Women Entrepreneurs in Mexico: Breaking Sectoral Segmentation and Increasing Profits Emilia Cucagna, Leonardo Iacovone, and Eliana Rubiano-Matulevich POLICY BRIEF: October, 2020 Key Messages • Female-owned businesses tend to exhibit lower productivity, fewer profits, and less growth potential than male-owned businesses. The di erences may be explained by the nature of the sectors in which women operate. • Mexican women who cross over to operate businesses in male-dominated sectors perform better than noncrossovers in a range of indicators, including sales and profits. • Female entrepreneurs are more likely to cross over if male mentors or role models support them. Role models and mentors have a positive impact on the performance of female-owned businesses. • Female entrepreneurs who tend to take advantage of opportunities are more likely to enter male-domi- nated sectors. • Microentrepreneurship training, complemented by mentoring or exposure to role models, may unlock network and financial opportunities that help women cross over into more profitable sectors. Context Across the globe, women often face lower income opportunities Preferences and aspirations can drive gender-specific constraints relative to men. Women are less likely to participate in the labor and labor market outcomes (Dalton, Ghosal, and Mani 2016). market, and, if they do work, they usually earn less and are more However, a large portion of the gender gap in income and produc- likely to participate in less profitable activities. Similarly, tivity can be explained by labor market frictions or gender norms female-owned businesses tend to show weaker economic perfor- that dictate the types of jobs women and men pursue and are able mance. On average, they are smaller and less profitable and grow to obtain. For example, between 20 percent and 40 percent of more slowly (Carranza, Dhakal, and Love 2018). productivity growth in the United States over the last five decades can be attributed to improved talent allocation, especially among Many of the di erences in economic outcomes can be explained women and black men (Hsieh et al. 2019). by the sectors in which women tend to operate, typically retail (that is, small commerce) and a subset of services. Sectoral segre- gation is tied to di erences in job quality, including wages, bene- fits, and opportunities for growth. Among businesses, Gender Innovation Lab for Latin America female-dominated sectors tend to exhibit less productivity, fewer profits, and lower growth potential than male-dominated sectors and the Caribbean (LACGIL) (Bardasi, Sabarwal, and Terrell 2011; Goldstein, Gonzalez Martinez, and Papineni 2019; Hallward-Driemeier 2011; Rijkers and Costa The LACGIL supports impact evaluations and inferen- 2012; Rosa and Sylla 2016; World Bank 2018). tial research to generate evidence on what works to close gender gaps in human capital, economic partici- Structural factors also contribute to the gender gap in economic pation, social norms, and agency. Additionally, the lab opportunities. Women bear a disproportionate share of childcare disseminates findings to improve operations and policy and housework, have fewer choices in their movement and mobili- making to design cost - e ective interventions that ty, and face gender norms that limit their access to more profitable tackle gender inequalities and drive change. business opportunities (Babbitt, Brown, and Mazaheri 2015; Field et al. 2015; World Bank 2018). In some cases and depending on To do this, the LACGIL works in partnership with World characteristics such as size, age, and sector, female-owned firms Bank units, aid agencies and donors, governments, may have less access to credit, bank accounts, and collateral to nongovernmental organizations, private sector firms, grow their businesses (Aterido, Beck, and Iacovone 2013; Klapper and researchers. and Parker 2011). 1 The Problem At 44 percent, female labor force participation in Mexico is one of the lowest in the Latin America and the Caribbean region.1 Women are concentrated in less productive sectors and in specific occupa- tions (Calónico and Ñopo 2008). Nonetheless, Mexico’s ranking on entrepreneurial activities is high (Fairlie and Woodru 2006). The early-stage entrepreneurial rate has seen steady growth in recent years, and it is currently at around 21 percent of the adult popula- into male-dominated or female-concentrated.a If more than 70 tion. Women account for 51 percent of the entrepreneurs in Mexico, percent of businesses in the survey sample are owned by men, and over 70 percent of women’s entrepreneurial activity is concen- this study defines the sector as male-dominated. This defini- trated in wholesale or retail (Elam et al. 2019).2 tion has been applied to the sample of women entrepreneurs in the experimental baseline survey. There, if more than 70 While sectoral segregation is widespread, evidence suggests percent of businesses in the entire sample are owned by men, that some women succeed in crossing over to male-dominated the study defines the sector as male dominated. Based on this businesses. Thus, a recent global study on sectoral segregation definition, 17 sectors have been classified as male-dominated suggests that female-owned businesses in male-dominated (figure B1.1). sectors make significantly greater profits than those in traditionally female-dominated sectors (Goldstein, Gonzalez Martinez, and Overall, male-dominated sectors in Mexico are capital intensive Papineni 2019). However, country-level evidence on factors that (automotive repair, land transportation, and mining), followed might encourage women to