Over a year ago, I wrote a post tabulating the share of AER: Insights authors who have also published in a top-5 journal*. (The answer was 67%, significantly higher than most other journals, except those that generally solicit papers, like the Journal of Economic Literature.)

Now that AER: Insights is in its second year of publishing and has 60 forthcoming/published articles, I decided to revisit this question, again using Academic Sequitur data. The graph below shows the percent of authors that (a) have published/are forthcoming in a given journal in 2018-2020 and (b) have had at least one top-5 article published since 2000. The journals below are the top ten journals based on that metric.

With a score of 66%, AER: Insights still has the highest share of top-5 authors among journals where submissions are not generally solicited.** The next-highest journal, Theoretical Economics, is five percentage points behind. (There is some indication that the share for AER: Insights is coming down: for articles accepted in 2020, the top-5 share was “only” 60%.)

What if we condition on having two or more top-5 publications? That actually causes AER: Insights to move up in the ranking, overtaking Brookings Papers on Economic Activity.

Whether this pattern exists because AER: Insights is extremely selective or because less-established scholars are reluctant to submit their work to a new-ish journal or for some other reason is impossible to know without submission data. But no matter how you look at it, the group currently publishing in AER: Insights is quite elite.

*Top 5 is defined as American Economic Review, Econometrica, Journal of Political Economy, Quarterly Journal of Economics, and Review of Economic Studies.

**AER: Insights would be even higher-ranked by this metric (#3) if we ignored top-5 publications in American Economic Review. Therefore, this pattern is not driven by the fact that both journals are published by the AEA.

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 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.

My recent post on a new way of ranking journals using data from Academic Sequitur (which you should check out, by the way!) was more popular than I expected. People pointed out important theory and macro journals I had missed (I’m clearly an applied micro person). So I added more journals. They also pointed out that making top 5 the reference journals may mean that the ranking reflects who is in “the club” with these journals more than anything else. One thing I will do in the future is make a giant matrix of pairwise journal relationships, so if you don’t like using the top 5 as a reference, you can use a different journal. But for now what I did is calculate what % of authors in a journal have only one top 5. This could plausibly make the rating noisier (maybe these people just got lucky), but it should reduce the influence of those who live in the top 5 club (as opposed to guests!).

Finally, someone pointed out that because AER and AEJs are linked, using publication in AER as a metric for the quality of AEJs may be misleading. So I calculated the percent publishing in top 4, excluding the AER. This metric is what the data below are sorted by.

So without any further ado, I give you the expanded and revised rankings! First, the “top 10”.

One thing worth pointing out here is that Quantitative Economics is linked to Econometrica, as is also evident from the high proportion of its authors who have published there. Theoretical Economics and Journal of Economic Theory were not originally in the set of journals I ranked, but they score high both with and without counting the AER. Overall, the rankings get re-shuffled a bit, but given how numerically close the original percentages were, I would call this broadly similar.

Next ten journals:

Next ten:

And here’s the final set:

How do the rankings with and without AER compare? Four journals rise by 5+ spots when AER is excluded: Quantitative Economics, Journal of Mathematical Economics, Review of Economic Dynamics, and Quantitative Marketing and Economics. And four journals fall by 5+ spots: AEJ: Micro, Journal of Human Resources, Journal of International Economics, and Journal of the Association of Environmental and Resource Economics (abbreviated as JAERE above). AEJ: Policy falls by four spots, AEJ: Macro falls by one spot, and AEJ: Applied stays in the same rank.

What if we only count authors who have just one top 5? That changes the rankings much more, actually, with 13 journals rising 5+ spots, including ReStat, JHR, JIE, JUE, and JPubEc. Nine journals fall by 5+ spots, including AEJ: Applied, JEEA, RAND, JEL, and IER. To me, that suggests that who we count matters much more for the ranking than which journals we count.

Bottom line is: stay tuned (you can subscribe to be notified when new posts appear on the bottom right). I plan to play around with these rankings a lot more in the next few months to figure out if/how they can be useful! If you want to play around with the data yourself, the full spreadsheet is here (let me know what you find).