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Gender and Entrepreneurship

Paper Session

Friday, Jan. 3, 2020 2:30 PM - 4:30 PM (PDT)

Marriott Marquis, Grand Ballroom 2
Hosted By: American Economic Association
  • Chair: Rembrand Koning, Harvard Business School

Innovating for People Like Me

Josh Feng
,
University of Utah - Eccles School of Business
Xavier Jaravel
,
London School of Economics

Abstract

This paper shows that unequal rates of innovation across socio-demographic groups affect the direction of innovation, in a way that exacerbates income inequality and the gender wage gap. We build new linked datasets on the socio-demographic characteristics of innovators and their customers, and establish three results. First, we find that innovators create products that are more likely to be purchased by customers similar to them along observable dimensions including gender, age, and socio-economic status. These homophily patterns hold across detailed industries as well as across firms within the same industry, in both the United States and Finland. Second, we use the observed homophily patterns to assess the potential distributional effects of unequal access to innovation in a simple quantitative framework. Compared to the current distribution of innovators' backgrounds, we find that an “equal opportunity” innovator pool would lead to 33% larger welfare gains for households with annual earnings below $60k, relative to those earning more. Similarly, a female-led startup generates welfare gains for female customers that are 27% larger than for male customers. Third, using random assignment of individuals to dorms during military service in Finland, we provide causal evidence that being exposed to peers from a lower income group increases an entrepreneur's propensity to create necessity products. These results indicate that sociological factors can have a significant impact on the direction of innovation, and that equalizing access to innovation across socio-demographic groups has large potential to promote inclusive innovations targeting a broad customer base.

Biased Experiments and the Direction of Product Innovation

Ruiqing Cao
,
National Bureau of Economic Research
Rembrand Koning
,
Harvard Business School
Ramana Nanda
,
Harvard Business School

Abstract

Using detailed data from the online-platform Product Hunt, we show that male and female consumers systematically differ in their preferences for new technology-based products. For each product, we compute a continuous text-based score measuring the gender orientation of the product’s consumer base. We estimate consumer preferences toward products by combining proprietary browsing data with API voting history, and show that the difference between female and male preferences increases in this new product gender measure. Using this measure, we find that female-oriented products acquire significantly fewer new users than male-oriented products upon launching on Product Hunt, and that the difference persists over time. This pattern holds even when the entrepreneurs developing women-oriented products are male. Using the content of daily newsletters as a source of exogenous variation in female user participation on the platform, we find evidence that attracting more women onto the platform leads to improved user acquisition outcome for female-oriented products. Our results highlight how biased signals of demand might bend the direction of product-innovations away form the needs of female consumers. Female entrepreneurs and consumers might lose out when the key gatekeepers to commercialization are mostly male.

Does Gender Matter for Small Business Performance? Experimental Evidence from India

Solène Delecourt
,
Stanford University
Odyssia Ng
,
Stanford University

Abstract

Many well-known studies have shown that female-owned micro-enterprises are less
profitable and have lower returns to capital than their male counterparts. This raises
an important question: what drives the estimated gender gap in business performance?
We examine this question in the context of vegetable sellers in Jaipur, India, a context
where observationally women make less than men. We conduct two field experiments
that keep every business aspect the same except for the gender of the owner, business
aspects such as location, goods supplied, and hours of operation. In Experiment 1, we
isolate demand-side constraints by training confederate sellers to sell packaged goods
at fixed prices using a standardized script, thereby additionally controlling for seller
behavior. In Experiment 2, we only control for supply-side characteristics. In both
experiments, we find that women earn at least as much as men. Our results demonstrate
that the estimated gender earnings gap in this context is not due to differential demand-side
constraints or seller behavior, but instead is likely driven by differences in access
to capital.

The Illegitimacy Premium: The Effect of Entrepreneurship on the Future Employment of Women

Olenka Kacperczyk
,
London Business School
Peter Younkin
,
University of Oregon

Abstract

Using evidence from a resume-based audit and a survey of Marketing and HR executives, this study assesses the effect of pursuing entrepreneurship on the future employment of women. Whereas much research has focused on promoting female entry into entrepreneurship, much less attention has been devoted to understanding whether women are penalized or rewarded when they attempt to re-integrate into paid employment. We propose that, whereas double standards put women at a disadvantage in entering entrepreneurship, the same double-standards might benefit them at exit into paid employment. To the extent that audiences in one context (paid employment) view women as subject to double standards in another context (entrepreneurship), this will likely benefit female entrepreneurs by inclining the audiences (employers) to perceive them as more favorable job candidate (i.e., less likely to de-commit). We find evidence for this claim with data from the audit study and experimental survey on HR professionals.
Discussant(s)
Heather Sarsons
,
University of Chicago
Elizabeth Lyons
,
University of California-San Diego
Pian Shu
,
Georgia Institute of Technology
Rembrand Koning
,
Harvard Business School
JEL Classifications
  • O0 - General
  • J7 - Labor Discrimination