Commitment problems and military effectiveness

The New York Times on concerns about the Nigerian military’s inability to defeat Boko Haram, which is generating support for a Buhari bid for the presidency:

“The resources meant for the military don’t go to the military; the bullets and boots don’t go to the soldiers,” Ms. Usman said. “And what is happening to security, you see it in all the sectors.”
“The support we’re giving” to Mr. Buhari “is for ending the insurgency,” she added. “And so no more children are abducted.”
A retired general in the crowd of supporters, Alhassan Usman, who is not related to Ms. Usman, agreed, expressing anger that Boko Haram had gained the upper hand over Nigeria’s soldiers.
“The issue is lack of discipline; the commander has eaten his money,” he said, arguing that officers take money meant for soldiers, who then see little reason to obey orders.


Article link.

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Can we hold theory fixed for a minute?

In the current PS, Luke Keele (link) makes a great point about the need for journals to let researchers take existing theories and subject them to multiple rounds of empirical scrutiny:

Of course, there is nothing wrong with new theories; however, I believe that an overemphasis on theory can impede the ability of the discipline to establish causal relationships. One point of emphasis in the identification revolution is that causal inference is difficult. A series of regression models is hardly the last word in whether a causal theory holds. Within causal inference, it is generally understood that only a series of different studies using disparate research designs can provide solid evidence for a causal relationship. This understanding implies that, as opposed to a single test, a theory requires a number of tests from different research designs. We might assert that whereas theory is critically necessary, too many theories might be harmful. It is probably the case that the gain from an incomplete test of a new theory is less than the gain from a new test of an existing theory.

Economics provides a useful example. The question of whether attending college increases income is one of long-standing interest to economists. The theory behind the question is relatively simple. Although I hesitate to state that the causal hypothesis that college leads to higher incomes is definitively settled, a review of the many different research designs used makes a convincing case for a causal effect. If all of the researchers conducting these studies had been told by reviewers that new theory was needed, little progress would have been made.

When we overvalue novel theories, we tend to dismiss attempts to answer old questions with new research designs. We can value papers with new theories and little or no empirics. We also can value papers with little in the way of new theory but that present novel research designs that provide new empirical evidence about causal relationships. We could argue convincingly that both topics require such attention that it may be difficult to present both novel theory and empirics in the same paper. Currently, I would state that, in general, a paper that does not engage in new theory development will have a difficult time being published in a top journal. I don’t think that is healthy. If we really want researchers to clearly establish causal relationships that is often worth doing alone in a single paper.


In my (and Luke’s) home discipline of political science, I have frequently seen reviewers at top journals suggesting rejection for papers because they don’t think the theoretical contribution is novel enough, even if the research design is compelling. (I am not talking about reviews for my own work either, but that of my much more capable colleagues who have discussed their reviews with me.) But journals seem to be okay with papers that propose new theories with no empirical tests whatsoever. Weird, isn’t it?

I am not saying pure theory papers shouldn’t be published—quite the contrary in fact. What makes sense is some division of labor in the discipline. I recognize the importance of pure theory papers. I also recognize the importance of compelling empirical work that offers a new and credible test of an existing theoretical claim. The usual refrain that I hear when I say this is that “top economics journals don’t seem to have this problem,” and with that I agree. I wonder why there is such a difference.

I agree with pretty much everything else in Luke’s paper too. It is part of a symposium on whether “big data,” “causal inference,” and “formal theory” are conflicting trends, an obviously ridiculous proposition, but one that triggered some nice essays by the contributors.

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“Identification” with a group as a physical process

An enduring question in social science is how people come to “identify” with a group and what implications that has for the individual’s behavior as well as the role that the group plays in society. Take for example “identification” with a political party followed by taking actions that promote the influence of the party. As it happens I was recently having a discussion with a graduate student about research on processing of coming to “identify” with a group. You might be thinking that this is all pretty abstract, and even though we hear and maybe even use “identify” all the time, what do we really mean by it?

The seminal work on identity by Akerlof and Kranton (e.g., this or this) provides a great framework for thinking through this. From their framework, identities are social categories that come with ideals and prescribed behaviors. To the extent that one has “internalized” an identity, one feels real pain or anxiety from betraying those ideals or prescribed behaviors. Understanding identity in these terms implies meaningful “identity change” is probably not so easy: it would require an internal rewiring such that behaviors that once produced anxieties now do not. This makes me wonder what is the state of research on the physiology of anxiety due to betrayal of ideals.

