Ontology and Economics

Edward Fullbrook

• Publisher: Routledge
• Year: 2008
• ISBN:
  9781134024186
• Edition: 1
• Topic: Commerce
• Subtopic: Commerce Général

Tony Lawson has become a major figure of intellectual controversy on the back of juxtaposing two relatively simple and seemingly innocuous ideas. He has argued firstly that success in science depends on finding and using methods, including modes of reasoning, appropriate to the nature of the phenomena being studied, and also that there are important differences between the nature of the objects of study of natural sciences and those of social science. This original book brings together some of the world's leading critics of economics orthodoxy to debate Lawson's contribution to the economics literature. The debate centres on ontology, which means enquiry into the nature of what exists, and in this collection scholars such as Bruce Caldwell, John B. Davis and Geoffrey M. Hodgson present their thoughtful criticisms of Lawson's work. Lawson himself presents his reactions to these criticisms, with full chapter replies to each of the scholars included.

This book is particularly useful for students and researchers concerned primarily with methodology and future development of economics. It is also relevant to the concerns of philosophers of science and to all social scientists interested in methodological issues.

1 Some comments on Lawson’s Reorienting Economics

Same facts, different conclusions

Bruce Caldwell

I welcome the opportunity to reflect on Tony Lawson’s Reorienting Economics (2003). Lawson covers a considerable amount of ground in his book, so my comments will of necessity be selective.

I will begin by stating that, for what it is worth, I am in substantial agreement with Lawson’s fundamental complaint that the economics profession is dominated by a mainstream orthodoxy which is “not in too healthy a condition” due to its insistence on following a specific methodological approach, one that is not well matched to the social reality it wishes to investigate (p. 3). I make similar complaints in the final chapter of my book on Hayek (Caldwell 2004), and indeed I quote liberally from Lawson’s earlier book (Lawson 1997) in that chapter. In this regard I consider Lawson a colleague who shares a quest, that of figuring out why economics turned out the way it did in the twentieth century. This quest has historical, methodological, ideological, sociological, and even pedagogical dimensions, and we are but two of many who have contributed to it (a selective sample might include Mäki 1999, Mirowski 1989, 2002, Weintraub 2002, and selected articles in Colander and Brenner 1992).

As an aside, I will add that Lawson’s broad-brushed description of structured social reality is quite attractive. For those who have read Hayek, it is also familiar: many of the things that Lawson identifies as features of social reality were similarly identified by the Austrian social theorist. For example, that “human social activity is intelligible” (p. 33), that we follow social rules (pp. 36–38), that human actions are “intentional human doings, meaning doings in the performance of which reasons have functioned causally, where reasons are beliefs grounded in the practical interests of life” (p. 47), that many actions are based on tacit knowledge (ibid.), that humans form plans that are forward-looking (pp. 50–51), and that all human agency takes place within given social structures, but also produce changes in those structures (pp. 48–49), are all Hayekian themes.

That such claims appear in both Hayek and Lawson is perhaps not altogether surprising, for they are also recognizable in the writings of other heterodox economists, post Keynesians (at least of the Shacklian variety) for example. Lawson explicitly recognizes this in Chapter 7, where he suggests that different heterodox traditions share the broad-based description of social reality, and are to be distinguished from one another according to the different aspects of that reality upon which each chooses to focus (pp. 180–183). Given the richness of the complex reality before us, this too makes sense. It may also help to explain why (especially if one accepts the proposition that many issues that separate such groups are empirically undecidable, more on which in a moment) such groups inevitably persist. Some may agree with Lawson and me that pluralism makes good sense; the complex nature of social reality may also mean that it is inevitable.

In Chapter 4 Lawson recommends that economists reorient their discipline by resolving to seek causal explanations. He lays out an explanatory strategy for accomplishing this, which he breaks into three steps: identify event regularities, form causal hypotheses that can account for them, and then discriminate among the competing causal hypotheses that are consistent with the regularities (p. 81). Though he does not say so explicitly in his general formulation, it may be that Lawson is calling for more long run causal explanations here, or, put another way, for more economic history. Some of Lawson’s examples (e.g., explanations of differential measured productivity growth rates, or of relative changes in primary versus produced goods prices over the last century) support this reading, as does Lawson’s italicized statement at the end of the chapter that “the explanatory process so facilitated is necessarily backward looking” (p. 108).

