Clark take-down

Standard rationalizing models, those that have agents optimizing their own material outcomes, don’t explain all economic facts, especially those dealing with the very, very long run. This has obliged many economist to augment the standard models to include other motivations or objectives of the agents.

For example, to explain the fact that in rich countries richer people tend to have fewer children (which is opposite of the case poor countries), in addition to their desire to optimize their own income you can add the desire of parents to optimize their children’s income. These parental preferences create a trade-off between the quantity and quality of children. Parents choose to have many low-quality children to work on the farm or few high-quality children they send off to college.

Professor Clark has criticized these sorts of adjustments to the standard model, saying they represent arbitrary additions. He complains: “This should make clear that the references specified over goods and children in all these models have no function other than making a bow towards the form of maximizing over preferences in economic models. They do not somehow better explain the world they are just ways of reproducing, mathematically, observed behavior.”

Personally, in the last month I’ve seen models that include preferences for “fairness”, “equality”, “efficiency” and “reciprocity”. There was a macro seminar a couple weeks ago that used “ambiguity aversion” to explain the home portfolio bias and I’ve seen models where “beliefs” and “norms” determine payoffs. In some cases, I felt these additions to the standard model were arbitrary and ill-supported, but my main issue is with model robustness. If we add one sort of psychological or sociological motivation to the model and we get non-standard results, why shouldn’t we add all such motivations? Perhaps adding more psychology to our models would change the results further, perhaps some psychological quirks cancel out other ones.

I guess I’m saying that if economic-man is unrealistic, why isn’t economic-man plus “reciprocity” (or whatever) equally unrealistic?

In any case, The Economist blogger ((who I bet has a really cool first name)) thinks adding such preferences to the standard model is moving the science forward and that Clark is wrong to object.

I think economists should become more comfortable with non-rationalizing models.

Why nations?

I agree with The Economist and Arnold Kling that the nation seems to be an arbitrary unit of measurement when considering economic outcomes.

To the extent economics is about efficiency, then we should talk about increasing efficiency for everyone. Trade is good, on balance, for everyone, foreign and domestic. Immigration is good, on balance, for everyone, natives and immigrants.

Yes, the “on balance” aspect of those statements is sticky. There will be some losers and some winners to trade and immigration, but “on balance” means that the gains of the winners outweighs the gains of the losers ((Rodrik claims many economists get mixed up here — “A pervasive such false belief, for example, is that trade necessarily benefits more people than it hurts.” — but I don’t know any of those economists.)). Economists give themselves an out by just saying the winners can compensate the losers so we don’t have to worry about the distributional issues. For example, trade with Japan puts American car manufacturers out of business, but all of the tax payers who benefit from having higher quality and cheaper Toyotas compensate the auto workers by paying for their retraining.

Economics isn’t just about efficiency, though, its about distribution too. Distribution is much harder than efficiency to get your head around. With efficiency, you either increase it or you don’t. There’s only one way to go. With distribution, on the other hand, its not obvious what the goal should be. Should we care about equality of outcomes? of opportunities? Should we care about the poorest members of society more than others? The answers to these questions aren’t obvious.

It is obvious that we shouldn’t choose answers to those questions arbitrarily. When Borjas argues against immigration, he has to arbitrarily assume natives are more important in the calculations of welfare than the immigrants. When Rodrik argues against trade, he has to arbitrarily assume the current distribution of jobs, the number of American auto workers versus Japanese ones, is more important than total welfare.

Of course distributional issues matter. Of course it matters that some people gain and some other people lose. But pointing this out does not make for a good argument against immigration (or trade). What matters is identifying those winners and loser and quantifying the degree to which the winners win and the losers lose… whether or not the winners are “us” and the losers are “them”.

So, yeah, when deciding what is right and wrong, the nation seems to be an arbitrary unit of measurement. But I can come up with two reasons why the nation is a good way to study economic phenomenon:

  • Nations have different institutions. If you want to test how institutions effect economic outcomes, nations are a pretty good starting point.
  • Nations have statistics bureaus. Basically data is collected at the national level. There’s starting to be some good micro/international data sets, but for the most part if you want to look at data across countries, its aggregated at the national level.

Gotchas aren’t biases

I’m sitting in on Matthew Rabin’s Psychology and Economics course this semester. The class is a theory course in which the standard models are tweaked to incorporate standard psychological facts about human decision making. Much of that theory is motivated by behavior economics findings of bias and “behavioral anomalies“.

I don’t really trust that those results from the laboratory necessarily translate well into our models precisely because the results are from the laboratory. That agents use certain heuristics that lead to biased behaviors in particular situations, doesn’t necessarily mean those heuristics produce bad results in general out in the wild. In other words, that people are biased when choosing their consumption of one good in a heterogeneous goods world, doesn’t mean they’re biased when choosing consumption in a model with homogeneous goods.

I think this is what Robin Hanson is getting at with this post:

As a kid I had a trick nickel from Disneyland’s magic shop – you were supposed to ask someone to look at your nickel, then push the backside to squirt them. Now we might wonder about someone who fell for this trick more than once, but surely it doesn’t make sense to call someone “biased” who fell for it once. Even if you tried the trick nickel on a hundred people, and showed that over ninety percent of them got a wet eye, you wouldn’t have shown people are biased about wet nickels.

Be sure to catch the comments section, too.

