7 Quick Takes of Undeniable Insight, Absent Evidence or Significant Explanation

  1. Over-fraternization within a line of work leads to all kinds of pathologies as social networks become too insular. If you’re a police officer and you spend your days constantly interacting with civilians having the worst day of their life, it’s really important you spend your free time with people who are having a perfectly normal and safe week. Same goes for politics, academia, entertainment, etc. This is not a “pop your bubble to improve the quality of your opinions” take. This is purely advice for your own personal mental health. Academics and entertainers need people in their life that they are rightfully embarrassed to complain in front of, to keep perspective on what the stakes of their decisions actually are. Cops and soldiers need reminders that the world is not constantly coming apart at the seams. Most of us will call the cops maybe once in our lives, and it probably won’t be because something good happened. Not a week goes by in a beat cop’s life where they don’t interact with someone who had to call the cops. They need to fill their set of observed experiences with stories uncorrelated with events where someone had to call the cops.
  2. The distribution of people’s opinions of Elon Musk needs to be compressed. Everyone with an above 75th percentile opinion needs to downgrade their estimation of him as a thoughtleader or agent of positive chaos/liberty. Everyone with a below 75th percentile opinion needs to upgrade their appreciation of him as an engineering genius committed to building tangible infrastructure innovations.
  3. The current political era we are living through isn’t defined by extremism, it’s defined by gambles on different sides of the “median voter vs institutional inertia” coin. The Democratic Party is struggling to hold together a coalition of progressives and moderates with nothing but bubble gum and reproductive rights because they believe the median voter remains an irresistible force. The Republican party, on the other hand, continues to bet the entire franchise on an activated base of extremists and gerrymandering. This bet is not ignorant, or in denial, of the median voter. It’s a bet that institutional inertia combined with potentially two decades of control of the Supreme Court will yield benefits greater than the costs of eventually losing control of all three branches across multiple elections.
  4. The best super hero movies are the ones where they take an auteur with at least 5 movies under their belt and say “make the most ‘you’ movie possible, but with our characters in our universe”. Why is “Doctor Strange and the Multiverse of Madness” so good? Because they hired Sam Raimi and gave him the greenlight to make “Evil Dead 4”.
  5. Even the people who *know* that crypto and blockchain technology will create enormous value – even those people aren’t sure if the coins that currently exist will have significant commodity value down the road.
  6. There are lots of right wing political positions that I view as wrong or costly, but most of them I view as “deviations from an uncertain optimal state of the world” which is to say I don’t worry about them in the slightest. The embrace of White replacement theory and increased framing of their opposition as enabling of sexual predation of children, on the other hand, scares me a lot because there is no action or option that is taken off the table for the people who believe them. Say what you will about corporate conspiracy theories and other intellectual pathologies of the current progressive left, they consistently keep terrorism and violence of the table. It can be hard to pin down the intellectual center of a political party or coalition, but the moral center is always composed of the voices that keep violence out of the choice set. I’m don’t know who those voices currently are in the Republican political and media coalition.
  7. The key to popular support for capitalism is the continued to expansion of mint-chocolate flavored options in our choice sets.

The propaganda premium puzzle

Beliefs I currently hold:

  1. In the past we have been surprised by the capacity of blatantly false information to persuade large groups of people.
  2. In the future we will continue to be surprised by the ability of blatantly false information to persuade large groups of people.

From the point of view of classic economic theory, this is almost a two-way paradox. First, why aren’t people rationally updating their beliefs to be more skeptical of the information presented to them by state and private media with fairly transparent agendas? If we accept the premise of the first, though, it invites a second question: why is anyone surprised by the efficacy of propaganda and the credulity of large swaths of the public? Shouldn’t we, the meta-observers, also be updating our beliefs?

My preferred explanations, as they stand, are:

  1. Preference Falsification i.e. people are not fooled, they just happen to believe that at the moment it is safer and more rewarding to appear as though they believe the lies.
  2. Social coordination i.e. narrowly held false beliefs make more better coordination mechanisms for solving collective action problems than broadly held truths

The first is a classic theory that originated with Timur Kuran’s seminal work. Whenever the median voter, or median would-be voter in an autocracy or failed democracy, seems to be held in sway by particularly transparent propaganda, I usually start from the default assumption of preference falsification. These people know the media regime they live within is a menagerie of lies that exist solely to flatter leadership and disrupt any opposition, but they also know that their short run futures remain more secure if they not only publicly accept, but actively parrot the lies.

For now at least. Preference falsification is an inherently fragile equilibria. As effective and impenetrable as propaganda can appear at a given moment, public support for those lies can collapse in the blink of an eye, a dynamic only intensified by modern communication technology.

The ability of false beliefs to solve coordination problems is more subtle, but no less salient to the propaganda premium puzzle, particularly when a regime is dependent on a small subset of a society to hold on to power (a “selectorate“) or the support of a political “base” who would otherwise have difficulty signaling their identity to one another. The reality is that obvious or widely shared truths have almost no value when trying to signal mutual affinity and trustworthiness to individuals trying to solve collective action problems. Patently ridiculous beliefs, on the other hand, work precisely because the only people who would publicly commit to holding such beliefs are those who are committed to the collectively produced club good.

So why does propaganda continue to work better than we think it should? Because we’re using the wrong metrics. Or, more precisely, because the right metrics aren’t available to us. We can ask people what they believe, but we can’t make them tell us the truth. And even if we could make them tell us the truth, we can’t measure the benefits motivating their reasoning, the value of the club goods they are gaining access to because they’ve performed the mental gymnastics necessary to hold those beliefs. Sure, it was cognitively costly to convince yourself the earth is likely flat, but those costs are trivial in the face falling out of the tightest network of friends you’ve ever been a part of.

All of this armchair theorizing is really just a long-winded way of suggesting that fighting propaganda is decidedly not about curing people of their false beliefs. If you want to unravel preference falsification, people don’t need the truth. They already know the truth. What they need are safe channels to express it to one another. If subgroups are forming around false beliefs, the answer is not to shame them for their beliefs. That will only strengthen their group and members’ committment to one another. Rather, the answer is to provide superior substitutes for the club goods they are currently receiving. When in doubt, if you want to break a social equilibrium, you’re better off giving people what they need rather than demeaning what they have.

Come to think of it, that’s probably pretty good life advice in general.

Let’s Talk about the NBER

The National Bureau of Economic Research (NBER) sent out its membership invitations this week. My twitter timeline quickly filled with explicit congratulations and oblique commentary. My private messages filled with…less than oblique commentary. Academia has always been hierarchical and economics has never been an exception. Talk of “top” departments and people is ubiquitous, but those categorizations remain fuzzy – “There are 40 departments in the Top 25” is a common adage. Aside from the obvious humor, I think there is also some healthy truth to it. There are lots of good departments and no one has any final say on who they are. Departments compete for recognition of contributions and the rewards that come from status in the profession. Having 40 or 50 “top 25” departments just means more status for everyone, which strikes me as nothing but welfare enhancing.

