The Mystery of the Awful Economists

This was originally published at the The Street.com’s Real Moeny on 3/2/2005 3:42 PM

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“We have 2 classes of forecasters: Those who don’t know… and those who don’t know they don’t know.”
— John Kenneth Galbraith

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A savvy speculator could have made a fortune lately betting on the outcome of the nonfarm payroll report. In the past year, taking “the under” of economists’ consensus view has been money 87% of the time.

Given the recent upward revision to fourth-quarter GDP, perhaps Friday’s February employment data will be the economists’ best shot for “the over” in a long while. Regardless of how the dismal scientists do this month — the consensus is for 225,000 — the issue remains that they have been continuously wrong in both quantity and velocity this entire recovery.

Nonfarm Payrolls, Post Recession: 2001-05 vs. Average Recovery

Source: Federal Reserve Bank of Cleveland (Caveat Forecaster, February 2005)

Those of us who work in glass houses — strategists, economists and meteorologists — ought to be careful about throwing stones. But clearly, something is amiss and we should be asking ourselves why this recovery is generating such weak job creation and correspondingly bad forecasts. Has something changed structurally? Are some basic assumptions about the business cycle flawed? Perhaps econometric models are missing or overweighting a key factor. Indeed, something has caused nearly the entire field of economists to be persistently wrong.

I have considered — and disposed of — myriad excuses proffered: The disproved claims of the BLS Payroll Survey undercounting jobs vs. their Household Survey; the uncounted “self-employed, work-at-home-independent contractor;” that the Bureau of Labor Statistics data is somehow bad; the rationale that (somehow) eBay (EBAY:Nasdaq) is the explanation for 7 million missing jobs.

As a person “unburdened” by a classical economics education, I am free to ask the questions most economists can’t. I have my suspects in the mystery of the awful payroll forecasts. Among the most likely factors contributing to forecasting errors, outsourcing and productivity have been pretty thoroughly reviewed by economists; so neither of those issues is likely the cause.

In the past, I discussed the dividend tax cut and post-bubble hangover here, and the unintended consequence of accelerated depreciation here. But that still leaves a long list of unconventional issues that may be at least partly responsible for anemic jobs numbers:

From Bias to Underemployment

Political Bias: Hard though it might be to imagine, some economists have a political bias.

I am not referring to well-known political economists such as Paul Krugman or Larry Kudlow. Both of these gentlemen are well-known partisans. Rather, I am talking about those hacks — on both the left and the right — who month after month put forth partisan predictions contradicted by the weight of the economic evidence. Rather than providing economic guidance to businesses, investors or policymakers, they serve as a balm to political operators looking for intellectual support of a particular agenda.

The analyst scandals of the 1990s focused attention on the biased, conflict of interest-riddled research departments of large brokerage firms. Today, economists have become the new analysts. But instead of whoring themselves out for banking business, some have allowed the hope of a plum appointment to the Fed or White House or think tank to influence their tortured modeling or forecasting. Their analyses have morphed from dismal science to political propaganda.

Not-in-the-labor-force: The 5.2% unemployment rate has been a soothing data point for the bullish economists. Unfortunately, it is also a highly misleading one. A new class of unemployed has been driving the unemployment data and could also be another source of forecasting error.

The math is simple: The employment rate is a percentage of people with full-time jobs divided by the labor force. The unemployment rate is the balance (100% minus employment rate percentage = unemployment rate percentage).

Historically, employment goes up (and unemployment rate goes down) when more people get jobs. But this time around, we see a new phenomenon: The employment rate has increased not because people are finding work, but because they are dropping out of the labor force, and in significant numbers. It’s not that the numerator is going higher (more jobs), it’s the denominator going lower (smaller labor pool) that has been driving the unemployment data.

A low unemployment rate is a good thing when increased hiring is what causes it. Frustrated job seekers dropping out of the labor force is hardly a cause for economic celebration.

Permanent layoffs: In the typical post-war recession, layoffs would spike, driving unemployment higher. But the majority of these layoffs were only temporary in nature. Once the recession ended, and demand ramped back up, most of those laid off would get rehired. The recovery following the recession would see unemployment rapidly fall back due to strong rehiring trends. Unemployment rose quickly in the recessions of 1969 (6%), 1974 (9%), 1980 (8%) and 1982 (11%). It fell rapidly after the recession ended.

Temporary vs. Permanent Layoffs

Source: Federal Reserve Bank of Cleveland (Caveat Forecaster, February 2005)

In the recessions of 1990 (8%) and 2000 (6%), a new phenomenon was observed. The number of temporarily laid off workers dropped to less than 1%. Most of the laid-off workers were never rehired by their old firms.

This reflects a structural change in the economy. Manufacturing is a decreasingly important source of job creation. Perhaps economists are not incorporating the more permanent nature of layoffs into their models. Failing to recognize this long-term trend could be yet another source of predictive error.

Underemployment: There’s another class of workers contributing to the ongoing slack in the labor market: Persons employed part time for economic reasons. This group, defined in the BLS’s table A-12, are those folks who want and are available for full-time work but have had to settle for a part-time schedule.

Source: EPI

March 2001 was the official start of the recession, and November of that year was its official end. Underemployment was actually higher in June 2004 than in November 2001 — 31 months after the recession ended.

The advantages to employers for hiring two part-timer workers vs. one full-time worker are numerous: Limited benefits, no health care expenses, cheaper labor. Part-time jobs is a category of employment that is increasing in size; it may be a possible source for some of the missing full-time jobs.

In Conclusion

My goal here is to stimulate discussion as to why economic forecasters have been unable to provide adequate guidance as to the economy’s ability to create jobs, as well as why that job creation has been so lackluster. I suspect that the same underlying causes may be at work. Indeed, many of the forces we have identified here today are likely to have contributed to both the forecasting error and the slow job creation. The first step in fixing something is acknowledging it is broken. I think the typical job-creating mechanism has been broken. Now it’s time to send the economists back to their drawing boards.