Physics Killed The Economics Star

There has been much debate recently about the failings of the discipline of economics and those who practice it. What good are any of them, the critics ask, if they could neither prevent nor foresee a financial crisis of such magnitude? Economists’ responses to this varied in tone from personal exclusion and blame shifting (everyone went digging through their pre-2009 blog posts) to honest soul-searching, also including retaliation that was as non-constructive as the initial critique.

When I personally encountered this debate, I defended the dismal science against all odds. No surprises there: I’ve invested most of my adult education in the field and learned to parrot the remarks of much more brilliant men: blame certain economists, not economics, I began. Hardly anyone in academe does forecasts at all- it is the explanation of phenomena, and not their prediction, that mainly interests economists. And the real knockout, the last refuge of the desperate: what else is there that is better, anyways?

Sociology? Political Science? Psychology? History? It seems difficult to imagine that these fields, with their embrace of complexity, could do better. These disciplines’ rejection of universal principles of behavior as a core makes quantifiable predictions even more difficult. Think of the banker, the manager, the investor, the president. This person does not want to hear about all the contextual elements, the defining minutiae of human idiosyncrasies, the complex power struggles determining the movements of economic aggregates. She wants to know if the number will go up, or if it will go down. And fast.

In this same mental exercise, the late Paul Samuelson turned in practice to mathematics and in spirit to physics. If we cannot state our assumptions and our reasoning in a rigorous manner, he said, the complexity of the issues will drown out everything in our theories but the rhetoric. And with his turning, all subsequent generations of economists marched forward – some with blind enthusiasm, some with trepidation – towards the ideal of economics as an objective, quantitative “social natural science”.

As someone who knew nothing of the emulated fields, I applauded the effort. The elephant in the room, that the object of a social science is fundamentally not the same as that of a natural one, was eventually addressed by the rise of behavioral economics with Kahneman and Tversky. In class, we reviewed contemporary approaches to the seemingly irrational behavior that threatened to wreck two centuries of work. Every day in every way, economics was getting better and better. The critics could wait a little and then be forever silenced.

But then I started reading a little about physics, or rather about its history. I read about Tycho Brahe, who developed the most advanced instruments of his day to collect data on the movements of the stars and planets. I read about his disciple, Johannes Kepler, who waited until the greedy Brahe died and then used his collected data to describe the geometric patterns within. And of course, I read about how Newton took this description of the motions of planets and developed a precise mathematical description of gravitation.

What shocked me was that none of them offered an explanatory (as opposed to a descriptive) theory for planetary motion; it would take until the 20th century (i.e. General Relativity and Quantum Mechanics) to offer explanations as to why gravity existed and thus shaped the motions of the planets. All the work before it was limited to describing the patterns in the data in increasing depth and rigor.

This wasn’t at all like what I’d learned in class. I don’t recall ever reading about any famous economist who simply dedicated himself to collecting data and describing it. Most of the theoretical papers I’d read spent little more than a paragraph in discussing anecdotal evidence, let alone focus entirely on modeling surface behavior. On the other side of a vast chasm, the empirical researchers bent over backwards to find testable implications of these theories, and often failed to confirm them. It was almost as if they weren’t on the same planet, let alone the same department.

I witnessed one of the clearest examples of this divide in the theory of international trade. It is one of the oldest branches of economics, and yet for the longest time it failed miserably to explain or predict the behavior of real-world exports and imports. The eminently rational arguments that motivated trade in the classical and modern theory- comparative advantage, factor abundance, differences in preferences – turned out to be very poor predictors of what trade flows actually look like.

It wasn’t until 1952 that an empirically successful model was proposed: Jan Tinbergen’s “Gravity” equation (an allusion to Newton’s formula). It’s argument was rudimentary: trade would increase with the GDP of trading countries, and decrease with distance and other barriers. If the simplicity of the argument was galling to theorists, its results were even more so – it explained the real world data beautifully. The empirical economists were pleased at this new available tool, and began using it to answer interesting questions about the world, while the theorists simmered.

