Brave New Math

In 1968, at age 56, my grandfather had a heart attack. It surprised a lot of people. With a full head of hair, he was thin, youthful looking, and rarely sick. He received standard patient treatment for the time—prolonged bed rest and morphine. When he recovered, he continued his pre-attack lifestyle which included smoking, almost no exercise, and a diet of meat, potatoes, and my grandmother’s cream pastries. Five years later, he was dead, the result of another heart attack.Had my grandfather been born a quarter century later, he surely would have lived longer than 61 years. Scientific advances in the last 40 years have greatly improved the prevention, diagnosis, and treatment of heart disease both in the United States and abroad. In the 1960s, the chance of dying within days of a heart attack was almost 40 percent in the U.S. By the 1970s, it dropped to 25 percent, and in the 90s, it fell to under 10 percent. Today, it’s about 6 percent. The field of medicine has advanced to provide us with early detection of heart disease, statins that reduce bad cholesterol, advanced coronary angiography to diagnose potential blockages, and reliable bypass surgery. We know that diet, exercise, and healthy lifestyle choices can also reduce heart disease risks, and new research continues to improve prevention and treatments.In some respects, the fields of medicine and economics have much in common. Both are multidisciplinary fields that strive to improve and maintain the health of complex systems. But unlike medicine, economics hasn’t progressed much in the last 40 years. In late 2008, the United States and many other countries suffered a major economic heart attack that might have been prevented by better diagnostics. Today, more than three years later, societies on every continent appear to be recovering, though many still face the threat of relapse. The reason so much of the world is on edge, with many countries still on life-support, is that governments have simply been prescribing the equivalent of economic bed rest and morphine (low interest rates and some fiscal stimulus) without any significant lifestyle changes.Yet there are better, more sophisticated treatments that should be prescribed—new sets of statistical indicators to help monitor economic health, as well as fresh policies based on new numbers that can help diagnose and treat these ailments to the principal organs of our fiscal well-being. Traditional measures point to an American economy that’s up even when Americans are feeling down. Across Europe and in Japan, there is also a sense of confusion over current economic directions—a universal sense that the numbers that have been our staples are increasingly meaningless to everyday people.Newspapers, radio, and television routinely spout headlines about key statistics on GDP, inflation, and employment—astonishingly influential indicators computed in the United States by the government’s Bureau of Labor Statistics and in capitals around the world. Most seem to have little correlation with the realities on the street. Yet, governments, businesses, and individuals still use these yardsticks in their decision-making worldwide, and minor revisions in the data can have major ramifications. Inflation measurements help determine mortgage and savings rates, stock market prices, interest payments on the national debt, and cost-of-living increases for wages, pensions, and Social Security benefits. Despite dramatic shifts in the world over the last few decades, we are still using the same old gauges, nomenclature, and policies of the past. These outmoded statistics skew perceptions, leaving us with a distorted worldview and a shaky foundation as a base for policy. If we can’t accurately diagnose the problem, we won’t cure it.The world of 2012 is so fundamentally different from 30 to 40 years ago that traditional, commonly held economic views and perspectives seem downright quaint today. Economically, the world of the early 1970s was a patchwork of inward-focused economies, with most goods domestically made and sold, together with small quantities of cross-border trade in finished products between 20 or 30 countries. We forget that back then, much of the world operated under some communist or socialist model. Even in the United States, trade comprised less than 10 percent of the economy. The widespread abandonment of socialist and isolationist policies since the mid-1980s in favor of global trade and investment—plus new information technologies—has ushered in the first truly global era where goods, services, capital, talent, and ideas move across borders faster than ever before. Over the last generation or two, the world has been transformed into a complex system of interdependent and constantly changing relationships. Global production and distribution chains link Brazilian iron mines, Greek ships, Chinese steelmakers, German automakers, Wall Street banks, and car dealers in Peoria. Financial markets instantly entangle California pension funds, insurers in Asia, and Cayman Island hedge funds with banks everywhere.Yet we are still using methods of a simpler past to measure, diagnose, and direct our economy today. The most widely used and closely tracked of such metrics is the Gross Domestic Product, created in the 1930s when congress asked a young University of Pennsylvania economist Simon Kuznets to develop a uniform set of national accounts. The intention was to help government officials get a grasp on Depression-era economic realities. These stats became the prototype of the GDP—the premiere measure of economic well-being the world over. GDP, defined as the total market value of all final goods and services produced in a country in a given year, has permanently changed how we look at public policy. There was some genius in Kuznets’ simple, easy-to-understand statistic. Previously, economists had rarely been consulted on public policy, but equipped with powerful new statistical tools, they have become the policy authorities of the postwar era.Even its creator, however, realized the limitations of GDP. In 1934, Kuznets warned, “the welfare of a nation can scarcely be inferred from measurement of national income.” He wrote again in 1962, “distinctions must be kept in mind between quantity and quality of growth, between its costs and return, and between the short and the long run.” In other words, GDP and its components can and do give us a measure of how much we produce and consume—but reflect none of the qualitative aspects of the economy. GDP cannot answer such essential questions as whether we are consuming too much of the wrong things or