Thursday, 4 February 2021

Intergenerational mobility: what about the daughters?

by Vincent Delabastita*^ and Erik Buyst*

*Department of Economics, KU Leuven
^Research Foundation - Flanders (FWO)

blog post based on the article, "Intergenerational mobility of sons and daughters: evidence from nineteenth-century West Flanders", now available on EHER early view here

Research of the intergenerational transmission of socio-economic attainment has long had a restrictive focus on the relationship between fathers and sons. Recently, a growing strand of literature has taken up the challenge to overcome the omission of women. In historical research, however, this is challenging because (1) cultural tradition often prescribes that women change their name upon marriage, making intergenerational tracking of female life courses much more challenging (2) the socio-economic attainment of women on historical labor markets is often poorly documented. The first challenge can be solved by either constructing indirect links based on naming practices (Olivetti & Paserman, 2015; Olivetti, Paserman, & Salisbury, 2018), or by looking at areas for which it is possible to construct direct intergenerational links. This research project adds to a range of recent papers that adopts the latter approach, by studying the case of 19th-century West Flanders (Craig, Eriksson, & Niemesh, 2019; Dribe, Eriksson, & Scalone, 2019).

The common approach to overcoming the second challenge with respect to the definition of women’s socio-economic attainment is to take the husband’s or father’s occupational status as a proxy. We argue that this stance leads to a problematic neglect of the female experience in labor markets in the past, as working women were definitely ubiquitous in European history (for example, see Humphries & Sarasúa, 2012). An examination of women’s social mobility solely based on their marital mobility or the attainment of her father/husband shows only part of the picture. Therefore, our paper takes a different approach by examining parental influence on women’s own occupational decisions on the labor market.

19th-century West Flanders presents itself as a suitable case study, given that its economic structure was characterized by its export-oriented rural linen industry and typically relied on women in the role of flax spinners. This makes that marriage certificates from the West-Flemish civil register system are an excellent opportunity to overcome both challenges with respect to the study of female intergenerational mobility: not only were brides identified by their maiden names, their occupational activity at marriage was also commonly recorded (see Figure 1). Furthermore, the economic history of West Flanders presents us with interesting variation. In the middle of the 19th century, its once-flourishing rural linen industry collapsed under the pressure of mechanized competition in neighboring regions. This dramatic demise hit women disproportionally hard, as flax spinning was a common source of income among West-Flemish women. Towards the end of the 19th century, this period of economic turmoil was followed by a gradual process of industrialization.

Figure 1: Registration of an economic activity of the bride; 1830-1900

Results and discussion

Building on the intra- and intergenerational linkage of more than a million digitized civil birth and marriage certificates, we were able to construct a comprehensive sample of 40,703 parent-child pairs. We find evidence of a gender gap in occupational mobility, with sons being more attached to their socio-economic roots. Throughout the period under observation, however, there were only modest mobility gains for daughters compared to sons, leading to a gender convergence in mobility. Moreover, the risk of ending up in an unskilled occupation became progressively bigger for West-Flemish women as the rural industry was replaced by mechanized industries in neighboring areas. Overall, this presents a gloomy picture for 19th-century daughters, as they missed out on the possibilities offered by industrialization in terms of intergenerational mobility and socio-economic status.

In the background of the demise and resurgence of West Flanders’ industry, we point to two causal factors underlying these differential trends in socio-economic attainment. First, hand spinning – a typically female activity - was mechanized much more rapidly, leading to a starker decrease in the payoff of investing in daughters’ human capital and to higher levels of female mobility. In contrast, traditional linen weaving remained competitive against mechanized production for much longer, so the deindustrialization process went more smoothly for men. A second explanation for the overall lower mobility in the post-crisis period as well as the observed gender differential in mobility can be found in the gradual emergence of migration. We find that selection effects due to geographic mobility played a more important role in the determination of male intergenerational mobility, suggesting that migration was a more effective way to achieve social mobility for male workers.

