Policy Research Working Paper 11281 Closing the Gender Gap in Entrepreneurship Overcoming Challenges in Law and Practice for Female Entrepreneurs Daniela M. Behr Yue Sophie Xi Global Indicators Group A verified reproducibility package for this paper is January 2026 available at http://reproducibility.worldbank.org, click here for direct access. Policy Research Working Paper 11281 Abstract Despite significant strides toward gender equality, women of stylized facts that illustrate how overcoming some of around the world continue to encounter systemic obsta- these existing barriers is correlated with improved wom- cles that hinder their entrepreneurial success. This paper en’s entrepreneurship and female labor force participation, systematically reviews the literature on the barriers female drawing on the World Bank’s Women, Business and the entrepreneurs face and the solutions proposed to overcome Law database as well as the World Bank’s Enterprise Surveys. these challenges. It discusses institutional factors, financial The findings underscore the need for creating an enabling factors, human capital factors, and social and cultural fac- environment where women can thrive as entrepreneurs. tors. The literature overview is complemented by a series This paper is a product of the Global Indicators Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at dbehr@worldbank.org; yxi@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click here for direct access. RESEA CY LI R CH PO TRANSPARENT ANALYSIS S W R R E O KI P NG PA The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Closing the Gender Gap in Entrepreneurship: Overcoming Challenges in Law and Practice for Female Entrepreneurs* Daniela M. Behr+; Yue Sophie Xi§ Authorized for distribution by Tea Trumbic, Manager, Global Indicators Group, Development Economics, World Bank Group Keywords: entrepreneurship, gender equality, women-led businesses JEL Codes: J16, J21, K38, L26, O12 _____ * We are grateful for feedback received from participants of the World Bank DECIG brown bag seminar series as well as Mend the Gap conference participants. The draft benefitted greatly from helpful comments, feedback, and guidance from Norman Loayza, Tea Trumbic, Ana Maria Tribin Uribe, Alev Gurbuz Cuneo, Clémence Pougué Biyong, Diego Ubfal, the Women, Business and the Law and Enterprise Surveys Team. This research was funded by the Gates Foundation (Grant: INV-061562). All remaining errors are our own. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. + Daniela M. Behr: DECIG, World Bank, Washington, DC. Email: dbehr@worldbank.org § Yue Sophie Xi: DECIG, World Bank, Washington, DC. Email: yxi@worldbank.org 1. Introduction Women entrepreneurs are powerful agents of change and have the potential to turbocharge the economy. They are not only businesses developers, but also job creators, innovators, and solution providers to social, environmental, and economic issues in most countries around the world (Bullough et al. 2022; Duflo 2012). Despite the benefits of female entrepreneurship, women remain underrepresented at all stages in the entrepreneurial ecosystem: from developing intentions and launching startups to growing new businesses, running established enterprises, and ultimately exiting the market. Across the board, entrepreneurship remains a male-dominated activity, and the gender gap remains particularly large for established business ownership (GEM 2023). Women entrepreneurs are facing both supply-side barriers—such as limited access to finance, business training, and markets—as well as demand-side challenges, including consumer biases or exclusion from key supply chains. The economic toll of these barriers is substantial, both on women and on societies. When women are unable to fully participate in the entrepreneurial ecosystem, economies miss out on potential contributions in terms of innovation, job creation, and economic output. Research increasingly supports the idea that expanding women’s economic opportunities is beneficial for both economic growth and development (Christopherson et al. 2022; Gonzales et al. 2015; Hyland et al. 2020; Sever 2023). Studies have shown that removing barriers to women’s economic participation can lead to substantial increases in GDP and overall economic growth and resilience (Cavalcanti and Tavares 2016; Chiplunkar and Goldberg 2021; Goldberg et al. 2024; Klasen and Lamanna 2009; Seguino 2000; Pennings 2022). Expanding women’s opportunities in entrepreneurship and the formal labor force are interconnected pathways to economic empowerment, enabling women to drive productivity, innovation, and economic resilience (Acs et al. 2008; Klapper and Parker 2011). Recognizing the need to overcome barriers, governments worldwide are working to enhance women’s labor force participation and support women’s entrepreneurial ventures. The purpose of this paper is twofold: First, we systematically review the literature identifying systemic barriers that women entrepreneurs face. In doing so, we assess existing evidence on how these barriers can efficiently be addressed, complementing recent reviews on what works for women entrepreneurs (Jennings and Brush 2013; Siegrist 2022, 2025; and Ubfal 2024). Second, we draw on data from the Women, Business and the Law (WBL) database, which measures legal rights and regulatory provisions – or the absence thereof – for women across 190 economies, 1 as well as firm-level data from the World Bank Enterprise Surveys (WBES) in 167 economies and 1 Women, Business and the Law consists of two data sets: (1) a panel data set spanning five decades from 1970-2023, covering eight indicators Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets, and Pension (referred to as WBL 1.0); (2) a cross-section dataset introducing two new indicators—Safety and Childcare—and using a new three-pillar framework, presenting indexes on legal frameworks, supportive frameworks, and expert opinions for ten indicators (referred to as WBL 2.0). For an overview on the various datasets and components, refer to: https://wbl.worldbank.org/en/wbl-data. 2 document in a series of stylized facts on how overcoming existing barriers can improve women’s entrepreneurship and labor market outcomes. Assessing both labor force participation and entrepreneurial activities is essential because these two domains represent the principal channels through which women engage in economic life, and each is shaped by distinct but overlapping sets of constraints, incentives, and policy levers. Labor force participation captures women’s engagement in wage and salaried employment, while entrepreneurship reflects self-employment and business ownership, both of which are critical for inclusive growth, poverty reduction, and gender equality. By analyzing both, we can disentangle the extent to which barriers differentially affect women’s ability to access wage employment versus start and grow businesses and identify complementarities and trade-offs in how to address these barriers efficiently. 2. Addressing Existing Barriers for Women Entrepreneurs Entrepreneurship is a driving force in today’s economy, with women playing an increasingly important role. Across the globe, gender inequality in entrepreneurship is a well-documented issue, with numerous studies highlighting the disparities between men and women in both the likelihood of becoming entrepreneurs and the success rates of their businesses in terms of profits, sales, or employment (e.g., Allison et al. 2023; Campos et al. 2019; Fairlie and Robb 2009; Fang et al. 2022; Jayachandran 2021; Islam et al. 2020; Klapper and Parker 2011). While the ratio of female to male entrepreneurship varies widely across countries, on average, women entrepreneurs are outnumbered by men in many parts of the world—often by a wide margin (GEM 2023; OECD/EC 2023). A stark gender gap persists in established business ownership, where there are 0.68 women for every one man, compared to a more balanced ratio of 0.80 in start-ups (GEM 2023). However, these averages may mask significant sectoral and regional variation. According to the WBES, while one in three businesses are owned by women, in some countries or industries, women-led firms may be virtually non-existent and there is a great variance across regions (figure 1). 3 Figure 1: Percentage of Firms with Women Ownership Participation by Region, Manufacturing Sector Note: The data presented in this graph are drawn from the World Bank’s Enterprise Surveys (WBES), covering 167 economies as of October 6, 2025. The data have been weighted appropriately and include selected data points from the most recent survey conducted in each of the 167 economies covered. The specific data point analyzed is the presence of female ownership within firms, as indicated by the survey question, “Amongst the owners of the firm, are there any females?” Every dot denotes the country average of the manufacturing sector. Regional medians are highlighted in red. A more detailed breakdown by firm size is presented in Annex 1. Literature commonly differentiates two types of entrepreneurs: necessity-driven and opportunity- driven entrepreneurs (e.g., Eddleston and Powell 2012; van der Zwan et al. 2012). Necessity- driven entrepreneurship occurs when entrepreneurs start businesses due to limited employment opportunities, financial hardship, or external economic pressures, often leading to informal, low- growth enterprises (Acs et al. 2008). In contrast, opportunity-driven entrepreneurs establish businesses to capitalize on market gaps, introduce innovations, or scale new ventures, contributing to economic dynamism and technological progress (Schumpeter 1934; Stam and van Stel 2011). Literature suggests that women may be more motivated by social needs, rather than focusing on traditional business outcomes such as growth or profit (e.g., Solesvik et al. 2019). In some countries, women may find entry into self-employment easier than overcoming barriers to entering formal sector jobs. For instance, Mroczkowski (1997) notes that many women in Poland began their businesses to escape unemployment following the post-communist transformation. Women may also decide to venture into entrepreneurship because they want to be independent or to enjoy flexibility that being self-employed provides (Babbit et al. 2015). Likewise, women may explore entrepreneurship as an option which provides them with the flexibility to work from home helping them to better balance work and household responsibilities (Edwards and Field-Hendrey 2002; Oladipo et al. 2023). In contrast, in countries where institutional agreements provide for flexible work arrangements and support mechanisms such as paid leave or subsidized childcare, women are found to be less likely to opt for business ownership as a fallback employment strategy (Thébaud 2015). 