Economic numbers have come to define our world. Individuals, organizations, and governments assess how they are doing based on what these numbers tell them. Economists and analysts loosely refer to statistics measuring GDP, unemployment, inflation, and trade deficits as “leading indicators” and subscribe to the belief that these figures accurately reflect reality and provide unique insights into the health of an economy. Taken together, leading indicators create a data map that people use to navigate their lives. That map, however, is showing signs of age. Understanding where the map came from should help explain why it has become less reliable than ever before.
None of today’s leading indicators existed a century ago. They were invented to measure the economies of the industrial nation-states of the mid-twentieth century. In their time, they did so brilliantly. The twenty-first century, however, is proving more challenging to measure. Industrial nation-states have given way to developed economies rich in services and to emerging industrial economies exporting goods made by multinational companies. The statistics of the twentieth century were not designed for such a reality, and despite the assiduous efforts of statisticians, they cannot keep up.
These shifts have created a temptation to find new formulas, better indicators, and new statistics. And that search, like the quest for new technologies, is certainly worthwhile. But the belief that a few simple numbers or basic averages can capture today’s multifaceted national and global economic systems is a myth that should be abandoned. Rather than seeking new simple numbers to replace old simple numbers, economists need to tap into the power of the information age to figure out which questions need to be answered and to embrace new ways of answering them.
The king of contemporary economic indicators is, of course, gross domestic product (GDP). Given
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