same time. The second definition (GVC4) is stricter as it combines the four dimensions together: firms that are simultaneously exporters and importers, that also have an international certification and a foreign ownership of its capital (Dovis and Zaki, 2020). The subscripts _i_ , _j_ , _c_ , _g_ and _t_ denote firms, sector, country, region and year respectively. i i is a vector that includes firms’ characteristics that are expected to affect female entrepreneurs and women’s participation in the workforce of the firm such as firms’ age, size, ii XXshare of government ownership and city of operation. <mark>FaF</mark> i i<sup><mark>is t</mark>he difference between the survey</sup> year and the year in which the establishment began operation. <mark>ag g g</mark> i i ii <mark>government ownership that is likely to attract women given that public employment is more</mark> ii<sup><mark>is the share of</mark></sup> <mark>women friendly than private one. F mgm my</mark> i i <mark>firm is operating in the main business city and is expected to positively affect women’s</mark> ii<sup><mark>is a dummy variable that takes the value 1 if the</mark></sup> <mark>participation due to agglomeration economies. smsF</mark> i i <mark>value 1 for small firms, 2 for medium firms and 3 for large ones. Large f</mark> irms get advantage of ii<sup><mark>is a categorical variable that takes the</mark></sup> their size and engage in economies of scale which, in turn, allows them to enjoy lower costs of production and might hire more women. Appendix 2 summarizes the definition of different variables. Given that we pool data for different countries and years, we include year, country, and sector fixed effects ( and ) to control for unobservables. i i is the disturbance term. Our estimations are run using a pooled Ordinary Least Squares (OLS) estimation method (when the ii ii ii ii dependent variable is a continuous variable, namely share of females’ workers) and a Linear ζζ , γγ θθ δδ Probability Model (when the dependent variable is binary, which is the case of a female manager or a female owner).

We extend the analysis in three ways. First, we investigate whether the impact of firms’ integration into GVCs on female participation is conditional on some external factors such as gender provisions in RTAs. The literature on the efficiency of gender provisions in regional trade agreements (RTAs) is relatively scarce. Hence, there is little empirical evidence that supports the idea that gender-related provisions or labor provisions with clauses related to gender equality significantly promote gender equality and women’s empowerment in the workplace. In that vein, López Mourelo and Samaan (2018) run a difference-in-differences model using the Cambodian Socioeconomic Survey (CSES) conducted by the National Institute of Statistics of the Ministry of Planning over the period 1993-2012 in order to assess the average effect of the 1999 CambodiaUS Bilateral Textile Agreement (CUSBTA) on the gender wage gap. The CUSBTA encloses labor provisions, which mainly aim to improve working conditions through two main pillars. First, the elimination of discrimination between employees and especially those based on gender basis. Second, the reduction of gender-wage gap. The results of the study show that labor provisions decrease gender wage gap and gender discrimination in workplace only in the textile sector. However, the gap is still increasing in the other manufacturing sectors that are not concerned by these provisions. Furthermore, the impact of these provisions is proven to be significant and important only during the period of the agreement and while the International Labor Organization (ILO) is monitoring the proper implementation of these provisions. However, the impact of the provisions starts to decrease during the post-agreement period. In our paper, the impact of gender related provisions in RTAs is studied using the World Trade Organization (WTO) database that compiles provisions related to women’s empowerment and gender equality. In this dataset, 11