The NBER, on the other hand, has hard boundaries of membership. Though I doubt it was founded with any such intention, it has become the club within the broader profession that comes with more prestige than any other. Exclusionary clubs are not unto themselves problematic, but it is hard to shake the feeling that the advantages exclusive to NBER members are greater than ever.

For those who are sick of preamble, let’s start building a hypothesis. Academic economics has acquired some pathologies of publication and promotion that are creating an increasingly grumpy and anxious profession, particularly amongst our junior colleagues. These pathologies are manifest as broad public goods (e.g. timely evaluation and dissemination of research to inform tenure and promotion decisions, professional network development, the transition into a discipline more dependent on significant outside funding, etc.) that the discipline is consistently failing to produce.

The NBER is producing exactly these public goods. They didn’t create any of these problems, but for their members they may have solved them.


Originally founded as a research institute in 1920, largely to produce and disseminate macroeconomic data, the NBER has evolved into a collection of 20 research programs and 14 working groups, all built around a bureaucratic hub that has 100 years of institutional experience running research groups, disseminating research, and organizing events. It has a storied history and deserves every ounce of the prestige it both enjoys and bestows.

From the point of view of any scholar looking to get a research agenda off the ground, an affiliation with the NBER offers 4 key advantages or “club goods”:

  1. The prestige of listing an NBER affiliation at the top of your CV and on every paper you write and submit.
  2. Invitation to NBER conferences, most importantly the Summer Institute collection of meetings every July in Cambridge, MA.
  3. The option to channel your grants through the NBER instead of your home institution’s bureaucracy.
  4. Permission to disseminate your new papers through the NBER working paper series.

I would like to contend that all 4 of these privileges confer enormous advantages for any scholar, doubly so for young faculty. I am not contending that these advantages are unearned or even necessarily unfair, but I do think that they are often underappreciated in their magnitudes, and that this under-appreciation offers some insight into the frustration expressed by those on the outside. So let’s talk about them.

Signal value #1 may be the most or least important, depending on your point of view, but it’s definitely the least interesting. Every CV is filled with myriad signals, the NBER is just another one. In fact, the only aspect worth discussing is its seeming correlation with another key signal: PhD-granting institution. It seems, with nothing more than a glancing ocular regression, that being invited to join as a faculty research fellow (i.e. a pre-tenure affiliation) correlates heavily with having a Cambridge, MA PhD or having an PhD advisor at an elite institution who is themselves an NBER Research Associate (i.e. post-tenure member). There’s nothing inherently bad here, but this compounding of highly correlated signals is a little ominous for the outsider trying to get their own career off the ground. If exclusion from the club is unto itself what bothers you the most about the NBER, you’re missing the point and you should probably just get over it. And yourself, for that matter.

Conferences. #2 is more interesting because the NBER conferences, including the Summer Institute, are widely appreciated for the important networking events that they are. What I don’t think is as appreciated are how they relate to the journal reviewing process. First, if you hang out there long enough people will learn your name and face. While academic economics is famously rigorous and occasionally brutal in its seminar and reviewing culture, the fact remains that humans are more forgiving, more generous of the benefit of the doubt, once we put a face to a name. It’s just harder to be mean or assume the worst in someone once you’ve had a real conversation with them and confirmed their genuine humanity. Second, and this is probably more important, to present a paper at an NBER conference is to present to the pool your eventual reviewers will be drawn from and receive pre-submission referee reports. Being able to learn the perceived weaknesses of your paper before submitting to the magical top-5 and elite field journals is a prodigious advantage, particularly for scholars who don’t yet have a decade of experience trying to publish in their field.

Grant Management. Being able to funnel grants (#3) is probably both the most boring and most underappreciated of member advantages, particularly for scholars building research agendas at smaller schools that place more teaching and service demands on faculty. Being awarded a significant grant can be something of a curse to the pre-tenure scholar if their institution doesn’t have the internal human resources and institutional experience to manage a grant properly. Losing 15 hours a weeks to bureaucratic transaction costs is crippling. If I were trying to start a career running field experiments, I’d probably spend my first semester camped out on the NBER’s front porch like I was petitioning for admission to a Buddhist monastery.

Working Papers. Access to the working paper series (#4) is probably what would strike non-professors, or even just non-economics professors, as trivial, but is actually the most important. I know it’s what I want access too. Lets explain why:

Academic economics has a publishing problem. This is nothing new. What I think is underappreciated is that the NBER solved it for its members.

When the authors of a paper feel that its contribution has been established, that it can exist independent of any supplemental explication with tolerable risk of significant changes between now and its final form, they put it out into the world as a working paper. As the submission and review process has lengthened over the past few decades, the working paper stage of a project’s life cycle has grown in importance. It’s not crazy to suggest that most economics papers reach their total citations “half-life” while they are still working papers.

Whether that sounds crazy to your or not, however, doesn’t actually matter. What matters is that the timeline from first submission to acceptance at a journal continues to expand while the tenure clock remains fixed at 6 years. I’ve written before about how we might mitigate some of the problems in the journal publication process, but that’s a far less pressing concern if you are an NBER member because your papers enter the field as contributions through their NBER-branded working paper series years before acceptance at a journal. The prominence of NBER working papers is sufficient to the point that publication for members exists solely to provide additive signals of quality for long-term career tracks. The contribution itself, how it is internalized in the field and propogated forward within the authors’ research agendas, is adjudicated by the jury of the authors’ peers years before an editor acquiesces and agrees to sacrifice invaluable journal real estate as tribute unto the paper’s now long established contribution. Published papers are old news.

It is no less important that research also enters the seminar, media, and policy cycle as soon as it is disseminated as an NBER working paper. I’ve been in discussions where whom to invite to a workshop reduced for many to nothing more than scrolling through the previous 3 months of NBER working papers. Journalists subscribe to the series for ideas on columns and features. Thinktanks similarly fill their calendars of lunch talks and policy events. The authors will know if their project is a success, or if they are on the wrong track, months before their first rejection and years before their final acceptance. The world learns of them, their research, and their specific expertise through a channel entirely separate of formal peer review or historic outlet prestige.

The NBER solved the economics journal problem by disintermediating scientific debut and evalutation from the publication process. But again, only for their members.

Have I said enough about the working paper series? Let me summarize with a only a touch of hyperbole: if I ran a regression to find the determinants of expected citations, I would expect nothing on the right hand side of the equation, not university affiliation, not PhD-granting institution, not even journal ranking, would have a bigger coefficient than a binary indicator for was it an NBER working paper.

So what should we do?