4 In many emerging markets and developing economies, according to the Global Entrepreneurship Monitor (GEM), women are still more likely to become entrepreneurs out of necessity rather than opportunity with almost three in four women (72.9 percent) citing this reason for business startup compared to about two-thirds of men (67.2 percent) (GEM 2023). Likewise, most women still operate subsistence-oriented micro businesses (Elam et al. 2021; La Porta and Schleifer 2014) and women-owned enterprises are more likely to be home-based, relying on personal savings rather than external financing (Coleman and Robb 2009). Further, female entrepreneurs are found to manage smaller and less productive firms, often operating within lower-productivity sectors of the economy (Fairlie and Robb 2009; Hardy and Kagy 2018; Islam et al. 2020; Rijkers and Costa 2012). Differences across female and male entrepreneurs can be attributed to specific barriers that women face that men do not. These barriers can shape how women perceive their abilities to start and sustain a business, develop an entrepreneurial mindset, navigate the socio-economic and cultural environment, and build essential networks and relationships. A comprehensive review of the literature reveals that institutional, financial, human capital, and sociocultural barriers are the most critical factors shaping the entrepreneurial experiences of women worldwide (see Annex 2 for the literature search strategy). Institutional factors may include barriers found in laws and policies that can restrict women’s equal opportunities in running and starting a business. Financial factors include barriers women may face related to obtaining credit or navigating financial systems, accessing equity financing or grants. Human capital factors include support through for instance business training or accelerator programs. Social and cultural factors encompass social norms, gender stereotypes and biases, or societal expectations that may limit women’s participation in the entrepreneurial ecosystem. In addition to identifying key barriers, the literature review systematically assesses the range and effectiveness of interventions designed to overcome these challenges, highlighting both successful strategies and gaps in current approaches. By synthesizing evidence from diverse contexts, the review not only catalogs solutions but also critically examines how and why certain policies, programs, and ecosystem-level changes facilitate women’s entrepreneurial advancement and what gaps remain. 2.1 Institutional and Enabling Factors Institutional factors, such as laws and regulations, play a crucial role in shaping the entrepreneurial landscape by either limiting or encouraging business creation. Restrictive legal frameworks, such as those that prevent women from owning property, accessing credit, or signing contracts independently, can significantly hinder female entrepreneurship by limiting their economic autonomy (Klapper and Parker 2011). Conversely, gender-responsive legal reforms, including those promoting equal property rights, financial inclusion policies, and non-discriminatory business regulations, can create an enabling environment that fosters women’s participation in entrepreneurship (Acs et al. 2008). 5 Legal Reform Around the world, women still encounter discriminatory laws that hinder their ability to start a business. In eight economies, for instance, women are directly constrained in undertaking entrepreneurial activities as they need their husband’s permission, signature, or information to open a bank account, sign a contract, or register a business (World Bank 2024a). 2 Likewise, in 20 economies, women are still prohibited from working at night; in 45 economies, they face legal restrictions on performing jobs deemed dangerous; and in 59 countries, women are constrained in working in certain sectors, such as mining, construction or transportation which are often higher paying (World Bank 2024a). On the one hand, these legal constraints have the potential to limit women’s entrepreneurial opportunities by reducing their access to higher-paying industries and preventing them from gaining diverse work experience, which is crucial for developing entrepreneurial skills and networks. On the other hand, restrictions like these may also push women into necessity-driven entrepreneurship, as limited formal employment options force them to start small, informal businesses as a means of survival rather than opportunity-driven ventures. Women have a higher probability of being in vulnerable employment than men of similar characteristics in countries where women cannot register a business and open a bank account in the same way as a man (e.g., Bue et al. 2022). Abdo and Kerbage (2012) reinforce these findings through a mixed-method analysis of organizations supporting women’s entrepreneurship development initiatives in Lebanon, revealing that sectarian inheritance laws continue to restrict Lebanese women’s access to land and resources, thereby limiting their ability to start and grow businesses. Likewise, legal barriers placed on women are negatively correlated with the proportion of new female business owners and sole proprietors, implying that they constitute a significant barrier for the development of female entrepreneurship (Meunier et al. 2017). Using data from over 59,000 firms in 94 economies, Islam et al. (2019) find that unequal laws significantly hinder women’s participation in the workforce and reduce their chances of becoming managers or business owners. In contrast, examining 24 industrialized countries, Thébaud (2015) finds that in countries with supportive work-family policies such as such as paid leave, subsidized childcare, and part-time employment opportunities, women are less likely to opt for business ownership as a fallback employment strategy but are more inclined to engage in growth-oriented forms of entrepreneurship. There has been significant progress, with several countries repealing legal restrictions, now allowing women to access a broader range of job opportunities on equal terms with men. For example, in 2022, Azerbaijan reformed its laws to repeal 674 job restrictions that prevented women from taking up specific professions – including roles such as driving large buses or laying asphalt (World Bank 2024a). Likewise, in May 2023, Sierra Leone eliminated restrictions on women’s 2 Cameroon, Chad, Equatorial Guinea, Eswatini, Guinea-Bissau, Kenya, Niger, and Suriname. 6 employment in the mining, construction, factories, energy, water and transportation industries (Behr and Cheney 2024). Across the board, literature finds that removing barriers like these is an important pre-condition to fostering female labor force participation and female entrepreneurship (Gonzales et al. 2015; Hallward-Driemeier and Gajigo 2015; Hyland et al. 2020). Legal reforms that expand women’s property and contractual rights have measurable economic effects. Ethiopia’s 2000 family-law reform, which granted married women equal rights to administer property and enter contracts, increased female employment and self-employment, specifically for young, single women (Hallward-Driemeier and Gajigo 2015). In India, amendments to the Hindu Succession Act enhanced daughters’ inheritance rights, boosting women’s asset ownership, education, and self- employment (Deininger et al. 2013). Further, Rietveld and Patel (2022) examine the relationship between gender inequality and entrepreneurial activity across 97 countries between 2006 and 2017, using the World Economic Forum’s Global Gender Gap Index as a measure of gender inequality and individual-level data from the Global Entrepreneurship Monitor to assess entrepreneurial activity. Their findings show that overall rates of early-stage entrepreneurial activity are higher in countries with greater gender equality and that across all countries, women are systematically less likely than men to engage in early-stage entrepreneurship (Rietveld and Patel 2022). Access to Business Opportunities Access to markets and opportunities is essential for the success of any business, yet women entrepreneurs often face significant obstacles. Women-owned small and medium enterprises (WSMEs) are underrepresented in regional and global value chains, as well as in public procurement opportunities. This underrepresentation is constraining women’s business opportunities since public procurement typically constitutes about 10–20 percent of a country’s GDP, with a global expenditure estimated at nearly US$9.5 trillion a year (WTO 2015). Despite this vast market potential, women-owned businesses globally earn less than 1-2 percent of the money spent on products and services by large corporations and governments (McManus 2011; Vazquez and Sherman 2013; Vazquez and Frankel 2017). Women business owners have been found to work harder than men to convince “government procurement officials and corporate customers that they are as competent as men” (Brush 1998, p. 163) and the probability that a women-owned business wins a government contract is significantly lower than that of their male-owned counterparts (Bates 2002). Several factors contribute to this disparity. Women entrepreneurs often lack the necessary contacts, information, and networks to become suppliers in corporate and public value chains. Moreover, enterprises within supply chains often require working capital to bridge payment gaps, but stringent bank requirements make it difficult for WSMEs to obtain such loans (International Trade Centre 2020; We-Fi and IFC 2021; We-Fi and World Bank 2020). In a regression discontinuity design, Brogaard et al. (2024) find that female politicians increase the proportion of U.S. government procurement contracts allocated to women-owned firms by 4.5 percentage points. In a back-of-the envelope calculation, the authors 7 find that the representation of female politicians led to a transfer of US$6.9 billion worth of government contracts to women-owned businesses in 2020 (Brogaard et al. 2024). Data and Supportive Policy Mechanisms Supportive policy mechanisms can further constrain or support female entrepreneurs. For policy makers to address barriers that female entrepreneurs face, they need comprehensive and accurate data that capture the realities of women (Bonfert et al. 2023). The collection of high-quality, quantifiable sex-disaggregated data is fundamental to the design of gender-smart policies. Yet, there is a stark absence of data on women-owned or women-led businesses, leading to considerable barriers to better understanding the factors holding women entrepreneurs back (Siegrist 2022). According to the most recent Women, Business and the Law data, of 190 economies, there are only 67 economies that regularly publish sex-disaggregated data on business activities, entrepreneurship or women-owned businesses (World Bank 2024a). Limited data management capabilities, a lack of common standards and definitions leading to inconsistencies, and low data quality, as well as a lack of awareness about the value of sex-disaggregated data are among the frequent challenges cited by regulators (Siegrist 2022). 