other studies on the financial inclusion of women in Myanmar, such as the UNCDF’s PoWER Women and Girls Financial Inclusion Country Assessment,<sup>32</sup> which shows a gender gap in the access to formal and informal finance. Women business owners in Myanmar remain disproportionately excluded from the formal financial sector.

**The larger the firm is, the more likely it is to have access to financial instruments.** Size of firm plays an important role in increasing the likelihood of the firm having a bank account (63 percent) and documents to request a loan (54 percent). Medium sized firms are also more likely to have an account specifically for their business. While 41 percent of medium sized firms have an enterprise account, only 11 percent of small and 8 percent of micro have one. Having a license to operate also increases the likelihood of having a bank account and documents to request a loan (by 21 and 45 percent). The level of education of employees, although small (3 percent), is also a significant and positive predictor of having loan documents. Larger, more stable firms, and firms with better-educated employees, are more likely to use financial services. Having documents to request a loan is also significant in bank account ownership, increasing the likelihood by 55 percent. Age of the firms, on the other hand, reduces the likelihood of firms having necessary documents by 14 percent, the older the firm the less likely they are to have documents in place.

**Belonging to the trade industry matters for financial access.** Firms in the trade industry display a 40 percent higher likelihood of having a bank account, most likely given it is critical in conducting trading business. Moreover, in the context of Myanmar, those companies that hold an import/export license must open a bank account,<sup>33</sup> potentially accounting for part of this result. Interestingly, the source of loans varies according to industry. Non-farming agriculture, trade, and logistics rely mainly on private commercial banks, while hospitality and light manufacturing instead rely on micro-finance institutions.

The regression outcomes that include the interaction terms present little variation from those with no interactions. Before turning to the description of the outcomes, we will explain how to interpret the margins tables. In our scenario, we are interacting the gender of the owner with binary explanatory variables, therefore, each interaction has four possible outcomes: female & characteristic – denoted by 1,1; female & no characteristics – 1,0; male & characteristic – 0,1; and, male & no characteristic – 0,0. These outcomes allow us to compare the effects of each of these interaction on the outcome of interest and determine the different impact of one variable depending on the owner’s gender. We start by looking at differentials in bank account ownership and move on to having loan documents.

**Loan documents matter more if you are a male entrepreneur.** Having loan documents increases the likelihood of having a bank account by almost 20 percent more for a male business owner than for a female entrepreneur. In Table 5a we saw how this variable was significantly related to having a bank account, we can now see how the magnitude of the effect actually depends on the gender of the business owner. Overall, a female entrepreneur with

> 32 http://www.uncdf.org/download/file/127/6266/uncdf-power-country-assessment---myanmar.pdf

> 33 <u>https://myanmar.gov.mm/en/business/service/-/asset_publisher/idasset472/content/a-2</u>

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