enter male-dominated sectors or by sectors that require information and communication prevent them from doing so is scarce. technology–type skills, finance, and stock market activities. FIGURE B1.1. SECTORS CLASSIFIED AS MALE-DOMINATED (BUSINESSES OWNED BY WOMEN AND MEN, %) Study Description Repair and maintenance of electronic equipment To uncover factors that enable women to cross over to more Internet service providers, web profitable, male-dominated sectors, the analysis used baseline search information services survey data from a randomized controlled trial to evaluate the Wholesale of pharmaceuticals, impact of a personal initiative and business skills training program perfume, domestic electrical appliances in Mexico. The sample consisted of 3,907 formal and informal female entrepreneurs in Mexico City and the states of Aguascalien- Plastic and rubber industry tes, Guanajuato, Mexico, and Querétaro. Using the definition of a male-dominated sector in box 1, the analysis identified 368 cross- over and 3,539 noncrossover female entrepreneurs. Financial service activities Printing and reproduction The analysis investigated the di erences in firm characteristics of recorded media and performance between crossover and noncrossover female entrepreneurs. It also looked for potential di erences in household Manufacture of leather and fur demographics, wealth status, cognitive and noncognitive skills, products (except clothing) access to finance, and external influences to determine the drivers Wholesale of agricultural and forestry of gender segregation in Mexico. It focused on the e ect of the raw materials and waste product presence of a role model or mentor, the e ect of other features, such as cognitive and noncognitive skills, and the likelihood that Wholesale of textiles and footwear women would cross over to male-dominated sectors. By investi- gating these characteristics, the analysis attempted to uncover Services related to transport factors that might help explain the ability of certain women entre- preneurs to cross over and succeed in male-dominated sectors. It Financial, insurance appears that this is the first study of female crossovers in Latin and bond institutions America. Wholesale of food, beverages and tobacco BOX 1: WHAT ARE MALE-DOMINATED Wood industry SECTORS? Freight transport The classification of firms according to their activities in male- or female-dominated sectors is not well established. The Land transportation literature often defines a male-dominated sector as one in (except railway) which men own more than 50 percent of the firms or make up Automotive repair more than 50 percent of the employees in the sector. Some and maintenance studies use a threshold of 75 percent and draw on the responses of entrepreneurs to questions about their percep- Construction tions of the sex of the owners of most enterprises in their sectors (Alibhai et al. 2017; Campos et al. 2015; Goldstein, 0% 20% 40% 60% 80% 100% Gonzalez Martinez, and Papineni 2019; IWPR 2013). Share of male owners Share of female owners Unlike previous studies, this study does not rely on percep- a. ENAMIN (Encuesta Nacional de Micronegocios, National Survey of Microenterprises) tions, but the actual distribution of self-reported ownership by (database), National Institute of Statistics and Geography, Aguascalientes, Mexico, sex to classify male- or female-dominated sectors. It uses the https://www.inegi.org.mx/programas/enamin/2012/?ps=microdatos. distribution of self-reported ownership by sex in a nationally b. Alternative definitions of man-dominated sectors at 65 percent and 75 percent were analyzed, and the results are robust across the di erent classifications. representative survey of microenterprises to classify sectors 1 ILOSTAT Database, International Labour Organization, Geneva, http://www.ilo.org/ilostat/. 2 See ENAMIN (Encuesta Nacional de Micronegocios, National Survey of Microenterprises) (database), National Institute of Statistics and Geography, Aguascalientes, Mexico, https://www.inegi.org.mx/programas/enamin/2012/?ps=microdatos. 2 What is the evidence? Firms owned by women who cross over outperform firms owned This is consistent with the results of the few studies on crossovers by noncrossovers on a range of indicators. The firms of women conducted to date that find that early exposure to male role who operate in male-dominated sectors are nearly twice as profit- models is important in encouraging female entrepreneurs to enter able as the firms of women who remain in female-dominated male-dominated sectors.3 Having a female role model does not sectors. Similarly, the value of sales per day reported by female seem to have any significant impact on the likelihood of crossing entrepreneurs in male-dominated sectors is more than double the over. value reported by female entrepreneurs in traditional sectors. Compared with noncrossovers, crossover firms are significantly Male mentors positively impact female entrepreneurs and larger according to average number of employees (0.7 vs. 1.3). increase the likelihood they will cross over. A mentor is a person These data show that supporting female entrepreneurs in entering who helps the entrepreneur to make important business decisions. male-dominated sectors fosters better firm performance. In the study, 49 percent of crossovers and 46 percent of noncross- overs reported they had mentors.4 More than 60 percent of the entrepreneurs reported they had had mentors for at least four years. Nearly two-thirds of the mentors were men, and most were the husbands or domestic partners of the women. If male mentors support