What is Social Ontology and why should Economists care?

Literally, social ontology is the study of social nature and it concerns itself with “how existents exist”1. It is the study of the social realm which includes the “domain of all phenomena, existents, properties”2 whose existence depends upon humans and their interactions. To paraphrase Little “almost all human action is social: socially oriented, socially embedded or socially constructed”6.  So how can it be useful for illuminating the study of economics? If economics is the study of people, and how they interact to form markets, bargain with each other, and more generally interact economically, then we need to examine an economist’s worldview on how these interactions are governed. Different schools of thought have different assumptions (worldviews) about how these interactions occur but more fundamentally, different schools of thought have different ideas about the framework we should use to analyse this social realm, and this is something which is often forgotten amongst student pluralists, along with others in the economic profession.

Dr Tony Lawson, a prominent ontologist at the University of Cambridge and convener of the Cambridge Social Ontology Group, believes that the mainstream group of economists, often (erroneously) known as neoclassicals are characterised by an “insistence upon methods of mathematical modelling”3. He argues that the problem with the economic discipline “lies not at the level of substantive theorising at all but at the level of methodology and social ontology”4. As Colander et al insightfully point out “if it isn’t modeled, it isn’t economics, no matter how insightful”5. The point Dr. Lawson is making is that it is not the theories of the mainstream which are necessarily wrong, per se, but the methods that they go about determining and explaining these theories.


The principle method of the mainstream – and arguably one of it’s few defining features – is that of mathematical deductivism. This presupposes event regularities such that if X occurs then Y occurs. This causal relationship need not be linear, we could take a non-linear relationship but still have issues, primarily because by doing so we would still be operating under a closed system. Furthermore, there is the assumption that each individual is atomistic meaning that each entity has its own separate effect which is independent and occurs whatever the context. Such event regularity implies that we have a closed system and hence proponents believe that the theorised rule always happens, regardless of the situation around it. An obvious example of this would be the so-called Phillips curve theory in the 1980s that higher inflation could lead to lower unemployment. Such a rule broke down almost as soon as it was formulated demonstrating the danger of assuming event regularities and closed systems. It is a little ironic that the mainstream assumes these event regularities, but yet failed to learn lessons from past economic failures. In summary, these event regularities aren’t guaranteed in the social realm, as the mainstream ideal dictates.

One could argue on many grounds how such a methodology is flawed, firstly is the dispute that economic agents (individuals, firms, government etc) can be classified as atomistic and are the predictable entities that a closed causal system implies. It could be counter-argued that whilst an individual may not be predictable, the aggregation of all individuals does lead to predictable patterns, but in reality we find that most situations cannot be well characterised in such an aggregate manner. As Keynes pointed out (and has been more rigorously proven from behavioural science) human beings are like sheep and have a herd mentality. Nobel prize winner, George Akerlof takes a story from biology and the discovery of DNA as the foundation of human life to emphasise his belief that we should be more concerned with studying “economic units” and the “economic behavior” underlying it, rather than making assumptions in aggregate:

“Positive economics [the mainstream], with its emphasis on statistical analysis of populations, would suggest that the intensive study of a single molecule would be an all-but-worthless anecdote. In the case of DNA, we know that the exact opposite is true: because DNA is a template that determines all of the cells of the organism, and also its reproduction, one molecule may not tell all, but it does tell a great deal. Form follows function.”8

The formalistic mathematical models we talk about aren’t restricted to econometric analysis of issues, although such analysis is a subset of the wider issue.  A particular issue unique to econometrics is that the same dataset can be used to produce different results – usually dependent on the prior beliefs of their creators which can be imposed through “data mining”* – depending on how the particular equation is stated; an unfortunate result of this as Leamer points out is that “hardly anyone takes anyone else’s data analysis serious”7.

Before proceeding to look at alternative methodologies, we should be careful to point out that an insistence against the predominance of mathematical modelling is not equivalent to arguing that formalistic techniques are never appropriate, simply that there are times and situations when this is inappropriate, and other tools in our toolbox need to be used. But equally, there may arise times when such techniques are suitable, such as when social conditions arise which do presuppose a closed system (e.g. perhaps in modelling traffic).  We are not arguing against the use of hammers, simply that we wouldn’t use a hammer to cut the lawn, we would use the more appropriate tool. We take a stance against the forces compelling an economist to have to frame their work in a formalistic prose if they wish to be published in leading journals and taken seriously in the profession.


Perhaps one of the many other tools we could recommend is the use of surveys, and talking to those in industry. Currently many economic academics see themselves as above businessmen and entrepreneurs yet these are the agents (along with policymakers and consumers) that are making the decisions which affect the economy. Understanding more about their way of thinking, as well as their motivations will help economists form more realistic beliefs and theories. “When people follow the norms, they use them to explain their actions; when, on the other hand, they violate the norms, they become the subject of local gossip. Those case studies are revealing because—like a language, which dictates how one should speak—the norms are common knowledge.”9 Of course, these beliefs may change over time, so it is important that such theories don’t become enshrined in the profession as laws, but it is understood that sentiment can change at different times, greater study may eventually allow us to get a better insight into the underlying sentiment which affects contemporary beliefs.

Obviously surveys may not be the appropriate tool to understand economic agents all the time. Some actions and motives may not be revealed by surveys, where individuals may be bound by social conventions requiring them to answer in some way (which is revealing in itself). Instead we could take a better approach to understanding these actions by simply observing what occurs, and/or conducting field experiments. Whilst laboratory experiments are certainly a step forward in providing us a narrative to why agents do what they do, it is quite artificial and may suffer from this fake environment** whereas field studies and simple observation can allow us to see motives truthfully. As the philosopher Bertrand Russell said, “the discovery of our own motives can only be made by the same process by which we discover other people’s, namely, the process of observing our actions and inferring the desire which could prompt them”.

