Posts Tagged ‘Economic Variables’
Monday, April 9th, 2012
On Friday, the Department of Labor reported that March non-farm payrolls increased by 120,000, falling well short of consensus expectations in excess of 200,000. For our part, we continue to expect a deterioration in observable economic variables, with weakness that emerges gradually and then accelerates toward mid-year. On the payroll front, our present expectation is that April job creation will deteriorate toward zero or negative levels.
Immediately after the payroll number was released, CNBC shot out a news story titled “Disappointing Jobs Report Revives Talk of Fed Easing.” Of course it does, because this remains a market dependent on sugar. And with little doubt the Fed will eventually deliver it – perhaps following a market plunge of 25% or more – but with little doubt nonetheless, because like the indulgent parent of a spoiled toddler, the FOMC can’t stand to see Wall Street throw a tantrum without reaching for a lollipop.
If the Fed indeed steps in with an additional round of QE, a few distinctions may be helpful. First, regardless of Fed actions, and even in the past few years, the market has invariably suffered significant losses following the emergence of the “overvalued, overbought, overbullish, rising-yields” syndrome that we presently observe. In contrast, the main window where it has not paid to “fight the Fed,” so to speak, has been the period coming off of oversold lows. That’s primarily the window where financials, cyclicals, materials, and garbage stocks with highly leveraged balance sheets have outperformed. Regardless of the fact that QE has had no durable economic benefits (more on that below), and does little but to repeatedly lay fresh wallpaper over the rotting edifice that is the global banking system, the main effect of QE has been to provide temporary support for the most speculative corners of the financial market after they have been pummeled.
Strategically, then, we concede that there is some latitude to ease back on defensiveness between the point where QE induces an early improvement in market internals and an upturn in various trend-following indicators (coming off of a previously oversold condition), and the point where an “overvalued, overbought, overbullish, rising-yields” syndrome is established. But once that syndrome is established, it is unwise to ignore it, and a defensive stance becomes essential (as we saw separately in 2010 and 2011, not to mention at most major market tops over history). Meanwhile, it is unwise to believe that additional rounds of QE will do much to help the economy in any event, as its primary effect is merely to drive investors into speculative investments by starving them of safer yields.
There is a very well-defined theoretical and empirical relationship between the monetary base and targets like short-term interest rates and monetary velocity (see Sixteen Cents: Pushing the Unstable Limits of Monetary Policy), but investors should note that the response of the stock market and other financial assets to quantitative easing is far more based on superstition than on structure. We can observe, for example, that drowning the financial markets in zero-interest assets has tended to lower the yields (and therefore raise the prices) of higher-risk, longer-duration assets, but that response is dependent on a certain form of myopia. Specifically, investors either have to assume that they can safely speculate until some particular date arrives on the calendar and they can all take their profits simultaneously, or they have to ignore the tendency for low prospective long-term returns to go hand in hand with quite negative prospective intermediate-term returns. For that reason, any “QE indicator” we might develop (as several people have requested) would likely be spurious and not very robust going forward, even though one might be back-fitted to the data. A better approach, as noted above, is to take a signal from market action and trend-following measures, but emphatically to also impose several alternate exit criteria – including for example a deterioration of those measures, or the establishment of an overvalued, overbought, overbullish, rising-yields syndrome. I remain convinced that investors who simply have blind faith that QE is reliably bullish in and of itself, or can be trusted to limit losses, will have their heads handed to them.
How QE “works”
Keep in mind that the U.S. banking system has trillions of dollars sitting in idle deposits with the Fed already. Quantitative easing simply does not relieve any constraint that is binding on the economy. Rather, QE is a method by which the Fed hoards longer-duration, higher-yielding securities like U.S. Treasury bonds and replaces them with cash that bears zero interest. At every moment in time, somebody has to hold that paper. The only way for the holder to seek a higher return is to trade it for a more speculative asset, in which case whoever sells the speculative asset then has to hold the cash. The process stops when all speculative assets are finally priced so richly and precariously that the people holding the cash have no further incentive to chase the speculative assets, and are simply willing to hold idle, zero-interest cash balances.