First of all, I’m not a member, so there is no we about it. Second, I’m not sure we should do anything. It’s not my club, it’s been wildly successful, and just because some of us don’t get to enjoy it’s benefits doesn’t mean it should be changed. So, rather than complaining about the NBER or telling them what to do, I would like to suggest that the discipline has some public goods problems. and that the NBER might be able to contribute to mitigiating them.

One more thing to keep in mind – the club goods provided by the NBER are broadly characterized by decreasing returns to scale. Personal time and attention simply do not scale, which means the answers to most concerns will rarely lie in increasing broad membership or access (though I agree fully that the solution is without question inclusive of letting you in, as you are very smart and grossly underappreciated).

That all said, let’s now revisit the four NBER club goods currently exclusive to members.

#1. The prestigate of membership. I hope you didn’t read this far hoping I’d try to “solve status” in academia. That said, when an exclusive club acquires this much value, you have to expect that the process of admission is going receive all the more scrutiny. As a grossly uninformed outsider, the shadows I see on the wall of a cave from a considerable distance through a crack in the wall is an irregular nomination process that probably bottlenecks in some places while spreading idiosyncratically across networks in others. My guess is that a lot of people who are asked to provide 100 hours of attention in an already 70 hour work-week are effectively being tasked with filling in the next round of nominations. This leaves them with little choice but to take the path of least cost, and that path is making nominations of the former students they came across in their own hallways and those of their closest peers. Occasionally this also grants opportunties for gratuitous favortism and subsequent resentment. More importantly, though, in increases the tightness and redundancy of academic networks, furthering the gap between insiders and outsiders.

How do we fix this? We probably don’t, but here’s one thought: delay the nomination process. If this is the most prestigious club in economics, why are we nominating new PhD recipients before they’ve produced a research agenda? One way to make an institution’s admission process seem more transparent is to have criteria that are at least partially realized, rather than just subjective potential. It probably wouldn’t hurt to make nominators into publicly observable sponsors of record. Never underestimate shame as a tool for mitigating the various ills than can characterize an institution. (NB: these could actually be internally transparent. Remember: just because I am writing this doesn’t mean I am particuarly well informed)

#2. Conferences. An insider has sugggested to me that the Summer Institute used to be far easier to crash, but relented in the face of skyrocketing costs, flooded sessions, and problematic favoritism of local schools. Reiumbursing travel costs extended the radius of access, but also dramatically increased the cost per attendee to the NBER.

One suggestion: the NBER should only pay for the expenses of graduate students and junior faculty. Everyone else, including members, should pay their own way (or at least expense the trip to their home deparments). The hope is that this will make it easier for the NBER to subsidize access to non-members outside of the immediate ring of members. It may also be beneficial to prioritize non-members who have never previously attended. I’ll give you one more, and this works even better if membership nominations are delayed until later in careers: reserve presentation slots in the winter meetings exclusively for junior scholars and non-members.

#3 Grant organization I got nothing except maybe allow non-members to apply for grant-organization access. I mean, if there’s a scholar from a smaller school who’s already established a track record of outside funding in desperate need of institutional support for their research, this sure seems like a hell of a public good that the NBER could provide. Would a lot of people take advantage of it? I have no idea. But it certainly sounds promising and my guess is that it would actually net add to the NBER coffers.

#4 The working paper series. I’ve thought about it a lot, and this is what I’ve got: allow non-members to apply for “working paper series (NBER WPS) membership.” There’s simply no way around the fact the NBER itself cannot possibly scale to include every scholar who “deserves to be a member”. That said, I can’t help but think decreasing returns to scale are going ramp up a lot later for the working peper series.

The changes I imagine are relatively straight-forward. Scholars are allowed to apply for NBER WPS membership, submitting a CV and a recent working paper. If they are denied they cannot apply again for 3 years. If they are admitted they may submit papers to the WPS, on the understanding that the NBER reserves the right to apply a more rigorous review process than with full members and to deny any paper at their discretion. This isn’t a trivial cost proposition, mind you, and it would be entirely borne by the NBER, but they have access to sufficient human resources (cough graduate students) to provide cursory reviews of papers to make sure they are up to basic snuff, pushing potential questions up the chain when a paper might not be of a high enough standard. This would be an enormous service to the profession that they are in a unique position to provide.

In a final closing sentiment, let me state a few things that are probably obvious, but hell, you read this far. I have the luxury of being a tenured professor, so the consequences of these institutions are pretty minimal to me. But I’ve also been a bit of an outsider in the profession since the beginning. I was 9 years and two “top-5″s into my career before I got my first seminar invite, 10 years before I attended my first NBER summer institute. Which is to say I am sensitive to the frustrations of younger scholars who feel like there are walls between them and what they need to get their careers off the ground. We shouldn’t dismiss their genuine (and not unreasonable) anxiety as prestige envy or a grotesquely privleged version of populism. The discipline of academic economics has real problems, and if the NBER has figured out internal solutions to some of those problems, then I’d like to think they might be interested in spreading access just a little farther.

Attention as Rational Addiction

I’ve never gotten this much attention before. Which is to say, my writing receives a small sliver of attention on occasion, but that small sliver is nonetheless far more than I’ve received previously in my life. To put it in better context, I’ve had a couple posts and tweets go mini-viral, which by the standards of major pundits or celebrities amount to little more than a throwaway post, but by the standards of my life up until now they elicited tidal waves of attention.

It felt pretty good.

Those good feelings, though, morphed into something else within a couple days. First, there came the fear of saying something wrong while more people were paying attention. That fear of negative approbation is nothing new or special, but it was certainly heightened. What was more disconcerting, however, was how the anticipation of attention, or more importantly possible lack thereof, crept into the back of my mind as I sat down to write future posts and tweets.

Here’s a an interesting phenomona: once you have enough followers on twitter, the lack of likes/retweets on anything you write becomes recognizable as implicit disapproval. You know what you wrote was put in front of a couple thousand people and yet nearly none of them felt it warranted a tenth of a second click. It stings.

That sting from the absence of approbation changes the incentives in front of you, maybe for some even more than the initial serotonin-dump from previous bursts of positive attention. You feel the pull to write about the things that got attention before, to write in the same manner or mood. To give the customers what they want.

And the customer that matters most is the part of your brain that wants to re-live the thrill of thousands of strangers telling you that you are good and smart and pretty and are totally worth keeping around. This is an addiction. Now there is, of course, no shortage of people calling social media an addiction. What I would like to argue is that it is a particularly dangerous addiction because it is a perfectly rational addiction.

A Rational Addiction Model of Attention

I’ll skip any real math, but indulge me a moment of framing:

A simple model of rational addiction to attention starts with three inputs: positive approbation (P), negative approbation (N), and total attention (T), where T = P + N.

