Category: Publishing

Where do men and women economists publish?

Posted on by tatyana

We all know that economics is a male-dominated discipline on average. But how does the representation of women look across different journals? Armed with Academic Sequitur* article metadata (going back to around 2000), I determined the genders of 82% of all authors in the data and calculated the prevalence of male authors by journal for 50 top-ranked journals in economics.** To see how things have changed over time, I also repeated this exercise with articles that were published in 2018-2019.

Just to set some expectations: in the gender-matched dataset, 82% of author-article observations are male (80% when restricted to 2018-2019). So if a journal has, say, 75% male authors, it’s doing better than average. With that, here are the top 10 male-dominated journals, ranked by share of male authors over the entire data period.*** To be super-duper scientific, 95 percent confidence intervals are also shown, and I added a vertical line at 82.1% for easy benchmarking to the average.

So three of the top five journals (Econometrica, QJE, and ReStud) have also been the three most male-dominated journals, at least historically, with 90%, 89%, and 88% male authors, respectively. A fourth (Journal of Political Economy) also barely made the top ten, with 87% male authors. These numbers also illustrate that there’s not much difference between the #1 and #10 male-dominated journal.

Encouragingly, there are some improvements as well. The share of male authors in QJE was almost 9 percentage points lower in 2018-2019 compared to the whole sample period. JPE‘s share decreased by 7 percentage points, putting these journals in the top 5 most improved. If ranked based on 2018-2019 shares, Econometrica would be #6, ReStud would be #11, QJE would be #24, and JPE would be #28, just barely in the bottom half.

The Journal of Finance, by contrast, has taken a small but statistically significant step backwards, with a 3 percentage point increase in the share of male authors. If ranked by the 2018-2019 male ratio, it would be number 1.

Here are the least male-dominated journals (rank 41-50). Economics of Education Review and JHR are both about 66% male. Surprisingly, both applied AEJs are in the least male-dominated group (AEJ: Applied is 71% male; AEJ: Policy is 74%). This may be because they are newer, though it is worth noting that their overall average is below the 2018-2019 average of 80%.

Here’s the rest of the pack. First, here are journals ranked 31-40 on the male-dominated scale (i.e., next 10 least male-dominated), ordered by share male in the overall sample. AER and ReStat are in this group, with 80% and 81% male, respectively. Thus, AER has historically been an outlier among the top five on this dimension (using 2018-2019 shares, it would rank #19, right in the middle of the other top five journals).

Here’s rank 21-30, all in the low-to-mid 80’s.

And here’s rank 11-20. AER: Insights is 84% male. The other two AEJs are in this group, with males representing about 85% of all author-article observations.

These patterns do not necessarily reflect discrimination: the representation of women in a particular field will obviously make a difference here (as evidenced by the positions of macro and theory journals). I leave it up to you, the reader, to interpret the numbers.****

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* Academic Sequitur is a tool I developed to help researchers keep up with new literature. You tell us what you want to follow, we send you weekly (or daily!) emails with article abstracts matching your criteria.

** Close to 1.5 percent of the initial observations are dropped because only the initials of the author are available. About 16.5 percent of the observations cannot be mapped to a name for which the gender is known. This includes a lot of Chinese names, for which it is very difficult to determine gender, according to my brief internet research. Names which can be both male and female are assigned a gender based on the relative probability of the name being male.

*** Each observation in the sample is an article-author, so those who publish in a journal multiple times will contribute relatively more to its average. Each coefficient is from a journal-specific regression. Confidence intervals are based on heteroskedasticity-robust standard errors.

**** If you want the numbers underlying these graphs, you can download the csv file here.

What publishes in top-5 economics journals?

Posted on by tatyana

Part I: agricultural economics, lab experiments, field experiments & economics of education

Most of us have a sense that it is more difficult to get certain topics published in the top 5 economics journals (American Economic Review, Econometrica, Journal of Political Economy, Quarterly Journal of Economics, and Review of Economic Studies), but there is not much hard data on this. And if a particular topic appears infrequently in top journals, it may simply be because it’s a relatively rare topic overall.

To get more evidence on this issue, I used Academic Sequitur data, which covers the majority of widely-read journals in economics. The dataset I used contains articles from 139 economics journals and spans the years 2000-2019. On average, 6 percent of the papers in the dataset were published in a top 5 journal.

I classified papers into topics based on the presence of certain keywords in the abstract and title.* I chose the keywords carefully, aiming to both minimize the share of irrelevant articles and to minimize the omission of relevant ones. While there is certainly some measurement error, it should not bias the results. (Though readers should think of this as a “fun-level” analysis rather than a “rigorously peer-reviewed” analysis.)

