The Weekend Economist "Quaerere Verum"

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Tuesday, March 13, 2007

#49 The Social Science of Economics Part 2

Be sure to read The Social Science of Economics Part 1 first!

Entering the twilight zone…

In part one I hinted at the idea of computers and complex quantitative models taking over from humans as active market makers. We are definitely going to see rapid further growth of quantitative financial modeling, computer run portfolios and computer market management based systems. Before you feel completely obsolete, however, keep in mind that there are still a number of factors involved that should, at least for a while, guarantee jobs for those beings with emotions and mortality.

There remain limiting factors to quantitative perfections, as computers and models require data. And there are many different types of data, such as trading volumes, stock prices, volatility, interest rates, Gross Domestic Product, consumer spending, job growth, inflation, etc. The problem with data is that some of it may not be a true reflection of the economy. Think again about our definition of the economy as a common denominator of human interaction.

Traditional economic approaches fail to capture the true scale and complexity of the global economy and therefore so do our data. In fact, there is a shadow economy, be it a twilight zone, completely untouched by the bias of our standard quantitative approaches to economics. For example, to what extent does GDP truly reflect the sum of economic behavior of a country? GDP only contains that what we measure and unfortunately (or fortunately depending on your profession) not everything is measured. Why not? Because the real world contains aspects that cannot be measured. In development economics this is partly captured by the notion of the "informal economy." The informal economy contains activity that is neither taxed nor monitored by a government and is subsequently not included in that government's Gross National Product.

The informal economy can encompasses everything from money laundering, drug trade, prostitution and bartering of goods and services, to mowing the lawn for grandpa, writing a blog and downloading or uploading content from the internet. With that in mind, the informal economy probably says much more about human behavior than does the formal economy. Although the informal economy is notoriously unquantifiable, it is probably a grossly understated element driving GDP.

Coming back to the idea that economics is a social science: exchange does not have to be monetary. In fact, most exchanges between people do not directly involve money. Inherently it means that value is actually arbitrary and, analogously, the value of money is arbitrary as well. Just as purchasing power parity can explain why an American middle class salary lets you live like a king in Vietnam, the arbitrary value of money explains how people value an X amount of money irrespective of the differences in their environment.

So now the twilight zone is complete: there is a world with arbitrary value, one where there are different modes of transaction – monetary and non-monetary. Monetary exchanges include informal monetary transactions (think about prostitution, micro finance (e.g. mini loans, transactions within families or farm cooperatives) and mafia practices). In terms of non-monetary alternative exchange based transactions, think of media exchange on the internet, bartering goods and services, etc. This twilight zone should encompass economics. But it doesn’t, because it presents a nightmare scenario of elements that are by their nature difficult to quantify and analyze in a traditional economic sense.

A common thread and constant within this twilight zone is human behavioral aspects. This is not saying that human behavior is constant (in fact it is probably highly variable and scenario driven), but it saying that, although the basis of exchange and circumstances is variable, there is perhaps a common thread (keeping in mind bounded rationality) that can accurately describe human economic behavior more accurately than traditional restricted economic models. So conclusively, if we accept that economics is a social, behavioral science, it needs to extend the breadth of analysis by drawing from disciplines it criticizes as soft or irrelevant. Finally, if we are to use economics to accurately model the aggregate of human behavior and exchange, it is imperative that we explore closer integration with fields such as behavioral finance, psychology and, in the future, neuroeconomics.

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