More on a theme

I noted before that Prof. Clark’s non-explanations (as The Economist put it) are a theme around here. Resident superstar blogger notsneaky comments on a previous post and I reply:

Clark has a chapter in his book called “the rise of modern man” suggesting modern (post-Malthusian) people are different than their ancestors in ways you suggest (e.g. they’re more patient, but also smarter, harder working and less violent).

For example, interest rates declined steadily over the centuries. One by one, using the usual Ramsey results on interest rates, he eliminates the possible reasons for this. Growth premium? Nope, there was no growth pre-1800. Risk premium? Nope, the King didn’t really confiscate too much and the characteristics of death statistics didn’t change much in the Malthusian era. Without stating it, the only thing left to cause steadily declining interest rates is changes in time preferences.

He then discusses rising levels of literacy, eliminating the possibility that people were responding to market pressures to increase their human capital… one by one, knock ‘em down… he shows work hours increased and violence decreased. It could only mean one thing… you know, the obvious thing… which was… well you know.

So you could counter Clark by arguing against each of these points, e.g. “yeah, maybe the King didn’t expropriate that often, but when he did it was a big deal, usually accompanied by a disembowelment or two”. Or you can take issue with the Ramsey model itself. But my biggest issue is that Clark never develops a positive theory of the “rise of modern man”, he simply tries a proof by exhaustion showing all the things that couldn’t explain the facts on demographics and interest rates.

To be fair, though, he hints, using testate records, that these deep parameters developed by selection.

To me that’s just a huge can of worms. What is being selected? Genes? Is there a temperance gene? If its genes, are there evolutionary models that select for such sophisticated behavior in just a couple of centuries? Instead were memes being selected? If so, what the hell are those?

Data 1, Theory 0

The number and severity of hurricanes has hasn’t increased over the last 100 years:

The warming theorists — most of whom, no doubt, earnestly believe that human activity has triggered nature’s wrath — have the ears of the news media. But there is another plausible explanation, supported by decades of physical observation. The spate of recent destructive hurricanes may have little or nothing to do with greenhouse gases and climate change, and everything to do with the Atlantic Ocean’s currents.

UC Davis Econ in the News

(… of the blog coverage variety …)

Will Wilkinson writes about Prof. Clark‘s good book:

This a profoundly insightful work sure to raise ire and inspire further progress. Key claim: labor quality is the difference between rich and poor. Depressing claim: Sub-Saharan Africa has largely Malthusian conditions, so success in increasing health and life-spans has decreased the average material standard of living below hunter-gatherer levels. Biggest disappointment: seems evasive on the question of the cause of variations in labor quality. Why not culture?

I should be careful critiquing Prof. Clark’s work, he’s grading my Growth Field exam next week, but I have similar questions about his work.

The professor does a great job of carving out the negative space of whatever topic he’s writing about. In his papers, he tells his readers what can’t explain the phenomenon. He leaves us hanging, though, on what can explain it.

For example, take cotton mills in the 19th century. Many of the countries to develop early, did so via the textile industry. So the mills are important for understanding why some countries are rich today and some aren’t. Why was productivity in Indian cotton mills so much lower than in England in the 19th century (jstor link)? Clark demonstrates it wasn’t because of differences in schooling or the skill of managers or differences in technology or anything else you can think of. What caused the productivity differences then?

Dunno and Clark doesn’t provide the answer either. He does defend himself, though:

These lessons from the mills will undoubtedly seem to some as merely destructive of conventional wisdom on underdevelopment without suggesting any replacement. Nevertheless, identifying the effects of the local environment or culture on the labor force as the source of the poor performance of textile mills in low-wage countries is a significant advance in understanding development. For if we can isolate one factor as supremely important, no matter how poorly we comprehend that factor at present, we are in a much better position to direct future research on economic growth.

Cargo Cults

The easiest way to explain this idea is to contrast it, for example, with advertising. Last night I heard that Wesson oil doesn’t soak through food. Well, that’s true. It’s not dishonest;
but the thing I’m talking about is not just a matter of not being dishonest, it’s a matter of scientific integrity, which is another level. The fact that should be added to that advertising statement
is that no oils soak through food, if operated at a certain temperature. If operated at another temperature, they all will– including Wesson oil. So it’s the implication which has been conveyed, not the fact, which is true, and the difference is what we have to deal with.

…this type of integrity, this kind of care not to fool yourself, that is missing to a large extent in much of the research in cargo cult science…

The first principle is that you must not fool yourself–and you are the easiest person to fool. So you have to be very careful about that. After you’ve not fooled yourself, it’s easy not to fool other
scientists. You just have to be honest in a conventional way after that…

One example of the principle is this: If you’ve made up your mind to test a theory, or you want to explain some idea, you should always decide to publish it whichever way it comes out. If we only
publish results of a certain kind, we can make the argument look good. We must publish both kinds of results.

Richard Feynman (h/t swong… get a blog dude!)

Deidre McCloskey famously charged that Economics was a Cargo Cult science (pdf). Here’s Davis Prof Kevin Hoover debunking some of her claims (pdf).

Data mining: tonal languages and genes edition

Bob Ladd and Dan Dediu found a correlation between geographical dispersion of certain genes and geographical dispersion of tonal languages.

There’s a great discussion of their method at Language Log and Mr. Ladd responds.

The bottom line is Bob and Dan found a correlation not causation (like the headlines are suggesting) and correlation can be spurious. As Bob says in his follow-up, data mining is good for “hypothesis-generating rather than hypothesis-testing.” Their next step is to go into the lab and do experiments.

I wish we had that option in Economics (or I wished we used that option more often).