Despite the growing gulf between econometrics – GDP, unemployment statistics, and consumer/producer price indexes, among others – and what they actually intend to measure, these numerical abstractions are increasingly the determinants of our policy decisions, with the very real danger of consequences for everyday life.
Take, for example, a NY Times commentary on the latest monthly unemployment statistics. Experts predicted the creation of about 150,000 jobs in January, which would curb unemployment so that the national average would only rise from 9.4 to 9.5%.
Instead, the economy created just 36,000 jobs in January, an absolutely dreadful number. But the unemployment rate fell like a stone from 9.4 percent to 9.0 percent. The crunchers stared at the numbers in disbelief. They moved them this way and that. No matter how they arranged them, they made no sense. Nothing even close to enough jobs were being created to bring the unemployment rate down, but for two successive months it had dropped sharply. (It dived from 9.8 percent to 9.4 in December.)
These results seem nonsensical, but may, in part, be explained by the Bureau of Labor Statistics’ definition of “unemployed” - those who are currently unemployed, available to work, and have sought employment at least once in the last four weeks. So unemployment may actually be decreasing, but not because those people are finding jobs. They are simply giving up (for the red line indicating “participation” read: actively seeking employment).
Meanwhile, Economic recovery is declared because GDP is growing again, but are Americans actually any better off?
Corporate profits are up likewise, but what about those at the other end of the socioeconomic spectrum – people not part of the financial elite? Are opportunities for bettering their circumstances actually increasing?
Perhaps it’s time for a new economic paradigm… and more holistic metrics.