I chose topics based on suggestions in response to an earlier Tweet of mine. To keep things manageable, I’m going to focus on a few topics at a time. To start off, I looked at agricultural economics (5.3% of articles in the dataset), field experiments (1.0% of articles), lab experiments (1.9% of articles), and education (1.8% of articles). I chose these to have some topic diversity and also because these topics were relatively easy to identify.** I then ran a simple OLS regression of a “top 5” indicator on each topic indicator (separately).***

The results are plotted in a graph below. Field experiments are much more likely to publish in a top 5 journal than in the other 134 journals (about 5 percentage points more likely!), while lab experiments are much less likely. Education doesn’t seem to be favored one way or the other, while agriculture is penalized about as much as field experiments are rewarded. Moral of the story: if you want to publish an ag paper in a top 5, make it a field experiment!

Now you might be saying, “I can’t even name 139 economics journals, so maybe this isn’t the relevant sample on which to run this regression.” Fair point (though see here for a way way longer list of econ journals). To address this, I restricted the set of journals to the 20 best-known general-interest journals—including the top 5—and re-generated the results.**** With the exception of lab experiments, the picture now looks quite different: both field experiments and education research are penalized by the top 5 journals, but agriculture is not.

Combining the two sets of results together, we can conclude that the top 5 penalize agricultural economics research but so do the other good general-interest journals. The top 5 journals also penalize field experiments relative to other good general-interest journals, but top general-interest journals as a whole rewards field experiments relative to other journals. Finally, top 5 journals penalize education relative to other good general-interest journals, but not relative to the field as a whole.

The second set of results is obviously sensitive to the set of journals considered. If I were to add field journals like the American Journal of Agricultural Economics, things would again look much worse for ag. And how much worse they look for a particular topic depends on how many articles the field journal publishes. So I prefer the most inclusive set of journals, but I welcome suggestions about which set of journals to use in future analyses! Would also love to hear everyone’s thoughts on this exercise in general, so please leave a comment.

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Endnotes

*I did not use JEL codes because many journals do not require or publish these and we therefore do not collect them. JEL codes are also easier to select strategically than the words in the title and abstract.

** An article falls into the category of agricultural economics if it contains any of the following words/phrases in the abstract or title (not case-sensitive, partial word matches count): “farm”, “crop insurance”, “crop yield”, “cash crop”, “crop production”, “crops production”, “meat processing”, “dairy processing”, “grain market”, “crop management”, “agribusiness”, “beef”, “poultry”, “hog price”, “cattle industry”, “rice cultivation”, “wheat cultivation”, “grain cultivation”, “grain yield”, “crop diversity”, “soil conditions”, “dairy sector”, “hectare”, “sugar mill”, “corn seed”, “soybean seed”, “maize production”, “soil quality” “agricultural chemical use”, “forest”. Field experiment: “field experiment”, “experiment in the field”. Lab experiment: “lab experiment”, “laboratory experiment”, “experimental data”, “randomized subject”, “online experiment”. Education: “return to education”, “returns to education”, “college graduate”, “schooling complet”, “teacher”, “kindergarten”, “preschool”, “community college”, “academic achievement”, “academic performance”, “postsecondary”, “educational spending”, “student performance”, “student achievement”, “student outcome”, “student learning”, “higher education” “educational choice”, “student academic progress”, “public education”, “school facilit”, “education system”, “school voucher” “private school”, “school district”, “education intervention”. Articles may fall into multiple categories.

*** Standard errors are heteroskedasticity-robust

**** The 15 additional journals are (in alphabetical order): American Economic Journal: Applied Economics, American Economic Journal: Economic Policy, American Economic Journal: Macroeconomics, American Economic Journal: Microeconomics, American Economic Review: Insights, Economic Journal, Economic Policy, Economica, European Economic Review, Journal of the European Economic Association, Oxford Economic Papers, Quantitative Economics, RAND Journal of Economics, Review of Economics and Statistics, Scandinavian Journal of Economics.

Political Science Journal Rankings

Posted on by tatyana

How do we judge how good a journal is? Ideally by the quality of articles it publishes. But the best systematic way of quantifying quality we’ve come up with so far are citation-based rankings. And these are far from perfect, as a simple Google Search will reveal (here’s one such article).

I’ve been using Academic Sequitur data to experiment with an alternative way of ranking journals. The basic idea is to calculate what percent of authors who published in journal X have also published in a top journal for that discipline (journals can also be ranked relative to every other journal, but the result is more difficult to understand). As you might imagine, this ranking is also not perfect, but it has yielded very reasonable results in economics (see here).

Now it’s time to try this ranking out in a field outside my own: Political Science. As a reference point, I took 3 top political science journals: American Political Science Review (APSR), American Journal of Political Science (AJPS), and Journal of Politics (JOP). I then calculated what percent of authors who published in each of 20 other journals since 2018 have also published a top-3 article at any point since 2000.

