federal programs were created. (Angell, part 1)

What is going on here? Is the prevalence of mental illness really that high and still climbing? Particularly if these disorders are biologically determined and not a result of environmental influences, is it plausible to suppose that such an increase is real? Or are we learning to recognize and diagnose mental disorders that were always there? On the other hand, are we simply expanding the criteria for mental illness so that nearly everyone has one? And what about the drugs that are now the mainstay of treatment? Do they work? If they do, shouldn’t we expect the prevalence of mental illness to be declining, not rising? (Angell, part 1)

To oversimplify, the thrust of several of these books is that the psychoactive drugs created the mental illnesses through the profit incentives and strategies of big pharma, rather than the diseases creating the drugs (through research and development aimed at treating the diseases).

This is over-simple, of course, since no one would question that mental illnesses exist prior to drugs. But the explosion of treated disorders like depression, anxiety, sleep disorders, and attention deficit disorder in children — the “epidemic” to which Angell refers — seems to conform to the reverse order. Deliberate strategies of marketing, influence on physicians, and influence on guiding medical documents such as the DSM seem to have produced a much larger patient base in specific mental disorders, with large profits accruing to pharma as a consequence.  (Ian Hacking looks at the degree to which mental illnesses are socially constructed in The Social Construction of What?.)

Here is the main thrust of the interpretation offered by the books that Angell reviews:

First, [the authors] agree on the disturbing extent to which the companies that sell psychoactive drugs—through various forms of marketing, both legal and illegal, and what many people would describe as bribery—have come to determine what constitutes a mental illness and how the disorders should be diagnosed and treated. (Angell, part 1)

A couple of pieces of evidence are especially pertinent in support of this telling of the story. One is the observation that psychiatrists as a profession are the largest beneficiaries of funding by pharma, by a large margin.

As psychiatry became a drug-intensive specialty, the pharmaceutical industry was quick to see the advantages of forming an alliance with the psychiatric profession. Drug companies began to lavish attention and largesse on psychiatrists, both individually and collectively, directly and indirectly. They showered gifts and free samples on practicing psychiatrists, hired them as consultants and speakers, bought them meals, helped pay for them to attend conferences, and supplied them with “educational” materials. When Minnesota and Vermont implemented “sunshine laws” that require drug companies to report all payments to doctors, psychiatrists were found to receive more money than physicians in any other specialty. The pharmaceutical industry also subsidizes meetings of the APA and other psychiatric conferences. About a fifth of APA funding now comes from drug companies.

Drug companies are particularly eager to win over faculty psychiatrists at prestigious academic medical centers. Called “key opinion leaders” (KOLs) by the industry, these are the people who through their writing and teaching influence how mental illness will be diagnosed and treated. They also publish much of the clinical research on drugs and, most importantly, largely determine the content of the DSM. In a sense, they are the best sales force the industry could have, and are worth every cent spent on them. Of the 170 contributors to the current version of the DSM (the DSM-IV-TR), almost all of whom would be described as KOLs, ninety-five had financial ties to drug companies, including all of the contributors to the sections on mood disorders and schizophrenia.  (Angell, part 2)

A second piece of evidence is a recounting of the drafting of the Diagnostic and Statistical Manual of Mental Disorders (DSM) through five editions, especially the third edition. In each case there is a strong suggestion of swaying of medical and scientific opinion through financial incentives.

These efforts to enhance the status of psychiatry were undertaken deliberately. The APA was then working on the third edition of the DSM, which provides diagnostic criteria for all mental disorders. The president of the APA had appointed Robert Spitzer, a much-admired professor of psychiatry at Columbia University, to head the task force overseeing the project. The first two editions, published in 1952 and 1968, reflected the Freudian view of mental illness and were little known outside the profession. Spitzer set out to make the DSM-III something quite different. He promised that it would be “a defense of the medical model as applied to psychiatric problems,” and the president of the APA in 1977, Jack Weinberg, said it would “clarify to anyone who may be in doubt that we regard psychiatry as a specialty of medicine.”

When Spitzer’s DSM-III was published in 1980, it contained 265 diagnoses (up from 182 in the previous edition), and it came into nearly universal use, not only by psychiatrists, but by insurance companies, hospitals, courts, prisons, schools, researchers, government agencies, and the rest of the medical profession. Its main goal was to bring consistency (usually referred to as “reliability”) to psychiatric diagnosis, that is, to ensure that psychiatrists who saw the same patient would agree on the diagnosis. To do that, each diagnosis was defined by a list of symptoms, with numerical thresholds. For example, having at least five of nine particular symptoms got you a full-fledged diagnosis of a major depressive episode within the broad category of “mood disorders.” But there was another goal—to justify the use of psychoactive drugs. The president of the APA last year, Carol Bernstein, in effect acknowledged that. “It became necessary in the 1970s,” she wrote, “to facilitate diagnostic agreement among clinicians, scientists, and regulatory authorities given the need to match patients with newly emerging pharmacologic treatments.”  (Angell, part 2)

