Wednesday, May 2, 2007

Why So Poor

Another great post by Rodrik.He points to a paper that looks at Total Factor Productivity (TFP) differences between the US, India and China.

For non-nerds TFP is a measure of how efficiently resources are combined. Different nations have different amounts of workers, factories, and natural resources. However, even when you account for all of that some countries like India and China are still poorer than the United States. Somehow, they are not able to combine there resources as effectively.

What the new study shows is that this is an industry by industry phenomenon. There are industries in China and India that are as efficient as those in the US but not all. The big question is why are Indians and Chinese still working and investing in the inefficient industries. Why don’t job move towards the industries that are more productive.

Perhaps, they are but we are just looking at a snap shot of the transition process. Give them a few decades and they will be there.

However, perhaps there is something more fundamental. Perhaps, dynamism is the critical component in strong economies. That is, there are barriers which prevent resources from flowing to where they are most efficient.

Here is what we know: People hate change. As an economist I usually make the nerdier quip that, “agents dislike uncertainty.” The underlying message, however, is the same. Safe economies are stagnant economies. Institutional and indeed preferences for stability will keep capital and labor locked into inefficient uses.

Here a real nut to crunch, too. Imagine that the poorer you are the more afraid of change you are. Now imagine that the world is changing in a way that slowly makes you poorer. We first see it happening it looks like its just a little loss so you don’t do anything. Why change.

Once it keeps happening you become aware that the potential losses are bigger than you realized. Yet, you’ve become poorer and thus even more afraid of change and so you still stay put, until you’ve become even poorer. The cycle continues until you are completely destitute.

Should I be thinking about a paper on The Vicious Cycle of Bayesian Updating and Rising Risk Premia or should I really be working on the papers I have already started. We both know the answer but alas hyperbolic discounting is a . . .

2 comments:

Unknown said...

Another way to think about the 'change' scenario is as an online learning/game framework, where the cost of changing your play is dependent on your cumulative 'winnings' (or lack thereof) from the previous rounds.

The exact cost functions needed to make you 'sit still' as your decision does worse and worse relative to the other decisions would then constitute the worst-case analysis of whatever online decision algorithm you were using.

What you'd need to avoid this hypothetical trap is some kind of randomized perturbation to force a new decision, or an explicit exploration/exploitation tradeoff.

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