It was offensive that such a shallow explanation of such a complex reality was preferred to the deeper models. As a student, deriving the equilibrium for Ricardian or Heckscher-Ohlin trade  was mathematically challenging and full of surprising insights, while learning about the pedestrian theory behind the “gravity” model took less than a single lecture. The rest was mostly computation and statistics, and that was a lot less fun, a lot less glamorous.

After reviewing the scientific history of gravity, however, I was ashamed of my initial reaction to this model. If I was really all for getting on the natural sciences bandwagon, then why not do it thoroughly? The minute the old theories of trade failed to make accurate and testable predictions, they should have been dismantled for whatever useful parts they had and then ditched. Instead, despite the fact that they have failed in every honest empirical test for the last 60 years, they continue to be taught and researched.

More importantly, the “gravity” model is precisely the kind of explanation to be looking for at this stage- an accurate description of the data. To accept this doesn’t mean that there aren’t deeper explanations for what it describes, just like Newton’s own law of universal gravitation did not exclude the deeper answer provided by general relativity. What it does mean is that a more humble approach – a gradual deepening of our explanations of reality- is bound to be more successful than writing theory from a vacuum. The problems we face are too urgent to allow such a broad division between the theorizing and verifying branches of the science and the ensuing lag in progress.

Admittedly, the limitations that the domain of economic research imposes are different from those of the natural sciences; laboratory experiments, the ideal environment in which to untangle these complex phenomena, are fairly recent in economics and downright  impossible for many subjects. The other source of data, the “natural experiments” sometimes provided by the real world, is impossible to control and difficult to interpret correctly. These are not, however, arguments that support the current divide between pure economic theory and empirical analysis. If anything, these limitations further motivate a more conservative approach: describe successfully, and only then attempt to explain.

I suppose it is clear that I cannot abandon my defense of economics for long. Like Samuelson, I am convinced that the only path that the discipline should follow is that of the natural sciences. Anything else is sophism, or at best a pre-Copernican notion that humans are somehow exempt from the laws  that rule the universe. However, economists must consciously beware of their tradition as speculative philosophers if they are to become scientists. It is an enormously difficult endeavor, since they must adapt the natural scientist’s method to a different and much more fickle field. But, I believe, there is no discipline that is better equipped or more urgently at task than economics.

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2 comments

  1. Ricardo Avillez

    Well said, dsilveyra! I especially liked the part when you talked about how a more humble approach (which, from the rest of the text, read as a more “empirically minded approach” to me) is bound to be more successful than theorizing in a vacuum. Here are some random thoughts/questions about the subject:
    – In my opinion, one of the main culprits for this “excess of theory”, so frequently unlinked from any recognizable economic reality, is the search for microfoundations. Macromodels, for instance, are no good unless they are microfounded… But microfounded models frequently yield results that don’t actually fit the data, because of the (way too) simplified assumptions about human psychology, decision making etc.
    – This brings me to a more general point. Economic models nowadays have clear assumptions, are microfounded and mathematically rigorous – i.e. they are “scientific”. Or, at least, this is how mainstream economics perceive what is (and what is not) “scientific”. The current state of things wasn’t brought about because economists tried to imitate, say, sociology or history, but exactly because they tried to be more like the natural sciences. I’m not really sure this is the “scientific rigor” we need. Perhaps it is time to take a step back… Being speculative philosophers is not all that bad, is it? Why would pursuing this path necessarily be sophism? Would this make humans exempt from the laws that rule the universe? Not at all – the question is not about imutable laws that rule the universe, but about often transitory laws that govern societies.
    – “These disciplines’ rejection of universal principles of behavior as a core makes quantifiable predictions even more difficult.” One interesting readings regarding this: Henrich et al (2001) – “In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies”. Also, I’m not really sure if quantifiable predictions are the main objectives of psychology, sociology and history… History? Nah. Psychology and sociology are definitely interested in predictions, but do they have necessarily to be quantifiable? I, for one, would trade 10 quantifiable predictions for a valuable insight about human beings, economics, politics or whatever.
    – I’ll end with a quotation from Friedman (“Essay in Positive Economics”):
    ‘The ultimate goal of a positive science is the development of theory” or “hypothesis” that yields valid and meaningful (i.e., not truistic) predictions about phenomena not yet observed. Such a theory is, in general, a complex intermixture of two elements. In part, it is a “language” designed to promote “systematic and organized methods of reasoning.” In part, it is a body of substantive hypotheses designed to abstract essential features of complex reality.’