If Lawson is advocating that economists do more economic history when he says that we should seek causal explanations, I have no quarrel, though as will be clear, I believe that there are other things that we can be doing as well. However, it may be that Lawson is calling for what might be termed short run causal explanations as well. In my opinion, seeking to produce valid short run causal explanations is an extremely ambitious goal, and in many instances an unreachable one. The complex nature of the open system that constitutes social reality, one that poses such problems for mainstream efforts at its analysis, will cause similar problems for any such program.

A homely example will illustrate the problem. I work in a largely empirical department of economics. Though the kind of research that I like to do is very different from theirs, I have come to admire and respect the carefulness with which my colleagues undertake their work. This is best revealed in departmental seminars, countless numbers of which I have attended (the high price of good departmental citizenship). Over the years certain features of a “typical” empirical seminar have emerged. A problem or puzzle is posed. Sometimes the problem arises from surprising relationships that have been discovered among the data (e.g., one colleague found that, during recessions, a number of variables associated with “better health” improved); other times it is an attempt to identify the impact of some policy change on some set of variables of interest (e.g., the impact of changes in the welfare laws on household and labor market variables of interest, or of the institution of charter schools on variables associated with educational outcomes). As the speaker goes through her presentation, typical questions arise. If the data set is a wellknown and frequently used one, the speaker is asked about how she handled the equally well-known problems associated with it. If it is a new data set, there are questions about how the variables of interest were constructed, and whether their composition raises problems for the questions that the speaker seeks to answer. Usually they do. The peculiarities of the data dictate which subset of econometric methods should be used to correct for the problems. A good speaker knows the limitations of her data, and has chosen the subset of methods that hold the best chance of correcting for them. Speakers judged as ineffective are either unaware of problems or of the appropriate tools for correcting for them, or worse, both.

Sometimes the speaker draws policy conclusions from the study. This typically provokes animated discussion, for a number of reasons. First, the relations among the data are correlations. To move from there to policy conclusions, one must speculate about causes, and there are typically many plausible interpretations on offer. Next, all empirical economists recognize that adding new variables to an existing set of variables, or using new data sets that include different variables or which cover different time periods, or using different types of corrections, all typically yield different results, always in terms of the coefficients attached to various variables of interest, and sometimes in terms of their signs. The latter phenomenon is sufficiently ubiquitous that an economist who has studied them has given them a name: “emerging recalcitrant results.” Robert Goldfarb draws the obvious inference about such findings:

These emerging contrary results or “potential reversals” present a dilemma for the conscientious economist who is part of an empirical literature’s audience. How is he or she to make believable inferences from such a literature, when results may have already been, or in the future be, challenged and even conceivably overturned?

(1997, p. 222)

The implications are evidently quite profound if one wants to take the step towards making policy recommendations. As a result, the most successful seminar presenters (the most “scientific”) are very careful about trying to discuss the policy implications of their papers. It is usually done only in the last five minutes, when the substance of the talk is over, sometimes with a bit of a smile or other body language to suggest that this is the speculative part, always using very careful language (“this study would seem to suggest…”). No claims are ever defended with anything like the vigor with which one defends one’s choice of econometric techniques.

The main reason why making the jump from the empirical results of a study to policy conclusions is so difficult is that a given set of facts always give rise to multiple plausible interpretations as to why the facts are as we find them. In my estimation, precisely the same holds true when one seeks short run causal explanations. To restate this using Lawson’s own framework, my point is that the third stage of his recommended strategy, that of formulating ways of discriminating among competing causal hypotheses, is in the short run extremely problematical. People are always able to reach different conclusions from the same set of facts.