2.2 Financial Factors Access to finance plays a crucial role in shaping women’s ability to start, sustain, and expand their businesses. Despite some progress in recent decades, women continue to face substantial disparities in accessing financial resources, both on the demand and supply side. According to recent data, approximately 700 million women, 55 percent of the unbanked adults worldwide, still lack access to bank services (Demirgüç-Kunt et al. 2025). Although the gender gap in financial inclusion has narrowed from 9 to 6 percentage points, it remains persistently high, disproportionately affecting women entrepreneurs. Likewise, about 70 percent of formal WSMEs in developing countries are underserved by financial institutions or are unable to obtain financial services to meet their needs. The total micro, small, or medium enterprise (MSME) finance gap for women is estimated to be valued at US$1.9 trillion, amounting to over 7 percent of total GDP (IFC 2025). Data from the WBES show that, on average, among a sample of 177 economies, only 5.64 percent of female respondents have reported borrowing any money to start, operate, or expand a business within a year (World Bank 2024b). Access to Credit Access to credit and financing is crucial for firm growth and plays a pivotal role in fostering new business creation (e.g., Beck et al. 2005; Banerjee and Duflo 2014; De Mel et al. 2008; Dupas and Robinson 2013; Klapper and Parker 2011). Despite the critical importance of credit, women frequently encounter barriers both on the demand and the supply sides, such as biased lending practices, lack of collateral, and limited access to financial networks. On the demand side, a growing body of literature has documented that women are more reluctant to apply for credit due to perceived discrimination or fear of rejection (e.g. Alesina et al. 2013a; 8 Galli et al. 2020; Treichel and Scott 2006). Using survey data from 17 countries, Ongena and Popov (2016) show that female-owned firms are more likely to opt out of the loan application process and to resort to informal finance than male-owned firms because they believe their request will not be approved. Similarly, Moro et al. (2017), for a large sample of European SMEs, show that women are more reluctant to file a loan application in the first place as they anticipate being rejected by the lender. Further, literature finds that negative past experiences with financial institutions can deter women from future credit applications. A study focusing on female small business owners in China revealed that women who had previously been denied credit were more likely to be discouraged from reapplying compared to their male counterparts (Caglayan et al. 2022). On the supply side, there are various factors constraining women’s access to capital. First, empirical evidence indicates that women-owned businesses face a higher likelihood of loan denial than men (e.g., Morazzoni and Sy 2022; Muravyev et al. 2009). Drawing on the Business Environment and Enterprise Performance Survey (BEEPS) across 34 countries, mostly the transition states of Central and Eastern Europe, Muravyev et al. (2009) show that the probability of receiving a loan is about 5 percent lower for female-owned/managed firms than for male- owned/managed enterprises. The authors find that female entrepreneurs are charged higher interest rates (about 0.5 percentage points) when loan applications are approved (Muravyev et al. 2009). Second, female entrepreneurs that do receive a bank loan are found to receive smaller loan amounts (e.g., Agier and Szafarz 2013; Bellucci et al. 2010; Demirgüç-Kunt et al. 2018). Grover and Viollaz (2025), for instance, drawing on firm-level data across 61 economies, show that female-managed firms are equally likely to apply for credit as their male counterparts, but they receive lower levels of credit either because they apply for lower amounts or because they are granted less than they requested. Third, women are found to face higher interest rates, greater collateral requirements, or worse price conditions (e.g., Alesina et al. 2013a; Asiedu et al. 2012; Mascia and Rossi 2017). Alesina and colleagues (2013a) find that women pay higher interest rates even though they are not significantly riskier, have gone bankrupt less often than male-owned businesses, and have a better credit history. Interestingly, the differential remains when including bank fixed effects, meaning that the gap can also not be explained by women choosing a specific type of bank (Alesina et al. 2013a, 46). Similarly, Mascia and Rossi (2017), using data from the European Central Bank’s Survey on the Access to Finance of Enterprises (SAFE), reveal that female-led firms face higher interest rates, fees, and commissions compared to their male-led counterparts, while firms that transition from female to male leadership are more likely to experience a reduction in interest rates. There are several explanations for these observed gender differences. One potential explanation is discriminatory behavior by loan officers, whether intentional or subconscious. Fay and Williams (1993), in a pioneering experimental study in New Zealand, demonstrate that loan officers considered educational qualifications more critical for female applicants than for males when 9 assessing loan eligibility. More recently, Alibhai and colleagues (2020), in assessing drivers of gender disparities in SME lending, identify that loan officers are significantly more biased against female applicants. Beck et al. (2018) exploit the quasi-random assignment of borrowers to loan officers to find that borrowers matched to officers of the opposite sex are less likely to return for a second loan. An experiment conducted by Brock and De Hass (2023) in Türkiye revealed that loan officers are 26 percent more likely to request a guarantor when the applicant is a female entrepreneur rather than a male entrepreneur. Assessing avenues in how to mitigate this bias, Bellucci and colleagues (2010) show that the presence of female loan officers is associated with lower collateral requirements when the borrowers are women and with lower interest rates when the borrowers are men. Access to Equity Financing Across the board, female entrepreneurs face greater challenges than male entrepreneurs when raising capital from venture capitalists or business angels (Koziol et al. 2025). Despite having businesses comparable in quality and potential, women entrepreneurs consistently receive less private equity financing (Bapna and Ganco 2021; Brooks et al. 2015; Ewens and Townsend 2020; Guzman and Kacperczyk 2019; Paglia and Harjoto 2014). According to data from PitchBook (2025), venture capital (VC) funding for female-founded startups has remained disproportionately low across the board. In Europe and the United States, in 2023, companies founded exclusively by women secured approximately 1.8-2 percent of the total VC invested (PitchBook 2025).While the disparity persists across regions and contexts, highlighting a systemic issue within the investment landscape, literature shows mixed results as to why women entrepreneurs are less likely to receive VC. Overall, female entrepreneurs have a lower number of deal counts and receive less capital overall (Bellucci et al. 2025; Edelman et al. 2018; PitchBook, 2025). Research suggests that women are held to different standards in obtaining financing from venture capitalists, and male- founded start-ups are significantly more likely to receive funding compared to those founded by women (Aernoudt and De San José 2020; Brush et al. 2018; Edelman et al. 2018; Guzman and Kacperczyk 2019; Nigam et al. 2022). Using data from all US businesses registered in California and Massachusetts, Guzman and Kacperczyk (2019) show that female-led businesses are 63 percentage points less likely than male-led businesses to obtain VC. Especially for early-stage start-up funding where business track records are limited, investors may rely strongly on observable characteristics and may subjectively assess ventures when making investment decisions (Pierrakis and Owen 2022). As such, education, experience, personality, and team attributes play a key role during investors’ decision-making, proxying for future success (Mason and Stark 2004; Pierrakis and Owen 2022). Such informal evaluations have the potential to exacerbate gender biases. For instance, Tinkler et al. (2015) find that female entrepreneurs with non-technical backgrounds had the lowest assessments of competency and leadership ability and received significantly less capital investment. At the same time, the authors also show that holding technical expertise is a significant 10 advantage for female entrepreneurs seeking VC. In contrast Lins and Lutz (2016), surprisingly, find that women entrepreneurs with a university degree have a greater disadvantage at raising capital, compared to their male counterparts who in lieu of higher degrees had more time in building their skills and networks for their entrepreneurial career. In contrast, Brush and Elam (2024), in a matched case-control sample approach across VC funded firms from 2011-2016, show that a degree from a reputable educational institution can offset potential gender discounts for women-led ventures. In addition, funders’ perceptions and attitudes toward female entrepreneurs have consistently been identified to affect women’s success in raising capital. The VC industry is overwhelmingly male dominated, with men making up 94 percent of VC partners (Brush et al. 2018). In this male- dominated environment, investors overall seem to prefer pitches by male entrepreneurs to those by female entrepreneurs due to bias against female entrepreneurs spanning from legitimacy issues, gender stereotypes, and gender homophily. For instance, Brooks et al. (2015) suggest that investors may perceive female entrepreneurs as less competent or less capable of scaling their businesses. Bapna and Ganco (2021), in a randomized field experiment find that inexperienced female investors are significantly more interested (138%) in ventures with female founders than those with male founders; however, the authors do not find gender preferences among experienced female investors concluding that the role of founder gender is less relevant for more experienced investors in equity crowdfunding. Ewens and Townsend (2020) highlight the role of network effects in perpetuating funding disparities. Male entrepreneurs often have better access to influential networks and investors, which can facilitate introductions and funding opportunities. Female entrepreneurs, on the other hand, may struggle to penetrate these male-dominated networks. Guzman and Kacperczyk (2019) explore how risk perception might differ when evaluating male versus female entrepreneurs. Investors might perceive women-led ventures as riskier investments, possibly due to stereotypes about women’s risk tolerance and business acumen. When asking founders questions early in interactions to understand a venture, investors are found to ask female founders more difficult questions compared to male founders, focusing on promotion-focused questions for men and failure-questions for women (Kanze et al. 2018; Miller et al. 2024). Access to Grants Research suggests that grants can be a viable alternative to other funding sources such as loans or VC, specifically for women running microenterprises (for an overview, ILO 2014; Abebe et al. 2025). Grants can influence firm performance in two ways: directly, they provide much-needed capital that enables firms to invest, grow, or overcome financial constraints; indirectly, receiving a grant can serve as a “quality stamp,” signaling credibility to investors, customers, and lenders, thereby opening doors to additional opportunities and resources (Srhoj 2022). Yet, the evidence on the impact of those grants on firm success is scattered. Comparing cash to in- kind grants in a randomized experiment in Ghana, Fafchamps et al. (2014) reveal a “flypaper 11 effect”, where in-kind grants led to significant increases in business profits, particularly among female-owned enterprises, while cash grants did not yield similar improvements. This suggests that capital provided directly as business assets is more likely to be retained and utilized effectively within the enterprise, whereas cash grants may be diverted to non-business uses. Similarly, other studies also reveal that women entrepreneurs are found to not always invest grant money into their own business but instead may use the funds for household spending or for investing in the husband’s business (Bernhardt et al. 2019; Jakiela and Ozier 2016). Experimental evidence from Tunisia targeting marginalized and poor women shows that cash grants had limited effects on income generating activities of vulnerable women, but boosted women’s access to finance and usage of financial institutions (Ferrah et al. 2021). Women in the treatment group were 8.5 percentage points more likely to have a bank account and they have higher levels of savings and are more likely to have borrowed money and repaid their debt (Ferrah et al. 2021). Using a quasi- experimental approach in Croatia to estimate the causal effects of small business development matching grants, Srhoj et al. (2022) find a positive effects on business growth, particularly among experienced women entrepreneurs. The study further suggests that these grants are a cost-effective policy tool for fostering small firm expansion. Larger cash grants are also found to significantly improve WSMEs’ business performance, while small cash grants can cover household expenses (Campos and Gassier 2017). Recently Abebe et al. (2025) systematically review causal studies on interventions improving women’s access to productive capital in low- and middle-income economies. They find that grants can stimulate women’s entrepreneurship and profitability, especially for those with higher baseline performance, but effects are often short-lived and limited for women running subsistence businesses. 