Another element of the strategy used by the drug companies to promote their products, according to these authors, is the selective way that clinical studies are used in order to establish the safety and effectiveness of a given psychoactive drug:

For obvious reasons, drug companies make very sure that their positive studies are published in medical journals and doctors know about them, while the negative ones often languish unseen within the FDA, which regards them as proprietary and therefore confidential. This practice greatly biases the medical literature, medical education, and treatment decisions. (Angell, part 1)

What this story made me think of was … slime molds. Here’s what I mean. Japanese researchers have discovered that certain examples of optimizing processes can be simulated with slime molds and food supplies distributed across space. Here is an example of this research in the context of rail networks: the researchers found that a colony of slime mold essentially reproduces the configuration of existing rail networks when food is distributed in a configuration mirroring major cities (Tero et al 2010; linklink). Here is the experiment based on the configuration of cities around Tokyo:



After about a day of growth, the slime mold has established a network of tunnels connecting the food supplies, and this network looks strikingly similar to the configuration of Japanese railroads in the region.

So here’s the question for consideration here: what if we attempted to model the system of population, disease, and the pharmaceutical industry by representing pharma as the slime organism and the disease space as a set of disease populations with different profitability characteristics? Would we see a major concentration of pharma slime around a few high-frequency, high profit disease-drug pairs? Would we see substantial underinvestment in pharma slime on low frequency low profit “orphan” disease populations? And would we see hyper-concentrations around diseases whose incidence is responsive to marketing and diagnostic standards?

I’m just speculating here, but I’m guessing that a Petri dish designed with these characteristics would produce the outcome described in the books included in the Angell reviews: a hyper-concentration of the slime organism around the “plastic” diseases that display positive feedback from marketing to incidence.  Essentially the model would suggest that the pharma industry “grows” into the space of emerging diseases, making investments in research and marketing that allow for growth of revenues around the disease segments of the population.

I suppose that this thought experiment simply supports a dismal but familiar finding: that profit-maximizing firms will aggressively seek out new sources of profits; that they will be particularly interested in opportunities where the possibility exists of strategically increasing the demand market; and that they will find creative ways of inducing other actors to behave in ways that enhance their business interests. Unfortunately, in this case the business optimal outcome seems to have very negative consequences for public health. And it seems to cast some doubt on the ability of professional ethics and conflict of interest policies to keep the medical profession as a whole on the track of placing the patient’s health as the highest priority.

(I think this thought experiment could be recast as an agent-based simulation, with similar results.)

Marx an analytical sociologist?


In an earlier post I gave a brief sketch of the emerging field of analytical sociology, and summarized its foundations around three premises: microfoundations, rational social actors, and causal mechanisms.

Marx is often thought to be a “structuralist” thinker, highlighting large social processes and entities such as the mode of production, the economic structure, and social class (for example, by Althusser and

Balibar in Reading Capital). However, I argued in The Scientific Marx (1986) that a careful examination of Marx’s economic writings reveals something quite different. I argued, first, that Marx embraced the idea that social explanations require microfoundations.

Marxist social science commonly has advanced macro explanations of social phenomena in which the object of investigation is a large-scale feature of society and the explanans is a description of some other set of macro phenomena. Some Marxist social scientists have recently argued, however, that macro explanations stand in need of microfoundations: detailed accounts of the pathways by which macrolevel social patterns come about. These theorists have held that it is necessary to describe the circumstances of individual choice and action that give rise to aggregate patterns if macroexplanations are to be adequate. Thus to explain the policies of the capitalist state it is not sufficient to observe that this state tends to serve capitalist interests; we need an account of the processes through which state policies are shaped and controlled so as to produce the outcome. (127-28)

Consider now a second issue underlying the call for “microfoundations” for Marxian explanations: the gap between the interests of a group as a collective and the interests of the individuals who comprise the group. (John Roemer refers to this as the “aggregation gap.”) “Rational-action” explanations depend on identifying an individual’s interests and then explaining the person’s behavior as the rational attempt to best serve those interests. The model is often extended to account for collective behavior of groups as well…. However, Mancur Olson and others have made it plain … that it is not sufficient to refer to collective interests in order to explain individual behavior. (129-30)

In both cases the objection being advanced to macro-Marxism is grounded in a recognition that there are no supraindividual actors in a society. (131)

After examining several examples of Marx’s most important explanations, I conclude that his arguments conform to the requirements of the microfoundations principle. His most characteristic explanations proceed from reasoning about the actions of typical individuals within capitalist institutions to an effort to aggregate these individual choices up to the level of larger collective patterns.

Second, I argued that Marx’s explanations were almost always grounded in an analysis that highlighted rational individual decision-making. But Marx differed from the perspective we would now call “public choice theory” in that he gave much greater attention to the historically specific motives and values of the actor.  Marx highlighted what we might now call “political psychology” of the actor — the socially specific ideas, motivations, and ideologies that the actor acquired through ordinary experience of capitalism. So there is a developed “action theory” present in Marx’s writings.  It is a theory that gives prominence to means-end rationality.  And it gives attention to the social specificity of the actor as well.

