There are considerable differences in the quality of working life among wage and salary earners. The segregation by gender in working conditions is also particularly striking, shows the profiling of the results of the 2018 Quality of Work Life Survey.
Gender equality and income distribution in foreign trade – globalization is a manly thing
Foreign trade can magnify gender segregation. Women participate – as employees and entrepreneurs – in profitable foreign trade activities far less than men. This finding is based on new information on gender equality in trade which Statistics Finland compiled by combining data from different statistical and administrative registers.
For a small open economy like Finland, the benefits of globalization and foreign trade are undeniable. Over the last ten years, the share of exports in GDP has remained around 25 to 30 per cent in Finland. Several Finnish companies and industries have been able to expand through participation in international markets.
However, the benefits of international trade are not evenly distributed between businesses, employees and consumers. In 2016, 13 per cent of companies participated in foreign trade with only 5 per cent of these engaged in exports. Merchandise exports are strongly concentrated in large companies and certain industrial sectors. ICT services form the most significant share of services exports.
The question of equal participation in international trade for the benefit of both sexes is relevant, as export companies are, on average, significantly more profitable than other companies.
Figure 1 shows that the difference between the value added per person employed is significant between trading and non-trading companies. The labour productivity of exporters was on average €84,800 in 2008 – 2016 and approximately €63,200 for companies only operating in domestic markets, when work input is measured by full time equivalent (FTEs) units.
In addition, the difference in labour productivity between exporters and non-exporters has increased in recent years. The difference was smallest during the end of the financial crisis in 2009.
The salaries paid by companies engaged in exports have also been notably higher than those paid by their non-exporting counterparts.
So far, gender equality in international trade has mainly been measured by macro-level indicators. This involves making assumptions such as the sectoral structure of male and female employees in trading companies is the same across industries (e.g. Fortanier and Miao, 2018). More accurate analysis can be done by linking individual employees to companies that employ them.
There are a number of studies on equality, economic growth and foreign trade, for instance by Dollar and Gatti (1999) and Busse and Spielmann (2006). Wage differentials and their causes have also been studied extensively in Finland (e.g. Korkeamäki and Kyyrä, 2006), and recent evidence from Norway shows that after a company engages in exports, the gender pay gap increases within the company (Bøler et al., 2018).
In view of these developments, the United Nations Conference on Trade and Development (UNCTAD) promotes the compilation of statistics on women's participation in foreign trade (Peltola and MacFeely, 2019). These statistics are essential for analysing and advancing gender equality of globalization. UNCTAD is looking for answers to this data gap in cooperation with Statistics Finland: by combining micro-data we present more accurate information on participation in foreign trade by gender.
In addition, Statistics Finland and the OECD are carrying out a joint project to produce more information by analysing the role of men and women in global value chains.
Finland has high-quality registers and, thus, the possibility to link micro-data sets on foreign trade (Company datasets by the Finnish Customs and Statistics Finland), employee characteristics (FOLK employee data set) and business owners (FLOWN business owner data set). This provides valuable and accurate information on women's participation in foreign trade as employees and entrepreneurs. These registers were recently linked together, and now this new information can be utilized for the development of new statistics, for instance on gender equality in trade.
Women constitute over a quarter of the workforce in exporter firms
The proportion of women employed, and their share of wages, can be examined by combining business data with data on the gender structure of employees. Figure 2 illustrates these shares by the export status of companies.
In 2016, women accounted for more than one third at 36 per cent, of staff in companies operating in the domestic markets, while comprising only 27 per cent in exporter companies. The female share of the workforce in exporter companies has been decreasing since 2012.
The first analysis indicates that economic globalization supports male-dominated jobs in Finland and the trend does not seem to be reversing.
By looking at women’s share of wages, the pay gap between women and men (non-standardized) has been approximately two percentage points higher in exporter companies than in domestic businesses.
Similar development is observed for fast-growing and young companies.
Companies can be distributed to specific categories based on their engagement in international trade: 1) exporters, 2) importers, 3) exporter-importer firms and 4) domestic businesses who do not engage in foreign trade.
Exporter: A company that receives at least 5% of its turnover from goods or services exports. In addition, the value of exports should exceed €5,000.
Importer: A company that purchases at least 5% of its purchases of goods or services from abroad. In addition, the value of imports should exceed €5,000.