2.3 Human Capital Factors Globally, more than US$1 billion is spent subsidizing business training programs (McKenzie 2021). Yet, literature on the effectiveness of support programs is rather mixed, with some studies demonstrating significant improvements in business outcomes while others report limited or null effects. Mixed results on business training programs may be driven by differences in the populations studied (Lang and Seither 2024). Business Training Programs Entrepreneurial and business training programs have become a central strategy in supporting women entrepreneurs. These interventions aim to build business and soft skills, enhance managerial capacity, and address gender-specific barriers. Several high-quality experimental studies show that targeted training interventions can positively affect business performance, particularly when designed to meet specific needs and contexts. For example, the International Labor Organization’s GET Ahead gender-sensitive entrepreneurship training program, tested in Viet Nam and Kenya, showed significant improvements in business practices and, in Kenya, increased profits and sales after three years (Bulte et al. 2017; McKenzie and Puerto 2021). In Malawi, Campos et al. (2015) demonstrate that formalization assistance not 12 only increased business registration rates but also improved access to finance for entrepreneurs. The intervention’s success is attributed to combining business training with targeted support for formalization. Similarly, Karlan and Valdivia (2011) evaluate a business training program for microfinance clients in Peru and find significant improvements in revenue and profit, alongside enhanced client retention rates. Similarly, Clayton (2024) finds that female entrepreneurs benefit more than men from participating in entrepreneurial education programs. McKenzie (2021) systematically reviews entrepreneurial training programs and finds modest improvements in business outcomes, particularly in formalization and revenue growth. On the other hand, personal initiative training, which focuses on mentorship rather than just technical skills, has shown more promising results. A meta-analysis by McKenzie and colleagues (2023) reveals that personal initiative training increased profits by 14 percent and sales by 10 percent on average. For example, Brooks et al. (2018) find that mentorship for women-owned microenterprises in Kenya led to higher profit growth compared to basic business training. Moreover, Campos et al. (2017) highlight the efficacy of personal initiative training in Togo, which led to a 30 percent increase in business profits over two and a half years, outperforming traditional business training. Yet, in an updated study assessing the long-term impact, the authors find that the impacts are very different for men and women: while the impact for men grows over time as they accumulate more capital and increase self-efficacy, the impact for women dissipates (Campos et al. 2024). While positive outcomes are evident in some contexts, other studies find more mixed results. Berge et al. (2015) report that business and soft skills training in Tanzania significantly boosted sales and profits, especially for male entrepreneurs. However, the impact on women entrepreneurs was notably lower, suggesting that training alone may not suffice in overcoming structural and social barriers. De Mel et al. (2014) conducted a randomized controlled trial in Sri Lanka, assessing the impact of cash grants and training on women-owned businesses. While the combination of training and grants yielded a temporary boost in profits, training alone showed limited effectiveness. The study highlights the critical role of financial capital in leveraging training benefits. Bruhn et al. (2010) emphasize the need for holistic interventions that address not only financial constraints but also human and social capital deficiencies. Their study demonstrates that comprehensive programs combining financial support and skill-building yield more sustainable outcomes. Klinger and Schündeln (2011) conducted a randomized control trial (RCT) in Central America revealing that the overall training intervention is successful in inducing the creation of new businesses and the expansion of existing businesses for women, but not at the same rate as men. Similarly, De Mel et al. (2012) found that training alone did not lead to substantial business growth among Sri Lankan microentrepreneurs. McKenzie and Woodruff (2014) caution that while many programs show short-term gains, the long-term effects often dissipate within one to two years post-intervention. Brooks et al. (2018) support this, showing that the positive impact of mentorship on women-owned businesses in Kenya diminishes once the support ceases. 13 Economies often suffer from a lack of a clear policy framework for supporting women entrepreneurs specifically, increasing the likelihood of fragmented, small-scale support system that is not well-aligned with policy objectives and that struggle to sustain their operations in the medium-term (OECD / EU 2023). While scholars largely concur on the positive, short-term effects of comprehensive gender-sensitive entrepreneurship support programs, the long-term effects have yet to be determined (McKenzie and Woodruff 2014; De Mel et al. 2012; Klinger and Schündeln 2011). Accelerator Programs Business accelerators – fast‐paced entrepreneurial programs – have become a vital component of the entrepreneurial ecosystems. Accelerators are entrepreneurial programs often utilizing extensive consultation with mentors, program directors, customers, guest speakers, alumni and peers “that provide cohorts of ventures with mentoring and education” (Hallen et al. 2020: 380). The original success of what is widely regarded as the first accelerator, Y Combinator launched in 2005, has led to a proliferation of accelerators worldwide (Lall et al. 2020). Accelerator programs usually provide training and technical assistance along with mentorship and networking support to aspiring entrepreneurs and help firms, particularly those new to the scene with capital investments (Cohen et al. 2018; Crișan 2021; Gonzalez-Uribe and Leatherbee 2018). Accelerator programs, during early stages can improve startups’ access to growth and funding, but with heterogeneous effects (Hallen et al. 2023; Pierrakis and Owen 2022). As women entrepreneurs often face knowledge, network, and capital gaps, literature suggests that accelerators are well positioned to overcome gender biases (Dames et al. 2022; Neumeyer 2022). Avnimelech and Rechter’s (2023) recent study of accelerator participants in Israel finds that accelerators have the potential to act as powerful catalysts for women’s successful integration into the entrepreneurial ecosystem and in reducing the gender gap in entrepreneurship. Similarly Dams et al. (2022) maintain that women-led ventures who have participated in an accelerator program increased their chances of equity financing by 14-30 percent compared to men-led ventures, most likely due to the intensive one-on-one counseling received. Chen (2020) further shows that accelerators can speed up startup development by mitigating entrepreneurs’ challenges to obtain capital and expertise, especially for female entrepreneurs. While these studies suggests that accelerators can support women entrepreneurship at the individual level, others maintain that accelerators cannot live up to their promise in helping women-led ventures to overcome systemic gender biases and are hence not yet ready to drive meaningful change in the entrepreneurial landscape (Galmangodage et al. 2025; Lall et al. 2020). Overall, findings on gender effects of accelerator programs are mixed and require further investigation (Dams et al. 2022; Kher et al. 2023; Hallen et al. 2020). 2.4 Social and Cultural Factors Social and cultural factors significantly shape women’s entrepreneurial activities and their ability to succeed in business. Social norms, cultural beliefs, and gender stereotypes can either hinder or 14 support women entrepreneurs, depending on the context and prevailing societal values (Bullough et al. 2022). Social Norms and Gender Expectations Social and cultural norms, defined by Guiso et al. (2006) as the customary beliefs and values transmitted rather unchanged from generation to generation, play a crucial role in determining the success or failure of women’s entrepreneurial activities across different societies. Unlike laws, social and cultural norms are not formally codified or upheld by material penalties or fines. They are widely recognized within a given society and informally enforced by social sanctions and rewards (Lane et al. 2023). Long-established cultural practices, such as the traditional division of labor and societal expectations around family responsibilities, contribute to persistent gender biases that can affect women’s entrepreneurship by shaping attitudes toward female entrepreneurship and limiting both opportunity and agency (Giuliano 2020; Alesina et al. 2013b). Traditionally, women have been more involved in household chores and domestic care duties, including childcare, which often leads to increased economic dependence, decreased interpersonal power, greater career discontinuity or shorter work hours (Becker 1965; Bertrand et al. 2010; GEM 2023; Hundley 2001; Folbre and Nelson 2000). Recent assessments on the impact of the COVID- 19 pandemic, for instance, highlight that female entrepreneurs were disproportionately impacted due to sector effects and taking on a greater share of household responsibilities, such as childcare and homeschooling during this period (OECD/European Commission 2021). Jayachandran (2021) further highlights that restrictive gender norms, such as expectations around domestic responsibilities and cultural beliefs about appropriate roles for women, significantly hinder women’s employment opportunities and economic empowerment. Marriage and motherhood often curtail women’s participation in entrepreneurial activities, particularly in societies where conservative patriarchal values continue to dominate (Villa 2019). Female participation in entrepreneurship, for instance, can challenge the established power structures within a family, unsettling the previously established distribution of responsibilities and activities (Karim et al. 2023). As such, women often face substantial internalized social norms and intra- household pressures to invest in their partner’s business rather than accumulating the capital needed for their own income-generating activities (Rubalcava et al. 2009; Bernhardt et al. 2019). Gender norms surrounding household roles and earnings expectations can shape women’s business activities. Women may disproportionately self-select into lower-return sectors because prevailing social norms assign men the role of primary earners and associate higher-income or capital- intensive enterprises with masculinity (Bertrand et al. 2015; Murray-Close and Heggeness 2019). By the same token, gender norms may pressure (married) women to engage more in household chores to fit societal expectations, which in turn diminishes their entrepreneurial intentions, even when resources are available (Bertrand et al. 2015; Karim et al. 2023). 