# **3. Methodology and Data Collection**

The Entrepreneurship Database was launched in 2007 to benchmark formal entrepreneurial activity across economies. An advantage of the Entrepreneurship Database is its reliance on official statistics that come mostly from business registries and national statistical agencies. The Entrepreneurship Database defines an entrepreneur as “any economic unit of the formal sector incorporated as a legal entity and registered in a public registry, which is capable, in its own right, of incurring liabilities and of engaging in economic activities and transactions with other entities” (Ács, Desai, and Klapper 2008, 267). In contrast to many entrepreneurship indices, the Entrepreneurship Database does not include the informal sector, owing primarily to the difficulties associated with quantifying the number of firms that comprise it. Considering that statistical agencies around the world define business entities in various ways, the Entrepreneurship Database takes into account their legal form. The standard unit of measurement provides comparable data on entrepreneurial activity across economies.

The Entrepreneurship Database helps clarify the relationship between new firm registration, the regulatory environment, and economic growth. Research using the Entrepreneurship Database shows a significant relationship between the level of cost, time, and procedures required to start a business and new firm registration (Divanbeigi and Ramalho 2015; Klapper, Lewin, and Quesada Delgado 2009; Klapper and Love 2010). A recent study, for example, shows that an improvement of 10 percentage points in the overall measure of business regulation (Doing Business distance to frontier score) is linked to an increase of around 0.6 new businesses per 1,000 adults (Divanbeigi and Ramalho 2015, 8). The Entrepreneurship Database also helps explain the relationship between entrepreneurship and financial development, including the impact of financial crises on the formation of new businesses in the economy (Klapper and Love 2011; Klapper, Meunier, and Diniz 2014).

The 2017 edition of the Entrepreneurship Database contains annual data for 143 economies on the number of limited liability companies (LLCs) registered (both new and total) between 2006 and 2016. The Entrepreneurship Database was expanded in 2017 to include a gender dimension of business ownership. To do so, it combines comparable cross-country data on new businesses registered in those economies where national statistics include sex-disaggregated data. Furthermore, recognizing the importance of a differentiated approach to entrepreneurship in terms of organizational form, the data on female and male business owners are collected at two levels—LLCs and sole proprietors. This allows for in-depth analysis of gender differences in business entry worldwide. The Entrepreneurship Database facilitates both a greater understanding of the dynamics of new business registration around the world and in-depth analysis of the relationship between gender and entrepreneurship at various organizational levels.

To ensure cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement that is applicable and available among the diverse sample of participating economies. The Entrepreneurship Database and World Bank Group’s Doing Business jointly developed a data collection methodology to measure entrepreneurial activity systematically. The primary sources of information for the Entrepreneurship Database are national business registries. In cases where the business registry is unable _—_ to provide the data, alternatives sources such as statistical agencies, tax and labor agencies, ministries of _—_ economy and chambers of commerce are used. The data collection process involves telephone interviews and email correspondence with business registries.

The gender-specific indicators used in the Entrepreneurship Database include the percentage of new female LLC owners, the percentage of new female sole proprietors and the percentage of new LLCs with female ownership. Table A2 in the appendix presents sources of sex-disaggregated data. The OLS regression analysis presented in this study uses two dependent variables: the percentage of new female LLC owners and the percentage of new female sole proprietors. Using these variables allows for the identification of 5