Thursday, May 21, 2009

Humans v Rats v Monkeys

This is a case of how “heuristic bias” in humans (a preference for rules of thumb in decision-making) and hubris proved to be their undoing when pitted against rats and monkeys in two experiments. The lessons drawn have implications for anyone engaged in economic development and industrial policy.
Prominent development economist Bill Easterly was not joking when he recently blogged that “rats outperform humans in interpreting data.” He was referring to the experiment recounted in Leonard Mlodinow book The Drunkard’s Walk in which rats and humans were pitted against each other and made to draw green and red balls at random. With probabilities rigged in favour of greens, they were made to predict the colour of the balls drawn after observing the process.

Surprisingly, the rats came out on top:
The rats followed the optimal strategy of always predicting green (I am a little unclear how the rats communicated, but never mind). But the human subjects did not always predict green, they usually want to do better and predict when red will come up too, engaging in reasoning like “after three straight greens, we are due for a red.” As Mlodinow says, “humans usually try to guess the pattern, and in the process we allow ourselves to be outperformed by a rat.”
This experiment is reminscent of the 14 year exercise initiated by the Wall Street Journal which tested Princeton Prof Burton Malkiel’s thesis contained in the book A Random Walk Down Wall Street that

a blindfolded monkey throwing darts at a newspaper’s financial pages could select a portfolio that would do just as well as one carefully selected by experts.
After 100 iterations of the game, the results showed that while the analysts came out on top, the margin was embarrasingly low, 61-39. One funny way to express this finding would be to say that when it comes to “picking winners”, “monkey see, monkey do” works fine.

Easterly whose stint in the UN led him to take a dim
view of so-called “growth experts” has sparked robust discussions with the likes of Jeffrey Sachs of The End of Poverty fame over the effectiveness of international development projects and Dani Rodrik author of One Economics, Many Recipes over the appropriateness of industrial policy.

In terms of developing growth strategies, Easterly’s advice has been to forego well-intentioned interventions emanating from the top (whether they be the in the form of a "big push" for public investment ala Marshal Plan or "
shock therapy" ala Sach's approach of introducing market-based institutions to ex-Communist regimes). Easterly’s most recent book contrasts "planners" and "searchers". The former use the instruments just mentioned to (not) achieve their goals. The latter rely more on local feedback and accountability with
lots of political and economic competition with freedom of choice of consumers, investors, and voters.
The belief is that there is no use second-guessing what works when the local market for ideas performs more efficiently and contains more information than the calculations of a detached planner no matter how sophisticated his heuristic models might be. The fact which all these experts agree on is that public investments and industrial policy may have been partly responsible for economic development in some cases in the past. Where they part ways is on whether experts can identify with any reliability the means with which to implement them in different situations in the future.

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