15 Conversely, societies characterized by more egalitarian social norms and higher tolerance for gender equality exhibit stronger female entrepreneurial participation, more gender-equal legal frameworks, and better implementation of those laws (Bussolo et al. 2025). Analyzing the effect of entrepreneurial ecosystems in 75 countries between 2001 and 2014 on the rates of entrepreneurship for men and women using aggregate data GEM, Hechavarría and Ingram (2019) find that low barriers to business entry and cultural norms are the most important factors to increase venture creation among women globally. Overall, the interplay between cultural norms, institutional frameworks, and social expectations remains central to understanding cross-country variations in women’s entrepreneurship, yet the relationship of gender role expectations and the entrepreneurial ecosystem are hitherto still under- researched factors. Gender Stereotypes and Entrepreneurial Perceptions Gender stereotypes, which attribute certain characteristics such as competence or status differently to men and women, can lead to lower evaluations of female entrepreneurs (Botelho and Abraham 2017; Ridgeway and Correll 2004; Snellman and Solal 2023) or can shape carer choices based on what society deems desirable and appropriate for one’s sex (Achtenhagen and Welter 2003). Entrepreneurs are often perceived as bold, strategic, and risk-taking—traits that are stereotypically associated with men. Such gendered perceptions not only influence women’s own decisions to pursue entrepreneurship but also shape how they are viewed and treated within the business community, potentially limiting access to networks, mentorship, and investment opportunities that are more readily available to their male counterparts (Marlow 2002; Ufuk and Özgen 2001). Further, since female entrepreneurs are generally less visible in the popular media (De Bruin et al. 2006; Gupta et al. 2008), role models of high-profile, successful female entrepreneurs are sparse (Marlow and McAdam 2013), resulting in the popular assumption that entrepreneurs are male (Ahl 2006; Liñán et al. 2021). Yet, role models and exposure to female founders who break stereotypes, can encourage female employees to pursue entrepreneurship and reduce the gender gap (e.g., Rocha and van Praag 2020). Role models can help challenge prevailing norms and reshape individual aspirations and self-perception (Perrin et al. 2023; Priyanka 2020). The growing body of literature on the impact of female business leadership on accounting performance, financial structure, and firm survival indicates that women in leadership positions can positively influence firm outcomes, challenging the stereotype that women are less competent in business (Ahern and Dittmar 2012; Matsa and Miller 2013; Weber and Zulehner 2010). Networks and Social Capital Social and cultural norms can result in female entrepreneurs having less robust networks compared to their male counterparts. There is growing evidence suggesting that female networks are smaller and less diverse, more often confined to private spheres, such as kinship and friendship, which are influenced by religion, culture, and societal expectations (Greenberg and Mollick 2017; Loscocco 16 et al. 2009; Mitra and Basit 2021). Further, women entrepreneurs are also more likely to be excluded from networks of a powerful few (Yetim 2008). Recent data from GEM show that compared to men, women globally are about 10 percent less likely to know an entrepreneur (GEM 2023). These limited networks can impede access to essential resources, knowledge, and opportunities that are crucial for business success (Field et al. 2010; Lockett et al. 2013; Yang et al. 2019). However, building strong networks can help women overcome gender-based limitations in entrepreneurship. Networks provide access to essential resources, knowledge, leadership opportunities, and can help identify new business prospects (Cai and Szeidl 2018; Vega-Redondo et al. 2019). Networks play a pivotal role in leveling the playing field for women entrepreneurs (Baughn et al. 2006). For instance, Venkatesh et al. (2017) in a field quasi-experiment among women in rural India, examine the impact of networks and technology on entrepreneurship. The authors find that access to technology and stronger social networks significantly increased the entrepreneurial activities and business success of women in these communities (Venkatesh et al. 2017). Field et al. (2016) examine whether peer effects can encourage female entrepreneurship in India. Using a randomized controlled trial, they assigned women to attend business training with friends or strangers. Women who trained with friends were more likely to attend sessions, complete the training, and start a business. Peer support also boosted confidence and reduced social barriers to entrepreneurship. The study highlights the importance of leveraging social networks to enhance program effectiveness. 2.5 From Barriers to Enablers Across institutional, financial, human-capital, and cultural dimensions, the literature demonstrates that closing gender gaps in entrepreneurship requires mutually reinforcing reforms rather than isolated interventions. First, legal equality and enforcement create the foundational incentives for women to participate in the labor force and engage in entrepreneurship. Robust country-level evidence shows that when restrictions on women’s economic agency are repealed, women’s participation and firm ownership increase measurably. Equal legal rights, both in property and inheritance rights, as well as labor or family law expand women’s access to assets and markets, creating opportunities for firm growth. Yet gaps remain in the implementation and monitoring of these reforms, particularly in low- income settings where institutional capacity is weak. Evaluations of procurement reforms remain limited, and more empirical research is needed to assess their effectiveness in driving women- owned enterprises’ access to larger and more formal markets. Second, interventions related to financial inclusion—access to credit, VC, and grants—have expanded women’s access to finance, but their effectiveness varies considerably across contexts. Programs that address both supply- and demand-side constraints, such as reducing bias in lending and building women’s confidence to apply for credit, show encouraging results. However, persistent disparities remain: women continue to face higher collateral requirements, smaller loan 17 amounts, and less favorable loan terms. Overall, literature shows that loans and grants can generate positive impacts on women’s business outcomes but may show limited or no effect in others. Grants can stimulate entrepreneurship and profitability, especially among women with higher baseline performance, but impacts can be short-lived for subsistence firms. Third, human-capital interventions work best when personalized, sustained, and embedded within supportive ecosystems. Randomized evidence highlights that training emphasizing personal initiative, goal setting, and mentorship outperforms traditional business courses. Holistic programs that combine skill-building, financial access, and network development yield more durable results, whereas short or stand-alone trainings show modest or short-lived effects. Intersectional factors, such as age, location, and socioeconomic status, shape outcomes, yet remain under-researched. The evidence suggests that, especially for women, gains from training may dissipate over time. Fourth, shifting social norms and expectations is essential to sustain progress. Interventions that promote role models, build peer networks, and challenge gender stereotypes have proven effective in altering perceptions about women’s economic leadership. Exposure to successful female entrepreneurs and supportive networks can help raise aspirations and entry rates into entrepreneurship. However, deeply entrenched cultural beliefs continue to limit the scalability of these interventions. Research on norm change is still in its infancy but seems to be most durable when paired with complementary policies such as childcare, parental leave, and flexible work arrangements that redistribute unpaid care and allow women to convert new opportunities into sustained economic activity. To conclude, women occupy a dual position: as entrepreneurs and as women navigating structural gender inequalities. This duality underscores the need for environments that safeguard women’s legal rights while fostering entrepreneurial ecosystems equipped with accessible finance, networks, and knowledge-exchange platforms. Legal reforms, financial-inclusion initiatives, comprehensive human-capital programs and socio-cultural shifts are interrelated elements that together define an enabling environment for women’s entrepreneurship. In many economies, private-sector initiatives preceded formal legislation, and subnational pilots often pave the way for national reform. These variations illustrate that building an enabling ecosystem for women entrepreneurs is an iterative, multi-layered process, requiring both legal transformation and continuous support mechanisms to sustain participation and growth. 3. Three Stylized Facts on Creating an Enabling Environment for Women Entrepreneurs Building on the preceding discussion of the barriers and enablers of women’s entrepreneurship, this section turns to the empirical evidence to examine two sides of the same coin of women’s economic rights: women’s participation in formal employment and their engagement in entrepreneurship. 18 The analysis draws primarily on the World Bank Group’s Women, Business and the Law (WBL) database (see Annex 3), which provides a comprehensive measure of the legal and regulatory frameworks shaping women’s economic participation. Complementary data from the World Bank Enterprise Surveys (WBES) are used to assess associations between an enabling environment and firm-level outcomes (see Annex 4). Detailed descriptions of these datasets are presented in the sections corresponding to each stylized fact. Together, these analyses underscore that fostering women’s economic empowerment requires not only targeted programs but also comprehensive legal and institutional reforms that translate rights into tangible opportunities for entrepreneurship. Stylized Fact 1: Government-led programs to support female entrepreneurs are most prevalent in ECA Globally, the implementation of government-led support programs for female entrepreneurs remains highly uneven (figure 2). As of October 2023, 77 economies have at least one government initiative that provides access to finance combined with training, coaching, or business development services (World Bank 2024b). These programs vary significantly in scope and ambition—some target women owning micro or small businesses, others support women operating in the informal sector, while a few focus on helping established entrepreneurs scale up. Figure 2. Globally, 77 economies provide support programs for female entrepreneurs Note: This map illustrates economies’ performance in relation to the question: “Are there government-led programs supporting female entrepreneurs by providing access to finance, training, coaching, or business development?” Source: Women, Business and the Law 2024. 