Now lets assume that your utility is increasing with P and decreasing with N, while also increasing with T. That’s all pretty uncontroversial for humans. Let’s also assume that negative attention is easier to reliably generate than positive attention (i.e. trolling is harder to ignore). To put a little structure on it, we’ll assume that they are all substitutes, but with different weights .

U = T^w1 + P^w2 – N^w3

What that means is that people have an incentive to pursue attention, but how they allocate their efforts across plays for positive and negative attention will depend on how much they weight the cost of negative attention relative to what they gain from total attention.

Here comes the twist, though.

What if T is not the absolute total attention you are receiving today, but instead T is the total attention you are receiving today relative to the average attention you have received in the past, the level of attention you have become accustomed to?

U = (T- T_mean)^w1 + P^w2 – N^w3

Well now you’re on a hedonic treadmill, but for attention instead of wealth or luxury. Your brain has grown used to a rush of serotonin from the attention of millions of strangers. You’re like an adrenaline junkie, but instead of jumping out airplanes you’re trolling public figures and latching on to “Twitter’s main character” everyday.

What’s interesting about this model of rational addiction, however, is how quickly you can find yourself pursuing negatiive attention. ostensibly producing negative utility (i.e. actively making yourself unhappy) by pursuing negative attention because the total cost of that negative attention to you is less than the even costlier option of no one paying attention at all. Would you log on to twitter everyday if if cost you a hundred dollars? You would if not logging on cost you ten thousand. Same thing for those who are rationally addicted. What started out as a positive reaction to a small number of well-received insights has created a utility monster trolling the world in a desperate plea for negative attention in the hopes that it will grant the slightest reprieve from the icy desperate loneliness inside that haunts my every moment.

I’m fine. Really. I’m making a point.

When we talk about the problems of social media for mental health, we tend to focus on bullying, dysmorphic self-images, and the creation of false standards of value. I think all of those problems are extremely real, but they also seem like things that can be addressed with policies, oversight, or cultural adaptation. What I want us to consider is that attention at this scale is something that is so baked into the construct of social media that problems emerge from perfectly rational engagement by otherwise well-intending people. I’ve previously tried to model the loneliness that can come with being extermely online, but this in some ways is actually deeper.

What if, for most of us, the only way to win at social media is not to play?

We can’t leave internal affairs to the police anymore

There are three open questions regarding police abuse and corruption:

1) How much is there?

2) What are the mechanisms underlying it?

3) What are the policy options for mitigating it?

This is a subject I have much interest in and have been researching for over a decade. I am still interested in the first two questions, but it’s increasingly difficult to invest in any conversation that doesn’t immediately contribute to how we are going to mitigate the problem.

This story of Hamilton County, Tennessee is a pure, unadulterated nightmare. We don’t want to make policy off a single nightmarish department or event, but there is nothing isolated or unique about this story. Bad officers migrate to other departments or are simply re-hired by their old one. Bad departments are rarely shut down. Bad sheriffs get re-elected. For large departments, “internal affairs” serve as the de facto monitors, but they are both part of larger social network of law enforcement and also shunned by the an insular sub-network of street officers. Both municipal police and sheriffs’ unions work tirelessly to solve the collective action problem for their members, but in doing so also provide the institutional capital that ensures that members are insulated from any form of accountability. Police take care of their own.

None of this is a new problem – “Who will watch the watchmen” has been a political puzzle since the advent of political thought. What is increasingly clear, though, is that the institutions we have in place for monitoring local law enforcement are largely impotent, either because they’ve always have been or because they’ve become obsolete. Internal and mutual monitoring i.e. “the watchmen watch themselves” only works when the individuals in question are unable to solve their collective action problem, in this case collectively preventing the reporting of misconduct by fellow officers. I regret to inform you that the police have solved their collective action problem.


There is arguably (and I would argue it) no one in our society less likely to be punished for committing an act of violence against another human being than a police officer. I don’t view that as an inflammatory or even particularly normative claim. That’s a reality, and it may in fact even be a welfare enhancing one i.e. maybe someone has be endowed with additional coercive force relative to most citizens. But I think the specific power of police is something well beyond simple “coercion”.

I am hard pressed to think of any occupation with more unwitnessed discretionary power than police officers. Judges may have more power, but they sit on benches in public courtrooms in front of an audience when they exercise their power. All regulatory power occurs via documentation. Political power eventually has to pass through the prism of public governance. Economic power comes via reward and deprivation, but is always constrained by the opportunity of individuals to exit the relationship. You can always move out on a bad landlord or quit a terrible job, but there’s no swapping out for the better officer when one’s got you pinched.

Police officers often exercise their power one-on-one, away from prying eyes, in settings where they themselves serve as the primary witness of record. They have the discretion to not just bear witness to a crime, but to establish its very event, and in doing so start a chain of events that will change how every institution in society treats a person for the rest of their life. They have the power to constrain a person physically, the power to kill, all in a context absent any external monitoring.

You might be imagining a story in an alley or in the back of a squad car, but a holding cell or interrogation room can be a far lonelier place when the only other potential witnesses are other officers. What little doubt a single officer’s testimony may carry is completely washed away by the matching depositions of multiple officers. If the story comes down to you versus them, you’re going to lose.

So I’ll say it again: police officers are endowed with more unobserved discretionary power than any other occupation in our society.


It’s time for significant resources to be invested in monitoring local law enforcement, and it needs to be made permanent. This can’t a be priority that lives at the whim of the Presidential election cycle. This can’t just be an ad hoc prioritization that manifests case-by-case and is largely driven by news coverage. Monitoring of local law enforcement needs to become a permanent feature of our federal bureaucracy. Whether that means creating an independent agency, a subset of the FBI, or a reappropriation of the labor in capital currently being wasted in the Drug Enforcement Agency, I don’t know.

Trust in local police is so low that “Defund the police”, an idea whose foolishness is only matched by its political naivete, actually got off the ground as an idea. That’s where we are at as a society: we have so little trust in the providers of law and order, a core good so central to the very idea of government it shows up in frontier towns before just about anything else, that people were open to appeals to simply live without law enforcement. That’s…that’s not good.

There is all kinds of really good research into what can be done to restore trust in the police. Training reforms, procedural justice, body-worn cameras, (ahem) public finance reforms, just to name a tiny few. These are all good ideas, but maybe we should also consider recommitting to our core belief that policing works, that monitoring and punishing people who break the law deters others from doing so. If we really believe it works for private citizens, then it might just work for the police.

In fact, I think already nailed it two paragraphs ago. Let’s rename the DEA the Department of External Affairs. We’re legalizing narcotics one drug at a time and these people will need jobs, right (I’m only 41% kidding)? We can have a Watchman “Czar” (they watch the watchmen, get it?). They can have tip lines. There can be informants in bad police departments, court ordered wire taps. They can seize resources from corrupt departments. They can keep doing all the things they’ve been doing, but instead of drug smugglers they can track abusive officers skipping across state lines from job to job, bust corrupt sheriffs, and occasionally seize the odd speed boat. If you’re going to be endowed with a badge and a gun, with the ability to pull a person out of their life and threaten to render moot every plan they ever had, then it seems only fair that you know someone might be watching you.

