Hostname: page-component-745bb68f8f-cphqk Total loading time: 0 Render date: 2025-02-06T17:41:42.310Z Has data issue: false hasContentIssue false

Joseph Stiglitz, Jean-Paul Fitoussi and Martine Durand (eds) (2019), For Good Measure: An Agenda for Moving Beyond GDP, New York and London: The New Press, $39.99, pp. 448, hbk.

Review products

Joseph Stiglitz, Jean-Paul Fitoussi and Martine Durand (eds) (2019), For Good Measure: An Agenda for Moving Beyond GDP, New York and London: The New Press, $39.99, pp. 448, hbk.

Published online by Cambridge University Press:  26 November 2020

IRIS BOROWY*
Affiliation:
Shanghai Universityborowyiris@i.shu.edu.cn
Rights & Permissions [Opens in a new window]

Abstract

Type
Book Review
Copyright
© The Author(s), 2020. Published by Cambridge University Press

All books come with a context, but some more than others. This volume forms part of a larger movement, within and outside of academia, to change the mainstream economic system as we know it. In itself, the underlying ideas are not new. The limitations and weaknesses of the Gross National Product (GDP) have been pointed out for decades, and renegade economists like Herman Daly have demanded a fundamental change in developmental goal-setting and accounting since the 1970s. But recent years, partly influenced by the financial crisis of 2007 and the subsequent occupy movement, have seen an upsurge in books on related topics. This includes publications critically reviewing GDP (Philipsen, Reference Philipsen2015), economic inequality (Piketty, Reference Piketty2014), or the destructive force of an economic system based on GDP growth for the environment.

Nobel prize laureate Joseph Stiglitz clearly establishes the connection of this volume to this context in his introduction: though all countries routinely calculate and report on their national GDP (Gross Domestic Product) this information value of this number is very limited. This was obvious in the aftermath of the recession of 2007-2009 when data about solid GDP growth in the United States were so at odds with people’s everyday experience that some suspected their government to be lying. In reality, the number was correct but failed to show that 91% of the increase of national income between 2009 and 2012 went to the top 1% of earners, leaving the rest of the population unaffected. The number was correct but misleading, and, because it was, governments lacked the information to make good decisions.

However, the origins of the volume predate the crisis. In 2008, French President Nicholas Sarkozy established a Commission on the Measurement of Economic Performance and Social Progress, chaired by Stiglitz and Jean-Paul Fitoussi. This group of high profile economists published a much noted report discussing alternative measurements of quality of life and sustainable development (Stiglitz et al., Reference Stiglitz, Sen and Fitoussi2010). This research tied into similar work at the OECD, headed by chief statistician Martine Durand, related to the biennial publication of How’s Life and a Better Life Index. In 2013, these strands came together in a High-Level Expert Group on Economic Performance and Social Progress. The volume under review is one of its outcomes. Another is a more reader-friendly summary, called Measuring what Counts. Both texts exist in book form and are also freely accessible on the OECD website (OECD, n.d.).

This background explains the hybrid character of the volume as something between an academic study and an extended policy paper. It is a collection of nine scholarly chapters, each dedicated to the discussion of statistical methods regarding items which are not (yet) measured in conventional economics. But it is also an effort with a political mission: to give stake holders and the public the statistical tools to understand socio-economic wellbeing. The list of contributors reads like the who’s who of eminent international economists, including Thomas Piketty, François Bourguignon, Nora Lustig, and Emmanuel Saez, assisted by two more Nobel laureates, Amartya Sen and Angus Deaton, who contributed to discussions at some point. Nine, often co-authored chapters address the economic and social progress in relation to the Sustainable Development Goals; the distribution of household income, consumption and wealth; horizontal inequalities; inequality of opportunity; distributional national accounts; subjective well-being; economic security; sustainability; and trust and social capital. The texts are well written but long, sometimes interspersed with pages of tables or mathematical equations, the scholarly weight underscored by impressive bibliographies. Readers who are unwilling to work their way through 422 pages of sometimes complicated analysis can limit themselves to the summary in the first chapter. Those who do read the entire volume are rewarded with a detailed, often fascinating discussion of data, their sources, strengths and weaknesses regarding essential components of socio-economic well-being.

A recurrent theme in the collection is inequality, be it between the wealthy and the poor (chapters 2, 3, 6 and 8), between men and women (chapter 4), in terms of income (chapter 3), of opportunity (chapter 5) or of economic security (chapter 8). Collectively, the chapters make clear beyond doubt that people experience the world in radically different ways and that societies need statistical tools to “see” these differences. Other focuses address subjective components of socio-economic wellbeing (chapters 7, 8 and 10) and different forms of sustainability (chapters 2 and 9). Repeatedly, authors insist that intelligent policies will require taking a more comprehensive view not only of what constitutes wellbeing but also of seemingly well-defined concepts such as income or wealth.

Overall, the volume paints an ambivalent picture of the field as being at once far more advanced than a decade ago and still painfully deficient. On the positive side, several chapters list an impressive number of places where relevant data are being collected and are often made publicly available online, notably with regard to household incomes (chapter 3), subjective well-being (chapter 7), inequality (chapter 6), and national and international monitoring of sustainable development (chapter 9). Clearly, the time when GDP was accepted as the only or even the central number depicting progress is coming to an end.

