The Development of Wellbeing in History: What can we learn from Summary Indicators?
At the heart of economic history is the question how human wellbeing has evolved throughout time. There is no simple answer. In fact, before being able to address this question and actually measure wellbeing, it has to be clear what wellbeing exactly entails. In other words, what aspects of welfare should be measured? And what statistical indicators are most suitable for studying those aspects of welfare?
The literature has not reached a consensus on any of these questions yet. Researchers have long since relied on GDP as a comprehensive welfare measure (Oulton, 2012), but this indicator is being increasingly criticized. Although the concept has proven useful, GDP per capita does not fully capture crucial aspects of wellbeing such as health, political freedom or inequality (Deaton, 2013). Going ‘beyond GDP’ by incorporating these elements can have important implications for our understanding of the past, especially in periods in which the development of GDP deviates from that of other welfare dimensions. This session aims at presenting the latest additions to this debate and their consequences for economic history.
To account for the multi-dimensional character of wellbeing, various alternative strategies have been proposed, ranging from the dashboard approach advocated in the Stiglitz, Sen and Fitoussi (2009) report to composite indicators such as the Human Development Index (UNDP, 1990). In this session, we invite paper proposals on all topics related to the ‘beyond GDP’ measurement of wellbeing, but a special interest goes out to work on composite indicators.
If wellbeing is studied using a composite indicator, there is a range of methodologies that can be applied to collapse various welfare dimensions in one measure, each of them with particular strengths and weaknesses. For instance, the HDI – which combines key aspects of people’s life such as income, education and health – is nowadays seen as problematic and raises important questions. Why are only these three dimensions included? Are they interconnected? What is their relative importance in the final indicator? There is a lack of strong theoretical basis and, consequently, the HDI and other composite measures that assign equal weights to the underlying components have been referred to as ‘mashup indices’ (Ravallion 2012).
Several promising research avenues have recently been explored to tackle the weighting problem. One employs statistical methods to aggregate the various dimensions of wellbeing such that the ensuing composite indicator results from a full and efficient use of the information contained in the underlying dimensions. An example of this strategy is Rijpma’s (2014) composite indicator of historical wellbeing based on the various social dimensions studied in the OECD’s How was Life?-project. Yet there are also drawbacks to this approach, among which the concern that the weighing process does not follow from economic theory.
This concern is partly addressed in the work of Prados de la Escosura (2016), who suggests an economic rationale to validate the collapse of several dimensions of economic liberty in a composite index of economic freedom. A more explicit link with economic theory can be found in the strand of literature that uses utility frameworks to combine different welfare aspects. Examples are the works of Williamson (1983) on Britain and that of Becker et al. (2005), Fleurbaey and Gaulier (2009) and Jones and Klenow (2016) on a broader set of countries.
Despite recent advances in this field, little is known about the implications of new composite measures of wellbeing for our understanding of and narratives in economic history. More research is needed and hence we invite papers on related topics.
Questions regarding the session can be directed to Daniel Gallardo Albarrán (e-mail: email@example.com).
- Joost Veenstra, University of Groningen, firstname.lastname@example.org,
- Leandro Prados de la Escosura, Carlos III University of Madrid , email@example.com,
- Daniel Gallardo Albarrán, University of Groningen, firstname.lastname@example.org,
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- David Weil, Brown University,