Why does the Fed want this? Simple. Chairman Bernanke believes that by creating a bubble in speculative assets, people will “feel” wealthier and keep consuming – regardless of the fact that real incomes are stagnant and debt burdens are already intolerable, and despite the fact that there is extremely weak evidence for any such “wealth effect” in the historical record. Undoubtedly, it would be difficult for Bernanke to refrain from these reckless policies when everyone is crying “do something!” But the willingness to tolerate short-term criticism in the interest of long-term benefit is part of what separates leadership from cowardice.
Given the bubbling concerns among various FOMC members about inflation risk, the next round of QE is likely to be “sterilized.” Essentially, the Fed would buy Treasury bonds from banks, and would pay for them with newly created cash, but the Fed would then borrow those funds back from banks, holding them as idle deposits with the Federal Reserve. By definition, the additional “liquidity” created by a sterilized round of QE would not be available for new lending (as if there aren’t enough idle reserves in the banking system already). So again, the main goal is to increase the outstanding stock of zero- and low-interest assets in the economy, in order to lower the yields and increase the prices of more speculative investments.
Now, if you think carefully about this, you’ll recognize that the U.S. government is still running a deficit of more than 8% of GDP, so the Treasury will have to issue more than a trillion dollars of new debt in the coming year anyway. Given that banks already hold trillions of dollars in idle balances, the Treasury could have the identical effect of an additional round of QE simply by issuing a larger portion of the new debt as very short-term T-bills, which also yield next to nothing. So why bother doing this as “quantitative easing” when the Treasury could just change the maturity profile of the new debt all by itself?
Well, for one, the Treasury securities are issued on the open market. The Fed typically pre-announces which issues it will buy, allowing the banks that act as primary dealers to essentially front-run: buying the newly issued debt from the Treasury in expectation of getting a higher price from the Fed. So doing all of this as QE has the benefit of handing the banks a nice trading profit. Second, the Fed has an awful lot of Treasury debt on its balance sheet, which is leveraged about 50-to-1 against its own capital. By purchasing Treasury securities and creating zero-interest cash (or low-interest reserves), the Fed essentially earns a spread that can cover any shortfall it might experience if it is ever forced to unwind its position and sell any of those securities at a loss. It’s true that if the Fed earns any surplus interest, it has to go back to the Treasury, but the surplus rendered back to the Treasury is only what remains after a night on the town in the Fed’s balance sheet.
Finally, the reason for doing QE through the Fed (rather than simply changing the maturity profile of the new Treasury debt) is that Wall Street – at least – believes that the Emperor is actually wearing clothes. Despite the fact that the main effect of QE is to boost speculation and release brief bursts of pent-up demand, both which immediately soften when the policies are suspended, this recurring pattern is still unclear to many investors and analysts. As long as that delusion persists, we can expect the Fed to periodically exploit it.
Ignore that the side-effect of this delusion is the misallocation of capital toward speculative assets in the belief that the Fed has set a “put option” under the markets. Forget that savings are discouraged, bad lending decisions are rescued, incentives and economic signals are distorted, and the accumulation of productive capital is disabled. We have the most creative, entrepreneurial nation on the planet, but our policy makers are intent on preventing debt restructuring and misallocating scarce capital. As a result, they continue to compromise long-term growth in favor of temporary bouts of short-term speculation.
What about recent employment gains?
But wait. How can we say that quantitative easing has such weak effects on the economy when we’ve clearly enjoyed a significant amount of job creation since mid-2009? Isn’t that clear evidence that Fed policy is working?
Well, that depends on what one means by “working.”
Last week, we observed “Real income declined month-over-month in the latest report, which is very much at odds with the job creation figures unless that job creation reflects extraordinarily low-paying jobs. Real disposable income growth has now dropped to just 0.3% year-over-year, which is lower than the rate that is typically observed even in recessions.” It wasn’t quite clear what was going on until I read a comment by David Rosenberg, who noted that much of the recent growth in payrolls has been in “55 years and over” cohort. Suddenly, 2 and 2 became 4.
If you dig into the payroll data, the picture that emerges is breathtaking. Since the recession “ended” in June 2009, total non-farm payrolls in the U.S. have grown by 1.84 million jobs. However, if we look at workers 55 years of age and over, we find that employment in that group has increased by 2.96 million jobs. In contrast, employment among workers under age 55 has actually contracted by 1.12 million jobs. Even over the past year, the vast majority of job creation has been in the 55-and-over group, while employment has been sluggish for all other workers, and has already turned down.