Exporter-Importer: A company that meets both of the above conditions.
Non-traders: A company that does not fulfil any of the above conditions.
Companies have been categorised as women-owned (> 60 % of shareholdings by women), equally owned (40 - 60 % of shareholdings by either sex), men-owned (> 60 % of shareholdings by men) and other companies for which principal person owners cannot be traced.
Different company groups have a relatively similar structure of personnel when looking at the level of education. The share of highly educated staff is around one third on average.
However, the share of women in highly educated personnel varies across this classification. Figure 3 shows that the share of highly educated women and men employed by importers and non-traders is fifty-fifty. In contrast, men account for a significantly higher proportion of the highly educated workforce in exporter and exporter-importer firms, at a share of over 60 per cent. The difference has increased from 2008 to 2016.
The gender differences in pay and educational background indicate that industrial and professional structures are significantly different between exporter and non-trader enterprises. For example, when looking at a narrower industrial sector, such as the high-tech sector, the gender differences are much smaller.
Ilmakunnas and Maliranta (2005) find, however, that these differences are not explained by industrial structures alone, as gender segregation is significant even within an industry. The share of men tends to be larger in the personnel of the most profitable companies within an industry. If the growing engagement in foreign trade seems to favour men, technological development may, on the other hand, favour women, as argued by some studies showing that robots will replace more jobs for men than for women (Acemoglu and Restrepo, 2017).
Less than a fifth of entrepreneurs in the export sector are women
There is surprisingly little prior knowledge of the role of female entrepreneurship in foreign trade. By looking at occupational status data, we can describe the entrepreneurial input of women in exporter and non-exporter companies.
Figure 4 shows that about one third of entrepreneurs of non-exporter firms are women, while only one fifth of entrepreneurs are women in the export sector. Furthermore, in recent years, the number of female entrepreneurs in exporter firms has decreased rather than increased.
The Finnish Tax Authorities’ shareholder data set enables an analysis of the gender structure of company shareholders (Maliranta and Nurmi, 2019), and by linking further, an analysis of the gender pay gap in businesses owned by women or men (Kritikos et al., 2019). In 2016, there were about 10,600 companies with most shares (>60 %) owned by women compared to 52,600 men-owned companies. The datasets also include 7,400 equally owned companies and 19,200 other companies for which the owner cannot be tracked.
As shown in table 1, women-owned firms employ only 2.7 per cent of employees working in exporter companies and 1.3 per cent of employees in exporter-importer companies. In contrast, men-owned businesses employ 44.1 per cent of employees working in exporter firms and 10.6 per cent of employees in exporter-importers.
Among importer companies, women-owned companies only employ 3.4 per cent of all employees. Naturally, the largest companies, for which owners cannot be tracked, employ the majority of people.
Further, it should be noted that the women-owned exporters are larger than average, measured by the number of employees (employing 25.3% persons on average), while among non-traders women-owned businesses tend to be smaller than companies owned by men.
|Enterprise owner group||Exporters||Importers||Exporter-importers||Non-exporters|
|Female-owned||2,7 %||3,4 %||1,3 %||8,4 %|
|Balanced ownership||5,4 %||2,9 %||1,8 %||6,6 %|
|Male-owned||44,1 %||24,2 %||10,6 %||49,6 %|
Source: Authors' calculations based on Statistics Finland's research data sets.
Successful women-owned exporter companies are scarce
Businesses owned by men are on average more productive than those owned by women, but the difference is much smaller among exporter firms (Figure 5).
There are differences between industries, however. For instance, women-owned exporters operate less in high-tech industries than men-owned exporters.
Finally, we will look at the proportion of women in different groups of companies by the sex of the owner.
Figure 6 shows that in 2016, women-owned exporters and non-exporters employ relatively more women than men-owned companies. However, in the export sector the difference is smaller, at about 5 percentage points, while in the case of non-exporters the difference is 28 percentage points.
In the export sector, women are most often employed by companies owned equally by women and men. Women make 34 per cent of the staff of these companies. Interestingly, the results show that a larger share of staff in the women-owned companies are highly educated women than in men-owned companies.
Benefits of globalization are distributed unevenly between sexes
Globalization has enabled enterprises’ growth to large and successful corporate giants, who in some cases have created well-being and prosperity. Sustainable economic growth should, however, also be equal. Equal opportunities promote trade, economic growth and prosperity.
