Tag Archives: economics job market

If top people have families and hobbies, then success is not about productivity


1 Productivity is continuous and weakly increasing in talent and effort.

2 The sum of efforts allocated to all activities is bounded, and this bound is similar across people.

3 Families and hobbies take some effort, thus less is left for work. (For this assumption to hold, it may be necessary to focus on families with children in which the partner is working in a different field. Otherwise, a stay-at-home partner may take care of the cooking and cleaning, freeing up time for the working spouse to allocate to work. A partner in the same field of work may provide a collaboration synergy. In both cases, the productivity of the top person in question may increase.)

4 The talent distribution is similar for people with and without families or hobbies. This assumption would be violated if for example talented people are much better at finding a partner and starting a family.

Under these assumptions, reasonably rational people would be more productive without families or hobbies. If success is mostly determined by productivity, then people without families should be more successful on average. In other words, most top people in any endeavour would not have families or hobbies that take time away from work.

In short, if responsibilities and distractions cause lower productivity, and productivity causes success, then success is negatively correlated with such distractions. Therefore, if successful people have families with a similar or greater frequency as the general population, then success is not driven by productivity.

One counterargument is that people first become successful and then start families. In order for this to explain the similar fractions of singles among top and bottom achievers, the rate of family formation after success must be much greater than among the unsuccessful, because catching up from a late start requires a higher rate of increase.

Another explanation is irrationality of a specific form – one which reduces the productivity of high effort significantly below that of medium effort. Then single people with lots of time for work would produce less through their high effort than those with families and hobbies via their medium effort. Productivity per hour naturally falls with increasing hours, but the issue here is total output (the hours times the per-hour productivity). An extra work hour has to contribute negatively to success to explain the lack of family-success correlation. One mechanism for a negative effect of hours on output is burnout of workaholics. For this explanation, people have to be irrational enough to keep working even when their total output falls as a result.

If the above explanations seem unlikely but the assumptions reasonable in a given field of human endeavour, then reaching the top and staying there is mostly not about productivity (talent and effort) in this field. For example, in academic research.

A related empirical test of whether success in a given field is caused by productivity is to check whether people from countries or groups that score highly on corruption indices disproportionately succeed in this field. Either conditional on entering the field or unconditionally. In academia, in fields where convincing others is more important than the objective correctness of one’s results, people from more nepotist cultures should have an advantage. The same applies to journals – the general interest ones care relatively more about a good story, the field journals more about correctness. Do people from more corrupt countries publish relatively more in general interest journals, given their total publications? Of course, conditional on their observable characteristics like the current country of employment.

Another related test for meritocracy in academia or the R&D industry is whether coauthored publications and patents are divided by the number of coauthors in their influence on salaries and promotions. If there is an established ranking of institutions or job titles, then do those at higher ranks have more quality-weighted coauthor-divided articles and patents? The quality-weighting is the difficult part, because usually there is no independent measure of quality (unaffected by the dependent variable, be it promotions, salary, publication venue).

Star job candidates benefit from appearing to be worse

Employers have a cost of making a job offer: filling out forms, getting approval, not being able to make other offers simultaneously in case too many job candidates accept, etc. A company who believes that it is not the top choice of candidates would want to avoid making an offer to a star applicant (one who is likely to receive better alternative offers from top employers, thus turn down the lower-ranked company’s offer).

If the star job-seeker is uncertain about the offers she or he will get, or wants a bargaining chip to use with the most preferred company, then (s)he prefers to obtain the lower-ranked employer’s offer, even when planning to reject it. A way to entice the company into offering a job is to pretend to be more attainable (have a worse outside option) by faking lower talent and potential when interviewing with lower-ranked employers. For this pretence to be (partly) credible, it must have a cost for the job-seeker, otherwise all the best candidates would pretend to be worse and increase their chance of obtaining offers from their backup employers. Then the next-best candidates would have to fake being less good to receive jobs, etc. This race to the bottom would only end once all candidates look like the worst possible, which does not seem realistic.