For most of history prior to the late-1990′s, employment growth in the 55-and-over cohort was a fairly small and stable segment of total employment growth. Undoubtedly, part of the recent increase has simply been a change in the classification of existing workers as they’ve aged (1945 + 55 = 2000, so the we would have expected to see some gradual bulge in this bracket since 2000 due to aging baby boomers). But the shift is too large to be explained simply by reclassification. Something more troubling has been underway.
Beginning first with Alan Greenspan, and then with Ben Bernanke, the Fed has increasingly pursued policies of suppressing interest rates, even driving real interest rates to negative levels after inflation. Combine this with the bursting of two Fed-enabled (if not Fed-induced) bubbles – one in stocks and one in housing, and the over-55 cohort has suffered an assault on its financial security: a difficult trifecta that includes the loss of interest income, the loss of portfolio value, and the loss of home equity. All of these have combined to provoke a delay in retirement plans and a need for these individuals to re-enter the labor force.
In short, what we’ve observed in the employment figures is not recovery, but desperation. Having starved savers of interest income, and having repeatedly subjected investors to Fed-induced financial bubbles that create volatility without durable returns, the Fed has successfully provoked job growth of the obligatory, low-wage variety. Over the past year, the majority of this growth has been in the 55-and-over cohort, while growth has turned down among other workers. Meanwhile, overall labor force participation continues to fall as discouraged workers leave the labor force entirely, which is the primary reason the unemployment rate has declined. All of this reflects not health, but despair, and explains why real disposable income has grown by only 0.3% over the past year.
It’s important to recognize that our concerns about the stock market here are independent of our economic concerns, in that the “Angry Army of Aunt Minnies” we’ve recently observed are associated with very negative average market outcomes regardless of economic conditions. Even in the past few years, the emergence of these conditions has invariably been followed by declines that have wiped out all of the intervening gains since the earliest signal was observed.
As noted above, even in the event of another round of quantitative easing, the particular window to ease back on a defensive position would be between the point where QE induces an improvement in market internals and an upturn in various trend-following indicators (coming off of a previously oversold condition), and the point where an “overvalued, overbought, overbullish, rising-yields” syndrome is established. To ignore the syndromes we observe at present, in the hope that the hope of QE will be sufficient to limit market risk, is a strategy that would not have been successful even in recent years.
Still, though our present market concerns are independent of economic concerns, they are also reinforced by those economic concerns. We’ve reviewed various lines of evidence, from leading indicators to “unobserved components models,” and I continue to view the coming weeks as a likely minefield of economic disappointments. The issue here remains the distinction between leading, coincident and lagging measures of the economy. As I’ve noted before, a tendency toward positive economic surprises over this period would improve the underlying economic state that we infer from observable data, but here and now, the most leading components remain clearly negative. The concerns are also clearly compounded by the uniform deterioration in economic measures in Europe, China and India, among other regions. The charts below convey the general situation.
Over the weekend, the New York Times published a good article (Some Dreary Forecasts from Recovery Skeptics) that summarized the concerns of a number of economic observers, placing Lakshman Achuthan of the ECRI and me into the classification of “perma-bears.” Actually, with respect to the economy, I’m pleased to be in good company, and don’t greatly object to the “perma-bear” label in that I continue to believe major underlying economic problems have merely been kicked down the road and remain unresolved (primarily an overhang of unserviceable debt, which continues to need restructuring, and which will leave the global economy prone to recurring crises until that happens).
I also periodically get the “perma-bear” label with respect to my views on the financial markets. While I do believe that stocks have been generally overvalued since the late-1990′s (a view that is supported by the predictably dismal overall total returns on stocks since that time), I do think that some observers misclassify the 2009-early 2010 period as being a reflection of our standard investment strategy instead of what it was – a period when we suspended risk taking until we were confident that we had adequately stress-tested our methods against Depression-era data. That may seem like a distinction without a difference, but the difference is that for most periods since 2000, our present investment methods would do very little differently than we actually did in practice (though there are of course a few moderate differences due to various refinements and ongoing research). The 2009-early 2010 period is distinct in that it is not at all indicative of the hedge position that can be expected of our strategy in future market cycles, even under identical conditions and evidence. The fact that we removed about 70% of our hedges in 2002 (when our projection for 10-year S&P 500 total returns was not much more compelling than what it is today), should be some evidence of that.