From an international perspective, our results largely align with recent developments in the literature. Our estimates for father-son mobility are consistent with the idea that intergenerational mobility was significantly higher across the Atlantic Ocean (see Pérez 2019). Importantly, we present first evidence that a similar case can be made for daughters. Expanding our empirical framework to marital mobility, in which we take the traditional approach of imputing female social status by their husband’s attainment, a direct comparison with recent work on the US reveals that mobility in the US was markedly larger not only for sons, but also daughters (Craig, Eriksson, & Niemesh, 2019). Strikingly, a similar pattern is also found for American women, as daughters enjoyed less benefits in terms of mobility growth throughout the 19th century.

Read more about Vincent Delabastita's research at his website here; you can follow him on twitter here

Read more about Erik Buyst's research at his website here


Craig, J., Eriksson, K., & Niemesh, G. T. (2019). Marriage and the intergenerational mobility of women: Evidence from marriage certificates 1850-1910 (Tech. Rep.). Department of Economics, UC Davis. (Mimeo)

Dribe, M., Eriksson, B., & Scalone, F. (2019). Migration, marriage, and social mobility: Women in Sweden 1880-1900. Explorations in Economic History, 71, 93 - 111.

Humphries, J., & Sarasúa, C. (2012). Off the record: Reconstructing women’s labor force participation in the European past. Feminist Economics, 18(4), 39–67.

Olivetti, C., & Paserman, M. D. (2015). In the name of the son (and the daughter): Intergenerational mobility in the United States, 1850–1940. American Economic Review, 105(8), 2695–2724.

Olivetti, C., Paserman, M. D., & Salisbury, L. (2018). Three-generation mobility in the United States, 1850–1940: The role of maternal and paternal grandparents. Explorations in Economic History, 70, 73–90.

Pérez, S. (2019). Intergenerational occupational mobility across three continents. The Journal of Economic History, 79(2), 383416.

Tuesday, 2 February 2021

Comparing Income and Wealth Inequality in Pre-Industrial Economies: the case of Castile (Spain), c. 1750


by Esteban Nicolini and Fernando Ramos-Palencia (@framospalencia)

blog post based on the article, "Comparing income and wealth inequality in pre-industrial economies: the case of Castile (Spain) in the eighteenth century", available on EHER early view here

Our knowledge of the evolution of economic inequality within countries in pre-industrial Europe has expanded considerably in the last years. The two most important dimensions of economic inequality in the literature are related with income (a flow) and wealth (a set of assets); although many researchers implicitly assume that these two variables are very good substitutes of each other, there is no study on the relationship between these two variables for pre-industrial Europe. 

In general, incomes are composed by the returns to physical assets (capital or land), to financial assets, to human capital and to raw labor; on the other hand, for a given person or household, the stream of incomes influence savings that accumulate in future wealth. The relative importance of the different kinds of assets in total wealth and in the generation of income, changed substantially with economic growth. In modern societies, the agricultural sector plays a relatively minor role in aggregate production, income inequality is only weakly linked to the distribution of land property and a large bulk of income inequality is related with labor incomes and retribution to human capital (Shorrocks 1982). However, in traditional pre-industrial economies, most of the population worked in the primary sector, land and labor were the most important productive factors and land property was a major source of income, power and status. In these economies, where average human capital was relatively low, most of economic inequality is expected to be explained by land distribution; even though labor retributions can be an important share of the total value of production, if labor is evenly distributed across individuals, its contribution to total income inequality would be small. So far, many scholars have relied on the methodological assumption that, in preindustrial economies, inequality of assets like land or real estate could be considered a reasonable proxy of income inequality because the different subsets of wealth would correlate very well with each other and all of them would correlate very well with income (for instance, Alfani 2015; Lindert 2014; Alfani and Ammannati 2017).