One potential cost is that faking lower talent has a random outcome, which may be so bad that the employer does not want to offer a job at all. This would temper the incentive to appear worse. Another cost is information leakage – if bad performance at a less desirable interview becomes known to higher-ranked employers, then the candidate may forfeit her or his most preferred interviews and jobs. It could also be that the top job-seekers cannot hide their quality, for example because their genius shines out despite their best effort, or employers base offers solely on recommendation letters, which the candidate cannot see or affect around the time of applying.

Empirical project ideas with econjobmarket and AEAweb JOE

The websites econjobmarket.org and AEAweb JOE are centralized job finding sites for economics PhDs. These have databases of application materials of thousands of job candidates, and the interviews many of them got. The subsequent jobs and publications of the job candidates are listed on the web. There are many empirical projects that can be done with this data, for example how certain keywords in recommendation letters predict the job that a candidate gets, or how the CV at the time of job application predicts future performance. One comparison that has been done in the sciences (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2572075/) is how recommendations of male and female candidates differ, i.e. what words are frequently used for one gender that are not used for the other. It is likely that economics recommendation letters contain similar biases.
The professors of top universities who have access to the databases of the job market websites have an advantage in hiring. They can predict which candidates perform well in the future and offer jobs to those. The employers without access to the databases are left with less promising candidates.

Claims that the economics job market is tough this year

It seems that every year since I started grad school, I hear someone say that the economics job market is tough (for candidates) that year. Usually it is in connection with some graduate student on the market getting a less good job than one anticipated. But the toughness of the market is a relative measure, so relative to what year is this year tough? Relative to 1950? After the Second World War, the US expanded its university sector with the GI Bill, which created a large demand for new faculty members. This made the market easy for candidates and as the effect gradually faded, the market got tougher. This is probably not what people have in mind when they claim a tough market.
As computing power becomes cheaper, the demand for people who are substitutes of computers (theorists) falls and the demand for complements of computers (empirical and computational researchers) rises. So the theory market may get tougher for candidates over time, but the empirical market should get easier.
There are other long term trends, like the fraction of the population getting a university degree increasing, but at a decreasing rate. If the university sector expands to cater to the increased demand, the market should get easier for candidates. But this also depends on the expectations of the universities. Hiring responds to anticipated future enrollment, not just the current number of students.  So if demand for university education rises less than expected (it does not have to fall), the demand for new faculty members falls.
Lengthening lifespans mean older faculty members free up fewer spots in universities, which reduces demand for new faculty members, but this effect is tiny, because lifespans lengthen very slowly.
A short term effect on hiring was the financial crisis, which reduced university hiring budgets. This made 2009 a tough year for candidates relative to the surrounding years.
A study on how tough the market really is would be interesting, but hard to do, because it requires a measure of the quality of candidates that is independent of the jobs they get or papers they publish. Both jobs and papers are subject to a congestion effect, so the toughness of the job market or publication market affects these measures. The definition of toughness is that the tougher the market, the worse the results for a graduating student of a given quality.
The market for economists is worldwide, so it would be easier to study academics in some field that is country-specific and thus has barriers to trade, say law.

Claims that placement officers do a great job

Those on the economics job market have probably heard statements in their department like “our placement officers do a great job” and “we place our students very well”. First, no university would say they place students badly, because then students would not apply there. Second, faculty members don’t want to be in committees, including placement, so if one faculty member said that another does a bad job in placement, then the immediate response would be: “You do it then, and do better.” Anticipating this, no faculty member will criticize another’s committee work quality.
Hence, an empirical project idea: how does the placement outcome (e.g. rank of institution making job offer) depend on student quality (e.g. papers published before graduating) and the placement committee and university fixed effects? The measures of quality and outcome are of course noisy, but the sample size (people on the job market) is fairly large.