Financial markets fluctuate, and prospective returns change. We will undoubtedly have ample opportunities to accept financial risk in expectation of reasonable returns, and if history is any guide, those opportunities will emerge well before our economic problems are behind us. What concerns me here is the refusal of investors to even recognize those problems; the army of hostile syndromes we observe in both financial and economic data; the blind faith that simply changing the mix of Treasury debt and bank reserves can produce growth and put a floor under speculative assets; the near-complete denial of ongoing debt strains; and heavily bullish sentiment that Investors Intelligence correctly notes is now in “territory associated with market tops.”
As of last week, the Market Climate for stocks remained characterized by a hostile “overvalued, overbought, overbullish, rising-yields” syndrome, and a variety of other hostile syndromes that I’ve reviewed in recent comments. Strategic Growth and Strategic International Fund remain tightly hedged here. Strategic Dividend Value has a hedge equal to about 50% of the value of its holdings – its most hedged stance. Strategic Total Return continues to have a duration of just under 3 years, and a small percent of assets in utility shares and foreign currencies. We raised our exposure in precious metals shares to just over 4% on last week’s price weakness, but there too, our stance remains decidedly conservative at present.
Tags: Balance Sheets, Banking System, Cnbc, Consensus Expectations, Cyclicals, Department Of Labor, Desperation, Economic Benefits, Economic Variables, Edifice, Fomc, Global Banking, Hussman, Job Creation, Lollipop, Lows, Market Plunge, Non Farm Payrolls, Payroll Number, Qe, Tantrum
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Thursday, June 23rd, 2011
by Lutz Kilian
23 June 2011
Reduced Libyan output, broader political unrest in the Middle East, and a slow global recovery have raised the uncertainty surrounding oil prices. This column discusses the challenges and value of forecasting future oil prices in real time, as opposed to fitting models to revised oil prices released months after economic decisions are made.
The real (inflation-adjusted) price of crude oil is a key variable in the macroeconomic projections generated by central banks, private sector forecasters, and international organisations (IMF 2005, 2007). The recent cutback in Libyan oil production, widespread political unrest in the Middle East, and ongoing concerns about the state of the global recovery from the financial crisis have sharpened awareness of the uncertainty about the future path of the real price of crude oil. It seems surprising that, to date, no studies have systematically investigated how best to forecast the real price of oil in real time.
One reason is perhaps that there has been no readily available real-time database for the relevant economic variables. Although it is common to assess the out-of-sample accuracy of competing forecasting models based on ex-post revised data, such comparisons can be misleading. Ex-post revised data are not available to forecasters at the time their forecasts are generated. Instead, real-life forecasters have to work with the latest vintage of data known at the time. The use of successive vintages of real-time data in forecasting raises two distinct complications.
- First, even preliminary data often become available only with a lag. For example, it may take months for the first estimate of this month’s global oil production to be released.
- Second, the initial data releases are continuously revised. It takes successive data revisions until we know, to the best of our ability, the true level of oil production in the current month. Little is known about the nature of these revisions in oil market data or about how data revisions and delays in data availability affect the out-of-sample accuracy of oil price forecasts.
In recent research with Christiane Baumeister (Baumeister and Kilian 2011), we aim to address this problem. We construct a comprehensive monthly real-time data set consisting of vintages for January 1991 through December 2010, each covering data extending back to January 1973. Backcasting and nowcasting methods are used to fill gaps in the real-time data sets. This database allows the construction of real-time forecasts of the real price of oil from a variety of models.
Perhaps surprisingly, it can be shown that suitably constructed model-based real-time forecasts of the real price of oil are more accurate than the no-change forecast at horizons up to one year. This result holds both for the US refiners’ acquisition cost for crude oil imports, which may be viewed as a proxy for the price of oil in global markets, and for the West Texas Intermediate price that receives most attention in the media. (The price of Brent crude oil is not available for a long enough time span to allow a similar analysis). These results are based on a forecast evaluation window covering January 1992 through June 2010. This window includes recent periods of turmoil in oil markets and provides a challenging test of the forecasting ability of alternative forecasting models. The evaluation criteria are the recursive mean-squared prediction error of the forecasts and their directional accuracy.
