The economics departments of research universities are particularly imbalanced. By contrast, at institutions without doctoral programs, more than 40 percent of tenure-track faculty are women. Among nontenured teaching faculty, women account for 37 percent at both types of institutions, suggesting that the barrier to women’s progress has something to do with research.
The root of the problem is in how established researchers evaluate the work of younger colleagues, according to Siniscalchi and Veronesi. If the lack of senior women were just down to implicit bias, the proportion of women at both research and nonresearch colleges would be similar, as would women’s share of tenure-line and nontenure-line professorships. The difference, they reason, could be the way research is evaluated.
Self-image bias is a well-established phenomenon in psychology, but Siniscalchi and Veronesi are the first to build it into a mathematical model to explain the gender gap in academic economics.
Their model assumes some heterogeneity in research characteristics, such as whether the research is empirical or theoretical, deep or broad, as well as its methodology, the field, the topic, the type of questions it asks, and its policy relevance. All of these approaches are equally valuable, but women and men tend to cluster around different characteristics. Consistent with the empirical evidence, the model assumes that the differences within the genders are much more pronounced than the distinctions between them.
Tenured men dominate decisions to hire or promote female economists, and their self-image bias gives extra weight to the more “male” characteristics in making hiring decisions, the researchers argue. In this world, it makes sense that fewer women choose to pursue PhDs because the odds of eventually securing tenure are slimmer than for men. This, in turn, reinforces the dominance of “male” research characteristics.
Without intervention, Siniscalchi and Veronesi’s model suggests, economics cannot achieve gender parity. They therefore conclude that affirmative action—mandating equal gender representation among researchers—may be more effective at preventing the loss of talent incurred because of self-image bias than more traditional policies.