Monday, September 17, 2012

Labor stats needn’t be such hard work





Anna Bernasek
It should have been good news that the US jobless rate fell last month from 8.3 per cent to 8.1 per cent. Surprisingly, that message landed with a thud.

Since peaking at 10 per cent less than three years ago, unemployment has fallen by almost 2 full percentage points. Yet instead of good cheer, Americans seem more pessimistic.

It didn’t help that the main news story from August’s job numbers was that the drop in joblessness was due to a sharp decline in the workforce. The labour force participation rate – percentage of the adult population employed or actively seeking work – dropped to 63.5 per cent, its lowest level in more than three decades.

Commentators automatically assumed it was due to discouraged workers leaving en masse. Perhaps that’s correct. But official figures don’t break it down in a meaningful way. The drop could be due to any number of reasons; there’s no official way to be sure.

Most accounts of the job figures focused on the bad news – a paltry 96,000 new jobs created last month – and more or less ignored the lower jobless rate. That says a lot about the official “headline” unemployment number: it’s not particularly useful.

The jobless figure comes from a government survey of households. The method dates from 1940. The survey has been updated over the years but relies on a crude binary paradigm. Those who answer the survey are either employed or not; there’s no in-between.

The Bureau of Labour Statistics, which compiles the report, says the basic concepts “are quite simple”. People with jobs are employed. People who are not working for pay and who are looking for a job and available to work are unemployed.

The BLS says being employed means getting paid for anything or earning profit on work done. It also includes pitching in on a family farm or helping out at a family restaurant even if you don’t get paid. People who are not employed and either not looking for work or not available to work are not in the workforce.

Simple, maybe. But way out of date. Those concepts arose in a world long gone where men worked at a job for life, women kept house and kids went to school. Looking back at the 1940 cohort, nearly anyone looking for work in the US that year would find it before long.

The labour market has only become more complex. These days there’s a whole spectrum of work from traditional full-time work, various part-time occupations, moonlighting, freelancing, volunteering, and entrepreneurial roles. A person in a job may not be earning to her potential, and a person out of a job may be very productive.

If the official job numbers tend to include everyone who gets a pay cheque, they’re not an effective measure for what we want to use them for: a guide to national economic wellbeing. The BLS does publish an alternative measure. But they are just additions to the base unemployment number and, therefore, not fundamentally different.

Of most concern is that we’ve come to rely on an official statistic that doesn’t tell us very much. We still have little idea how much unused labour capacity is being wasted and how financial hardship arising from that unused capacity is distributed among the population.

It’s not just the jobless figure though. For instance, the poverty line that we use to set critical policy has been long criticised by economists as needing a complete overhaul to keep up with changes since it was introduced in 1963. The measure assumes an average family spends one third of income on food, yet today that’s more like 12 per cent.

While economists remain stuck in the typewriter age, the rest of mankind is in the middle of the biggest revolution in data and information in history. The cost of acquiring and analysing data has fallen so far, so fast, that it has become possible to measure the economy on a granular level. Many government agencies would like to modernise the major economic measures but often the talent and funding just aren’t there.

Meanwhile, outside government, thousands of economists pore over the same dubious numbers month after month. Private sector economists could devote more time and energy to making innovative measurements of the economy.

A few enterprising economists have done just that. Bob Shiller, Karl Case and Allan Weiss devised a national housing price index. Introduced just in time to capture the housing bubble, the Case-Shiller index provided invaluable help in understanding the extent and impact of the housing crash.

Today’s digital economy needs and deserves better economic data. Developing better ways to measure economic performance may be the single biggest opportunity in economics today.

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