To add a bit a self-important context to this suggestion, please know that advocating for the establishment of federal agencies is far from my default solution. I know that the US government is littered with departments and agencies that do little but drag down the efficient expenditure of resources, inch by inch eroding the credibility of the public enterprise. Part of the promise of federalism is not just pushing local goods down the government hierarchy, but pushing national goods up. Not since the Civil Rights Movement has it been more clear that local law enforcement is in crisis. The Hamilton County Sheriff’s office, the Ferguson police department, these are no longer local problems. Each story of tragedy and abuse chips away at the broader reputation of law enforcement across the country and we are all less safe for it. Nor are they dependent on tacit local knowledge or relationships– quite the contrary, local relationships are likely to inhibit proper monitoring through either personal loyalty, collective intimidation, or being outright complicit.

The law enforcement crisis has been become a national problem. A federal problem. It’s time to treat it like one.

Religion at its best can protect science from politics at its worst

I choose to believe these tweets are true because I want to write about it. I’m pretty sure they are, but unlike some people, I don’t have “medievalist friends” to verify it and I’m to tired to open Google.

Regardless of whether the “the book preciptated witch hunting” is true, I am in full agreement that much of misinformation is demand driven. Even when motivated by an alterior motive, disinformation has to be wrapped in the candy-coating of something people want to believe is true. For all the talk of disinformation though, the connection to witch hunting and religion is what I find most interesting, particularly in our pandemic times. There’s been a lot of frustration over people’s eagerness to believe non-scientific and pseudo-scientific garbage, but what I find most concerning is how rapidly identities solidified around believing experts and not believing experts. My suspicion is that this is, at least partly, a symptom of becoming a more broadly secular society, where political and scientific beliefs have for many people substituted for faith affiliations as group signifiers and shibboleths.

Religion makes for better and safer group identities than science. Why? Because religion is predominantly interested in untestable assertions whose veracity is entirely orthogonal to the quality of our lives and how we function as a society. This isn’t to say that societies can’t just as easily violently fracture as peacefully congeal around these beliefs, but the “truth” of them is entirely irrelevant. Communities and sub-communities can form Russian nesting dolls all the way up to continents and all the way down to Tilda Swinton, and the truth of the individual sets of religious beliefs won’t matter in the slightest.

Science, on the other hand, is a vastly different story. Groups that form around disbelief in the germ theory of disease or the food safety of the Green Revolution in agriculture will face vastly more limited prospects in the lives of members and their future generations. Groups naturally split into insiders and outsiders– that’s how we solve whole swaths of the collective action problems and Prisoner’s Dilemmas we face everyday.

Science needs religion to stake out territory in the ineffable and claim beliefs as their own. From these beliefs religion can provide people with the tools to tell stories, form bonds, and cultivate trust beyond the limits of kinship and familiarity. Religion needs to thrive so that science can work its way unmolested, and unco-opted, through the unending labryinth of truth-seeking, of learning and unlearning, discarding old truths as evidence mounts. It’s hard enough to accept evidence denying old truths when repuations are built around them (science does, after all, advance “one funeral at a time”). But it’s nearly impossible to discard old truths if they are holding a community together. People will cling to them because there’s too much immediately at stake, and in doing so you become trapped at the sclerotic local maximum of a costly falsehood.

I know there’s a tendency to focus on shared social media clips of preachers advocating against vaccines and masks and what not. But I don’t think that’s religion competing with science. I think that’s ostensibly religious leaders giving up on their faith to sell what they see people buying. Yesterday they were selling God, today they’re selling disinformation. Not because God is disinformation, but because they are seeing more demand for disinformation than God.

I don’t have a faith to sell anyone, and I certainly don’t have a policy solution in my back pocket (though I can only assume the answer starts with crypto and ends with profit). But I do think that if we are going to keep science safe from the short-term vicissitudes of our petty political identities, we will have to better resist the urge to call ourselves, our group, pro-science. It inevitably creates an anti-science opposition, cornering people into rallying around ideas that benefit no one in the long run. And we also have to have more faith in our faiths. If you don’t hold that your beliefs, and the community you’ve built around them, are appealing enough on their own merits, then you’re not really a believer. You’re not a scientist either. You’re a salesman, and one with a bad product at that.

Happiness is Zeno’s hedonic treadmill

I don’t take Maslow’s Hiearchy of Needs very seriously. I don’t much worry about hedonic treadmills. I don’t worry about a cursed existence where I am forever advancing half-way closer to whatever goal will bring happiness and emotional fulfillment.

I don’t worry about it, but I understand.

I’m struggling to find much inspiration sketching my little ad hoc economic models of daily life with the backdrop of Ukrainians struggling to survive in the face of an invading army. Perspective is a hell of a drug. This struggle has brought to the front of my mind Maslow’s Hierarchy of needs, which lays a psychological layering onto the economic prioritization of needs (food and shelter first, social needs second, “self-actualization” last). It’s the kind of model that gets used and abused because it adds a veneer of psychological depth to absurd reductionist theorizing. Don’t take my petty academic denigration too seriously, though. Just because I think it’s not particularly useful doesn’t mean it’s wrong.

Similarly, I find consternation over hedonic treadmills unnecessary because whenever your result is that utility is declining as resource constraints are loosening, the likely explanation is that you aren’t observing utility correctly. Specifically, there are dimensions to utility you aren’t observing, be it temporal (i.e. the distribution of future possibe utilities), network (i.e. sympathetic utilities of children, spouses, friends, etc), or most likely that you are in fact not observing utility but rather one of many inputs into total utility i.e. there’s more to utility than just “happiness”.

But maybe you’re not interested in how to optimally model the pursuit of happiness under the dual constraints of finite resources and the human condition. Maybe you’re just worried about managing your life under the limitations of your own flawed humanity. Maybe you’re worried about getting stuck on a hedonic treadmill, the carrot of self-actualization dangling forever just out of reach. Now I’m not a licensed therapist or trained psychologist, but I am an economist who has to constantly struggle against my own technical limitations. What that means is that I have a lot of experience solving problems beyond my own mathematical limitations, not through technical elegance but by simply hacking the problem until the problem solves itself.

You know. Cheating.

If you’re on a hedonic treadmill, all that really means is that you’ve defined your units wrong. It’s only a treadmill measured in feet. If you define happiness not as feet advanced but as having a positive first derivative in microns per microsecond, you can establish the model such that you’ll be long dead before you reach the dipping edge on the horizon. Happiness isn’t a destination or a journey. It’s a positive first derivative or, barring that, a sufficiently positive second deriviative. If that’s out of reach, f*** it, there’s a third one you can push into the positive.