We have scrutinized the validity of this assumption in our paper. In highly urbanized commercial junctures, trading capital is probably important as well as Soltow and Van Zanden (1998) assume for Amsterdam in the eighteenth century and even in less economically advanced societies, labor income differences can be important: Nicolini and Ramos-Palencia (2016) have suggested that labor incomes contribute up to 65% of income inequality in urban areas of Old Castile in the 18th century and Álvarez and Ramos-Palencia (2018) have stressed the importance of human capital to explain income inequality in the same region and period.

Our article presents a new data set to analyze economic inequality in Spain based on information, circa 1750, from Palencia, Madrid, Guadalajara and Granada. This data set has some unique characteristics. First, it combines information from two different sources: probate inventories, which contain detailed descriptions of household wealth; and the Ensenada Cadastre, a mid-century government census that contains information about household income, the contribution of each income source (for instance land or labor) to total income and other characteristics like household head’s occupation and ability to sign. Second, the data set enables us to link the households from the set of inventories with their corresponding records in the Cadastre; this connection makes it possible to analyze the relationship between the income of a household when the Cadastre was produced and the wealth of that household some years later, when its head passed away. This data set opens the possibility to link the distributions of income and wealth so that we can propose hypotheses via which their differences can be better understood and the possible shortcomings of using one as a proxy for the other.

We find that the income assigned by the EC and the wealth registered in the PIs are closely associated suggesting that, even though income inequality seems to be consistently less than wealth inequality, both variables capture very well a unique dimension of economic inequality in pre-industrial economies and that a given household’s location in one distribution depends strongly on its location in the other. Given that many times, data scarcity forces researchers to use the distribution of wealth, real estate or other assets to approximate the distribution of income (Alfani 2017, Lindert 2014), the confirmation that household’s wealth can be a very good predictor of income is extremely valuable from a methodological point of view.

Using an econometric specification in which both income and wealth are stated in terms of their logarithms the elasticity of income with respect to wealth varies between 0.4 and 0.6 (depending on the specification). These values imply that a 10% increase in the wealth of a household is associated with its income being from 4% to 6% higher. Elasticity that is less than 1 is consistent with general observations –confirmed with our data- that wealth inequality is greater than income inequality.

The parameters associated with our Secondary and Tertiary dummy variables are positive and the former is statistically significant in all the specifications. This result suggests that, for a given level of wealth, households with a head who works in one of those sectors, particularly in the secondary sector, tend to have more income than households with a head who works in the primary sector. Variables proxying human capital also have a sizable impact on the income distribution: for a given level of wealth those heads of households with skills (mainly captured by the kind of occupation but also by the ability to sign) have significantly larger incomes than those without skills highlighting the importance of the human capital in the determination of labor incomes (Álvarez and Ramos-Palencia 2018). 

For instance, using the parameters obtained in the regression in levels (see specification C in the table above), we can compare the income predicted by our equation for a head of a household without any wealth or human capital and working in the agricultural sector (394 reales) with the income predicted for a similar household but with some human capital; if we add literacy to this head of the household, income would increase 90% (up to 749 reales) and if we predict the income with a high-skill occupation income would increase 224% (up to 1278 reales).

These examples show that the way in which the wealth and income distributions are related is more complex than the one suggested by a pure traditional and agricultural society in which land and real estate are the only productive assets generating social differentiation. Our results suggest the relationship between income and wealth can be affected in some non -trivial ways if the whole society or some households experience shocks like mortality picks or migration (voluntary or forced) that change the nature and strength of that correlation. This multidimensional nature of the income inequality is not necessarily surprising and the roles of different kind of assets and human capital in the income distribution have been already emphasized for urban sophisticated economies in 17th and 18th centuries (Soltow and Van Zanden 1998). However, the confirmation of this pattern in a relatively backward and traditional economy (Alvarez-Nogal and Prados de la Escosura 2013) would suggest that in Modern Europe, structural change, urbanization and sophistication of labor markets would generate complex changes in the income distribution and in the relationship between overall income, income sources and wealth that can be overlooked if we focus only on one dimension of economic inequality.