In particular, it can be shown that recursive forecasts from vector autoregressive models motivated by the economic analysis of global oil markets in our research tend to have lower mean-squared prediction errors at short horizons than forecasts based on oil futures prices, forecasts based on autoregressive and autoregressive-moving average models, and the no-change forecast (see also Kilian and Murphy 2010). These models include data on global oil production, global real activity, the real price of oil and the change in global crude oil inventories. Real-time recursive mean-squared prediction error reductions may be as high as 25% one month ahead and 24% three months ahead. This result is in striking contrast to related results in the literature on forecasting real exchange rates or real stock returns, where it has proved very difficult to improve on the no-change forecast benchmark. The same models also have consistently and often significantly higher directional accuracy with success ratios as high as 65% in real time in some cases. Such success ratios are high by the standards of the empirical finance literature. In contrast, more conventional forecasting methods based on oil futures prices do not produce significant mean-squared prediction error reductions and have lower directional accuracy than suitably chosen vector autoregressive models. Likewise, vector autoregressive models have advantages over models based on non-oil industrial commodity prices alone.
Figure 1 illustrates the implementation of real-time forecasts in practice. The upper panel of Figure 1 shows the real-time forecast of the real US refiners’ acquisition cost of crude oil imports as of December 2010, well before the outbreak of the Libyan crisis in mid-February 2011. The nowcast of the real price of oil for 2010.12 is $97. The real-time model forecast indicates an initial increase in the real price of oil to $105 after one quarter, followed by a decline to between $75 and $83 in the second year. By contrast, the real-time forecast based on oil futures prices indicates a gradual decline from $97 to $90 after two years, while the no-change forecast suggests a constant price of $97. Based on our evidence, the vector autoregressive real-time forecast is the most reliable forecast overall in terms of mean-squared prediction errors and directional accuracy among these three forecasts, at least in the short run.
Figure 1. Baseline real-time forecast of real refiners’ acquisition cost as of 2010.12 and risk analysis
Notes: The alternative forecasting scenarios in panel (b) are discussed in detail in the discussion paper. The vertical line indicates the last nowcast and corresponds to December 2010. Source: Baumeister and Kilian (2011).
An important limitation of standard reduced-form forecasting models from a policy point of view is that they provide no insight into what is driving the forecast and do not allow the policymaker to explore alternative hypothetical forecast scenarios. Policymakers not only expect oil price forecasts to be interpretable in light of an economic model, but they also want to be in a position to evaluate the risks associated with the baseline forecast based on an analysis of how this forecast changes with changes in the economic environment. This task requires additional econometric tools.
A natural approach is to build on the vector autoregressive forecasting approach. It can be shown that – with the additional identifying assumptions proposed in Kilian and Murphy (2010) – the structural moving average representation of the forecasting model may be used not only to forecast the real price of oil out-of-sample, but also to construct real-time conditional projections of how the oil price forecast would deviate from the unconditional forecast benchmark under hypothetical scenarios about future oil demand and oil supply conditions. Using this new econometric tool, it can be demonstrated, for example, that an unexpected full recovery of the world economy would raise the real price of oil by an additional 50% after a year and a half. On the other hand, a surge in speculative demand driven by civil unrest in the Middle East would increase the real price of oil by 20% after about one year, if the shift in speculative demand is comparable to that during the Iranian crisis of 1979.
The lower panel of Figure 1 shows the baseline forecast as of December 2010 implied by the Kilian-Murphy (2010) model as well as a wide range of alternative forecasting scenarios. It illustrates that the real price of oil may rise as high as $148 after one quarter or fall as low as $100, depending on the scenario. After one year, the range is between $76 and $131; at the two-year horizon between $66 and $115. For example, a complete shutdown of Libyan oil production in January 2011 (all else equal) would have been expected to drive the real price of oil as high as $115 in early 2011. These results, while necessarily tentative, illustrate how structural models of oil markets may be used to assess risks in oil price forecasts and to investigate the sensitivity of reduced-form forecasts to specific economic events.
Conditional projections, of course, are only as good as the underlying structural models. Figure 1 highlights the importance of refining these models and of improving structural forecasting methods. Clearly, forecast scenarios could alternatively be constructed from dynamic stochastic general equilibrium models, provided that these models incorporate suitable structural oil-market models. One reason for focusing on the model in Kilian and Murphy (2010) instead is that currently available dynamic stochastic general equilibrium models are still too simplistic when it comes to modelling the global oil market to be useful for policy analysis. In particular, modelling the global demand for industrial commodities (as opposed to measures of value added or productivity) has proved challenging. As these models become more sophisticated, we would expect this situation to change, however. Whether the additional model structure required in specifying a dynamic stochastic general equilibrium model compared with a structural vector autoregressive model on balance will help improve out-of-sample forecast accuracy remains an open question.
