Looking at recent growth successes and failures, some of the positive stories of economies were characterised by relatively high female autonomy: Botswana had the highest GDP growth rates of the last decades and had not only favourable institutions, but also high gender equality (Robinson 2009; data on gender equality: Carmichael, Dilli and Rijpma, 2014). Similarly, China and South Korea moved from extreme gender inequality in the early 20th century to relatively high gender equality during the 1960s and 1970s, before the most dramatic economic growth process in the world economy could set in (ibid.).

A number of development economists have found that gender inequality was associated with slower development. Stephan Klasen, with co-authors, used macroeconomic regressions to show that gender inequality has usually been associated with lower GDP growth in developing countries during the last few decades (Klasen and Lamanna 2009; Gruen and Klasen 2008).

In a new study, we directly assess the growth effects of female autonomy in a dynamic historical context. Given the obviously crucial role of direction-of-causality issues in this debate, we carefully consider the causal nature of the relationship. We use the fact that lactose tolerance was a relatively exogenous genetic factor in the centuries studied, and it increased the demand for dairy farming. In dairy farming, women traditionally had a strong role in participating in income generation (Voigtländer and Voth 2013). In contrast, female participation was limited in grain farming, as it requires substantial upper-body strength (Alesina et al. 2013). Hence, the genetic factor of lactose tolerance influences long-term differences in gender-specific agricultural specialisation and can help to solve direction-of-causality issues in the statistical analysis.

We employ the new method of age-heaping-based numeracy estimates. These estimates reflect a crucial component of human capital formation namely, numerical skills that matter most for economic growth. Hanushek and Woessmann (2012) observed that math-related skills outperform simple measures of school enrolment in explaining economic development. Hence, we focus on math-related indicators. We use two different datasets: a panel dataset of European countries from 1500 to 1850, and study 268 regions in Europe, stretching from the Ural Mountains in the East to Spain in the Southwest and the UK in the Northwest.

Age at marriage is highly correlated with other indicators of female autonomy, such as the share of female household heads or the share of couples in which the wife was older than the husband. Age at marriage is particularly interesting due to the microeconomic channel that runs from labour experience to an increase in women’s human capital: after early marriage, when they drop out of labour market and switch to work in the household economy, women provided less teaching to their children, including numeracy skills. Early-married women sometimes also valued these skills less because they did not “belong to their sphere”, i.e., these skills did not allow identification (Baten et al. 2017).

Figure 1. Average age at marriage in Europe, 1500-49

  Dark countries: high average age at marriage; light grey: low average age at marriage; white countries: no data.
Dark countries: high average age at marriage; light grey: low average age at marriage; white countries: no data.
Image: Baten and de Pleijt (2018).

In the early 16th century map of age at marriage in Europe, the UK was far ahead (Figure 1). This might have already forecasted some of the rapid growth taking place later on in the UK, which ultimately led to the Industrial Revolution of the late 18th and early 19th century (Kelly et al. 2013). In the early 18th century, Central Europe starts to recover in terms of female autonomy, whereas now some of the East Central European economies demonstrated relatively low rates (Figure 2).

Figure 2. Average age at marriage in Europe, 1700-49

 Dark countries: high average age at marriage; light grey: low average age at marriage; white countries: no data.
Dark countries: high average age at marriage; light grey: low average age at marriage; white countries: no data.
Image: Baten and de Pleijt (2018).

This continues in the early 19th century, while South Eastern Europe had low rates. In contrast, Scandinavia and Central Europe, including Switzerland and Austria, had quite high female autonomy values which later became superstars in the Second Industrial Revolution.

Figure 3 depicts a strong and positive relationship between average age at marriage and numeracy for two periods: the half centuries following 1700 and 1800. Denmark, the Netherlands, Germany, Sweden had high values of female autonomy and numeracy.

Figure 3. Average age at marriage and numeracy in 1700

 The figure shows the relationship between average age at marriage and numeracy in the half century following 1700 for a sample of 20 countries
The figure shows the relationship between average age at marriage and numeracy in the half century following 1700 for a sample of 20 countries

In our regression analyses, we include a large number of control variables, such as religion, serfdom, international trade and political institutions. We find that the relationship between female autonomy and numeracy is very robust.

We also study the relationship between female autonomy and human capital formation at the regional level in the 19th century. Numeracy and age at marriage yields an upward sloping regression line (Figure 4).

Figure 4. Partial scatter-plot of the regions

Image: Source: Baten and de Pleijt (2018)

Most importantly, the effect is not driven by single outliers. For example, in the Croatian-Italian province of Fiume, there was both a higher residual numeracy and a higher residual age at marriage. In contrast, in central Russian Smolensk and in the Italian region of Basilicata, both a low residual age at marriage and a low residual numeracy was observed.

In sum, the empirical results suggest that economies with more female autonomy became (or remained) superstars in economic development. The female part of the population needed to contribute to overall human capital formation and prosperity, otherwise the competition with other economies was lost. Institutions that excluded women from developing human capital – such as being married early, and hence, often dropping out of the independent, skill demanding economic activities – prevented many economies from being successful in human history.