The bedrock claim that underlies this pessimistic conclusion is that the complexity of social phenomena implies severe limitations on what we can expect of empirical work in economics. This does not mean that progress in the empirical domain is impossible. We now have better and more varied statistical methods, more powerful computers, and more detailed data, so that we can describe the economy at a point in time much better than we could even a generation ago. But even with all of these advances, the complexity of the phenomena we analyze means that forecasting will be difficult, it means that making the move from an econometric study to a policy conclusion will be difficult, and it means that discriminating among competing causal hypotheses, at least in the short run, will be difficult. These are not problems that will go away through time, once we have better tools. They are a permanent feature and are due to the nature of the open system that we study. This pessimistic conclusion is probably the most important implication that I drew from my study of Hayek’s writings on the study of complex phenomena. My working subtitle for my book, and one I had wished now that I had retained, was “F.A. Hayek and the Limits of Social Science.”

Does providing long run causal explanations exhaust the contributions that economists can make? No, there are other things that we can and should do. For example, economists have long contributed a method of analysis that helps all of us to make better sense of the world. I have discussed this contribution both in my book and on the pages of the postautistic economics review under the not very well-defined label “basic economic reasoning” (Caldwell 2002, 2004, pp. 382–388). What constitutes basic economic reasoning is hard to describe (though I am tempted to say, like pornography, I know it when I see it), so instead of offering a definition I have provided a number of examples of what I have in mind in my article and book.

Basic economic reasoning uses simple tools, like production possibility curves or demand and supply curves, to facilitate understanding of real world events. Such diagrams almost “think for themselves.” They embody common sense, even proverbial knowledge (e.g., the notion of opportunity cost suggests the adage, “you can’t have your cake and eat it too”), knowledge that has survived and been passed down through time in various forms because it has proved useful.

Because they embody common sense, the diagrams themselves are not really even necessary. Last week I read in the paper that, due to the hurricanes that hit Florida in the summer and fall of 2004, Americans should expect that the prices of certain produce (oranges, grapefruit), of lumber and other products used in construction, and of certain types of insurance to rise, and that east coast resort beaches outside of Florida should experience more business. One could use a demand and supply diagram to show why we might expect such things to happen, one carefully hedged with ceteris paribus clauses, but one doesn’t need to do all that, and they certainly did not do it in the newspaper. Nor does such reasoning depend on humans acting like the perfectly rational agents that are necessary for deriving such predictions in our formal models.

So what is the status of such knowledge? In a recent paper on Frank Knight and pragmatism, Wade Hands (2006) describes Knight’s views about economic science. Knight’s views are helpful here, because what he describes is very similar to what I have in mind when I talk about basic economic reasoning.

For Knight … even though economics is not a positivistic science, it is a type of science: an intentional or common-sense science based on the beliefs and desires of economic agents. Such economic science is essentially a formalization of age-old common sense, but it successfully provides both predictions and explanations of human behavior (though a different type of prediction than available in the natural sciences). Given the particular character of the objects in its domain—humans—this intentional common sense science is not only useful, it actually predicts better than the application of positivistic science to the human domain. As Knight says, “in this instance the position of common sense is better grounded in terms of the ultimate and inclusive facts of experience than is that of scientific logic”.

(p. 580; the quotation from Knight is from Knight 1935, p. 81)

Basic economic reasoning is a powerful tool, it helps us to make sense of the world, it allows us to make better decisions, and it makes human behavior more ordered. It is part and parcel of what makes human behavior intelligible, and predictable in certain domains, to the extent that it is at all. Seeking to explicate and to expand the domain of such reasoning is one of the most important contributions that economists can make.

Yet as Hands’ passage makes clear, the status of such knowledge is ambiguous. It clearly does not meet the criteria of positivistic science. Nor, as far as I can see, does its use fit easily into the categories that Lawson provides.

But perhaps I am wrong. It may be that the phenomena that basic economic reasoning identifies are event regularities, or “demi-regs.” So it may be that I am saying that we should not worry about establishing causes, but simply use these tools that have proven to be so useful in identifying event regularities in the past, even if we do not know precisely why they work. Alternatively, I also suggested in both my article and my book that exploring just why such reasoning works might also be a fruitful research endeavor: this may well be equivalent to Lawson’s call for forming and discriminating among causal hypotheses. But such activity should not, in my view, obscure the fact that such reasoning is essential, and should be retained even if we are not sure (because we are unsure of the underlying causal mechanisms) why it works as well as it often does. In any event, I would welcome hearing Lawson’s views on such matters.