them, women are 5 percent more likely to cross over, relative to women not supported by male mentors. There are various reasons why male mentors matter. The subset of crossover women who had male mentor reported that the mentors had helped them (1) improve their businesses or solve business problems (27 percent), (2) help them start or plan their businesses (25 percent), (3) find clients (20 percent), (4) find new ideas for products or services (12 percent), (5) find suppliers (10 percent), or (6) gain access to financing (7 percent) (figure 1). FIGURE 1. MENTORS HELPED WOMEN ENTREPRENEURS, BY AREA OF ASSISTANCE Find new ideas of products Access finance 6% or services 12% Find suppliers 10% Opportunity entrepreneurs are more likely to cross over. Some women start businesses because they see an opportunity, while other women start businesses out of necessity because they have no other options. According to data collected as part of a larger experimental study, opportunity entrepreneurs typically started Help improving Find clients or or solving new markets businesses because they (1) wanted to become independent, (2) business-related 20% had money and found a good business opportunity, or (3) wanted problems to advance their careers. Less than one entrepreneur in three (27 27% percent) was classified in this category. The results indicate that starting a business to take advantage of an opportunity is associat- ed with a higher probability of entering a male-dominated sector. Moreover, evidence from a large sample of women entrepreneurs in Mexico suggests that, on average, opportunity entrepreneurs show higher profits and sales as well as better management practices than necessity entrepreneurs (Calderón, Iacovone, and Start or help planning business Juarez 2017). 25% Male role models encourage female entrepreneurs to cross over. A role model is a person who serves as an example. In the study sample, 63 percent of female entrepreneurs who had crossed over Male mentors can unlock networking and financial opportunities. reported that they had role models, compared with 54 percent of Male mentors can help female entrepreneurs expand their social noncrossovers. On average, 35 percent of the role models were networks and gain visibility within a sector. They can also help men; fathers were the most common male role models. If women them gain access to financing opportunities to grow their entrepreneurs have male role models who support them, they are businesses. Among female entrepreneurs who reported they had 6.5 percent more likely to cross over, compared with women who mentors, women with male mentors had obtained, on average, 36 have no male role models. percent more credit during the year before the survey. Male role models and male mentors foster business growth. The availability of a role model has a positive e ect on key business performance indicators, even after one controls for the e ect of crossing over. Among female entrepreneurs who reported they had role models, the women with male role models showed, on average, 50 percent higher profits per week and 70 percent higher revenues per week. Male role models are also associated with higher levels of business activity (3.2 more working hours per week), even after one controls for crossing over. Among female entrepreneurs who reported they had mentors, the women with male mentors showed, on average, 29 percent higher profits and 35 percent higher revenues per week. They also had an average of 3.4 more clients and sold 12 more products per day. 3 See Alibhai et al. (2017) on Ethiopia and Campos et al. (2015) on Uganda. 4 The di erence between crossovers and noncrossovers is not statistically significant in this case. 3 The educational attainment of their fathers matters in women • Complement skills training programs with mentorship opportuni- crossing over. The study analyzed the e ect of the educational ties. Networks are often less widely available and less diverse level of the fathers and mothers of female entrepreneurs. It found among female entrepreneurs, which places the women at a that one additional year in a father’s educational attainment disadvantage. If they become part of skills training, male peers increases the probability that a female entrepreneur crosses over can be valuable as business partners or in providing support, to a male-dominated sector by 0.3 percent, after controlling for thereby increasing the likelihood that the women cross over to the woman’s educational level, her mother’s educational level, and sectors with higher returns. Thus, programs designed to empow- cognitive skills. The e ect of a mother’s educational attainment is er women through skills training or cash grants may be more not statistically significant. successful if they are complemented with mentorship support (de Mel, McKenzie, and Woodru 2009). Cognitive skills have a substantial e ect on the likelihood of crossing over. Women who cross over seem to di er from • Incorporate smart designs in skills training programs. Skills noncrossovers in various measures of cognitive skills. Thus, one training programs might o er opportunities to improve additional year of education is associated with a 0.5 percent outcomes among female entrepreneurs. However, because of increase in the probability of crossing over. This implies that a family responsibilities, movement restrictions, and gender female entrepreneur with secondary education will be 3 percent- norms, it is often more di cult for women than men to access age points more likely than a female entrepreneur with only prima- and complete such programs (Cho and Honorati 