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The Mystery of the Awful Economists By Barry Ritholtz 2005 March 7 John Mauldin's "Outside The Box" 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 economics. This is an intriguing "whodunit" to me. Non Farm Payrolls, Post Recession: 2001-05 versus Average Recovery: Chart 1 Source:Federal Reserve Bank of Cleveland (Caveat Forecaster, February 2005) 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 wrong? 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 errors: 1. Globalization & Outsourcing 2. Productivity Gains 3. Post-Bubble Excess Capacity 4. ADCS (ERP) 5. Dividend Tax Cuts 6. Political Bias 7. NILFs 8. Permanent versus Temporary Layoffs 9. Underemployment 10. 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 the cause. But that still leaves a long list of unconventional issues that may be at least partly responsible for anemic jobs numbers. Let's delve into the details of these topics more closely: 3. Post-Bubble Environment: The 1990s bubble saw a massive amount of over-investment, with capital as plentiful and cheap as it was. This created excess capacity across many industries, but most especially in the fast growing technology and telecom sectors. Part of the hangover caused by the bubble's bursting has been that demand has not yet ramped up to the point where it can absorb all this excess. (You can see exactly how far below trend the economy is regarding industrial production and capacity utilization at the Federal Reserve's Web site). Five years after the bubble burst, some people think its ill effects are behind us. I suspect we will continue to pay for the excesses of the 90's for some time to come. Regardless of your economic persuasion - be it Supply-sider or Keynesian - excess capacity in a post-bubble environment makes it especially difficult for the economy to absorb any slack in the labor market. 4. Unintended Consequences of Accelerated Depreciation of Capital Spending (ADCS): There's no such thing as a free lunch. While the (now sunsetted) accelerated depreciation schedule undoubtedly generated a boon in capital spending, the unanswered question is "At what cost?" It has long been a staple of economic theory that capital spending makes companies more competitive, boosts profits, adds to the gross domestic product, and puts people to work. This held true throughout most of the 20th century. When companies purchased oil rigs, drill presses, or large trucks, someone had to manufacture those goods. So companies added workers to meet the rising demand for capital equipment, and once a device was manufactured, someone else was hired to work it, operate it, or drive it. But in an economy so heavily reliant on intellectual property, that's far less true. iPods and PCs maybe designed here, but they are manufactured overseas. Large physical items, such as aircraft are globally sourced and create far fewer jobs locally than they did in the past. Enterprise Resource Applications, one of the big beneficiaries of ADCS, requires almost no new employees to install or operate, especially when compared to drilling rigs or trucking equipment. And, once the install is complete, it enables a company to operate with fewer employees. As far as employment was concerned, the impact of ACDS was at best muted, and at worst counter-productive. Without a similar, off-setting tax credit for new employment, this legislation inadvertently tipped the scales against job creation. That's the law of unintended consequences: ADCS led to large capital purchases, but at the expense of hiring. It's management's job to deploy their shareholders monies effectively, and the huge write down of ADCS made spending - rather than hiring - the more cost efficient use of corporate capital. Without a corresponding tax credit for creating jobs, this legislation inadvertently had reduced job creation. 5. Dividend tax cut: The second major corporate tax change that may have impacted job creation is the dividend tax cut. By creating a new ultra-low rate for dividend income, new tax policy encouraged firms to raise their dividend payouts. But not without a cost: This new tax rule has created an incentive for corporations to transfer working capital out of the firm. That reduced the pool of capital that otherwise would be used to build new plants, make more capital improvements, and yes, hire new workers. Consider that senior management often consists of members of the 50%+ club - that's what they cumulatively pay in Federal, State and City income tax. Compare that with a mere 15% on dividends. Is it any surprise that insiders and managers - large shareholders themselves - have been raising dividend payouts? They get a nice chunk of cash, and at a very advantageous tax rate. As we learned in the 1990's, management rarely finds it difficult to make those decisions where they stand to benefit personally. Even worse, this tax cut had a de minimus impact on the overall economy. While putting money into the hands of shareholders is generally stimulative, this tax cut may have been less so. Calculations show that more than half of all dividend-paying stocks are held in tax-exempt accounts - pension funds, endowments, charitable trusts and retirement accounts. Increased dividends may sit in tax-advantaged accounts - in some cases for decades - where they have little impact on the broader economy. While the dividends are likely to be recycled in the same asset class, the cash is neither spent nor reinvested in the broader economy. Instead of stimulating the economy via a "multiplier effect," these monies essentially lay fallow. They may have had a positive impact on Wall Street, but their effects were little felt on Main Street. 