On the basis of the results presented in the article, there appears to be large differences by gender in how the economic benefits of globalization are spread in our society.
A particularly important finding is the considerably low female participation in international trade. As workers and entrepreneurs, women receive a smaller proportion of salaries and capital income from exporter firms, which may lead to an undesirable development when considering income differentials.
A closer look reveals many differences in exporting companies related to the owner's gender. Men-owned enterprises are more productive generally, but women-owned export firms are on average larger by number of employees.
The share of women in the workforce is highest in companies where ownership is evenly distributed between men and women. By contrast, women’s proportion of the workforce is the lowest in men-owned businesses.
We need more research and information on the various factors that may prevent women from participating in foreign trade. Some of these reasons may be self-evident - such as women's and men's pursuit of different fields of education - but some may be hidden behind the structures of working life and society.
A more detailed micro-level analysis can shed light not only to differences at the industrial and professional groups, but also on how we could promote women’s employment in export industries and their participation in exports as entrepreneurs, thus reducing the barriers to trade.
We will need more internationally agreed indicators to allow policy makers to keep track of the multiple effects of trade and trade policy on jobs, businesses and citizens globally, and more knowledge-based policy measures to promote the achievement of equality in globalization.
Henri Luomaranta and Pontus Lindroos work at Statistics Finland on Business Statistics and Satu Nurmi on Research Services. Their aim is to promote the wider use of register data and consider, for example, factors of business growth and productivity in their projects. The authors thank Anu Peltola, Mika Maliranta and many partners and colleagues for their helpful comments.
FOLK Ready-Made Modules for Research
The combination of protected personal and business data from Statistics Finland's research services provides a comprehensive knowledge base for research. The combined Employee-Employer Data (FLEED) has been very popular among researchers and is already a major source of data for many articles published in internationally peer-reviewed publications. The new FOLK- ready-made modules, that will replace FLEED, will expand the data content and new topics to the entire population.
The FOLK Basic Data Module provides background information on individuals in demographic and employment statistics, as well as some basic family and education information. Its thematic modules contain more detailed information on topics such as education, family, income and employment. More detailed descriptions are available in the “Taika” research catalog.
The material will be provided with secure identifiers via a secure remote connection. Each research project will be evaluated individually with regard to the necessity of using personal data and considering the necessary scope of target population and data content.
Acemoglu D. ja Restrepo P. (2017). Robots and Jobs: Evidence from US Labor Markets. NBER Working Paper No. 23285.
Bøler, E. A. & Javorcik, B. & Ulltveit-Moe, K. H., (2018). Working across time zones: Exporters and the gender wage gap, Journal of International Economics, Elsevier, vol. 111(C), pp 122-133.
Busse, M. ja Spielmann, C. (2006). Gender Inequality and Trade, Review of International Economics, Vol 14(3), pp. 362-379.
Dollar, D. ja Gatti, R. (1999). Gender Inequality, Income, and Growth: Are Good Times Good for Women? Gender and Development Working Papers, No. 1, The World Bank.
Fortanier, F. ja Miao, G. (2018). Gender in Global Value Chains. How does trade affect male and female employment? OECD Statistics and Data Directorate.
Ilmakunnas, P. ja Maliranta, M. (2005). Technology, Labour Characteristics and Wage-productivity Gaps, Oxford Bulletin of Economics and Statistics, vol. 67(5), pp. 623−644.
Korkeamäki, O. ja Kyyrä, T. (2006). A Gender wage gap decomposition for matched employer-employee data, Labor Economics, vol. 13(5) pp. 611−638.
Kritikos, A., Maliranta, M. ja Nurmi, S. (2019). Female entrepreneurs, firm performance, and gender pay gap, unpublished manuscript.
Maliranta, M. ja Nurmi, S. (2019). Business owners, employees, and firm performance, Small Business Economics, 52(1), pp. 111−129.
Peltola, A. ja MacFeely, S. (2019). Towards a conceptual framework for measuring gender-in-trade in official statistics, United Nations Economic Commission for Europe, Conference of European Statisticians working paper no. 25.
 Because the review is based on a combination of multiple data sources, the timeliness is limited by the release schedules of the slowest individual-level data on employees.
 Since the data set is formed by combining various data sources, timeliness reflects the slower availability of the most detailed data sets regarding individual employees of enterprises.