In conclusion, though Lawson and I share much common ground in terms of our descriptions of what ails the economics profession, our “policy conclusions” as to the best way forward appear, at least, to be different. Given all that I have said above, the fact that we might reach different conclusions starting from the same set of facts is not surprising to me.

References

Caldwell, Bruce. “In Defense of Basic Economic Reasoning,” post-autistic economics review, no. 13 (May 2, 2002), article 4. Online, available at: www.btinternet.com/~pae_news/review/issue13.htm (accessed 12 June 2008).

——. Hayek’s Challenge: An Intellectual Biography of F.A. Hayek. Chicago, IL: University of Chicago Press, 2004.

Colander, David and Brenner, Reuven (eds). Educating Economists. Ann Arbor, MI: University of Michigan Press, 1992.

Goldfarb, Robert. “Now You See It, Now You Don’t: Emerging Contrary Results in Economics,” Journal of Economic Methodology 4, no. 2 (December 1997), pp. 221–244.

Hands, Wade. “Frank Knight and Pragmatism,” European Journal of the History of Economic Thought 13 (December 2006), pp. 571–605.

Knight, Frank. “Economic Psychology and the Value Problem,” in Frank H. Knight (ed.) The Ethics of Competition and Other Essays. New York: Harper, 1935, pp. 76–103.

Lawson, Tony. Economics and Reality. London and New York: Routledge, 1997.

——. Reorienting Economics. London and New York: Routledge, 2003.

Mäki, Uskali. “Science as a Free Market: A Reflexivity Test in the Economics of Economics,” Perspectives on Science 7, no. 4 (1999), pp. 486–509.

Mirowski, Philip. More Heat Than Light: Economics as Social Physics, Physics as Nature’s Economics. Cambridge: Cambridge University Press, 1989.

——. Machine Dreams: Economics Becomes a Cyborg Science. Cambridge: Cambridge University Press, 2002.

Weintraub, Roy E. How Economics Became a Mathematical Science. Durham, NC: Duke University Press, 2002.

2 History, causal explanation and “basic economic reasoning”

Reply to Caldwell

Tony Lawson

It is hugely desirable to be charitable in interpreting an opponent’s arguments. Being so constitutes not only an expression of respect, but also a principle of good methodological practice. For revealing the limitations of a simplistic caricature of someone else’s position rarely constitutes much of an advance in understanding.

I expect most commentators will agree with this. But I am aware of few who seek m...

Table of contents

• Cover Page
• Title Page
• Copyright Page
• List of contributors
• Foreword
• Introduction: Lawson’s reorientation
• 1 Some comments on Lawson’s Reorienting Economics: same facts, different conclusions
• 2 History, causal explanation and “basic economic reasoning”: reply to Caldwell
• 3 Critical realism in economics: a different view
• 4 Underlabouring for substantive theorising: reply to Davidsen
• 5 The nature of heterodox economics
• 6 Heterodox economics and pluralism: reply to Davis
• 7 Reorienting economics through triangulation of methods
• 8 Triangulation and social research: reply to Downward and Mearman
• 9 Irrelevance and ideology
• 10 The mainstream orientation and ideology: reply to Guerrien
• 11 On the problem of formalism in economics
• 12 On the nature and roles of formalism in economics: reply to Hodgson
• 13 Finding a critical pragmatism in Reorienting Economics
• 14 Ontology or epistemology? Reply to McFarling
• 15 (Un)real criticism
• 16 Ontology and postmodernism: reply to Ruccio
• 17 Feminism and realism: a contested relationship
• 18 Feminism, realism and essentialism: reply to van Staveren
• 19 Conjectural revisionary ontology
• 20 Provisionally grounded critical ontology: reply to Vromen