Solely out of curiosity, I have been collecting data on the characteristics of economics job market “stars” over the past few years. In order to receive a tenure-track offer, an economist must first be “flown out” to a university to give a talk presenting their best research. I define a star using an somewhat arbitrary cutoff based on flyouts reported publicly online – roughly, the minimum cutoff would be a candidate who is flown out to, e.g., Chicago Booth, UCLA, Cornell and Toronto. 95%+ of the job candidates from prior years above that cutoff have been hired into what I would consider a highly prestigious job, and hence are in a good place to influence the direction of the profession in the years to come.
It is widely recognized that the topics and methodologies of interest to young economists are a leading indicator of where economics might be heading. Overall, as Hamermesh pointed out in a JEL article last year, there has been an enormous shift over the past couple decades towards empirical work, particularly work where the parameters of interest are either simple treatment effects from observational or experimental data; this work is often called “reduced-form”, though that term traditionally had a very different meaning.
This trend does not hold among the top candidates this year. I find 42 candidates, from 21 universities including 6 outside the United States (LSE, CEMFI, EUI, Toulouse, Sciences Po, UCL) above the “star” cutoff; this list omits junior candidates coming off extended (> 2 year) post-docs. I generally use self-reported field in the table below.
Job Market Stars by Field
Macro 8
Labor 6
Micro theory 5
IO 4
Econometrics 4
Applied Micro 4
Intl./Trade 3
Finance 3
Public 2
Development 1
History 1
Political Economy 1
In the following tables, I split papers up into pure theory and empirics, and then split the empirical papers into structural models (where the estimates of interest are parameters in a choice and/or equilibrium-based economic model), “light theory” (where the main estimates are treatment effects whose interest is derived from a light model), and pure treatment effect estimation (where the work is purely experimental, either in the lab or the field, or a reduced form estimate of some economic parameter).
Theory versus Empirics
Pure Theory 11
Empirical 31
of which
Structural 25
“Light theory” 4
Experimental/Reduced-form 2
Data Source if Empirical
Custom Data 11
Public Data 20
Finally, there seems to be a widespread belief that publications are necessary in order to be a top job market candidate. In the table below, “Top 5” means AER, Econometrica, ReStud, QJE or JPE, and R&R denotes a publicly divulged Revise & Resubmit. I include AER Papers & Proceedings as a publication, but omit all non-peer reviewed publications such as Fed or think tank journal articles. Categories refer to the “best” publication should a candidate have more than one.
Publication History Among Stars
No Pubs or R&Rs 20
Sole-authored top five 1
Coauthored top five 4
Sole-authored top five R&R 1
Coauthored top five R&R 6
Sole-authored other pub 2
Coauthored other pub 5
Sole-authored other R&R 3
What is the takeaway here? I see three major ones. First, the market is fairly efficient: students from many schools beyond the Harvards and MITs of the world are able to get looks from top departments. Second, publications are nice but far from necessary: less than 20% of the stars even have a sole-authored revise & resubmit, let alone an AER on their CV.
Third, and most importantly, theory is far from dead; indeed, purely applied economics appears to be the method going out of favor! Of the 42 star job market papers, 11 are pure theory, and 25 estimate structural models; in many of those papers, the theoretical mechanisms identified clearly trump the data work. Only 6 of the 42 could by any stretch be identified as reduced form or experimental economics, and of those 6, 4 nonetheless include a non-trivial economic model to guide the empirical estimation. Given Hamermesh’s data, this is a major change (and indeed, it seems quite striking even compared with the market five years ago!).
A Fine Theorem 
do you have anything against publishing your data with names and everything? Thanks. Hope the market is treating you well.
Andrea – I don’t want to make the data public because I am always worried about unintentionally harming some student on the market (by, e.g., miscoding their field). I will email you the raw data when I get home from the office later tonight, though.
I can’t complain about the market thus far personally, but of course, it is always stressful until an offer is in hand and accepted (and this is particularly true given the somewhat idiosyncratic nature of my research interests).
Very interesting. Any chance that you could list the 21 universities from which the ‘stars’ are graduating? Personally, I am surprised (pleasantly) that the number of universities is that high.
In my data, I have people from MIT, Harvard (econ and HBS), Stanford, Chicago (econ and finance), Yale, Northwestern, Princeton, Penn, NYU, Columbia, Michigan, Berkeley, UCLA, Wisconsin, Minnesota, UCL, LSE, Toulouse, Sciences Po, EUI and CEMFI.
In the data going back to 2010, I would add Bonn, UPF, Toronto, UBC, Oslo, IIES, UCSD, Iowa, Penn State, Caltech, Duke, Brown, Boston U (among others) as programs placing at least one candidate into a very top job. I agree it’s fairly surprising!
Do this for below top 30 departments, I very much doubt your efficiency claim once you get out of this league.
Agree that it’s harder when it comes to median candidates; that said, look at the list above. The market was able to find great candidates this year at places outside the traditional elite PhD programs – witness CEMFI and EUI.
I appreciate the analysis, but do keep in mind that most PhD students even at top programs aren’t stars and aren’t competing for tenure-track jobs at the most prestigious departments. I don’t have the data, but I hypothesize that the share of pure / “light” theory JMPs of flyouts among the top 100 or so research universities doing more field-specific searches is lower than the top programs (which advertise open field searches), and I also expect that this share has declined over time. I don’t dispute the conclusions in this post, but I just want to suggest that most PhD students considering JMPs without empirical methods should not find false comfort in this data.
Agree completely. Certainly this data should be taken as data, rather than advice. But I do think the year-over-year changes are at least suggestive of the direction the field may be heading, since the stars in any cohort are generally doing the PhD teaching in future cohorts.
I am curious as to how many of the pure theory stars are doing macro.
Overall, I agree with the general pattern but am worried that a lot of people you classify as “Structural” are folks who primarily do reduced form work, and then overlay a structural model. i.e. there is a difference between a standard structural approach and the newly popular method where a structural model is often introduced once the reduced form estimates are presented. So its not so much a move away from reduced form work, those are still considered essential, its just that more structure is being overlaid once reduced form estimates have been presented.
It is a good question – I classified a job market paper as structural if the primary estimates of interest were the parameters of an economic model. This doesn’t necessarily mean that some clever new estimation technique is used, but it does require a formal attempt to explain the reduced form estimates and a formal attempt at extracting external validity; I think any trend, no matter how small, in that direction is a great thing for the profession.
Do people get job offers because their job market paper is important or because their paper demonstrates that they are smart?
Pure theory and structural estimation are more mathematically difficult, so they will very effectively signal that the candidate is quite smart. People have to excel at a very difficult task to set themselves apart from the hundreds of other candidates. When you look at the stars of the job market, it doesn’t surprise me that you would see a lot of pure theory, because that’s the type of work you have to do to demonstrate that you’re brilliant. Otherwise, perhaps you just stumbled into a lucky idea that happens to be interesting.
For example, if my field were health, I’d be more likely to do a job market paper that involved structural estimates than one that was reduced form, as the structural estimate does a better job of signaling that I’ve learned something.
Concretely, one of the best placements out of my institution was purest theory. While the person’t ability to do that work earns my respect, it doesn’t mean that I think that it is an important contribution.
In contrast, theorists sometimes joke, “How hard is it to press enter in Stata?” Perhaps they will make that joke in the metaphorical unemployment line.
To me this makes your results less convincing. Thanks for posting them anyway, and I’d love to read your thoughts.
Nice analysis. The switch to structural estimation is quite evident. I wonder if this has changed now as the demand for applied economists seems to have increased. Have you repeated this exercise for the recent years?