Framed this way, Zeno’s paradox is no longer a curse, it’s a blessing. To always be advancing half-way to your goal for all eternity is to live in eternal bliss. To self-actualize. Whether you get there is outside the model. It’s irrelevant.

Which is a really long way of saying that one way you might hack the puzzle of self-actualization is to help support the physiological and safety needs of Ukrainians be transferring some of your resources to them as means of supporting the first-derivative of sympathetic inputs into your utility function.

Do people actually feel trapped in their careers?

A reader (though perhaps not yet a loyal one) wrote me:

“I don’t know if you take reader requests – but on the Nurse/Teacher/Kitchen Staff post from a little while ago – I am curious what the economic data might say about career switchability. I.e. sure, a teacher or nurse may feel trapped, but how free does everyone else actually feel? I’m assuming it’s hard to get data on this (what counts as an actual career change?) – but I (as someone scanning a list of blog titles and clicking on the one titled “It’s a Trap!”) would be interested in your perspective on this from an economics angle.”

I’m not quite sure how to go about answering this question directly, but I’ll venture a couple things. Some lazy searching on google scholar turned up a paper from 1988 that itself rediscovered a survey by the San Diego Teachers Association from 1964(!) that found “A feeling of being trapped in the profession” to be the #1 cause of burnout reported by teachers. A couple thoughts!

First, 1964! Second, while the reasons for feeling trapped in the teaching profession in 1964 were no doubt different than they are today (*cough* extreme institutionalized sexism *cough*), but we need to consider that the profession of teaching at the primary and secondary levels isn’t one that creates a lot of opportunities for adding to your human capital, which can lead to feeling, correctly and incorrectly, of the job market passing you buy.

A more recent paper from 2002 notes that “The lack of anything resembling a genuine career ladder contributes to the feeling of many teachers that they are trapped in a career that has become not only joyless but futureless.” As someone who’s been there myself, I can tell you there grows quickly in the mind a specific anxiety that that to stay a teacher too long is to risk being left on a career ladder with no rungs. If there was ever a reason to have the now clichéd “quarter-life crisis”, that’s it.

While teachers may leave the profession early for fear of being trapped by atrophied human capital, nurses appear to be more a story of over-specialized human capital. A relatively simple analysis found that nurses with more education and experience were more likely to stay within the professions. Nothing terribly shocking (or causally identified) there, but other work has found within-profession concerns of overspecialization as well: one paper found that emergency department nurses were especially concerned about becoming trapped ED-only nurses, particularly those in more rural hospitals, losing access to more lucrative urban jobs that require more advanced care-giving and physician support related skills.

Sure, it’s a little methodologically kludg-y, but I also enjoyed this endeaver to create a career typology separating ladders from dead-ends.

This is a great time to remember that causal identification is important, but it isn’t everything. Sometimes its really useful to create a super-charged summary statistic and look for patterns, like the above.

To get back to the readers question about extending beyond teachers and nurses, I think the key to understanding the transition costs of a career is to appreciate the two channels for becoming trapped:

  1. Human capital atrophy
  2. Human capital overspecialization

Atrophy speaks to a lack of options because of an absolute disadvantage, while overspecialization is because of an intense comparative advantage. The first is, in most ways, far scarier because you have limited options save to stay in a career where years tenure is your only real advantage. The second, on the other hand, is really only problematic if you have a strong preference against the field of your specialization or you fear the risk of obsolescence. That doesn’t mean you shouldn’t take overspecialization fears seriously. We’ve all seen a againg musician who can still fill an audience but looks like they’d rather get a root canal than spend another evening on stage. They’re not there because they want to, they’re because they’re second best option can’t cover their mortgage.

Do I have an career advice for maximizing career advancement and adaptability ?

Do I ever! Get an advanced degree in economics from a respectable school. Or, barring that, a school entirely absent in respect or prestige. More specifically (and more seriously), my advice is this: major in tools, minor in substance.

Substance can be acquired piecemeal, in a disjointed sequence with random and sometimes large intermittent breaks. Acquiring tools, on the other hand, is far more dependent on uninterrupted periods of intense learning and application. You can read about the Ottoman empire over coffee breaks and bus rides. Learning Python, R, real analysis, econometrics, virology, chemical spectroscopy, or evolutionary game theory are all far more easily learned if you can dedicate months or years to them in large uninterrupted bursts of focus.

Further, tools tend to exist in their own phylogenetic hierarchy. Once you’ve acquired a tool, it is often an order of magnitude easier to acquire a new, closely related tool. It might have taken 2 years to get really good at C++ or Java, but because of that you can learn Python in a couple weeks of fooling around on a side project. Those first tools are the most important ones you will ever acquire, but they are also the hardest.

A secondary bit of advice: major in something that people know is always at least a little hard. I try not to overrate the “signalling theory of education” but there remains the hard to deny reality that education does have some signaling value. One of the signals is “I’m smart”, but as a signal I think it’s highly overrated. A more important signal is “I’m willing to learn things that are hard”. Most careers within persistance advancement and robust demand require the continuing acquisition of new skills and adaptation to new circumstances. You want very badly to signal, early and often, that you are someone who is willing to put in the effort to adapt and remain productive.

Despite that some members within my vocation may suggests, however, the answer to every problem is not in fact more school. Which leads me to my final, most important, but probably most trite piece of advice:

Quit.

No, seriously, quit. If you can pay your bills and you want out, get out. If you can’t, start laying the groundwork for your exit. Yesterday would have been better, but today is a close second. There’s no room for sunk cost thinking in careers. You only booked two commercials in 7 years in LA? Move to Kansas City and learn to code. You want out of the service industry? Jump start your BS in chemistry two classes a semester. You hate nursing? Start applying for admin positions in your hospital, apply for reimbursement for a 2 year executive MS in IT management through your hospital. You hate your PhD program and realize there’s no market for your degree outside of academia? Start writing ad and social media copy for local restaurants trying to get off the ground.

This isn’t me trying to admonish you with “by-your-bootstraps” ra-ra BS. This is me saying that the time you’ve put in shouldn’t matter if you want something else. But maybe you don’t want something else. That’s fine too! Just don’t tell me you’re trapped then, just say that you’re bored and you need a new hobby. And then sell your hobby on Etsy. And then market your hobby through google. And then write a book and tell Martha Stewart about it. That’d be pretty cool.

But then again, it’s easy to give advice. Do your best. Feed your kids. Keep trying. It’ll be fine.

College sports are better when they’re worse

It’s spring break and that means catching up on both research and my social network. It also means college basketball. I remain firmly in the camp that college athletes should be paid for their incredibly high-value labor and, in turn, recapture a huge share of the surplus currently enjoyed by schools and coaches. What I am beginning to rethink, however, is the way that “professionalization” can and will play out.