International Monetary Fund (2005), World Economic Outlook.
International Monetary Fund (2007), World Economic Outlook.
Kilian, L and DP Murphy (2010), “The Role of Inventories and Speculative Trading in the Global Market for Crude Oil”.
Tags: Central Banks, Commodities, Crude Oil, Cutback, Economic Decisions, Economic Variables, Forecasters, Future Path, Global Oil Production, Global Recovery, Initial Data, International Organisations, Lutz Kilian, Macroeconomic Projections, Oil Prices, Political Unrest, Price Of Crude Oil, Price Of Oil, Real Time Data, Time Database, True Level, Vintages
Posted in Commodities, Markets, Oil and Gas | Comments Off
Wednesday, January 5th, 2011
In Defense of the “Old Always”
by James Montier, GMO
The concept of the “new normal” abounds in markets these days. It seems I can’t open the Financial Times without at least one headline proclaiming the importance of the new normal. But what does it mean for the way we invest?
Part of the difficulty in answering that question is the plethora of meanings that have become associated with the term “new normal.” For some, it is an environment of subdued growth in the developed markets (the result of ongoing deleveraging – similar in essence to the “seven lean years” that Jeremy Grantham, among others, has previously described). For others, it encapsulates a prolonged period of high volatility (in either economies or asset markets).
According to PIMCO, the coiners of the term, the new normal is also explained as an environment wherein “the snapshot for ‘consensus expectations’ has shifted: from traditional bell-shaped curves – with a high likelihood mean and thin tails (indicating most economists have similar expectations) – to a much flatter distribution of outcomes with fatter tails (where opinion is divided and expectations vary considerably).” That is to say, the distribution of forecasts has become more uniform (as per Exhibit 1).
Exhibit 1: The New Normal: A Flatter Distribution with Fatter Tails
For some economic variables, this is certainly an accurate description. The Bank of England provides us with a good example. It is one of the few central banks brave (or foolhardy) enough to provide us not only with their forecasts, but the ranges around those forecasts (the so-called fan graphs shown in Exhibit 2).
The first chart in Exhibit 2 shows the range of forecasts as of May 2009 going from -0.4% to around 3.5% annually. Fast forward to August 2010 (the second chart in Exhibit 2), and we see a wider distribution of outcomes, which range from -0.6% to approximately 4.5% annually. This is evidence that is clearly consistent with the description of the new normal provided above.
Exhibit 2: Bank of England’s Inflation Forecasts (May 2009 and August 2010)
However, the flatter distribution with fatter tails version of the new normal shouldn’t be taken as a universal truth. For instance, if we turn our attention from the Bank of England’s inflation forecasts to its GDP forecasts, we see something very different (Exhibit 3). The May 2009 forecast has a significantly wider distribution than that of August 2010. This is the antithesis of the new normal. Ergo, the concept should not be applied unconditionally.
But what concerns me more than this are some of the implications that proponents of the new normal seem to draw when it comes to investing. For instance, Richard Clarida of PIMCO wrote the following earlier this year, “Positioning for mean reversion will be a less compelling investment theme in a world where realized returns cluster nearer the tails and away from the mean.”
This certainly isn’t the first premature obituary written for mean reversion. During pretty much every “new era,” someone proclaims that the old rules simply don’t apply anymore … who could forget Irving Fisher’s statement that stocks had reached a “permanently high plateau” in 1929?
Mean reversion is in some august company in being well enough to read its own obituary. Men as varied as Samuel Taylor Coleridge, Ernest Hemingway, Steve Jobs, Rudyard Kipling, and Mark Twain were all recipients of the news of their own demise. Personally, I think Kipling’s response was among the best. Upon learning of his departure from the mortal coil while reading a magazine, he wrote to its editors, “I’ve just read that I am dead. Don’t forget to delete me from your list of subscribers.” With respect to mean reversion, I can’t help but say, in the spirit of Mark Twain, that reports of its death are premature and greatly exaggerated.