19 While the existence of such programs alone does not capture their effectiveness, their presence – or absence – reveals much about a government’s commitment to fostering an enabling environment for women’s entrepreneurship. The literature emphasizes that entrepreneurial ecosystems are context-dependent and that outcomes depend on how well programs are integrated into broader frameworks that address structural barriers (Elam et al. 2021; Minniti and Naudé 2010). Examining whether countries have comprehensive entrepreneurship programs rather than isolated interventions therefore provides a first indication of the depth of institutional support for women entrepreneurs. There is great regional variance of availability of these government-led programs. The Europe and Central Asia (ECA) 3 region stands out as a leader in providing support to women entrepreneurs, with 65 percent of economies in the region (15 out of 23) implementing both financial facilitation and capacity-building programs to boost female entrepreneurship. Other regions follow with fewer economies implementing support programs for female entrepreneurs: Latin America and the Caribbean at 56 percent, South Asia at 50 percent, OECD high-income economies at 44 percent, East Asia and Pacific at 36 percent, Sub-Saharan Africa at 25 percent, and Middle East and North Africa region at 20 percent. Some programs are an all-in-one, amalgamating various elements within a single initiative, while others represent a suite of ongoing efforts under a broader development strategy (World Bank 2024a). Recent global developments illustrate this variation. Canada’s Women Entrepreneurship Strategy (WES) launched in 2018, represents nearly CAD 7 billion in commitments across federal agencies to expand women’s access to finance, mentorship, and markets, including a Loan Fund, an Ecosystem Fund, and supplier-diversity initiatives in public procurement (Government of Canada 2025). Italy’s Women’s Enterprise Fund (Fondo Impresa Donna) provides non-repayable grants and subsidized loans to promote the creation and growth of women-led businesses, supported by accompanying measures (mentoring, technical and management support, work-life balance measures, etc.), multimedia communication campaigns and events, and monitoring and evaluation actions (Government of Italy 2021). Tajikistan has approved the “National Strategy for Enhancing the Role of Women in the Republic of Tajikistan for 2021-2030” under Government Decree No. 167. This strategy aims to raise the status of women in society by ensuring gender equality and promoting female entrepreneurship through various measures, including financial support, business skills training, and the creation of economic opportunities for women, particularly in rural areas. Further, established by Government Decree No. 5 on January 28, 2021, a dedicated grant program for women’s entrepreneurship (2021–2025) allocates 120 annual grants to support and develop women’s entrepreneurial activities. Likewise, Uzbekistan has implemented several 3 This paper follows the classification of Europe & Central Asia used in the Women, Business and the Law (WBL) database. The economies under this classification include Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Kazakhstan, Kosovo, Kyrgyz Republic, Moldova, Montenegro, North Macedonia, Romania, Russian Federation, Serbia, Tajikistan, Türkiye, Ukraine, and Uzbekistan. Please note that WBL’s database has a separate classification of high-income OECD economies. 20 government-led programs as part of a comprehensive national strategy to foster women’s economic empowerment. Uzbekistan has provided mentorship grants, and a nationwide training program aimed at building entrepreneurial skills among women, particularly those registered in the “Women’s Registry.” The government has also established Women’s Entrepreneurship Centers and a Council of Women Entrepreneurs to provide institutional support, legal advocacy, and business development services. Similarly, the Kyrgyz Republic has adopted a state program for the support and development of women’s entrepreneurship in the Kyrgyz Republic for 2022- 2026. This national program aims to enhance women’s economic empowerment by improving access to finance, business development services, and initiatives to strengthen women’s agency. Administered primarily through civil society organizations with both government and donor support, the program aims at making financial services more accessible to economically active women through special loans and financial instruments offered by state banks. While the long-term effects of these government-led initiatives are not yet evaluated, their existence signals an important shift: governments are increasingly cognizant of the structural barriers women face in entrepreneurship and committed to addressing them through integrated, large-scale strategies. These programs move beyond isolated, small-scale interventions by embedding support for women entrepreneurs into national development agendas, combining access to financial resources with skills development, mentorship, and institutional support. Nevertheless, systematic empirical research is needed to assess their effectiveness, distributional impact, and sustainability over time. Rigorous evaluations could illuminate which design features most effectively enhance women’s entrepreneurial outcomes and inform the development of evidence-based policy models for broader replication. Stylized Fact 2: Removing existing legal barriers for women is positively associated with female labor force participation Despite much progress, economies continue to uphold laws that restrict women’s ability to hold property, become entrepreneurs, or make autonomous decisions in the public or private sphere (World Bank 2024b). Evidence shows that legal gender equality, measured by Women, Business and the Law is positively correlated with women’s labor force participation, especially in the non- agricultural sector (figure 3). Removing existing legal and regulatory barriers outlined in section 2.1 is, therefore, crucial for empowering women to participate in the economy and to step into an enabling environment in the entrepreneurial ecosystem. 21 Figure 3: Gender equitable laws are associated with higher female labor force participation Note: Results from a cross-sectional regression analysis, controlling for (logged) gross domestic product (GDP) per capita, show a statistically significant and positive association between the WBL 2.0 Legal Score (2023) and women’s labor force participation in the non-agricultural sector. GDP per capita data are sourced from the World Bank’s World Development Indicators. To account for more observations, the analysis uses the latest available GDP per capita value for each economy within the 2022–2023 period. Using a fixed-effects panel regression, we assess the association of legal gender equality on women’s labor force participation in the non-agricultural sector while controlling for time- and country-invariant characteristics. We ran the following specification: =   0 +   (, −3) +  (, −3) + + +  (, ) (1) FLFP denotes female labor force participation in the non-agricultural sector in economy e. We focus on women’s labor force participation in the non-agricultural sector following Hyland et al. (2020), as it is typically characterized by formal employment relationships, wage contracts, and standardized working conditions. In contrast, the agricultural sector in many countries often consists of informal or subsistence work that does not adhere to formal labor regulations or standardized practices. As a result, legal frameworks that guarantee equal rights and protections for women are more likely to be implemented and monitored in the non-agricultural sector. WBL represents the Women, Business and the Law index or one of its compositive 8 indicators of Economy e at time t-3, GDPpce is economy’s GDP per capita at time t-3 and is country-fixed and is year-fixed effects to control for time- and country-invariant characteristics, e,t is the error term. 22 The results indicate that a higher score on the WBL index is positively associated with an improvement in women’s participation in the non-agricultural labor market (table 1). The estimated coefficient indicates that a one-point increase in the WBL legal index is associated with a 0.1 percentage point rise in women’s labor force participation in the non-agriculture sector. A ten-point increase in an economy’s WBL score—for example, from 70 to 80—is associated with an average rise of approximately one percentage point in female labor force participation. While this increase may appear modest in absolute terms, it can translate into hundreds of thousands of additional women joining the labor force in a given economy. Moreover, a one percentage point gain is comparable to the effects of well-identified policy interventions. For instance, a study from the United Kingdom found that providing full-time free childcare, as opposed to part-time, increased the likelihood of mothers participating in the labor force by three percentage points and being in paid work by one percentage point during the first term of eligibility (Brewer et al. 2020). Table 1: Regression Results Showing Association Between Gender Equitable Laws and Women Participation in Non-Agricultural Labor Market (1) Labor force participation rate (nonagricultural), female Legal gender equality, WBL Index (3-year lag) 0.119*** (4.06) GDP per capita (log) (3-year lag) 0.882 (1.95) Constant 16.83*** (3.45) R-squared 0.448 Observations 6,025 Number of economies 177 Cluster Economy Country Dummies Yes Year Dummies Yes Note: This regression includes economy and year fixed effects. Robust standard errors are reported in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001. The outcome variable is the female labor force participation rate in the nonagricultural sector. Data on female labor force participation in the non-agricultural sector come from two sources—national estimates and modeled the ILO estimates, both of which are available via the World Bank’s World Development Indicators database (World Bank 2020c). We use national estimates only for the 32 high-income OECD economies and use modeled ILO estimates for all others. Data on GDP per capita are retrieved from the World Bank’s World Development Indicators database. When assessing these findings at the indicator level, it becomes apparent that not all the Women, Business and the Law indicators, which capture specific areas of the law, matter for female labor force participation in the same way (table 2). Interestingly, Mobility and Marriage have the highest coefficient among the eight indicators, suggesting that laws regulating intra-household dynamics related to whether a woman can get a divorce or become head of household have a strong association with female labor force participation. These results underscore the idea that gender- 23 equal laws across a wide range of domains—not just in employment regulations—are important for enabling women’s full economic participation. This correlation aligns with a growing body of evidence showing that family law is a powerful economic institution shaping women’s intra- household bargaining power and labor market decisions (Behr and Braunmiller 2025; Deininger et al. 2013; Gonzales et al. 2015). Table 2: Regression results, by indicator DV: Female Labor Force Participation (1) (2) (3) (4) (5) (6) (7) (8) (9) WBL Mobility Workplace Pay Marriage Parenthood Entrepreneurship Assets Pension WBL INDICATOR (3-year lag) 0.119*** 0.0647** 0.0336*** 0.0258* 0.0532** 0.0401* 0.0289* 0.0306 -0.00402 (4.06) (2.74) (3.61) (2.22) (2.86) (2.47) (2.02) (1.24) (-0.35) GDP Per Capita (log. 3-year lag) 0.882 1.014* 0.939* 0.896 0.937* 0.886 0.980* 1.019* 0.993* (1.95) (2.17) (2.04) (1.91) (2.05) (1.95) (2.10) (2.17) (2.12) Constant 16.83*** 16.38** 21.82*** 21.15*** 19.41*** 22.07*** 20.10*** 19.56*** 21.99*** (3.45) (3.19) (4.52) (4.27) (3.90) (4.40) (4.06) (3.91) (4.30) Observations 6,025 6,025 6,025 6,025 6,025 6,025 6,025 6,025 6,025 Number of countries 177 177 177 177 177 177 177 177 177 Cluster Country Country Country Country Country Country Country Country Country Country dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes Year dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes R-squared 0.448 0.434 0.443 0.433 0.438 0.437 0.432 0.431 0.428 Note: This table reports the coefficients and robust standard errors (in brackets). All