Here is how I described Marx’s assumptions about the actors within capitalism in TSM:

Marx’s accounts depend on an examination of the circumstances of choice of rational individuals. Marx identifies a set of motivational factors and constraints on action for a hypothetical capitalist and then tries to determine the most rational strategies available to the capitalist in these circumstances of choice…. A second part of this model of explanation involves an attempt to determine the consequences for the system as a whole of the forms of activity attributed to the typical capitalist at the preceding stage of analysis. (141-42)

But Marx has a nuanced and socially specific conception of the actor:

Against both these positions — the nonsocial individualism of political economy and the uncritical holism of speculative philosophy — Marx puts forward an alternative position. On this account the socialized individual is the ultimate unit of analysis in social explanation. “Individuals producing in society — hence socially determined production — is of course the point of departure” (Grundrisse 83)…. On this account society is not a freestanding entity, and social relations exist only through the individuals who stand within them. At the same time, however, individuals exist only within particular sets of historically given social relations. Consequently, social explanations must begin with a concrete conception of the individual within specific social relations.” (150)

These assumptions about social actors conform fairly well to the assumptions incorporated into analytical sociology.

And third, I argued that Marx offered causal mechanism explanations based on an analysis of what I termed the “institutional logic” of a particular social setting. So various features of capitalism are explained as resulting from rational actors situated within a particular set of institutions. These accounts serve as descriptions of the social mechanisms through which capitalist dynamics take place.

Marx attempts to work out the institutional logic of these capitalist institutions. What distinctive features of organization and development are imposed on the capitalist economy by its defining structural and functional characteristics? What are the “laws of motion” of the mode of production defined by these conditions? We may call this an institutional-logic analysis of social regularities, and it is significantly different from the construction of theoretical explanations in natural science. Such an analysis is concerned with determining the results for social organization and development of an entrenched set of incentives and constraints on individual action. (34)

Marx’s interest in discovering and elaborating the social mechanisms that drive social processes is found within his theory of historical materialism as well.  In TSM I argue that Marx’s claims about causation between levels of the social and economic structures of various modes of production are best understood as “mechanisms” explanations.

In order to understand fully this view of the relation between the economic structure and noneconomic phenomena, it is necessary to describe the mechanisms through which the lower-level structures constrain or filter superstructural elements. The filtering may occur through a variety of mechanisms, both intended and unintended. (56)

This account of Marx’s implicit theory of social explanation — microfoundations, rationality, and mechanisms — reproduces Coleman’s boat (Foundations of Social Theory).  The institutions and structures of capitalism create a local environment of choice for individual capitalists and workers, and their behavior aggregates to a macro-outcome of interest (for example, the falling tendency in the rate of profit). This is a “logic of institutions” argument in a specific sense. The institutions (property relations) create an environment of choice in which actors pursue specific strategies, and these strategies aggregate to a certain kind of macro-level outcome. These are the “laws of motion” of the capitalist mode of production, in Marx’s terms. And it is a mechanisms-based explanation in a specific sense as well. Marx is deliberately seeking out the social mechanisms through which the institutional setting produces a set of macro-outcomes, through their influence on the behaviors of the actors. The Scientific Marx offers a handful examples of these aggregative explanations. The point here is that this logic conforms very well to the framework of thought associated with analytical sociology.

There is one additional point of convergence between the methods I identified in Marx’s writings in 1986 and the current doctrines of analytical sociology. I argued that the covering law model of explanation and the deductive-nomological model of justification did not work at all well in application to Marx’s reasoning. The reason? Because the covering law model assumes that explanatory warrant proceeds from laws and regularities, whereas the heart of Marx’s explanations rests upon the discovery of particular social processes and mechanisms.

Do Marx’s explanations conform to the subsumption theory? … There are statements of lawlike regularities in Marx’s explanations, but these statements are somewhat trivial…. The real weight of the argument lies elsewhere: in the particular details of the circumstances of choice in which capitalists find themselves, and in Marx’s reasoning from these circumstances to patterns of collective behavior. (152) [Or in other words, he seeks to uncover the social mechanisms of capitalism and their aggregative dynamics.]

The process of discovering an institutional logic is not merely one of working out the deductive consequences of the theory; it is rather discovering new aspects of the social process. These aspects are perhaps “implicit” in the original theory, but their discovery is a substantive one, not a mere deductive exercise. (153)

Here too there is a strong affinity between Marx’s theory of science (as I interpreted it in 1986, anyway) and the philosophy of social explanation developed within analytical sociology.

So it looks as though Marx’s analysis of capitalist society — at least as it is reconstructed in The Scientific Marx — falls squarely within what we would now call “analytical sociology” with a commitment to microfoundations, mechanisms, and socially constituted purposive actors. What a surprise!