This rethinking began with the the realization that my enjoyment of the product is largely insensitive to the presence of great players. The gap between NBA and NCAA basketball, in terms of quality of play, is so great that I simply don’t watch the sports in the same way. I consume the NBA the way I do Denis Villeneuve films: enjoying an artform in its closest approximation to perfection at the bleeding edge of innovation. NCAA basketball, in contrast, is a soap opera for genre aficionados. It’s Battlestar Galactica for sports fans.

There is a floating, ever-changing cast of characters supporting a handful of recurring leads. Clans and sub-clans. Rises and falls. Tragic failures and heroic redemption arcs. And, much like the latest show about wizards or post-apocaplyptic alien invasion survivors on the SciFy channel, the enjoyment of this product doesn’t require high level precision or execution. Quite frankly, the show is more enjoyable when the actors aren’t famous or especially elite; it keeps me squarely focused on the shlocky fun, rather than getting distracted by any urge to pick apart the film composition, story logic, or actor subtext. College basketball, in much the same way, keeps me squarely focused on the drama of gifted athletes doing their best to help their team achieve success in a limited window before moving on to the rest of their lives. Trying to get a little slice of glory now, while their knees will allow for greatness, before getting on with the endless particulars of adult life later.

Which brings me back to the eventual professionalization of college sports with athlete compensation. Schools will find themselves faced with a decision of whether they should spend money on the very best athletes or try to compete with less expensive players. Athletes will have to decide where the best opportunities to develop their professional game are, and how much of their human capital investment portfolio they want to dedicate to sports. What might the equilibrium look like?

We can coarsely reduce the pool of athlete’s into three categories: all-in on athletics, those looking to purely subsidize secondary education, and those aiming for a mix of both. Currently schools capture the most rents from the pure athletics all-ins, who dedicate nothing but the bare minimum to schooling while maximizing their athletic preparation. The all-ins will often be the best players, who get the most media attention and contribute the most to winning glory, attracting applications from young fans and donations from nostalgic alumni. You might expect that compensation would shift the most suprlus to them. We have to consider, however, the possibility that a proper market for elite college athletic labor would provide the prices needed to accelerate the formation of pre-professional academies and player futures contracts. The very best 18-year old basketball players may find it far more lucrative to take a $120K in income and full-time coaching today in exchange for 2% of future professional earnings.

At the same time, college basketball may similarly learn the true nature of their collective good: that it is, in fact, a zero-sum competition where the total amount of talent isn’t nearly as important for earnings as they think. While a small number of schools absorbing all of the top talent might be exciting for covers of no longer existent sports magazines, in reality 120 teams competing for a less skewed distribution of talent more predominantly interested in subsidizing the full cost of college (i.e. tuition, lost wages, etc) may actually make for more drama, which means more ratings, which means more money. Why try to compete with the academies for 1 year of the next Lebron when those same resources, will get you 5 good players for 4 years? Combined with the fact that this bundle of athletes will place greater value on (nearly) marginally costless scholarships, teams looking to compete in the long-term with a maximimally effcient allocation of resources could shift the competitive equiibrium could actually shift away from the top talent.

Sports are fun when they are played at the highest level. They are also fun, however, when a little chaos is injected into the drama. It’s great when Steph Curry casually hits shots 40 feet from the basket, when Lebron James or Nikola Jokic make Matrix-esque passes through impossible angles. But it’s also great watching players struggle at the edge of far more human limitations to a find to win on the biggest stage of their lives while wearing the jersey of one of hundreds of colleges. The highest drama includes players making shots, but sometimes it needs players to dribble off their foot, too.

We don’t have to limit earnings to capture that glory. We don’t have to take money from young people whose particular talents put them in the sliver of the human population whose greatest earning potential might be age 20. We don’t need to appeal to platitudes or false nostalgia to explain why they’re being compensated with something better than money. We can just pay them. Some things will change, but I think you’ll be shocked to see how little the experience of college basketball will change. College sports will remain largely the same, but it will be a bit less shady, a bit less hypocritical. It will place greater value on, and care for, the players they have directly invested in.

Which, at least to me, would be a little more fun.

Why Agent-Based Modeling Never Happened in Economics

I had the title of this post sitting in “Drafts” for a couple months now, but Kris and Paul have given me good reason to actually write about it. These thoughts are largely off the cuff, but they do come from experience.

What is Agent-Based Modeling?

This is not actually as straight-forward question as one might think. If you define it broadly enough as, say, any model within which agents make decisions in accordance with pre-defined rules and assigned attributes, then the answer to the overarching question posed by this post becomes: well, actually, economics has been producing agent-based models for decades, but that answer is as annoying as it is useless.

Instead, let’s start with a minimal definition of an agent-based model:

  1. They are composed of n >3 agents making independent decisions
  2. Agents are individually realized within the model.
  3. Decisions are made in accordance with pre-defined rules. These rules may or may not evolve over time, but the manner in which they evolve are themselves governed by pre-defined rules (e.g. learning, mutation, reproduction under selective pressures, etc).

If we stop at this minimalist definition, then the answer becomes only marginally less trivial, as essentially any dynamic programming/optimal control model within macroeconomics would meet the definition. This leads to what I consider the minimal definiton of an agent-based model as a distinct subclass of computational model:

  1. Agents within the model are characterized by deep heterogeneity.
  2. Agents exist within a finite environment which serves as a constraint in at least one dimension (lattice, sphere, network, etc).
  3. Decisions are made sequentially and repeatedly over time

Now we’re getting farther into the weeds and beginning to differentiate from whole swaths of modern macroeconomics that either employ a “representative agent” or collapse agent attributes to the 1st and 2nd moments of distributions. But that doesn’t eliminate all of modern macro. If embracing heterogeneous agents in your models of macroeconomics, banking, etc, are of interest to you, there are scholars waiting to embrace you with open arms.

Which brings me to the final attribute that I believe fully distinguishes the bulk of the agent-based models and their advocates from modern economics:

  1. Agent-based models exist as permanently dynamic creations, absent any reliance on equilibria as a final outcome, characterization, or prediction.

The departure from general or partial equilibria as outcomes or predictions is where the schism actually occurs and, I suspect, is where many purveyors found themselves with a research product they had a hard time selling to economists. Economics, perhaps more than any other social science, demands that theoretic predictions be testable and falsifiable. Agent-based models (ABMs) don’t always produce particularly tidy predictions that lend themselves to immediate validation. Which doesn’t preclude them from making a scientific contribution, but it puts them on unsteady footing for economists who are used to having a clear path from the model to the data.

OK, but really, why didn’t agent-based modeling happen?

As much as big, irreconcilable differences in scientific philosophy would make for a satisfying explanation, I suspect the most salient reasons are less sexy and, in turn, less flattering of the day-to-day realities of grinding out research in the social sciences. Here are a few.

