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"Economists' Grail: A Post-Crash Model"

Monday, November 29, 2010


"In the wake of a financial crisis and punishing recession that the models failed to capture, a growing number of economists are beginning to question the intellectual foundations on which the models are built. Researchers, some of whom spent years on the academic margins, are offering up a barrage of ideas that they hope could form the building blocks of a new paradigm.

Today's models emerged from a revolution of their own. In the 1970s, economists were struggling to figure out how policy moves, such as raising taxes or cutting interest rates, could change how people behave. They were also eager to subject their own reasoning to the unforgiving judge of mathematical logic.

So they populated their models with rational people who can calculate the value of various possible moves and choose the optimal path. A person deciding whether to buy a car, for example, would take into account the potential return on investing the money, the probability that car prices will rise, and the chances that an increase in tax rates will cut into her disposable income.

By translating peoples' preferences into equations, and finding the point at which they meet those of firms and other players, the models forecast an exact trajectory for the economy. That feature makes them very attractive to economists, who can plug in a change in interest rates and see precisely how the move might affect an entire country's output for the next few years.

The problem...is that the models bear too little relation to reality. People aren't quite as rational as models assume...Advocates of traditional economics acknowledge that not all decisions are driven by pure reason.

...

To keep things simple, economists leave out large chunks of reality. Before the crisis, most models didn't have banks, defaults or capital markets, a fact that proved problematic when the financial crisis hit. They tend to include only households, firms, central banks and the government. They also commonly use a single equation to represent each player, impairing the models' ability to explain the unexpected outcomes that can emerge when millions of different people interact.


...

'Economic forecasts have never been very good, and it's not clear that if we stick with the methods we're pursuing we'll do any better...We need to try something new.'"





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