Nevertheless, challenges abound on several levels: One is practical, as with regard to incomes of the very poor and the very rich, which are routinely underreported, or to distributional differences within households, usually not reported at all. Then, there are difficulties to find statistical expressions of non-monetized aspects of socio-economic reality such as subjective wellbeing, human capital or inter-personal trust. Comparability of data is compromised when services, such as education and health care, are organized in different ways; so, depending on whether they are private or public goods, access to them can be more or less sensitive to income variations. Similarly, different monetary or non-monetary taxes or subsidies make it difficult to calculate and compare household incomes, and different forms of public and private buffers make it difficult to compare economic insecurity between countries.

Other challenges are conceptual: defining (in-)equality of “opportunity” requires decisions between ex ante opportunities of fair chances, difficult to specify and even harder to measure, and ex post opportunities of outcome, easier to measure but difficult to distinguish from effort (chapter 5). Similar challenges await for definitions of economic (in-)security, human capital and trust, and for all data, how do you establish causality between correlated items, and how do you capture the value of systems, i. e. the interaction of different sets of data whose systemic impact is presumably larger than and possible different from the sum of every individual set? This is an important effect in matters of sustainability (chapter 9), but interactions have likewise been found in matters of trust (connected with human and social capital), subjective wellbeing (connected with inequality and resilience), inequality (connected with opportunity and life expectancy). Sometimes these questions invite thinking not only about data but about the philosophical underpinnings of how we define values of social life and wellbeing.

Most chapters focus on discussions of statistical methodologies but some add findings gained from such data. Thus, chapter six on economic inequalities describes how the spectacular economic growth in China provided enough improvements for everybody to gloss over the rising inequality which accompanied it. Meanwhile, the situation is different in the United States, where income gains have been virtually monopolized by the top earners, and in France where economic gains have been modest but relatively fairly distributed. Chapter seven explains that evaluative subjective wellbeing is highest in Scandinavian countries and lowest in some countries of Sub-Saharan Africa, but that differences are much smaller in experienced wellbeing. Readers also learn that economic insecurity is more widespread than often suspected even in high-income countries. According to one estimate, more than half of all Americans or working age have spent at least one year below 150% of the federal poverty line in recent decades. Meanwhile, there are dramatic differences in how far citizens in different countries trust one another, with people in Norway most trusting of their fellow citizens and Trinidad and Tobago least so (p. 399).

Throughout, the contributions make clear that these wellbeing oriented measurements will not replace but complement conventional economic goals: human and social capital are correlated to GDP and economic growth (chapters 9 and 10); trust is important for trade, innovation, investment, employment as well as health, equality and tax payment; inequalities often constitute misallocation and inefficiency in the use of resources and can breed economically harmful social conflict (chapters 3 and 4). Evaluative subjective wellbeing is tied to relative (though not absolute) increases in income, health, employment and environmental quality, all of which, in turn, have an economic component (chapter 7). And, impressively, Yann Algan in chapter 10 cites a study according to which “[i]ncome per capita in 2000 would have been 546% higher in Africa if, all else being equal, the level of inherited trust had been the same as inherited trust from Sweden” (p. 401).

Overall, the volume shows that research and application into non-conventional measurements is growing but still relatively recent and highly concentrated in – mostly Western – high-income countries. For instance, so far, virtually all participants in experiments regarding interpersonal trust have been students at Western universities, globally one of the least representative group of people imaginable. So, there is an urgent need for more data from poor countries, as well as for long-term observations and, above all, for more systemic approaches, needed not only for a more realistic understanding of the drivers of important global dynamics and reasonable goal settings, but also for more resilient responses to inevitable future shocks to human systems.

Generally, the volume is a highly welcome contribution to necessary ongoing debates on innovative, systemic and, frankly, more useful approaches to developmental thinking. But some readers may wonder about the unmitigated trust in numbers. This point may be inevitable: after all, this is what the entire book is about. But it might have been fruitful to include some reflection at some point about the limits to what can be expressed with data. Besides, there is no reflection on the fact that if the data are about mathematical modelling they are also about power, and considerations about inequality seem deficient without at least some acknowledgement of the power asymmetries they reflect and perpetuate. If not commenting on these political aspects was a conscious decision by authors and editors in order to prevent distractions from the factual quality of the findings or to avoid the risk of findings being discredited as “political”. But if that was so, a brief clarification of this issue might have been better than ignoring its existence.

Finally, the purpose of this volume might have been served even better if more explanations had been incorporated on the practical implications of those measurements. Some examples exist, and chapter nine makes a strong case that more awareness of the economic value of human capital might have prevented austerity measures. Most straight forward, Yann Algan argues in chapter 10: “Insufficient measurement of nonmonetized capital (such as human, social, and natural capital) will lead policy-makers to ignore it, and to invest insufficient resources to protect it” (p. 415).

This reviewer hopes that many policy makers will read this book.

References

Philipsen, D. (2015), The Little Big Number: How GDP Came to Rule the World and What to Do about It, Princeton: Princeton University Press.Google Scholar
Piketty, T. (2014), Capital in the Twenty-First Century, Cambridge: Harvard University Press.10.4159/9780674369542CrossRefGoogle ScholarPubMed
Stiglitz, J., Sen, A. and Fitoussi, J.-P. (2010), MIS-Measuring Our Lives: Why GDP Doesn’t Add Up, New York: New Press.Google Scholar