Economics was already a “model” social science

One of the reasons mobile phones caught on faster in Africa than North America was an absence of infrastructure. The value add of going from “no phones” to “mobile phones” is far larger than going from “reliable land lines in every edifice” to “mobile phones”, making it easier to justify both investments in relevant infrastructure and bearing of personal costs. Such a thing occurred across the social sciences with regards to ABMs.

Rational choice and mathematical sociology always had a limited following. Evolutionary biologists were often alone in their mathematical modeling, computational biology barely existed, and cultural anthropologists were more excited about Marx’s “exchange spheres” than they were about formal models of any kind. For a PhD student in these fields, the first time they saw a Netlogo demonstration of an agent based model, they were seeing something never previously available to their field: the ability to formalize their own theories in a way fully exogenous to themselves. There would be no fighting about what their words actually meant, whose ideas they were mischaracterizing, what they were actually predicting. Their critics, be it journal referees or thesis committee members, would have no choice but to confront their theory as an independent entity in the world.

This advantage of formality, of independent objectivity, in agent-based modeling was not something new to economics. While critics have many (often correct) complaints about modern economics, it’s rare to air concerns that economics is insufficiently formal or mathematized.

Too many “thought leaders”, not enough science

Axtell and Epstein wrote their landmark book “Growing Artificial Societies” in 1996. In it they produced a series of toy simulation models within which simple two-good economies emerged. This wasn’t revolutionary in it’s predictions by any means (whole swaths of macro models were able to make comparable predictions for two decades prior), but the elegance through which minimalist computer code could produce recognizable markets emergent from individual agent decisions was just incredible. The potential to readers was immediately obvious: if we can produce such things from 100 lines of code, what could we simulate the fully realized power of modern programming?

What came next was…still more people evangelizing and extolling the power of ABMs to revolutionize economics. What didn’t come were new models. Forget revolutionary, its hard to even find models that were useful or at least interesting. The ratio of “ABMs are gonna be great” books and articles to actual economic models is disappointing at best, catastrophic to the field at worst.

There were a couple early models that got attention (the artificial Anastazi comes to mind), but after a few years everyone noticed that same 2-3 models were still be brought up as examples by evangelists, and none of them had meaningful economic content. As for the new models that did end up floating out there, there was also an oversupply of “big models”, with millions (billions) of agents and gargantuan amounts of code that intended to make predictions about enormous chaotic systems. Models, such as the Santa Fe Artificial Stock Market, tried to broadly replicate the dynamics of actually stock markets across a large number of dimensions. Such ambitions were greeted with skepticism by economics for a variety of reasons, not least of which the “curse of dimensionality”, which limits what you can learn about underlying mechanisms when the number of modeler choices exceeds your ability to test them or, for that matter, verify their internal coherence. For better or worse, these models felt akin to amateurs trying to predict a town’s weather 30 days out.

Bad models drove out good

The problem of too few good models was closely followed by the over-supply of bad models. Agent-based modeling, for good and for ill, is not a technique with high entry costs. A successful macroeconomic theorist is effectively a Masters-level mathematician, bachelors level computer programmer, and PhD economist. Netlogo programming can be learned in a week. You can get really good at programming agent-based models in a dedicated summer.

This isn’t unto itself a problem, but I can tell you this: in my first 5 years as an assistant professor, I was asked to review at least 100 papers built around agent-based models. I’m not sure if any of them were any good. I am sure that many of them were extremely bad. Most concerning is that I don’t think I learned anything from any of them. The costs of producing bad ABM papers is much lower than the costs of producing bad theory papers based on pure math. Bad science is often evolutionarlily selected for in modern science, a dynamic that in the case of ABMs was only amplified by a lower cost supply curve.

Now, here’s the thing: there was probably huge selection effects into what I interacted with. I doubt I was getting the best papers sent to me for review given my status in the field. But the quantity of bad papers was astonishing. They were just too easy too churn out. I suspect that some decent papers were lost in haystack of ad hoc pseudoscience and, in turn, some decent scientific careers probably got lost in the shuffle. More than once I had the thought “Editors are going to start rolling their eyes every time they see the term agent-based modeling if this what keeps coming across their desks.” Combined with the fact that ABMs are tricky to evaluate because you really need to go through the code to know what is driving the results, I think a lot good modelers got lumped in with the dreck.

[Not for nothing, it wasn’t uncommon for ABM papers to spend the bulk of the paper describing model outputs, while having nearly nothing about model inputs (i.e. rules, code, math, etc). These models were essentially black boxes that expected you to take their coherence on faith. I should note here that I haven’t really kept up with the field in the past few years. Hopefully transparency norms have improved, particularly in biological, ecological, and anthropological modeling, where ABMs have thrived to a far greater extent.]

The empirical revolution took hold of economics

I’ve save the biggest reason for last, but honestly I think it dwarfs the others.

The same rise in cheap computational power that gave rise to other forms of computational modeling, including ABMs, came along with the plummeting cost of data creation, storage, analysis, and access. By 2010 it was already increasingly clear that theory was taking a backseat in economics. Not because we were becoming an a-theoretic discipline (far from it), but because the marginal contribution of theory against the body of broadly accepted economic framings was small compared to those made by empirically testing the predictions of the existing body of theories against real data. The questions were no longer “How do we mentally organize and make sense of the world”, but instead “What is the actual measured effect of X on Y?” Theory gave way to statistical identification. Modeling technique gave way to causal inference.

Agent-based models are hard to empirically evaluate and test

Which gives way to a sort of subsidiary problem. It is more difficult for agent-based models to take advantage of the new data-rich world we live in. They don’t produce neatly direct predictions the way that microeconomic theories do, nor do they lend themselves to measured empirical validation in the same way as general equilibrium predictions of macroeconomic models. Empirical validation is by no means impossible, but it requires the matching of observed dynamics or patterns, which is generally a taller order. In this way, agent-based computational models are a bit of a throwback to the days of “high theory”, making for interesting discussion but of secondary importance when it comes to the assigning of journal real estate that makes and breaks careers.

Bonus story

I once presented my ABM paper on emergent religious divides, only to have an audience member become extremely upset, closing with the denouncement that “This isn’t agent-based modeling, this is economics!” That was my first exposure to the theme of ABMs as “antidote” to the hegemony of economics and all of its false prophecies. The idea that the destiny of ABMs was to unseat economics as the queen of the social sciences was probably an effective marketing strategy in many hallways, but not so much in economics departments (well, maybe at The New School).

So whey should economists give agent-based modeling another shot?

That’s another post for another day. If you’re curious though, I did write about how and why ABMs are useful for economists interested in the study of religious groups and movements. The logic of that piece applies to anyone interested in studying the macroscopic dynamics characterizing social norms, group formation and decay cycles, and how social outliers can pull entire populations in interesting directions.