Subscribe... the problems of economics and of social science in general are part of a broader methodological problem that afflicts many fields: how to deal with complex systems.Is there ANY rational way to [evaluate a proposed policy] without "just going with your gut" or "going with the way you were raised"?
It is in a way unfortunate that for many of us the image of a successful field of scientific endeavor is basic physics. The objective of the most basic physics is a complete description of what happens. In principle and apparently in practice, quantum mechanics gives a complete account of what goes on inside, say, a hydrogen atom. But most things we want to analyze, even in physical science, cannot be dealt with at that level of completeness. The only exact model of the global weather system is that system itself. Any model of that system is therefore to some degree a falsification: it leaves out some (many) aspects of reality.
How, then, does the meteorological researcher decide what to put into his model? And how does he decide whether his model is a good one? The answer to the first question is that the choice of model represents a mixture of judgement and compromise. The model must be something you know how to make -- that is, you are constrained by your modeling techniques. And the model must be something you can construct given your resources -- time, money, and patience are not unlimited. There may be a wide variety of models possible given those constraints; which one or ones you choose actually to build depends on educated guessing.
And how do you know that the model is good? It will never be right in the way that quantum electrodynamics is right. At a certain point you may be good enough at predicting that your results can be put to repeated practical use, like the giant weather-forecasting models that run on today's supercomputers; in that case predictive success can be measured in terms of dollars and cents, and the improvement of models becomes a quantifiable matter. In the early stages of a complex science, however, the criterion for a good model is more subjective: it is a good model if it succeeds in explaining or rationalizing some of what you see in the world in a way that you might not have expected.
Notice that I have not specified exactly what I mean by a model. You may think that I must mean a mathematical model, perhaps a computer simulation. And indeed that's mostly what we have to work with in economics. But a model can equally well be a physical one, and I'd like to describe briefly an example from the pre-computer era of meteorological research: Fultz's dish-pan....
The only thing I do remember is a conversation over dinner with an adviser to the new [Mitterand] government, who explained its plan to stimulate the economy with public spending while raising wages and maintaining a strong franc.
To the Americans present this program sounded a bit, well, inconsistent. Wouldn't it, we asked him, be a recipe for a balance of payments crisis (which duly materialized a few months later)? "That's the trouble with you Anglo-Saxon economists--you're too wrapped up in your theories. You need to adopt a historical point of view." Some of us did, in fact, know a little history. Wasn't the plan eerily reminiscent of the failed program of Leon Blum's 1936 government? "Oh no, what we are doing is completely unprecedented."
I'm assuming that all participants want general economic prosperity, meaning they would like -- say -- all people (or as many people as possible) to have enough money to afford, clothes, shelter, food, etc. beyond the bare subsistence level. In other words: no more poverty or greatly reduced poverty. To keep things relatively simple, lets say I'm talking on the country level, not on the planet level.Both productivity growth (productivity = output per worker) and inequality are important.
... Some of these people seem SURE that the way to do this is to spread the wealth; others seem SURE that the best way to do this is to feed the top and watch the wealth trickle down.
In classical models, economic growth depends chiefly on the rate at which nations accumulate productive resources, a factor that traces to aggregate savings rates. In this context, distributional considerations matter for growth only if households’ propensity to save varies systematically with wealth. If the rich save at a high rate, a view closely associated with prominent economist Nicholas Kaldor, unequal societies can actually build up their productive infrastructure faster than equal ones, achieving higher growth rates.As usual with tradeoffs, the question becomes, what level of redistribution will reduce poverty to an acceptable level, while not reducing productivity growth unacceptably? It depends on what you consider to be "acceptable", which is a political rather than economic criterion. Economists can help by calculating the likely effects of a particular level of redistribution, but the actual decision is political, rather than economic.
Inequality could also foster growth because new industries typically require large initial investments. If credit markets function poorly, a society’s savings may not be efficiently transferred to investments. In this environment, a high concentration of wealth may allow some investors to overcome these impediments and stimulate growth by bringing capital-intensive industries into being.
In the early work, income or wealth redistribution policies are overwhelmingly viewed as detrimental to growth based on at least two arguments. First, redistribution via such instruments as progressive taxation distorts incentives to save, which reduces resource accumulation. Second, some variation in economic rewards helps provide incentives to invest and work.
The classical view long dominated economic thought and emphasized that policies designed to reduce inequality would entail adverse consequences for economic growth.
posted by Rock Steady at 7:41 AM on May 31, 2008