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Unification of the social sciences? Gintis’s “The Bounds of Reason”

I recently finished Herbert Gintis’s The Bounds of Reason (link), in which the author tries to bring the foundations of game theory into better alignment with actual social behavior and make a case for the unification of the social and behavioral sciences (economics, psychology, sociology, and political science). Gintis suggests that certain dividing lines drawn between humans and other living beings’ behavior can be indefensible: traits commonly construed as “distinguishing” of humans, like language and property rights, commonly appear among other animals as a matter of fact.

Gintis introduces behavioral postulates that go beyond canonical game theoretical analyses, such as allowing for rational agents to pursue goals that go beyond narrow self-interest. The conflation of rationality with narrow self-interest is major peeve for anyone with more than a cursory knowledge of rational choice theory, myself included, and Gintis does a good job of exposing this fallacy. He also discards improbable or illogical constructs such as deep backward induction or actual randomization in mixed strategies. He shows that by reconfiguring the rudiments in this way, one is able to carry out even more compelling and true-to-life analyses of strategic problems like coordination and commitment without losing tractability. Gintis thus responds to Ariel Rubinstein’s famous statement that “models in economic theory … are not meant to be testable” (quoted on p. 129), calling Rubinstein “dead wrong: the value of a model is its contribution to explaining reality, not its contribution to society’s stock of pithy aphorisms” (p. 129).

Gintis also provides a spirited critique of methodological individualism, another totem to which many assume rational choice theory is tethered. Methodological individualism cannot properly account for the emergence of social norms, social cues, or frames, but norms, cues, and frames are fundamental to social behavior. The repeated games literature has been the primary venue for methodological individualists to explain cooperative behavior. But Gintis demonstrates that attempts to loosen the strict knowledge assumptions that underpin the classical folk theorem have failed to produce compelling explanations for cooperative equilibria. This impels one to think about other sources of cooperative behavior, like hard-wiring, perhaps through evolutionary processes, of other-regarding preferences and “social choreography” through prescriptive norms. Gintis proposes that Robert Aumann’s concept of correlated equilibrium provides analytical foundation for understanding the operation of social norms.

The book is technically demanding at times, and the rather frequent typos don’t help to make it digestible. But it is well worth the attention of researchers across the social sciences.

In fact, I’d be most interested to hear what social psychologists have to say about the book. Social psychology is a branch of the social sciences where formal decision- and game-theoretic modeling has not caught on. But it is also a branch from which economists and political scientists seem to be drawing a lot of inspiration these days. By Gintis’s logic, the translation of social psychological insights into the formal decision and game theoretical models represents a crucial scientific step forward. I wonder whether any of this work in synthesis and formalization will be done by social psychologists themselves?

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What a solid theoretical framework does for you

Paul Krugman had a superb paragraph in a column last week [link], explaining how we can’t get away from theoretical models:

[W]henever somebody claims to have a deeper understanding of economics (or actually anything) that transcends the insights of simple models, my reaction is that this is self-delusion. Any time you make any kind of causal statement about economics, you are at least implicitly using a model of how the economy works. And when you refuse to be explicit about that model, you almost always end up – whether you know it or not – de facto using models that are much more simplistic than the crossing curves or whatever your intellectual opponents are using.


This came to mind today as I was commenting on some student work, and felt the need to explain how important it was to have a strong theoretical foundation even if you are working with a well-identified experiment or natural experiment. Here’s what I wrote (with specific references to the paper removed):

Developing a theoretical framework is important for lots of reasons. First, it provides a basis for both deriving hypotheses coherently and also setting us up to draw out implications from the results of the empirical analysis. Right now the hypotheses sort of come from nowhere, based on some intuitions. But this is inadequate motivation. How would evidence in favor of (or against) these hypotheses affect the implicit or explicit models that we rely on to form expectations about the phenomenon you are studying? Second, it helps people who do not care about the specific application you are studying to take interest nonetheless in your research. Identifying the relevant theoretical framework is a way of addressing the all important question, “what more general thing is this a case of”? (Sorry for the hanging preposition.) We want to reduce the specific, applied problem to something that can be analyzed in a general way such that the results of this particular study have implications for other types of actors in other types of situations.

Well that’s how I see it at least.

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