Blackberry Pie Murder
By Joanne Fluke
(Diane Coyle is an economist and the author of "GDP: A Short but Affectionate History.")
In the dark days of the Great Depression, the economist Simon Kuznets set about calculating the total national income of the United States. It was a case of a demand creating its supply, the demand by Congress and citizens to understand the scale of the economic calamity the nation was then experiencing. The same demand for understanding helps explain the public’s interest these days in what might otherwise seem to be dry, uninviting economic statistics. How secure is the recovery from the impact of the 2008 financial crisis? What good is a recovery that benefits only the wealthy minority? Do our children have any hope of seeing their living standards rise as ours did over the late 20th century - or is that dream of progress over?
Zachary Karabell’s lively account, “The Leading Indicators,” is a terrific introduction to the range of statistics economists and governments use to address these questions. As Karabell tells us, the role of the government in the economy explains why we have the statistics we do: “Until the early 20th century, significant economic hardship was so woven into human history and experience that it wasn’t yet seen as an aberration. Only the combination of a severe crisis and the belief that such crises not only could but should be prevented by collective government action led to the creation of unemployment statistics.” Karabell also shows how many judgment calls are involved in developing statistics. Even so seemingly straightforward a measure as unemployment requires assumptions - for example about how to treat transient workers or students or people who are working fewer hours than they would like. This is why there are several different unemployment measures, although only one hits the headlines.
Rulers have long collected some statistics, Karabell points out. William the Conqueror’s Domesday Book of 1086 was a comprehensive register of his kingdom’s assets. Karabell also pinpoints right at the start the central challenge of economic measurement: The reality is complex, but the politicians and the public demand simple answers. Gathering statistics is both a sophisticated technical exercise and an art of storytelling aiming to show the main contours beneath the confusing mass of numbers. Just as in the famous short story by Jorge Luis Borges, “On Exactitude in Science,” a map with a one-to-one scale would defeat its purpose.
Karabell’s book gets into its stride with the 1930s, and the impetus the Depression and then World War II gave to the collection of the economic statistics so familiar to us now. He breathes life into what could be a dull story by giving walk-on parts to some of the economists and statisticians involved, and to politicians like Herbert Hoover and Franklin Roosevelt, who made the collection of economic data a government activity. A set of official statistics is now published pretty much every day; the key numbers drive the financial markets and are listed like magical incantations by commentators in the news media.
“No single number has become more central to society in the past 50 years” than gross domestic product, Karabell says. It led to nothing less than the invention of “the economy” as a concept. “Until the 1940s, there was no 'the economy.' People did not use the term, and they had only just begun to think of the material affairs of a nation as a coherent and cohesive subject that could be defined, measured and tracked over time.”
Here he might have made more of the way the measurement of G.D.P. and the theories of the British economist John Maynard Keynes reinforced each other. Without G.D.P., it would have been hard to put into practice the idea that the government could manage the economy like a machine.
The second half of the book turns to more recent history and the way changes in the character of the economy are making the conventional statistics less useful. Take inflation. Karabell describes the fraught history of the Consumer Price Index, politicized from the start by accusations that the government wanted to underplay cost-of-living increases to limit Social Security payments and bear down on wage claims. The methodology has changed frequently, including the introduction of a “core” measure that excludes food and energy prices, although any normal person would think these a central part of most people’s cost of living. The most recent issue has been how much to adjust rises in the C.P.I. to take account of the large improvements in the quality of consumer electronic goods, the so-called “hedonic” adjustments. The digital economy poses all kinds of statistical problems, from how to actually collect price data to reflect online purchasing to the deeper question of how to assess the benefits consumers get from “free” services online. Economists like Erik Brynjolfsson and Andrew McAfee in their book “The Second Machine Age” and Michael J. Mandel of the Progressive Policy Institute have written extensively about this.
So we come full circle to the question of what we mean by “the economy” when it is changing so much. Karabell is far too kind to the claim that governments should try to increase “gross national happiness.” The kingdom of Bhutan replaced standard economic measures with measures of happiness as long ago as 1972. Yet Bhutan’s G.D.P. per head is still one of the lowest in the world, life expectancy is relatively low and infant mortality high, so it is easy to see why the king would not want anyone to mention the economy. And Karabell is too unkind to the idea suggested by the Nobel Prize-winning economists Amartya Sen and Joseph Stiglitz, together with the French economist Jean-Paul Fitoussi, of looking at a “dashboard” of indicators of well-being instead of simply one. He writes here: “All of these efforts dance around the core challenge of what to do with a set of entrenched indicators that frame the way almost every country in the world - Bhutan notwithstanding - assesses its economic success and the viability of its national economic policies.” Yet he goes on to describe the great success the statistician Hans Rosling has had in bringing to life the way numbers tell meaningful stories. There is no reason to believe dashboards cannot become both engaging and influential statistical reports, and to be given as much attention as the quarterly G.D.P. figures.
For as Karabell himself concludes, “no one number will suffice.” Modern economies are complicated, with a vast range of products and services. G.D.P. was adequate for the age of mass production, but adding up the components of today’s American economy is not the same as adding up the number of cars rolling off the assembly line. Even more important is a distinction not made clearly in the book, namely the difference between economic activity and society’s well-being. We need a measure of total activity, but G.D.P. cannot indicate how good economic prospects are for the next generation, or even for a majority of us today. The so-called leading indicators no longer answer the most important questions people are raising about how they live.
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