models are ordinary least squares regressions at the country level. Regressions include economy and year fixed effects. All models have variance robust to heteroscedasticity and clustered at the country level. *** p<0.01, ** p<0.05, * p<0.1. The outcome variable is the female labor force participation rate in the nonagricultural sector. Data on female labor force participation in the non-agricultural sector come from two sources—national estimates and modeled the ILO estimates, both of which are available via the World Bank’s World Development Indicators database (World Bank 2020c). We use national estimates only for the 32 high- income OECD economies and use modeled ILO estimates for all others. Data on GDP per capita are retrieved from the World Bank’s World Development Indicators database. While these associations are evident, the issue of causality warrants further discussion. Legal reforms may both influence and be influenced by women’s labor force participation, making causal direction difficult to establish within the current specification. Existing literature (e.g., Hallward- Driemeier and Gajigo 2015; Hyland et al. 2020) documents evidence for both directions of influence—stronger legal rights can increase women’s participation, while rising female economic activity can also spur legal reform. Untangling these dynamics requires empirical strategies that exploit exogenous variation. Progressive legislation may also emerge in response to broader social change, further complicating causal attribution. Recent experimental evidence from Saudi Arabia (Abou Daher et al. 2025) illustrates this complexity: granting women the legal right to drive led to substantial increases in female employment, highlighting the causal impact of mobility rights. Yet the reform also catalyzed broader shifts in social norms and employer behavior, which collectively amplified women’s labor market participation. 24 Stylized Fact 3: Removing legal barriers is associated with greater female entrepreneurship This section assesses how removing legal barriers is associated with greater women’s participation in firm ownership, but at the country and firm levels. Hence, enabling environments not only facilitate women’s entry into formal labor markets but also expand their opportunities to participate equally in decision-making and business leadership roles. The first stage draws on economy-level data to explore the relationship between legal gender equality and women’s participation in firm ownership across countries with varying Women, Business and the Law (WBL) 2.0 Legal Scores (ranging from 0 to 100) (figure 4). Data on percentage of firms with female participation in ownership, 4 come from the World Bank Enterprise Surveys (WBES), which use a standardized global methodology to ensure cross-country comparability and are available at both the firm and economy levels. The analysis shows that greater legal gender equality is strongly associated with increased women’s entrepreneurship, as enabling legal frameworks that remove barriers for women entrepreneurs can foster more women-owned firms. Figure 4: Gender equitable laws are associated with more firms with women participation in ownership Note: In the scatterplot above, each point represents a single economy within a region. A fitted regression line (red) is also included. Results from a cross-sectional regression analysis, controlling for (logged) GDP per capita, show a statistically significant association between increase in WBL 2.0 legal scores and increases in women’s participation in firm ownership. GDP per capita data are retrieved from the World Bank’s World Development Indicators. To account for more observations, the analysis uses the latest available GDP per capita value for each economy within the 2022–2023 period. The dependent variable is the percent of firms with women participation in ownership, provided by the World Bank’s Enterprise Surveys. We use the most recently available datapoints over the past 5-year time frame (2019-2023) for economies. 4 The WBES aggregated economy-level datasets include information on the percentage of firms with female ownership. Based on the most recent data available from 2019 to 2023, such data is available for 93 economies. 25 Drawing on firm-level WBES data from over 225,000 firms across 167 economies, we investigate how the presence of female owners within firms relates to the legal environment supporting gender equality, while accounting for firm-specific characteristics such as size, age, and sector (table 3). The literature employs varying definitions of women-led firms, reflecting different aspects of women’s participation in business leadership. Ubfal (2024) defines women-led firms as those with either more than 50 percent female ownership or a female top manager, while Fang et al. (2022) restrict the definition to firms whose top manager is a woman who also holds an ownership share. Some scholars argue that ownership-based definitions may overstate women’s actual influence in firm decision-making. For instance, when women inherit shares in family businesses without exercising effective managerial control, the firm may technically have female ownership but is not in practice female led. In the WBES dataset, 31.64 percent of firms report female participation in ownership, while 16.07 percent report a female top manager. In our analysis, the variable of interest is a binary indicator denoting whether there is the presence of women involved in firm ownership. Business ownership remains as a key channel through which women exercise economic agency. The motivation for choosing women-owned rather than women-managed is because ownership captures women’s direct control over productive assets and wealth generation. Ownership structures also tend to be more enduring than managerial appointments. The following specification is pursued: Pr�  , ,  = 1�  =  α0  +  β1 , −3 + β2 GDPpc,−3   +  β3 ,  , +  β4 ,   +  β5 , ,    + β6  , ,  + δᵣ + ₛ + ₜ + ᵢ, ₑ, ₜ where Female Owner Presentᵢ,ₑ,ₜ is a binary variable equal to 1 if firm i in economy e and year t has at least one female owner, WBLindexₑ,ₜ₋₃ is the Women, Business and the Law index lagged 3 years, GDPpcₑ,ₜ₋₃ is GDP per capita lagged 3 years, Train,ₑ,ₜ indicates whether the firm provides formal training for permanent, full-time employees in last fiscal year; FemalePopₑ,ₜ is the logged female share of population aged 15 to 64, FirmSizeᵢ,ₑ,ₜ is the log of firm size as in terms of the number of full-time employees, adjusted for temporary and part-time workers; FirmAgeᵢ,ₑ,ₜ is the log of years since the firm’s establishment; δᵣ, θₛ, and μₜ are region, sector, and year fixed effects and εᵢ,ₑ,ₜ is the error term. Results from logic regressions controlling for sector, year, and region fixed effects, reveal that a one unit increase on the WBL legal index is positively associated with a 1.1 percent increase in likelihood that the firm has women involved in ownership (table 3). 26 Table 3: Logit Regression Results Female Owner Present Y/N Legal Gender Equality, WBL Index (3-year lag) 0.0106*** (0.00201) Formal Training 0.252*** (0.0517) Size of firm (log) -0.0103 (0.0221) Years of operation of firm (log) 0.135*** (0.0350) GDP per capita (log, 3-year lag) -0.231*** (0.0341) Female Population (% of total) 0.0158 (0.0134) Constant -0.985 (0.970) Number of Observations 215,873 Sector Fixed Effects YES Year Fixed Effects YES Region Fixed Effects YES Pseudo R-Sq 0.0897 Note: This logit regression includes sector, year and region fixed effects. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. The outcome variable is a binary indicator obtained from the World Bank’s Enterprise Surveys firm-level data, based on the question: “Among the owners of the firm, are there any females?” Control variables are retrieved from the Enterprise Surveys firm-level data and the World Development Indicators database. Given that the distance between the lowest performer and the highest performer on the WBL 1.0 index is 74 points, closing the gender gap to reach the frontier (score of 100) would carry substantial implications for women’s economic participation. For example, Uzbekistan scored 67.5 on the WBL 1.0 index in 2019 and 26 percent of firms were female-owned (WBES 2019). If Uzbekistan removed all existing barriers captured by the WBL index and achieve a perfect score, model estimates suggest that the probability of a firm having a female owner would increase by 34.5 percentage points. The implications extend to other economies in the region with similarly restrictive legal environments and low rates of women’s business ownership. Likewise, in Bangladesh, India, Iraq, Pakistan, and Saudi Arabia, where women have low participation in business ownership and the percentages are below 10%, improving their WBL 2024 scores through legal reforms to the highest level would increase the likelihood of a firm having a female owner by 53.7, 27.2, 55.0, 43.7, and 30.5 percentage points, respectively. While further research is needed to establish causality, these associations provide a strong empirical basis for considering legal 27 reforms as a foundational component of strategies aimed at narrowing the gender gap in entrepreneurship. 4. Conclusion The evidence reviewed in this paper underscores that closing the gender gap in entrepreneurship requires addressing multiple, interlinked constraints, institutional, financial, human-capital, and socio-cultural aspects, through coherent, mutually reinforcing strategies. The literature reveals that reforms in isolation yield limited effects, while integrated approaches that create an enabling environment seem to be most promising. Across contexts, institutional reform emerges as a foundational precondition for women’s economic participation. This paper provided a comprehensive examination of the multifaceted barriers that women entrepreneurs face, and the critical importance of dismantling these barriers to unlock women’s full economic potential. From institutional and financial constraints to gaps in human capital and the influence of deep-rooted social and cultural norms, the challenges female entrepreneurs encounter are systemic and interconnected. Drawing on an extensive literature review and supplemented by stylized facts from the Women, Business and the Law (WBL) and World Bank Enterprise Surveys (WBES) data, the analysis highlights that meaningful progress needs more than isolated interventions. Progress requires coordinated, long-term strategies that address structural inequalities and create enabling environments. Taken together, the evidence suggests that “what works” for women’s entrepreneurship is not a single instrument but a system of complementary levers: rights that ensure equality before the law; finance that expands opportunity; skills and networks that build capacity; and norms that legitimize women’s economic agency. The magnitude of benefits depends critically on institutional quality, program design, and social context. Importantly, we find that removing legal barriers and creating an enabling institutional framework are closely associated with higher levels of women’s entrepreneurship and labor force participation. The evidence from novel data on government-led programs supporting female entrepreneurs are most prevalent, further illustrates that multi-dimensional approaches can support women in accessing finance, networks, training, and business opportunities. However, while these programs are a promising start, there is a clear need for more rigorous research to establish the causal impact of such initiatives, especially in the long run. Importantly, further research is needed to understand the consequences for women entrepreneurs when support mechanisms are phased out, especially in setting where systemic legal and structural barriers persist. Temporary interventions may offer limited benefits if the underlying constraints remain unaddressed. 