Methodological Convergence in the Social Sciences

In a post over at orgtheory.net, Fabio Rojas makes the case for more math in sociology:

“By ‘math’ I mean models and proofs, not statistics. That’s an important distinction. Statistics is using math to test hypotheses (verbal or otherwise) with quantitative data. Math is used to express statistical ideas and prove things about them. However, math can also be used to express sociological ideas and derive ideas through logical proof. By ‘math in sociology,’ I mean ‘writing down equations describing social processes (the models) and proving new things about the models.'”

Fabio then goes on to give six reasons why he thinks sociology needs more mathematical theoretical models.

I fully agree with his assessment and, for me, this is part of the methodological convergence that is currently taking place in the social sciences. Let me explain.

As an economist in a policy school, I feel like I have an excellent vantage point on what is going on not just in economics, but also in political science, and sociology — within which I include demography — through the seminars I get to attend. And although I am much less familiar with anthropology, the only paper I have ever refereed for an anthropology journal consisted of a field experiment.

What I have noticed over the five years since I finished my Ph.D. and joined the Sanford School of Public Policy is a methodological convergence in the social sciences, at least as regards the testing of hypotheses derived from economic, political, or sociological theory.

Reference Point

Before addressing the methodological convergence taking place in the social sciences, I should discuss two things about myself which will explain what my reference point was. First, when I was in college at the Université de Montréal, the only students who took any serious statistics in the Faculty of Arts and Sciences were those of us who majored in economics. Students who majored in political science, sociology, or anthropology never took any math or stats classes. In other words, social sciences at my alma mater were done the old-fashioned French way.

Second, toward the end of my Masters in Economics at the Université de Montréal, I briefly dated a French woman who was writing her doctoral dissertation in Paris on the sense of belonging developed by employees at a large multinational corporation which she used to work for. Worse, her structured interviews actually relied on a convenience sample of the friends she had made while she worked for that  corporation!

Back to Our Scheduled Programming

I was thus quite surprised when I came to the US for grad school and discovered that graduate students in political science and sociology were actually required to receive solid training in applied statistics. I was also quite surprised when I discovered many political scientists and sociologists care about identification and establishing causal relationships between variables of interest and dependent variables as much as applied microeconomists do.

What’s more, in political science, there is an entire field dedicated to the empirical investigation of theoretical models (EITM), which closely resembles what we economists would call structural econometrics, so it was only a matter of time until a similar field of EITM emerged in sociology.

I actually welcome the greater emphasis on developing mathematical theoretical models in the social sciences. My motivations do not arise out of some economic imperialism. It’s just that there are obvious benefits to more formalism and there are obvious costs to a complete absence thereof. Among the benefits are the ones noted by Fabio in the post I link to above. For me, the most important benefit of formal theoretical modeling is that it often leads to counterintuitive and unexpected results, and the most important cost incurred in the absence of formal theoretical modeling is that it can open the door to all sorts of abuses by charlatans. (Note: I am not saying that social scientists who do not do any quantitative work are charlatans; that is not what I am saying!)

The End of Disciplinary Departments?

If I am right and there indeed is a convergence in the social sciences in terms of theoretical modeling, this could very well mean that disciplinary departments as we know them (of Economics, of Political Science, of Sociology, etc.) will soon be a thing of the past. Political science departments frequently hire economists. For example, Mike Munger, who recently finished his term as chair of the Department of Political Science at Duke, has a Ph.D. in economics.

It thus looks as though the boundaries between disciplines are becoming increasingly porous. Even economists, who are often accused of imperialism, having been incorporating more and more insights from psychology over the last 15 years. Over the next 50 years, I expect disciplinary departments (e.g., economics, political science, sociology, etc.) to be replaced by “thematic” departments (e.g., international development, education policy, etc.) within which researchers study different facets of a broad problem. I would like to hear what readers think in the comments.

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