Sharpening my knife
AC let me know that Angus Maddison has died. He’s the guy with all the historical data. Some of it, they say, he made up. But at least we were able to include Angus Maddison fixed effects in our specifications. Now, sadly, not.
I just finished the first happiness tracking cycle and they‘ve sent me my Happiness Report. There’s some unsurprising things like I’m happier on the weekends and when I’m doing stuff I want to do. The surprises:
I’m not sure how to explain that last one. Perhaps I mark middling productivity when I really want to get work done, or when some potential leisure activity is distracting me from my work. But this would suggest “focus” should have a similar relationship with happiness. I’m not sure what productivity is net of focus.
Here’s my happiness by activity:
A vast majority of the mass is in the middle groups: “home computer” and “working”. Also, most of these activities probably generate a level of happiness, but I suspect the causation works the other way on “listening to music”. This makes me think the real problem with happiness research in the context of economic analysis is not the revealed preference critique. This stuff might also get the outcomes and behaviors mixed.
Another thought: there may be a finance twist to happiness correlations. Controlling for the level, folks with more swings in utility generating behavior (call it “consumption”) will, on average, have higher marginal utility, i.e. they’ll be less happy on average. With standard arguments from finance, they would be willing to pay more for “investments” that have payoffs which are positively correlated with marginal utility like listening to music and having children.
UPDATE: Some potentially testable hypotheses (assuming happiness panel data exists): do people that have/ have more children have higher variance in happiness? Controlling for income, do people in richer societies have higher variance of happiness?
Or does it?
Angus Deaton:
Structural estimation is useful, not only for the estimates (whose credibility is often undercut by the panoply of supporting assumptions that are required to obtain them), but for understanding the empirical predictions of the theory.
Do we do this with DSGEs? We try to replicate known patterns in the data, but I don’t think we use these models to find potential new patterns.
In one of my myriad of yet-unfinished papers I report things I call “simulated comparative statics”. I can’t solve the model, so I have the computer generate numerical derivatives. People don’t like ‘em. Can I market them better? “Simulated theorems”? “Generated predictions”? “Computed hypotheses”?
I always laugh when Paul Krugman urges others to read the literature. He’s a brilliant economist, but he’s not exactly the goto guy for literature reviews…
Today he says that Sumner and Avant should read the literature on macro vs micro labor supply elasticities. Well, ok, he says they should only read half of that literature. Over the last decade, Prescott has been doing a lot of work showing that differences in taxes explain differences in employment and hours worked between Europe and the US. I think his Nobel speech was about this.
The micro people threw fits though because their estimates of the response of labor supply to tax changes is much less extreme than Prescott’s finding suggest. They basically find labor supply curves are vertical. This would mean that taxes simply can’t have an effect on labor supply.
For a while, these guys had me convinced because, in general, micro/labor types do a much better job of identification and I trust their estimates more than I trust macro estimates. More recently, however, macro people1 have been making the case that the “labor supply elasticity” estimated by the micro people is different from the “labor supply elasticity” the macro people estimate. The difference isn’t due to statistical methodology, we were just calling two different things the same thing.
Of course, its the macro elasticity that matters for tax policy, though. Prescott’s work (and not the paper that PK links to) is the place to go for understanding differences between Europe and the US. He says that difference is due to differences in tax and transfer policies.
UPDATE: AC found the PSID paper.