    ‘Viewed as a language, theory has no substantive content; it of tautologies. Its function is to serve as a filing system organizing empirical material and facilitating our understanding of it; and the criteria by which it is to be judged are appropriate to a filing system. Are the categories clearly and precisely defined? Are they exhaustive? Do we know where to file each individual item, or is there considerable ambiguity? Is the system of headings and subheadings so designed that we can quickly find an item we want, or must we hunt from place to place? Are the items we shall want to consider jointly filed? Does the filing system avoid elaborate cross-references?’

    ‘The answers to these questions depend partly on logical, partly on factual, considerations. The canons of formal logic alone can show whether a particular language is complete and consistent, that is, whether propositions in the language are “right” or “wrong”. Factual evidence alone can show whether the categories of the “analytical filing system” have a meaningful empirical counterpart, that is, whether they are useful in analyzing particular class of concrete problems.’

    Er. Longest comment ever. Cheers, man!

    • dsilveyra

      Hey R., thanks for your comment – I had a lot of fun thinking about the things you wrote. Hopefully you will keep them coming. In particular, your Samuelson quote was interesting in that it is a little vague about how narrowly “valid” predictions should be, or how much they should abstract from a complex reality. I suspect that the devil of the matter lies precisely in these details.

      Anyways, I tried to sketch some thoughts about what you wrote:

      On micro-foundations

      I think your argument argument is a compelling one. There’s an entertaining talk by Stiglitz that talks about the linkage between the failure of DSGE models and their microeconomic assumptions.

      I would further add that the failure of the micro models lies at the excess of their ambition. Instead of merely trying to explain superficial behavior, they tried to construct an entire framework for human decision-making.

      Consider Classic Consumer Theory and its attempt to motivate aggregate behavior through axioms of rational (or, more formally, consistent) choice. Despite being a wonderful achievement in reasoning and producing several important notions, it is doomed to fail – it is abstracting too much from reality in order to make it analytically tractable. In trying to understand the whole mechanism of human choice, the theory bit off way more than it could chew. As a related example of an approach that seems to me more “humble” is Samuelson’s own Revealed Preference argument: A superficial, ex-post description of what certain patterns seem to reveal.

      On being scientific
      I find it useful to distinguish between axiomatic and empirical approaches. I suppose one of the main criticisms one could raise against the discipline is that theory has become increasingly axiomatic – i.e. content to raise a few “self-evident” truths and then rigorously derive their logical consequences. In a George Soros talk (same conference as the Stiglitz one above), he likened this approach to Pythagorean reasoning, noting however that Pythagoras’ findings had the virtue of being perfectly applicable in the real world.

      The empirical approach is eminently that of natural science – it asks the scientist to observe the data and draw her theories from it alone. Further, once she has come up with a theory, it compels her to try and “break” it through whichever empirical means possible. Everything revolves around the real world.

      On speculation

      I don’t believe there’s anything wrong with speculation – it is by necessity the starting point of all scientific endeavor, since it lies behind the generation of hypotheses. It also happens to be the most fun – it requires little work in terms of rigorous thinking and it is easy to come up with things that sound very impressive. The problem is that speculation without the rest of the steps in the scientific method is, well, not science.

      It is not too bad being a speculative philosopher, just as long as no-one has any money riding on your speculations. Speculation does not necessarily lead to sophism, either – but a person who is content to only take ideas as far as speculation will take them is showing a similar disregard for reality or objective truth as a textbook sophist.

      I didn’t mean, by the way, to imply that the history, psychology, etc. were focused on the same problems and methods as economics. Rather, I was trying to make the point that precisely due to this misalignment they cannot replace the economic approach.

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