This article briefly discusses several recent papers from various journals of the AEA which I like.
I am not a proponent of the journal structure of economic research, but in response to an assignment for a microeconomic policy analysis class in which I am enrolled I googled “best economics journals.” This Mankiw blog article, A New Ranking of Economic Journals, was the first result. Knowing Mankiw to be a solid economist, I read the article he referenced, which I will directly link to here.
Then I disregarded the paper and went to the American Economic Association website, which is here. Don’t feel like I’ve wasted your time, however, as the new ranking of journals was very good. It was definitely worth mentioning. AEA has several journals including well known macro and micro specialty journals and the very well known American Economic Review. Here are several articles I ran into around there site of which I am a fan, and I will summarize why after each bullet:
- This is an awesome article that uses both experimental data and a structural model to demonstrate that teacher attendance improves when it is tied to pay, which in turn caused an increase in student test scores. Education is important in economics and in policy, so this is kind of a big deal.
- This article uses a structural model for herd behavior in financial markets. This is like mania buying and panic selling. They demonstrate that in their sample, NYSE data from 1995, “the proportion of herd buyers is 2 percent; that of herd sellers is 4 percent.”
Coenen, Günter, Christopher J. Erceg, Charles Freedman, Davide Furceri, Michael Kumhof, René Lalonde, Douglas Laxton, Jesper Lindé, Annabelle Mourougane, Dirk Muir, Susanna Mursula, Carlos de Resende, John Roberts, Werner Roeger, Stephen Snudden, Mathias Trabandt, and Jan in’t Veld. 2012. “Effects of Fiscal Stimulus in Structural Models.” American Economic Journal: Macroeconomics, 4(1): 22-68.
- This article is great because it allows readers to quickly familiarize themselves with 7 mainstream structural macro models, called DGSE models. Otherwise I can’t really stand the article because it blathers on about how stimulus is a good idea without giving enough attention, in my view, to the negative implications of where the stimulus money comes from (be that taxes, printing or whatever) and weighing those negative effects against the ostensible positive effects which they selectively uncover.
- This article is a great article evidencing what many financial investors have known for a long time:
- The short-run is pretty unpredictable from theory.
- The short run is mostly driven by news.
- (Cont’d) The article shows that structural VARs, “cannot be used to identify news and noise shocks, but identification is possible via a method of moments or maximum likelihood.” A VAR is a vector autoregression, which is a certain kind of statistical regression often used for econometric regression over time. The fact that VARs cannot be used to identify these things means they are fairly unpredictable. They show that identification of these shocks is possible using another, non-VAR model, which is very interesting and well worth the read if you can understand it – but if you can’t understand it, the usual “trade the news” idea works pretty well. I would call unexpected news an ‘information shock.’ They take a slightly different (but better? Idk.) approach by talking about ‘noise shocks,’ which are similar, but not quite the same.
- This article uses experimental data to demonstrate that money fosters cooperation/coordination in groups of strangers. Ironically, they refer to the money they use as, “intrinsically worthless tokens,” but I think their own work very much proves that money as a system, including these tokens, endow the utilizing system with an intrinsic, objective benefit and therefore intrinsic, objective value.
- This article argues for ways to elicit minimally biased expert information when other data is hard to come by.
- This article demonstrates that people tend to overestimate the accuracy of their own information.