Yes yes, I could have written this earlier, but I didn’t want to, uh, overshadow Columbus Day? (Technically Columbus Day was yesterday, since the first time one of Columbus’ crew members saw land was on October 12, 1492.) Actually, I haven’t been feeling well, but I didn’t want to leave you hanging forever, so…
The Nobel Prize in Economics* was awarded on Monday to Peter Diamond, Dale Mortensen and Christopher Pissarides for their work on search in labor markets and its effect on unemployment. You can read all about it here.
* Fine, the “Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel.” I get it- the economics prize wasn’t one of the original Nobel prizes. The original prizes started in 1901 with physics, chemistry, physiology or medicine, literature and peace, and economics was added in 1968. Contrary to what I read on the Internet every year around this time, this distinction has no bearing on whether economics is in fact a science, since last time I checked literature and peace weren’t exactly in the science category.
Given that the above article was pretty comprehensive, I’ll just add in/repeat some fun facts:
- It’s important to remember that the Nobel Prize (at least in economics) is more like a lifetime achievement award than anything else. I point this out because it doesn’t exactly seem groundbreaking today to point out that the worker/employer match is more complicated than “hey, that dude’s not working, get him over here to help us out,” but it was kind of a big deal when these guys started talking about it back in the 1970’s.
- One of the winners had my old teaching job. Via Greg Mankiw:
I took Ec 10 during my freshman year, 1979-1980. It may not be obvious from his profile, but today’s Nobel Prize winner Chris Pissarides taught my Ec 10 section that year during his one-year visit to Harvard. So tell your current students that the section leader they are struggling to understand through accented English may someday be a Nobel prize winner.
So this means that I’m going to win a Nobel Prize, right? (Answer: No, at least not unless I get better at statistics than the previous statement would suggest.) I recall reading that Barney Frank taught undergraduates when he was at Harvard working on his Ph.D. in Government, and now I can’t decide which of these guys would make for a better story.
- None of these guys were front runners in any of the Nobel betting pools that I am aware of. (Yes, such things exist, and they are like a nerdy version of fantasy football or something.) For example, the lead horse on betting site iPredict was Richard Thaler, followed by Robert Shiller and Marty Weitzman, and Diamond, Mortensen and Pissarides were relegated to the “other” category. (You can see more details on the betting pools here. There was in fact an “other” category on iPredict that gave odds somewhere in the 30% range, but it’s not mentioned in that article for some reason.) I suppose this is just another example of the fact that economists are bad at making predictions. *rim shot*
- Peter Diamond has yet to be confirmed to the Federal Reserve Board due to what Senate Republicans refer to as lack of experience in dissecting the inner workings of the nation’s economy. I would like to a. point out that Peter Diamond was Ben Bernanke’s advisor at MIT, and b. hope that, regardless of your political leanings, you find that the combination of point a and the Nobel Prize make the inexperience claim a little hilarious.
- The Simpsons gave me a nice little gift in its season premiere, since the show opens with Lisa and her fiend on the couch waiting for the announcement of the Nobel Prize in Economics:
See, the writers didn’t get it right either. I will, however, give credit where credit is due and point out that not only are the names on the ballot real, they are people who are fairly reasonable choices to actually win the prize. (Jagdish Bhagwati is a professor at Columbia, Bengt Holmstrom is at MIT, Avinash Dixit is at Princeton, and has been referred to as “India’s Future Nobel Winner,” and Elhanan Helpman is at Harvard. Now you know.)
In order to better understand what these guys did that made then all nerd-famous and whatnot, we need to start with a brief review of the types of unemployment. You may or may not recall that there are three types of unemployment:
- Frictional unemployment: the unemployment that happens simply because it takes a worker some time to find a new job after he gets laid off. In a perfect world, firms looking to hire would be circling the airspaces of the firms laying people off like hungry buzzards, but instead workers have to go and actively seek companies out after they finish licking their wounds from having gotten laid off. (Some of you may remember that this process was even more fun in pre-Internet days.)
- Structural unemployment: the unemployment that happens because there is a mismatch between the skills of unemployed workers and the needs of the economy. For example, the makers of horse-drawn carriages likely suffered a decent amount of structural unemployment once Henry Ford started producing cars. Structural unemployment is a bit of a sticky situation from a social and political perspective because people often feel entitled to the jobs that they are trained for, especially if that training was difficult or expensive. While economists would argue that it’s efficient for the surplus lawyers of the world to go and learn how to work at Starbucks instead, it’s a little difficult to put that principle into practice. (It’s also difficult to tell a worker who has done the same job for 40 years and is near retirement to just go learn to do something else.)
- Cyclical unemployment: the unemployment that happens simply because the economy is in the toilet at a particular point in time.
It follows from the definitions above that frictional and structural employment explain why we can see both job openings at companies and lots of unemployed people- it’s not necessarily that the unemployed people are lazy, since it’s entirely possible that the unemployed people either haven’t found the companies yet or they aren’t qualified for the jobs that the companies want filled.
What does this all have to do with our esteemed Nobel Prize winners? What they (henceforth referred to as DMP in my world) have done is flesh out a model of search in matching markets that is directly applicable to unemployment and labor markets and allows for the different types of scenarios described above. They also use these models to show the likely effects of different forms of unemployment policy and employer regulation. In other words, even though the supply and demand diagrams in your econ 101 textbooks can’t explain how there can be both too many and too few workers, DMP can, and now they have a nice shiny prize to show for it.