Exhibit 3: Bank of England’s GDP Forecasts (May 2009 and August 2010)
Why do I think that mean reversion is still very much alive and well? First, I fear that the concept of the new normal confuses the distribution of economic outcomes (and forecasts thereof) with the distribution of asset markets. As I pointed out above, for some (although not all) economic variables the new normal offers a good description of the current state of play. So, perhaps the world of forecasts will be characterized by a flatter distribution with fatter tails.
However, attempting to invest on the back of economic forecasts is an exercise in extreme folly, even in normal times. Economists are probably the one group who make astrologers look like professionals when it comes to telling the future. Even a cursory glance at Exhibit 4 reveals that economists are simply useless when it comes to forecasting. They have missed every recession in the last four decades! And it isn’t just growth that economists can’t forecast: it’s also inflation, bond yields, and pretty much everything else.
Tags: Accurate Description, Asset Markets, Bank Of England, Central Banks, Consensus Expectations, Curves, Economic Variables, Economists, Environment, Financial Times, Graphs, Invest, James Montier, Jeremy Grantham, Lean Years, Likelihood, Plethora, Prolonged Period, Snapshot, Volatility
Posted in Energy & Natural Resources, Markets, Oil and Gas | Comments Off
Monday, September 13th, 2010
Except for a burst of census hiring that briefly pushed payroll growth above trend during the second quarter of this year, job growth has been perpetually below trend over the past two years. During the post-war period, the civilian labor force has historically grown at about 0.15% each month, which currently implies that normal “trend” job growth should be about 225,000 jobs per month.
While last month’s labor report was favorably received by Wall Street, that reception was based strictly on the fact that job losses were not as bad as anticipated, given concerns about a “double dip” in the economy. The problem with this celebration, however, is that analysts continue to overlook the typical lags between deterioration in leading indicators and deterioration in coincident measures, much less lagging ones. As I’ve noted frequently in recent commentaries, the typical lag between deterioration in say, the ECRI Weekly Leading Index and the ISM Purchasing Managers Index is about 13 weeks, and sometimes longer. The typical lag with respect to new claims for unemployment is about 23-26 weeks (which puts the likely window of deterioration at about the October – November time frame), and the typical lag with respect to the payroll unemployment report is, not surprisingly, about 4 weeks beyond that. The critical risk area here extends for several months, not a few weeks.
The labor reports of the past three months cannot possibly be considered to be favorable from a macroeconomic perspective. The reason for this is that these reports were each more than 500,000 jobs short of what should have been expected.
To provide some perspective on this, below is a simple estimate of what economists call an “impulse response” profile for the U.S. labor market. When we deal with economic variables – such as employment – that are subject to positive or negative “shocks,” it is often helpful to estimate how those shocks tend to “propagate” over time. For employment, a 1% shock in job creation or destruction (versus trend growth) tends to be followed over the following year by an additional 1% movement in jobs in the same direction. After that, the impulse gradually attenuates over a larger period of years, as the initial positive or negative burst is followed by a trajectory back toward trend growth. In effect, positive and negative “shocks” to job creation have very strong tendency to “cluster,” propagating in the same direction for a period of about 12 months, and then gradually attenuating toward the long-term trend.
Note that the impulse response curve shifts direction after the first year. Evidently, both when hiring workers and when laying them off, businesses tend to shoot first and ask questions later. In economic recoveries, large initial bursts of hiring tend to propagate for a year, and then the new hiring is rationalized. Similarly, large bursts of layoffs in a recession tend to propagate and then reverse.
We can apply this impulse response to prior economic shocks to get an idea of what the economic headwinds or tailwinds would be for the job market in a “normal” cycle. I stress the word “normal” here because in our view, the current economic picture is well outside of postwar norms, and is much better characterized by previous periods of credit crisis. This can be seen most clearly in sluggish final sales, and in the failure of income, less government transfer payments, to show any normal sign of meaningful growth.
Tags: Commentaries, Critical Risk, Deterioration, Double Dip, Economic Variables, Economists, Hussman, Impulse Response, Ism, Lags, Leading Indicators, Macroeconomic Perspective, Payroll, Post War, Purchasing Managers Index, Response Profile, Risk Area, Shocks, Unemployment Report, War Period
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Wednesday, August 4th, 2010
This article is a guest contribution by Richard Clarida, EVP, and Mohamed El Erian, CEO and Co-CIO, PIMCO.
