Criticism of GDP—Gross Domestic Product—has grown dramatically over the last few years. By definition, GDP is simply an expression of the value of all goods and services produced within a nation in a given year. Yet many critics argue that it is much more than that, and that our use of the statistic requires serious rethinking just as the statistic itself needs revision. Scholars, activists, and policy experts have charged that it no longer effectively captures how economies function; that it is far too reductive to be of much use; that it has proven far too susceptible to errors of counting; and, most pressingly, that it has led to misguided aspirations and destructive values.
Three books published in the past year—Diane Coyle’s GDP: A Brief but Affectionate History, Zachary Karabell’s Leading Indicators: A Short History of the Numbers that Rule Our World, and Lorenzo Fioramonti’s, Gross Domestic Problem: The Politics Behind the World’s Most Powerful Number—have now entered into these debates. They each ask the same set of vital questions: Why did GDP arise? What’s wrong with it? And what should be done? While all the authors present very similar explanations for the concept’s creation and its pitfalls, they offer starkly different suggestions for what we should do about it.
Coyle, an economist and writer, believes that GDP is, by and large, a useful tool. She believes it should be tweaked, rather than discarded. In her view, GDP worked well for the largely national, industrial economies of the early and middle twentieth century. It works less well for our own economy, with its emphasis on services, finance, rapid technological innovation, and globalization.
All that said, Coyle claims that the metric “does a better job than any currently available alternative.” So we should keep GDP, she says, though only if we supplement it with alternatives, such as the Human Development Index (with its emphasis on social indicators, such as literacy and education levels), develop a better measure of environmental sustainability for national governments, and modernize the collection of statistics using new technologies. She ends with a firm statement on the importance of keeping GDP separate from discussions of social welfare; the metric was never meant to measure that, she points out, so we should refrain from conflating the two any longer. In the end, her solutions are modest and generally technical—supplementing old numbers with new ones.
Karabell, a financial manager and strategist with a PhD in international history from Harvard, is less sure. While he agrees that GDP no longer harmonizes well with the nature of economic activity today, he is more wary of the quest for reductive indicators (he does not, after all, limit his book to national income statistics). The “key limitation of GDP,” he says, is not “its methodology, not what it includes or excludes.” Rather, it is “the very fact that it attempts to distill into one figure complicated, ever-changing economic systems.” In the 1930s, economists first created and used GNP (Gross National Product, the forerunner to GDP) with a specific set of purposes in mind—planning to get out of the Depression chief among them. Since circumstances have changed, Karabell points out, so too must our statistics.
So what to do? We need “bespoke indicators,” by which he means numbers “tailored to the specific needs and specific questions of governments, businesses, communities, and individuals.” We’ll still need statistics, to be sure, but they’ll be tailored to specific needs, not general principles. And, he explains, any new statistics “would have to be used modestly and not become fetishized as ‘the truth’ the way current indicators have been.” His solution is thus both technical and cultural—changing the numbers we use, but also reshaping the ways we rely on them and think about them in our daily lives.
Of the three authors, Fioramonti, a political scientist, is the most strident in his criticism. He shares many of Karabell’s concerns, but goes even further to question the very assumptions that gave rise to aggregate economic statistics in the first place. He questions whether the use of such numbers now has any value at all. For him, thinking in terms of GDP is symptomatic of deeper problems. “GDP dogma” has “impoverished democracy” by glorifying the role of technocrats. It has also deeply harmed cultural life, because the dogma has “reduced the time spent on leisure and amplified the burden of work.” Fioramonti is less concerned with the statistic itself than he is with the thinking that created, legitimized, and naturalized its use; his book is, at base, an argument against technocracy.
While he celebrates reform movements offering alternative statistics (such as ecological economics and some social indicators), he also writes approvingly of movements that focus on the decentralization of power and production. In particular, he spotlights the “de-growth” movement that seeks to arrest our current economic growth (and reverse it in some cases), as well as local communities that use their own currencies and banking systems to break free of the larger financial power structures (states, multinational corporations) that dominate economic transactions worldwide. At root his prescriptions are cultural and political; no technical fixes will suffice.
Each author states his/her case with passion, and each provides some insight into the “problem” of GDP today. Yet for all their rich analysis, the authors skirt over a key problem.
Each book lacks an explanation of how the underlying process of cultural change surrounding these numbers unfolded. Or, to put it another way, how statistics adopted by national elites reshaped what citizens expected and thought about the world, and in so doing, altered what they valued. Karabell writes, “The transformation of these numbers [such as GDP] from statistics used by bureaucrats and managers into markets of societal success happened so quickly yet subtly over the course of a few decades that no one quite noticed what was happening.”
That is indeed remarkable, but how and why did it occur? Why did the conflation between GDP and welfare and happiness (along with the implicit conflation between measurement and assessment) stick? Historians such as Ted Porter have looked into how statistics gained cultural power, and historians such as Michael Bernstein and Angus Burgin (among others) have identified how and why economists developed policy influence and cultural authority in the twentieth century. But more work needs to be done to bridge the gap between the ways in which these numbers set the parameters for policy making and the ways in which they have come to shape entire world views. If GDP’s stranglehold on our policymaking and discourse is ever to be loosened, we’ll need not only better numbers but new ways of thinking about what we want those numbers to mean, to show, and to do. To start, we’ll need more work that lays bare the relationship between the normative character of our leading indicators and our own normative assumptions about them. Only after understanding how and why GDP has taken hold in contemporary life—and how and why the thinking that supports its ongoing misuse persists—can we begin to redress the anxiety over measurement that has ensnared so many of us today.
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