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The specific data point analyzed is the presence of female ownership within firms, as indicated by the survey question, "Amongst the owners of the firm, are there any females?" The data are drawn from most recent survey conducted in 167 economies. 41 Annex 2: Literature Search To provide a comprehensive literature review on the vast field of what works for female entrepreneurs, we conducted a structured literature search following two steps: The first step in this literature review consisted of searching for peer-reviewed articles, working papers from renowned institutions, 5 and reports 6 that directly or indirectly address the barriers faced by women entrepreneurs. The overarching research question for the search strategy read: “What are the key barriers for female entrepreneurs and what works to overcome them?” To that end, we used four multi-disciplinary platforms EbscoHost, google scholar, JSTOR, and Proquest Central. Subject of interest. As for the keywords in the search strategy, we used “female” “wom*” (capturing woman and women), “gender”, “entrepreneur*” (capturing entrepreneur, entrepreneurs, entrepreneurial, entrepreneurism, entrepreneurship etc.), “small business”, “founder” “business owner” “small firm” ,“SME”, “WSME*” and combinations thereof. We combine these search words with keywords on both the barriers and the solutions offered, including key words on • barriers: “gender barriers”, “practical challenges”, “business success”, “legal constraints”, “constraints”, “gender inequality”, “obstacle, “stereotypes”, “gender bias”, “access to finance”, “financial inclusion”, “economic barrier”, “access to markets”, “technology”, “bias”, “social bias” • solutions: “policy”, “support”, “support program”, “support project”, “training”, “mentoring”, “strategy”, “legal [gender] reform” Since our keywords are rather broad, our search covered studies from several disciplines which we hence constrained based on the following categories: Methodology. In terms of methodology and results, we focused on articles that used robust empirical strategies, beyond simple correlations. We mostly selected papers that implemented a methodological approach aiming at uncovering causal relations. Hence, we added keyword terms such as “impact evaluation”, “experiment”, “policy”, “outcomes”, “RCT”, “empirical”, “impact”, and “effects”. We also included literature review papers as well as country and regional reports that provided us with additional context and allowed us to snowball. Timeline. We primarily started our literature search with articles published after 2010s, which denoted a steep increase in researching the topic of female entrepreneurship and coincided with the inauguration of the first academic specialty journal launched in 2009 (International Journal of Gender and Entrepreneurship) as well as the adoption of the 17 Sustainable Development Goals (SDGs). The primarily language used was English. 5 Working papers considered include papers from the i) Centre for Economic Policy Research, ii) National Bureau of Economic Research (NBER), iii) SSRN (Social Science Research Network), iv) Institute of Labor Economics, v) RePEc (Research Papers in Economics), vi) World Bank Policy Research Working Papers Series, and vii) IMF Working Paper Series. 6 Reports or repository from leading think tanks or institutions, such as the Brookings Institution, the Harvard University Working Papers, and the Oxford Economics Papers. 42 The second step involved expanding the search of the pre-identified articles through platforms using Artificial Intelligence (AI) to map and identify related articles to the seed article. Specifically, we drew on Inciteful.xyz, a free online tool that maps academic literature on a given topic. The tool builds a network of articles from citations, finding the most similar, relevant, and most cited papers related to the original paper. It further connects two or more papers through citations. Hence, it connects domains of research and allows the addition of papers to the seed papers to refine the network. This broad, multi-pronged search strategy allowed us to identify papers that directly address the barriers faced by women entrepreneurs and the solutions offered to tackle these barriers. Through a combined assessment of these papers, we categorized the barriers and solutions into four key buckets: Institutional and enabling factors; financial factors; human capital factors; and social and cultural factors which were the key overarching themes in the literature assessed, affecting women entrepreneurs differently from male entrepreneurs. Our review complements recent literature reviews on what works for women entrepreneurs such as those by Jennings and Brush (2013), Siegrist (2022; 2025), and Ubfal (2024) by focusing on both the barriers and solutions, and by providing cross-country evidence on what works to increase labor force participation and women’s entrepreneurial activity. 43 Annex 3: Women, Business and the Law: Legal and Supportive Frameworks Question Table 1: Legal Frameworks Question Indicator Question Safety 1. Does the law address child marriage? 2. Does the law address sexual harassment? 3. Does the law address domestic violence? 4. Does the law address femicide? Mobility 1. Can a woman choose where to live in the same way as a man? 2. Can a woman travel internationally in the same way as a man? 3. Can a woman travel outside her home in the same way as a man? 4. Do a woman and a man have equal rights to confer citizenship on their spouses and their children? Workplace 1. Can a woman get a job in the same way as a man? 2. Does the law explicitly prohibit discrimination in recruitment based on marital status, parental status, and age? 3. Does the law prohibit discrimination in employment based on gender? 4. Does the law allow employees to request flexible work? Pay 1. Does the law mandate equal remuneration for work of equal value? 2. Can a woman work at night in the same way as a man? 3. Can a woman work in a job deemed dangerous in the same way as a man? 4. Can a woman work in an industrial job in the same way as a man? Marriage 1. Is the law free of legal provisions that require a married woman to obey her husband? 2. Can a woman be “head of household” or “head of family” in the same way as a man? 3. Can a woman obtain a judgment of divorce in the same way as a man? 4. Does a woman have the same rights to remarry as a man? Parenthood 1. Is paid leave of at least 14 weeks available to mothers? 2. Are leave benefits for mothers paid solely by the government? 3. Is paid leave available to fathers? 4. Is dismissal of pregnant workers prohibited? Childcare 1. Does the law establish the provision of center-based childcare services? 2. Does the law establish any form of support for families for childcare services? 3. Does the law establish any form of support for nonstate childcare providers? 4. Does the law establish quality standards for center-based childcare services? Entrepreneurship 1. Can a woman undertake entrepreneurial activities in the same way as a man? 2. Does the law prohibit discrimination in access to credit based on gender? 3. Does the law prescribe a gender quota on corporate boards? 4. Does the law include gender-sensitive procurement provisions for public procurement processes? Assets 1. Do a woman and a man have equal administrative power and ownership rights to immovable property, including land? 2. Do sons and daughters have equal rights to inherit assets? 3. Do male and female surviving spouses have equal rights to inherit assets? 4. Does the law provide for the valuation of nonmonetary contributions? Pension 1. Are the ages at which a woman and a man can retire with full pension benefits the same? 2. Are the ages at which a woman and a man can retire with partial pension benefits the same? 3. Is the mandatory retirement age for a woman and a man the same? 4. Are periods of absence due to childcare accounted for in pension benefits? Source: Women, Business and the Law 2024 database. 44 Table 2: Supportive Frameworks Question Indicator Question Safety 1. Has the government developed comprehensive mechanisms to address violence against women? 2. Are special procedures in place for cases of sexual harassment? 3. Is a government entity responsible for monitoring and implementing national services, plans, and programs addressing violence against women? 4. Is an annual budgetary allocation devoted to violence against women risk mitigation, prevention, and response programs? Mobility 1. Are passport application processes the same for a woman and a man? 2. Are the application processes for official identity documents the same for a woman and a man? 3. Does a current policy or plan explicitly consider the specific mobility needs of women in public transportation? Workplace 1. Does a specialized body receive complaints about gender discrimination in employment? 2. Has the government published guidelines on nondiscrimination based on gender in recruitment? 3. Has the government published guidelines on flexible work arrangements? Pay 1. Are pay transparency measures or enforcement mechanisms in place to address the pay gap? 2. Have sex-disaggregated data on employment in different industries or sectors been published? Marriage 1. Is there a fast-track process or procedure for family law disputes? 2. Are there specialized family courts? 3. Is legal aid available for family law disputes? Parenthood 1. Is it possible to apply for maternity benefits using a single government application process? 2. Are incentives in place to encourage fathers to take paternity leave upon the birth of a child? 3. Have sex-disaggregated data on unpaid care work been published? Childcare 1. Is there a publicly available registry or database of childcare providers? 2. Is there a clearly outlined application procedure to request financial support from the government for childcare services by parents? 3. Is there a clearly outlined application procedure to request financial support from the government for childcare services by nonstate childcare providers? 4. Has the government published any reports on quality of childcare services? Entrepreneurship 1. Have sex-disaggregated data on business activities, entrepreneurship, or women-owned businesses been published? 2. Are there government-led programs supporting female entrepreneurs providing access to finance and training, coaching, or business development? 3. Does a current national government plan or strategy focus on women’s access to financial services? Assets 1. Are mechanisms or incentives in place to encourage women to register immovable property (including joint titling)? 2. Are awareness measures in place to improve women’s access to information about marital and inheritance rights? 3. Have anonymized sex-disaggregated data on property ownership been published? Pension 1. Are incentives in place to increase women’s retirement benefits? 2. Is a procedure in place for pension beneficiaries to challenge the decisions of the competent authority regarding their benefits? Source: Women, Business and the Law 2024 database. 45 Annex 4: Summary Statistics Observations Mean Std. Dev. Min Max WBL WBL 1.0 Legal Index (3-year lag) 249,940 72.67 16.70 23.75 100.00 WBES Female owner present in firm (Y/N) 245,757 0.33 0.47 0.00 1.00 Firm offers formal training (Y/N) 229,522 0.36 0.48 0.00 1.00 Firm size (log) 252,050 3.32 1.37 0.00 14.33 Firm operation years (log) 249,999 3.16 0.61 0.00 5.87 WDI Population, female ages 15-64 (%) 249,328 50.06 1.85 34.75 56.46 GDP Per Capita (log, 3-year lag) 248,901 8.29 1.28 4.71 11.61 Female Labor Force Participation 247,450 36.53 15.96 4.44 70.46 (Non-Agricultural) (% of female population ages 15+) 46