Here are the top 10 journals, according to this ranking (the above-mentioned stat is in the first column).


Quarterly Journal of Political Science and International Organization come out as the top 2. This is noteworthy because alternative lists of top political science journals suggested to me included these two journals! Political Analysis is a close second, followed by a group of 5 journals with very similar percentages overall (suggesting similar quality).

Below is the next set of ten. Since this is not my research area, I’m hoping you can tell me in the comments whether these rankings are reasonable or not! Happy publishing.

Finally, here’s an excel version of the full table, in case you want to re-sort by another column. Note that if a journal is not listed, that means I did not rank it. Feel free to ask about other journals in the comments.

A new way of ranking journals 2.0 – journal connectedness

Posted on by tatyana

A few weeks ago, I proposed that one could rank journals based on what percent of a journal’s authors have also published in a top journal. I calculated this statistic for economics and for finance, using the top 5/top 3 journals as a reference point.

Of course, one does not have to give top journals such an out-sized influence. One beauty of this statistic is that it can be calculated for any pair of journals. That is, we can ask, what percent of authors that publish in journal X have also published in journal Y? This “journal connectedness” measure can also be used to infer quality. If you think journal X is good and you want to know whether Y or Z is better, you can see which of these two journals has a higher percentage of authors from X publishing there. Of course, with the additional flexibility of this ranking come more caveats. First, this metric is most relevant for comparing journals from the same field or general-interest journals. If X and Y are development journals and Z is a theory journal, then this metric will not be very informative. Additionally, it’s helpful to be sure that both Y and Z are worse than X. Otherwise, a low percentage in Z may just reflect more competition.

With those caveats out of the way, I again used Academic Sequitur‘s database and calculated this connectedness measure for 52 economics journals, using all articles since 2010. Posting the full matrix as data would be overkill (here’s a csv if you’re interested though), so I made a heat map. The square colors reflect what percent of authors that published in journal X have also published in journal Y. I omitted observations where X=Y to maximize the relevance of the scale.

A few interesting patterns emerge. First, the overall percentages are generally low, mostly under 10 percent. The median value in the plot above is 3 percent and the average is 4.3 percent, but only 361 out of 2,652 squares are <0.5 percent. That means that a typical journal’s authors’ articles are dispersed across other journals rather than concentrated in some other journal. This makes sense if the typical journal is very disciplinary or if there are many equal-quality journals (eyeballing the raw matrix, it seems like a bit of both is going on, but I’ll let you explore that for yourself).

There are some notable exceptions. For example, 41% of those who have published in JAERE have published in JEEM, 54% of those who published in Theoretical Economics have published in JET, and 35% of those who have published in Quantitative Economics have published in the Journal of Econometrics. These relationships are highly asymmetric: only 13% of those who have published in JEEM have published in JAERE, only 16% of those who have published in JET have published in Theoretical Economics, and only 4% of those who have published in the Journal of Econometrics have published in Quantitative Economics.

There is also another important statistic contained in this map: horizontal lines with many green and light blue squares indicate journals that people seem to be systematically attracted to across the board. And then there’s that green cluster at the bottom left, with some yellows thrown in. Which journals are these?

I had the benefit of knowing what the data looked like before I made these heat maps, so I deliberately assigned ids 1-5 to the top 5 journals (the rest are in alphabetical order). So one pattern this exercise reveals is that authors from across the board are flocking to the top 5s (an alternative interpretation is that people with top 5s are dominating other journals’ publications). And people who publish in a top 5 tend to publish in other top 5s – that’s the bottom left corner. In fact, if you omitted the top 5s, as the next graph does, the picture would look a lot less colorful.

But even without the top 5, we see some prominent light blue/green horizontal lines, indicating “attractive” journals. The most line-like of these are: Journal of Public Economics, Journal of the European Economics Association, Review of Economics and Statistics, Economics Letters, and JEBO. Although JEBO was a bit surprising to me, overall it looks like this giant correlation matrix can be used to identify good general-interest journals. By contrast, the AEJs don’t show the same general attractiveness.

Finally, this matrix illustrates why Academic Sequitur is so useful. Most authors’ articles are published in more than just a few journals. Thus, to really follow someone’s work, one needs to either constantly check their webpage/Google Scholar profile, go to lots of conferences, or subscribe to many journals’ ToCs and filter them for relevant articles. Some of these strategies are perfectly feasible if one wants to follow just a few people. But most of us can think of way more people than that whose work we’re interested in. Personally, I follow 132 authors (here’s a list if you’re interested), and I’m sure I’ll be continuing to add to this list. Without an information aggregator, this would be a daunting task, but Academic Sequitur makes it easy. Self-promotion over!

If you think of anything else that can be gleaned from this matrix, please comment.