Collaboration among academics and practitioners can fix economics

July 27, 2011

By Ashwin Parameswaran
The opinions expressed are his own.

Reuters has been collecting responses to Mark Thoma’s Op-Ed on the “great divide” in economics and will be publishing the responses. Here are responses from Roger MartinJames HamiltonDean BakerLawrence Summers, and a recap of Paul Krugman’s.

In an excellent article, Mark Thoma highlights the great divide between academics and practitioners in economics. He also identifies the fundamental reason for this divide – practitioners typically rely on intuition and rough heuristics whereas academics rely on rigorous theoretical constructs.

In Herbert Simon’s terminology, practitioners are satisficers, not optimisers. In a recent post, I outlined my preferred framework to analyse monetary policy as an attempt to influence the real rate curve. Clearly, this viewpoint is not rigorous but for my purposes transforming this framework into a theoretically watertight construct is not worth the effort. The aim of the framework is simple to give me a quick and dirty but useful way to process information and market data. It is also almost certain that in some scenarios, this framework will break down – but instead of thinking about all such scenarios in advance, I simply trust that my experience and my gut instinct will warn me when such a scenario occurs.

To most academics, the process I have outlined above would seem to be a distinctly unscientific and “irrational” method. But as I have argued before, heuristics and intuition are rational responses in an uncertain environment where time and resources are scarce. Herbert Simon and Gerd Gigerenzer have both done excellent work on the role of heuristics but the most relevant research on the role of intuition has been undertaken by Gary Klein and other researchers in the field of ‘Naturalistic Decision Making’ (NDM). NDM originated from Klein’s work in analysing the decision-making of firefighters – as Klein explains in this recent interview, expert firefighters follow a process that is far removed from the conventional definition of rational choice. They “build up a repertoire of patterns so that they can immediately identify, classify, and categorize situations, and have a rapid impulse about what to do. Not just what to do, but they’re framing the situation, and their frame is telling them what are the important cues. That’s why they’re always looking, or usually looking, in the right place. They know what to ignore, and what they have to watch carefully.” There’s nothing magical about this:

“Intuition is about expertise and tacit knowledge. I’ll contrast tacit knowledge with explicit knowledge. Explicit knowledge is knowledge of factual material. I can tell people facts, I can tell them over the phone, and they’ll know things. I can say I was born in the Bronx, and now you know where I was born. That’s an example of explicit knowledge, it’s factual information.

But there are other forms of knowledge. There’s knowledge about routines. Routines you can think of as a set of steps. But there’s also tacit knowledge, and expertise about when to start each step, and when it’s finished, when you’re done and ready to start the next one, and whether the steps are working or not. So even for routines, some expertise is needed.
There are other aspects of tacit knowledge that are about intuition, like our ability to make perceptual discriminations, so as we get experience, we can see things that we couldn’t see before….

Judgments based on intuition seem mysterious because intuition doesn’t involve explicit knowledge. It doesn’t involve declarative knowledge about facts. Therefore, we can’t explicitly trace the origins of our intuitive judgments. They come from other parts of our knowing. They come from our tacit knowledge and so they feel magical. Intuitions sometimes feel like we have ESP, but it isn’t magical, it’s really a consequence of the experience we’ve built up.”

Larry Summers is correct in noting that the solution is not for practitioners to become academics. It is for more academics to rigorously analyse the intuitive and heuristic-based methods and explanations that practitioners use. The real gap is in the paucity of applied economists and the misguided view of applied work with data-crunching rather than practical knowledge. As Daniel Kahneman explains in his introduction to Gary Klein’s interview:

“In the US, the word ”applied“ tends to diminish anything academic it touches. Add the word to the name of any academic discipline, from mathematics and statistics to psychology, and you find lowered status.  The attitude changed briefly during World War II, when the best academic psychologists rolled up their sleeves to contribute to the war effort. I believe it was not an accident that the 15 years following the war were among the most productive in the history of the discipline.  Old methods were discarded, old methodological taboos were dropped, and common sense prevailed over stale theoretical disputes. However, the word ”applied” did not retain its positive aura for very long. It is a pity.

Gary Klein is a living example of how useful applied psychology can be when it is done well. Klein is first and mainly a keen observer. He looks at people who are good at their job as they exercise their skills, sometimes in life-and-death situations, and he reports what he sees in clear and eloquent prose.  When you read his descriptions of real experts at work, you feel that it is the job of theorists to accommodate what he has seen – instead of doing what we often do, which is to scan the “real world” (when we think of it at all) for illustrations of our theoretical notions.”

The divide that Mark Thoma identifies is not restricted to economics – in the age of ‘Big Data’, all academic disciplines are moving away from the sort of work that requires researchers to get their hands dirty. In an excellent post, Jennifer Jacquet explains how field ecologists like Robert Paine are a dying breed, being replaced by ecologists more at home on a computer than in the field. This is not a criticism of mathematical ecology, simply an assertion that the kind of insights that Bob Paine derived from spending “45 years knee-deep in kelp and invertebrates on Washington State’s coast” are valuable and cannot be replicated by other means. This presumption that data and theory can substitute for experience on the ground is symptomatic of the broader problem of the downgrading of tacit and contextual knowledge highlighted by many other changes in academic economics, most notably the neglect of economic history and institutional detail. One of the most striking deficiencies in economic theory that was exposed during the crisis was the disconnect between monetary economics and the institutional reality of the new regime of shadow banking and derivatives. Hyman Minsky’s theories are relevant not because of their theoretical elegance but because of their firm grounding in the institutional evolution of the post-war monetary and banking system, a topic that he researched in great detail.

An example of how this balance between the theoretical and applied fields can be restored is provided by the collaborative work between Daniel Kahneman and Gary Klein. Kahneman and Klein have spent their entire careers tackling the same field (the psychology of decision-making) with diametrically opposed approaches – Kahneman focuses on controlled lab experiments, comparisons of decision-making performance to an objective optimum, and a generally skeptical stance towards human cognition. Klein focuses on research in real-world organisations, analysis of actual performance through more subjective variables and a generally admiring stance on human cognition. Yet they were able to collaborate and find common ground, the results of which are summarised in a fascinating paper. Economics could do with more applied researchers like Gary Klein as well as more theoretical researchers like Daniel Kahneman who are open to applied practical insights.

This post was republished from Ashwin Parameswaran’s blog with permission.


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