2013; Hicks et ry education to enter a male-dominated sector. Female entrepre- al. 2011). Although the precise skills needed is not yet clear, it is neurs with substantial cognitive abilities, as measured through important that programs integrate smart design that helps Raven’s Progressive Matrices (a nonverbal test of abstract reason- women overcome constraints (World Bank 2020). Operational ing typically given in educational settings), are also 0.8 percent aspects include holding training in accessible and safe locations, more likely to cross over (Tang, Karunanithi, and Shyu 2018). Mean- arranging childcare options to help women participate as in the while, noncognitive skills do not seem to a ect the probability of case of the Jóvenes en Acción Program in Colombia (Attanasio, choosing a male-dominated sector. Kugler, and Meghir 2009), and making transportation easy and safe as in the Peruvian Projoven jobs training program. These programs have shown long-term positive employment outcomes among both women and men. Policy • Provide information on sector-specific profitability. Providing information about higher return businesses in man-dominated sectors relative to female-concentrated sectors could change recommendations beliefs about profitability and encourage women to enter male-dominated fields. It may also motivate women to enroll in skills training in nontraditional trades. Information can be o ered through career guidance in schools, informational sessions • Understand the factors that allow women to cross over into more accompanying skills training programs, or edutainment (Bjor- profitable male-dominated sectors, thereby helping in the design vatn et al. 2020). E orts aimed at supplying female entrepre- of interventions that enable women to develop businesses that neurs information about the di erential returns in male-dominat- reduce gender gaps in economic opportunities. Rigorous ed sectors may matter, but there are few rigorous studies evidence on what works in assisting women to cross over into available, and they are focused on lower-middle-income coun- male-dominated sector is scarce, but promising. tries. For example, an intervention in Kenya used posters and handouts to display information on the returns to vocational • Complement microentrepreneurship programs by exposure to education among women and men engaged in di erent fields of male role models. Standard microentrepreneurship programs work. The information treatment encouraged women to prefer that incorporate male role models can foster motivation and and ultimately enroll in traditionally male-dominated trades initiative. Exposure to a successful role model may provide (Hicks et al. 2016). information about the returns in male-dominated fields and help women gain market information (Field et al. 2016; Wilson 2012). Male role models could also a ect behavior by incentivizing female entrepreneurs to apply the successful business practices of men or by encouraging women to make the decisions STAY CONNECTED required for the business to succeed (Bursztyn et al. 2014). Visit the LACGIL website for more information. • Evidence from a training program in Chile suggests that a role E-mail: lacgenderlab@worldbank.org model intervention generates impacts similar to those of inten- sive technical assistance at a lower cost and may be more well ACKNOWLEDGMENTS suited for less highly experienced entrepreneurs (Lafortune, This work has been funded by the Umbrella Facility for Gender Riutort, and Tessada 2018). In Indonesia, an intervention combin- Equality (UFGE), which is a multi-donor trust fund administered ing information on local best practices with exposure to success- by the World Bank to advance gender equality and women’s ful role models led to significant improvements in sales and empowerment through experimentation and knowledge creation profits (Dalton et al. 2019). Building on the literature on the to help governments and the private sector focus policy and returns to education, future research could explore the e ective- programs on scalable solutions with sustainable outcomes. The ness of using role models to socialize the expected returns in UFGE is supported with generous contributions from Australia, male-dominated sectors (Jensen 2010; Nguyen 2008). Canada, Denmark, Germany, Iceland, Latvia, the Netherlands, Norway, Spain, Sweden, Switzerland, United Kingdom, United • Engage men in entrepreneurship training programs. Microentre- States, and the Bill and Melinda Gates Foundation. preneurship programs can engage husbands and other men relatives to o set gender norms or attitudes that might The findings, interpretations, and conclusions expressed in this constrain women from successfully participating in the brief are entirely those of the authors. They do not necessarily programs. Female entrepreneurs with male role models or male reflect the views of the World Bank, its a liated organizations, mentors (other than husbands) are more likely to cross over. Men the Executive Directors of the World Bank, or the governments could be encouraged to introduce female entrepreneurs to their they represent. business networks, pass on key technical skills, and help the women gain access to financing opportunities. This material should not be repro- duced or distributed without the UMBRELLA FACILITY FOR GENDER EQUALITY World Bank's prior consent. 1818 H. St NW Washington, DC 20433 4 REFERENCES Alibhai, Salman, Nicklas Buehren, Sreelakshmi Papineni, and Rachael Susan Goldstein, Markus P., Paula Gonzalez Martinez, and Sreelakshmi Papineni. 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