Federal Reserve chairman Ben Bernanke’s characterization of the economic outlook as “unusually uncertain” has attracted much attention, and rightly so. It speaks to the immediate impact of a series of ongoing national and global realignments whose effects are consequential but not yet sufficiently appreciated.
At a fundamental level, the unusual uncertainty reflects the disruptive combination of deleveraging, reregulation, structural unemployment and other ongoing structural changes.
The phenomenon is not limited to the U.S. It is also visible in other industrial countries. Just look at the latest inflation report issued by the Bank of England, which points to unusual dispersion in policymakers’ expectations for such basic economic variables as growth and inflation.
It is the shape of such dispersion that strikes us as particularly important. It seems that, wherever we look, the snapshot for “consensus expectations” has shifted: from traditional bell-shaped curves – with a high likelihood mean and thin tails (indicating most economists have similar expectations) – to a much flatter distribution of outcomes with fatter tails (where opinion is divided and expectations vary considerably).
We should all feel sorry for policymakers who face such distributions. The probability of a policy mistake is materially higher, especially as policy measures are subject to lags. What is less appreciated is the extent to which this changing shape of distributions affects conventional wisdom in the investment world, together with the rules of thumb that many investors have come to rely on.
We can think of five implications, some of which are already evident while others will only be obvious over time.
First, investing based on “mean reversion” will be less compelling. Even though flatter distributions with fatter tails have means, the constituency for mean reversion investing will shrink as those means will be much less often realized in practice. A world where the realized return rarely equals the expected valuation creates a bigger demand for liquid, default-free assets; it also lowers the demand for more volatile asset classes such as equities. These shifts are already taking place.
Second, frequent “risk on/risk off” fluctuations in investors’ sentiment are here to stay. Investors, based on 25 years of rules of thumb that “worked” during the great moderation, thought they knew more about the distribution of risk than they in fact did. This led to overconfidence during the bubble. The crisis reminded investors that these rules of thumb are less useful, if not dangerous.
With declining confidence in a reliable set of investing rules, markets have become more susceptible to overreactions to daily news and are, therefore, more volatile. Just think of the number of triple-digit days in the Dow.
Tags: Bank Of England, Changing Shape, Clarida, Consensus Expectations, Conventional Wisdom, Economic Outlook, Economic Variables, Evp, Federal Reserve Chairman, Federal Reserve Chairman Ben Bernanke, Fundamental Level, Industrial Countries, Inflation Report, Investment Landscape, Investment World, Mean Reversion, Mohamed El Erian, Policy Measures, Rules Of Thumb, Structural Unemployment
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Wednesday, April 22nd, 2009
“Green shoots”, “glimmer of hope” and “light at the end of the tunnel” are three phrases economists have recently started bandying around, referring to a slowing in the deterioration of a number of economic variables, i.e. that the rate of global economic deterioration is bottoming out. This is also referred to as the so-called second derivative of growth turning positive; continuing economic contraction is the first, negative, derivative.
These claims were validated by Goldman Sachs’s Diffusion Index (a composite of 34 economic data points from across the globe) that increased to above 50 in February and March, indicating improvement.
The results of two surveys released over the past two days also seem to back up the “green shoots” claims.
Firstly, the ZEW Indicator of Economic Sentiment for Germany, considering the outlook six months hence, improved again in April to 13.0 from -3.5 in March. This was the sixth monthly gain and the first time the index has turned positive since July 2007. “Investors are growing confident that the worst of the financial crisis and recession has passed,” said Moody’s Economy.com. This ZEW Indicator has not been a bad leading indicator in the past.
Secondly, in its latest Survey of Business Confidence of the World Moody’s Economy.com reports that global business “has taken on a slightly better hue in recent weeks”. The Survey highlights that “broad assessments of current and prospective conditions have moved up measurably since the beginning of the year. It is premature to conclude that businesses are turning measurably more upbeat, but recent survey results are somewhat encouraging.”
More signals are required, but it would seem that some measures have started pointing in the direction of an economic recovery. However, the big question mark remains the magnitude and duration of the recovery.
Tags: Business Confidence, Derivative, Diffusion Index, Economic Contraction, Economic Data, Economic Deterioration, Economic Rate, Economic Recovery, Economic Sentiment, Economic Variables, Financial Crisis, Glimmer Of Hope, Global Business, Goldman Sachs, Hue, Leading Indicator, Light At The End Of The Tunnel, Question Mark, Recession, Survey Results
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