Summary of Article on Gender by Thébaud

This paper takes a different approach to the prevailing research on the gender gap in entrepreneurship by pairing the already existent resource-based approaches (that examine an individual’s ability to obtain capital) with new analysis about the so-called “supply side.” Or, in other words, the article intends to examine how women perceive themselves in the marketplace, using status characteristics theory to study the beliefs by which an individual considers entrepreneurship a viable career option. The hypothesis is that men and women draw on beliefs about their gender differently, such that women and men assess their abilities, capacities, and experiences differently. The author constructs four concrete instantiations of that hypothesis. First, men will determine their entrepreneurial competence higher than women, despite no measurable difference in resources. Second, women will on average require a higher level of education. Third, assessing one’s ability positively will have a positive effect on the likelihood of becoming an entrepreneur. Fourth, women entrepreneurs will be less likely to consider themselves competent than men. These hypotheses are reliant on status characteristics theory, which suggests that individuals expect more competence from individuals with higher states (men) versus lower-valued states (women). This theory argues that this will happen regardless of whether or not this is a gendered task. This creates a double standard for assessment; when women do well, it is inconsistent with expectations and thus deserves a second, closer evaluation, whereas for men, doing well is the predicted result.

In order to evaluate these hypotheses, Thébaud uses large-n, logistic regression modeling based on survey data. Specifically, she uses Global Entrepreneurship Monitor (GEM) data, which is a large cross-national dataset with information on individuals; once missing necessary data were excluded, there were 15,242 respondents. The dependent variables are two dummy variables that measure, respectively, self-assessment of capacity to start a business and currently being a business owner. The central independent variable is gender, but there are also a lot of human capital variables and network resources, to try and control that the differentiation in the dependent variable can be attributable to gender.

The results consistently support the hypothesis the researcher offered. Most interestingly, the researcher found that differentiated self-assessments, when added to the regression, accounted for a large portion of the gender inequalities in entrepreneurship. The gender coefficient, sans this addition, indicates that men are 1.15 more likely to be entrepreneurs. When self-assessment is added to the regression, the difference between men and women drops down only to 0.02. That is to say, a lot of the large differentiation between men and women in the data is explained by their differential self-assessments, which begins to speak to a causal hypothesis about the mechanisms that create the distinction.

This suggests that as much as resources are important for developing the capacity to become an entrepreneur and taking on startup investments, first the individual must decide that they are capable of attempting such risky behavior. There is no objective criterion for determining when or if one is ready to become an entrepreneur, allowing for biases based on status assessment to come into play, even when a woman is assessing herself. This research has the limitation of its method, large n regression, which makes it difficult to trace the process of causality Ethnographic research would be better able to assess more complicated network structures, choices, and beliefs for individuals.