“We have 2 classes of forecasters: Those who don’t know… and those who don’t know they don’t know.” — John Kenneth Galbraith
I’ve been making a fortune lately. (No, I don’t own any Google IPO shares). Each month, I’ve been
betting on the outcome of the Non-Farm Payroll report against my economist
colleagues. I’ve been taking “the under,” and, over the past
year, it’s been money 87% of the time. I expect this wager on a monthly
jobs shortfall to remain successful for the foreseeable future.
Less lucrative, but much more fascinating than my book-making activity is the perplexing question “Why?” Why have the dismal scientists been unable to accurately discern what the
employment situation is? It has certainly been perilous predicting job growth
this business cycle; aside from a tendency towards over-optimism, what explains
the consistent forecasting errors? Job growth predictions have been wronger,
longer, and by a greater amount, than at any other time in the modern era of
This is an intriguing “whodunit”
Nonfarm Payrolls, Post Recession: 2001-05 vs. Average Recovery
As Yogi Berra so wisely
observed, “It’s tough to make
predictions, especially about the future.” Those of us who work in glass
houses – strategists, economists and weatherman – ought to be careful about
throwing stones. But my crowd (Market Strategists) are typically wrong about the future. This cycle, Economists have
been unusually bad at predicting what happened just last month. The monthly consensus on Non-Farm Payrolls plays out
like an old joke: “There are 3 types
of economists: Those who can count, and
those who can’t.”
Clearly, something is amiss.
But rather than merely poking
fun, 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 over-weighting a key factor. Indeed,
what is it that nearly the entire field of economics has been somehow getting
I’ve been pondering this
question for some time now. I have considered – and disposed of – the myriad
excuses proffered: The disproved claims of the BLS Payroll Survey undercounting
jobs versus 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 is the explanation for 7 million missing jobs..
As a person unburdened by a
Classical Economics education – I’m not an economist, but I sometimes play one
on TV – I am free to ask the questions most economists can’t. I have my
suspects in the mystery of the awful
economist. These are the most likely factors contributing to forecasting
Globalization & Outsourcing
Post-Bubble Excess Capacity
ADCS (ERP) (Accelerated Depreciation)
Dividend Tax Cuts
Permanent versus Temporary Layoffs
Shell Shocked Executives
The first two points – Outsourcing issues and Productivity improvements – have been
pretty thoroughly reviewed by economists – so neither of those issues is likely
But that still leaves a long list of unconventional
issues that may be at least partly responsible for anemic jobs numbers . . .
UPDATE: March 5, 2005 7:25am
You can download the full report here.
Please use the comments to demonstrate your own ignorance, unfamiliarity with empirical data and lack of respect for scientific knowledge. Be sure to create straw men and argue against things I have neither said nor implied. If you could repeat previously discredited memes or steer the conversation into irrelevant, off topic discussions, it would be appreciated. Lastly, kindly forgo all civility in your discourse . . . you are, after all, anonymous.