Auke Rijpma

Vast amounts of heterogeneous knowledge are becoming publicly available in the form of knowledge graphs, often linking multiple sources of data that have never been together before, and thereby enabling scholars to answer many new research questions. It is often not known beforehand, however, which questions the data might have the answers to, potentially leaving many interesting and novel insights to remain undiscovered. To support scholars during this scientific workflow, we introduce an anytime algorithm for the bottom-up discovery of generalized multimodal graph patterns in knowledge graphs. Each pattern is a conjunction of binary statements with (data-) type variables, constants, and/or value patterns. Upon discovery, the patterns are converted to SPARQL queries and presented in an interactive facet browser together with metadata and provenance information, enabling scholars to explore, analyse, and share queries. We evaluate our method from a user perspective, with the help of domain experts in the humanities.

Attempts to measure social mobility before the twentieth century are frequently hampered by limited data. In this paper, we use a new source – annual, matched tax censuses over more than 70 years – to calculate intragenerational income mobility within a preindustrial, settler society, the Dutch and British Cape Colony at the southern tip of Africa. Our unique source allows us to measure income mobility along several dimensions, helping to disentangle reasons for the high levels of persistence we find.

Economists and social scientists have widely contributed to the so‐called “Beyond GDP” debate—the view that current measures of economic growth are inadequate to measure well‐being and multidimensional indicators. While economic history has not been prominent in these debates, multidimensional indicators have captured the interest of economic historians, with both theoretical and empirical contributions. In this contribution, we examine the areas of consensus and debate in economic history. A comprehensive literature review shows a lack of consensus on how to use multidimensional indicators and that they face substantial critiques. We use two case‐studies (a long‐term series for the Netherlands and one on the basis of the CLIO‐INFRA panel dataset) to illustrate how common findings emerge in the literature and empirical exercises despite methodological differences. We argue that debates on the relation between economic growth and well‐being in the long‐run using these indicators can not only contribute to many founding questions in economic history—though greater precision and transparency in our assumptions about well‐being measurement are necessary—but also to better understand present‐day challenges such as how to better pursue growth in well‐being and not merely in GDP.

We investigate the demographic effects of forced labor under an extractive colonial regime: the Cultivation System in nineteenth-century Java. Our panel analyses show that labor demands are strongly positively associated with mortality rates, likely resulting from malnourishment and unhygienic conditions on plantations and the spread of infectious diseases. An instrumental variable approach, using international market prices for coffee and sugar for predicting labor demands, addresses potential endogeneity concerns. Our estimates suggest that without the abolition of the Cultivation System average overall mortality in Java would have been between 10 and 30 percent higher by the late 1870s.

A century ago, the 1918–19 influenza pandemic swept across the globe, taking the lives of over 50 million people. We use data from the Dutch civil registry to show which regions in the Netherlands were most affected by the 1918–19 pandemic. We do so for the entire 1918 year as well as the first, second, and third wave that hit the Netherlands in summer 1918, autumn 1918, and winter 1919. Our analyses show that excess mortality was highest in Oost-Brabant, Zuid-Limburg, Noord-Holland, and Drenthe, Groningen, and Overijssel, whereas excess mortality was low in Zuid-Beveland, the Utrechtse Heuvelrug, and the Achterhoek. Furthermore, neighboring municipalities resembled one another in how severely they were affected, but only for the second wave that hit the Netherlands in autumn 1918. This non-random spatial distribution of excess mortality in autumn 1918 suggests that regional differences affected the spread of the disease.

How was life in 1820, and how has it changed since then? This question, which was at the core of How Was Life? Global Well-being since 1820, published by the OECD in 2014, is addressed by this second volume based on a broader perspective. How Was Life? New Perspectives on Well-being and Global Inequality since 1820, presents new estimates of working hours, biodiversity loss, social spending and GDP (accounting for the 2011 round on purchasing power parities) as well as measures of inequalities in wealth, longevity and educational attainment, gender disparities and extreme poverty. A final chapter synthesises the historical evidence included both in the current and previous volume of How Was Life? through composite measures of the average well-being performance of each country, and of different within-country inequality measures. As was the case for the previous volume, this book combines both a historical and a global perspective, presenting estimates since 1820 for 25 major countries and 8 world regions. While this evidence sometimes relies on partial and limited evidence, each chapter in this book assesses the quality of the data used and identifies areas for further historical research. This second volume of How Was Life? is the product of collaboration between the OECD and the OECD Development Centre, on one side, and a group of economic historians gathered around the CLIO-INFRA and Maddison projects, on the other. The historical evidence included in the report is organised around dimensions of well-being that mirror those used by the OECD in its report How’s Life?

Despite recent progress, women are still disadvantaged by their greater domestic labor commitments and impaired access to well-paid jobs; and, in extreme cases, denied the right to live. This has consequences for the well-being of individuals and economic development. Although tools to evaluate country performance in gender equality, especially composite indicators, have been developed since the 1990s, a historical perspective is lacking. This study introduces a composite index of gender equality covering 129 countries from 1950 to 2003. This index measures gender equality in four dimensions (socioeconomic, health, household, and politics). The index shows substantial progress in gender equality, though there is little evidence that less gender-equal countries are catching up. Goldin's “quiet revolution” hypothesis is tested as an explanation for this observation, but fails to provide a good explanation. Rather, the long-term institutional and historical characteristics of countries are the main obstacles to convergence.