Integrating data from different sources for measuring gender aspects of trade

Provided by UNECE and UNCTAD

For a long time, international trade was considered gender-neutral, and the gender variable was not part of trade statistics. However, it is now widely accepted that international trade affects women and men differently. Recent data about gender and trade are still rare, but a few countries are doing pioneering work to learn more about gender perspectives in trade.

Producing better and more gender-disaggregated trade data will give new clues for trade policymakers. Moreover, gender-in-trade statistics can also contribute to the achievement of SDG 5 in ensuring women’s participation in leadership positions (5.5), and sound policies for the promotion of gender equality and empowerment (5.c); and SDG 17 to the promotion of a universal, rules-based, open, non‑discriminatory and equitable multilateral trading system (17.11).

Earlier data on European Union countries44 shows that women occupy a lower share of jobs in export-oriented production activities than they do in total economy. As jobs in exports tend to provide higher pay, the fact that women are underrepresented has further implications for their economic empowerment.

44 Rueda-Cantuche J M, Pinero P, Kutlina-Dimitrova Z (2021). EU exports to the world: effects on employment. doi:10.2760/556206.

UNECE and UNCTAD supported a pilot study in Georgia45, to establish a way for a sustainable production of gender-in-trade statistics using existing data sources. Given the importance of international trade for the Georgian economy (the shares of exports and imports in the country’s GDP over 2015-2020 averaged at 46 and 59 per cent, respectively), the availability of trade indicators disaggregated by different variables, including gender, is critical for the country’s economic and social policies.

45 UNECE & UNCTAD (2021). Gender in trade assessment in Georgia. Report prepared for UNECE by Tengiz Tsekvava.

The immediately available sources for statistical data allow measuring gender aspects of trade using data on the level of the sector of industry. However, the National Statistics Office of Georgia (Geostat) has the advantage of possessing external trade microdata that can be linked to the business register and enterprise surveys, enabling further disaggregation and insights. The pilot study created such a linked data set of companies involved in trade in Georgia.

There are notably less women than men employed in companies involved in external trade. Over the last five years, employment growth for women in those companies exceeded that for men, and their share increased from 35 per cent in 2016 to 39 per cent in 2020. Women’s average wage in trading companies was lower than the average wage of men by one third. While wages in trading companies improved slightly in those five years, the gender pay gap decreased only very little, from 34 per cent in 2016 to 32 percent in 2020.

The insights enabled by the linked dataset include the possibility to examine differences by skills levels, type of trade, the gender of the company owner as well as ownership shares for men, women and legal entities. The number of men owners of trading companies exceeded the number of women owners approximately 9 times for two-way traders, 5 times for importers and 3 times for exporters. Businesses with higher women ownership tend to employ more women and have a lower gender pay gap.

Figure 18

Percentage of women and the gender pay gap in trading companies by gender-specific ownership in Georgia, 2020

Note: The data are from Geostat external trade statistics and structural business statistics survey. Enterprises are classified as “women-owned” where the ownership share of women is at least as high as that of men. Enterprises where ownership by legal entities is more than half and enterprises with indirect ownership are not included.

The project shows how the National Statistics Office could sustain the production of gender-in-trade indicators in the future by linking trade data with enterprise-level data from registers and surveys, responding to the demand for such data for policymaking.

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