Akerlof, again in his Presidential Address to the American Economic Association, is supportive of such measures that try to understand the beliefs, and what he calls “norms” of individuals and firms:

“The individual economic unit, be it a firm, a consumer, or an employee, behaves the way it does for a reason. And if these actors behave as they do for a reason, we can expect to find those reasons from the structures that we see in close observation; and because of those structures their behavior will also tend to be duplicated. This duality between duplicability and structure explains why much of science concerns very close observation, as it also explains why the study of even a single part of a single DNA molecule will be revealing.”10

A final tool I will briefly mention is a reversion back to the simple theorising and philosophising akin to some of the economic greats such as Keynes, Hayek and Smith. Whilst these great minds all had different ideas and perhaps quite opposing politics, they all expressed their theories without the aid of formalistic mathematical models, implying that these might not always be necessary in order to get a theory across. In fact the issue with constructing a model – as a pedagogical tool to explain the underlying theory – is that the reader can get subsumed into the narrow confines of the model, and forget that what they are dealing with is simply a theory, and that they are not examining arbitrary homo economicus agents, but actual people and real-life situations. As Colander et al say “the economics profession has failed in communicating the limitations, weaknesses, and even dangers of its preferred models to the public”.11 Taking a step-back from models allows a reader to more easily see the limitations of an idea and to meld it more closely with other theories and ideas.

I caution that the list above is by no means exhaustive, it is simply a few other methods which could provide insight into economics. Ultimately, moving away from an insistence on mathematical deductivist methods will allow economics to incorporate methods from other subjects, and create new tools, which ought to allow us to provide more realistic predictions about the actions of society and the economy. The key take-away from this article though, is that the profession shouldn’t be looking for a new method to subsume economics at the expense of all other methods, it needs to embrace the point that different tools are needed for different jobs.


By moving away from a predominance on deductivist techniques, we will be able to enrich ourselves with a dearth of other plausible ideas, to help explain the phenomenon we observe around us, and which as the Financial Crisis has shown, we still can’t yet explain.

Social ontology talks about the phenomenon of emergence, whereby the organisation of individual components in aggregate leads to properties greater than those possessed by the individual. Abstractly put, it would be like adding 1, 2 and 3 and getting an outcome greater than the simple sum of the individual numbers (6). We see such occurrences around us all the time, for example a cake can only exist due to the organisation of the recipe; a heap of ingredients would not constitute a cake, it is the organisation which makes the cake from the ingredients, yet the mainstream ignores this. For example, their current hobby with formulating macroeconomics by building on micro-foundations inherently demonstrates their incapability to believe in emergent systems. This presents a flaw in their grand ambition to micro-found the study of macro, and questions whether such a feat is plausible, necessary and worth the attention it is given.

Another ignorance of neoclassical economics is that of path dependency, the belief that an outcome depends upon the initial state, and so a different history will lead to a different outcome. As Veblen declares, homo economicus has “neither antecedent nor consequence”. By ignoring the history of an agent we forgot what makes it so. This has important implications in many aspects, particularly in labour economics when we consider factors such as hysteresis and the education of a worker.

So as pluralists, what does ontology mean for us? We have found that ontology is concerned with the presuppositions, beliefs and techniques used by a given economist to analyse the world we live in. It should be our job to educate students of other existing beliefs and techniques. Whilst I believe CSEP has done a good job of extending the knowledge of different schools of thought and their assumptions and theories (beliefs), I think we still have to make further progress in inviting speakers who use different – non-formalistic – techniques to get their message across, if we really want to take the underlying points from ontology to heart.

This article has explored the flaws of the mainstream, not only in their assumptions (a point which many heterodox economists make) but in their methodologies and techniques. We have explored possible alternative methodologies whilst explaining some concepts which could bear fruit for economics, outside of mathematically formalistic frameworks. Obviously social ontology as a subject is much greater than what has been described here, but this is just an insight into the powers which can be taken from observing more carefully the viewpoint we take on social interactions and how we can enrich our study for its self-betterment. If you are interested in discussing more about some of these ideas then I’d be happy to point you in the right direction, you can contact me on rjw218@cam.ac.uk .

*Data mining is the process of including variables in an equation even when there is no understood or believed reason to include such a variable, simply to increase the predictive power of the model. Whilst this may seem useful, it tells us nothing about the causal mechanisms, and the relationship between such variables.

**I would also caution against experiments being conducted solely on undergraduates at high-ranking universities, as this is hardly a representative sample of the whole population. Whilst certain norms may be considered hardwired into homo sapiens in general, other norms will be dependent upon a variety of demographic factors such as age, income, educational attainment etc. Hence field experiments may be more beneficial in that they are generally tested on a more diverse sample.


(1) Lawson – A Conception of Social Ontology  (http://www.csog.econ.cam.ac.uk/documents/AConceptionofSocialOntology.pdf)

(2) Lawson – A Conception of Social Ontology  (http://www.csog.econ.cam.ac.uk/documents/AConceptionofSocialOntology.pdf)

(3) Lawson – What is this ‘school’ called neoclassical economics?

(4) Lawson – What is this ‘school’ called neoclassical economics?

(5) Colander et al, 2004

(6) Little – Levels of the Social

(7) Leamer 1983

(8) George Akerlof – AEA Presidential Speech

(9) George Akerlof – AEA Presidential Speech

(10) George Akerlof – AEA Presidential Speech

(11) Colander et al,The Financial Crisis and the Systemic Failure of Academic Economists

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