saving too little. To any government statistician tallying GDP, $100 spent on textbooks is sadly no more valuable to society than $100 spent on cigarettes. Americans spend more than $80 billion on smoking each year and an estimated $160 billion on the health care costs related to smoking-induced illnesses. Together that’s about 1.5 percent of American GDP—nothing to boast about. Debt also boosts GDP in the short run by stimulating consumption but could curb future growth when both governments and households have to pay it back and spend less. Consider the over $5 trillion in new U.S. government borrowings with interest since 2000.GDP as a statistic may have fallen victim to the phenomenon of Goodhart’s Law. Devised by an adviser to the Bank of England in the 1970s, the law states that as soon as an indicator is relied upon for policy decisions, it stops being effective. For example, the police can reduce the rate of shoplifting by diverting more resources from other crime-fighting activities. Shoplifting rates go down, but other crime rates go up. As a result, shoplifting becomes a useless indicator of overall crime trends. In this respect, when a particular yardstick like GDP is used as a performance indicator of a complex system—like a national economy—the government may choose to target the measure, improving its value but at other costs to the country. As such, GDP may improve, but it becomes less useful as a measure of the broader economy and national well-being.While the limitations of GDP have since been echoed by many prominent economists including Nobel laureates Joseph Stiglitz and Amartya Sen (whose landmark 2010 report included dozens of important socio-economic measures drawn from the developing world), there has been little change in the obsessive overreliance on GDP as the primary economic barometer. And if GDP was an unreliable indicator in the pre-globalized world, it is woefully misleading today. Increasingly, understanding the quality of GDP and its composition, especially the weighting of its four constituent parts—consumption, government spending, investment, and net exports—is most important to our long-term national health. Yet few governments have managed to divorce themselves from the simple GDP figure, regardless of how irrelevant it has become.GDP is not the only statistical fetish in global economics. Employment-related figures, too, are a point of obsessive attention. The unemployment rate is supposed to convey how many people are employed in the workforce, but it says nothing about the quality or security of such jobs. Without further research, the headline number used by policy-makers and lay people alike is rarely qualified. From the unemployment number alone, it is impossible to know whether true progress is being made as a society.Simple unemployment numbers may have been informative in the past, but societies have changed dramatically since 1980. Automation and globalization have eliminated many American factory jobs and are even eliminating others in places like China, which are losing out to lower cost countries like Bangladesh and Vietnam. But the United States. has posted unemployment rates below 5 percent for the majority of the last 15 years. Nobel-winning economist Michael Spence suggests America’s employment “success” was actually the replacement of some 10 million manufacturing and export-related jobs with low-wage, low skilled service jobs like construction workers, interior decorators, or paint department managers—domestic jobs that cannot be outsourced to lower-cost labor markets. As soon as the economy took a hit in 2008, these were the first to go, because they weren’t central to consumer needs.But stepping back from the job quality issue, a far greater failure is our inability to understand the fundamentals that enter into the employment rate—in the United States or abroad. Indeed, the real unemployment rate in the United States is likely far higher than the official figure. This confusion is rooted in an ever-changing definition of the eligible labor pool. In fact, America’s Bureau of Labor Statistics actually computes six different unemployment figures with varying definitions, with most people looking at the lowest headline number. The United States is not alone in these idiosyncrasies. While all OECD countries are supposed to use the International Labor Organization definition for “unemployment,” most create their own versions.On the surface, calculating the unemployment rate should be straightforward—divide the number of unemployed workers by the total labor force. However, defining an “unemployed worker” and the “total labor force” is necessarily an imprecise task. America’s headline unemployment rate is actually based on the number of people who draw unemployment benefits. The British use a similar measure. But once those benefits end, those who are still unemployed, but no longer eligible for benefits, statistically evaporate. They are no longer counted, and neither are the discouraged, frustrated people who stop looking for work.For example, let’s say there are 100 eligible workers, and five can’t find jobs—that’s simply 5 percent unemployment. One year later, the economy hits a rough patch and five more people lose jobs. Now we have 10 percent official unemployment. But let’s assume that of the original five unemployed people, three are no longer eligible for unemployment benefits. The way government statisticians adjust for this is to reduce the total labor force by three to 97. Official stats now calculate a labor force of 97, with seven more unemployed, dropping the “unemployment rate” to 7.2 percent.According to government statistics, if the same number of Americans were job-hunting today as in 2007, the official unemployment rate would be more than 11 percent, not the official rate of 8.3 percent released in early 2012. The labor pool has been reduced by the so-called “discouraged” workers who permanently drop out of the official numbers. Logic tells us more “discouraged workers” are a bad sign for any economy. Yet such a practice actually makes the official unemployment rate look better. In Japan, the historic practice of companies keeping idle employees on the books versus outright firing them is believed to depress unemployment rates substantially. Some economists believe the real rates may be as high 12.2 percent compared to the current “official” rate of 4.6 percent.Even with headline 8.3 percent unemployment (or higher, unofficially), most Americans would be surprised to learn that the United States has labor shortages today. 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