6. 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 (dare I say it?) partisans. They wear their political hearts on their sleeves, with no guile or misrepresentation. Indeed, their politics inform their economics. 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. Their witless spewings are not designed to provide economic guidance to businesses, investors or policy planners. Rather, their jingoistic jeering or cheering is less an econometric exercise, and more a political maneuver. They serve as a balm to political operators looking for a positive or negative backdrop to their electoral campaigns. The analyst scandals of the 1990s focused attention on the biased, conflict of interest riddled research departments of large brokerage firms. Some analysts infamously compromised their integrity to troll for investment banking business and its accompanying riches. Today, Economists have become the new analysts. Instead of whoring themselves out for banking business, some have allowed the hope of a plum political appointment to the Fed or White House to influence their tortured modeling or forecasting. Their analyses have morphed from dismal science to political propaganda. The difference between analysts and economists, however, is stark: Unlike stock analysts, so few actual investor dollars are deployed based on their economic declarations that Eliot Spitzer has no interest in investigating the group. (In a way, its kinda sad: their bias and conflict of interest actually matters very little to society at large . . . ) 7. NILFs: 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: Not-in-the-labor-force (NILFs). It could also be another causative source of error. The math is simple: The employment rate is a percentage of people with fulltime jobs divided by the labor force. The unemployment rate is the balance (100% minus employment rate% = unemployment rate%). 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. Its 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. That creates the appearance of a robust, job-creating economy. The reality is far subtler and more complex. 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. And, it could be another reason for the economist's predictive error rate. 8. Permanent (rather than temporary) 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 re-hiring 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 versus Permanent Layoffs Chart 2 Chart 3 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 numbers of temporarily laid off workers dropped to under 1 percent. 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 longterm trend could be yet another source of predictive error. 9. 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. Chart 4 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 - 31 months after the recession ended - than at the recession's end. The advantages to employers for hiring two part-timers versus one full-time are numerous: Limited benefits, no health care expenses, cheaper labor. Part-time jobs is a category of employment which is increasing in size; it may be a possible source for some of the missing full-time jobs. 10. Shell Shocked Executives: One of the simpler explanations for the lack of job creation is this: CEOs have become "shell shocked" by the three-year bear market. Their options are finally above water after a long, long dry spell. This has created a corporate timidity towards risk-taking, along with an excess focus on making the quarter's numbers, lest those options lose go below strike price again. At the end of most recessions, bold corporate leadership gambles on a recovery, and races to hire the highest quality employees (if sometimes too soon). They feel compelled to beat their competitors. Not so today, where we see CEOs extremely cautious about hiring. The aberrational behavior of execs might be throwing off the economists. Management is simply not doing what they typically do in an economic recovery. Their apprehensiveness could very well result in a self-fulfilling prophecy. Conclusion Don't feel too bad for the economists; given the recent upward revision to 4th Quarter GDP, perhaps the February Employment data - which comes out Friday - will be their best shot for "the over" in a long while. Regardless of how they do on this month, however, the issue remains that they have been continuously wrong in both quantity and velocity this entire recovery. My goal is not, however, to assign blame Rather, I hope 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 of Wall Street and the slow job creation. I am reminded of a quote from John Kenneth Galbraith, who long ago observed "We have 2 classes of forecasters: Those who don't know . . . and those who don't know they don't know." The sooner the latter become the former, the more likely we are to start seeing better forecasts. That's the first step in fixing something: acknowledge it is broken. I think the typical job creating mechanism has been broken; this column is my contribution to discerning why that actually is. Now its time to send the economists back to their drawing boards . . _______________________________________________ http://www.mccmedia.com/mailman/listinfo/brin-l