Here’s the second installment of excerpts from my new book Nowcasting The Business Cycle: A Practical Guide For Spotting Business Cycle Peaks Ahead Of The Crowd. Earlier this month I published the Preface.
In February 2004, a rising star at the Federal Reserve delivered heartwarming news at the winter meeting of the Eastern Economic Association. The business cycle had been tamed, the speaker advised. “One of the most striking features of the economic landscape over the past twenty years or so has been a substantial decline in macroeconomic volatility,” Ben Bernanke explained. The implication: recessions had become a diminishing threat to the body economic. Downturns arrived less frequently and when they did bite the pain was modest compared with their predecessors. The trend wasn’t limited to the United States, the future chairman of the Federal Reserve said. The Great Moderation, as he called it, was smoothing the rough edges of economies the world over. 1
Prevailing conditions at the time supported Bernanke’s analysis. In fact, many analysts concluded that a new era of economic tranquility had dawned. But as the world was reminded during the Great Recession of 2008-2009, which started just four years after Bernanke’s speech, the received wisdom in macroeconomics has been known to suffer a limited shelf life as a practical guide for thinking about the future.
The dark side of the business cycle slips into hibernation most of the time, perhaps due to enlightened policy—or luck? Yet the Bernanke in 2004 wasn’t shy about giving the Federal Reserve a healthy dose of credit for the apparent change for the better in the macro climate. “My view is that improvements in monetary policy, though certainly not the only factor, have probably been an important source of the Great Moderation,” he said. 2
History, however, suggests that economic slumps (like rats and cockroaches) are virtually immune to clever extermination plans. That doesn’t deter macroeconomists, who endeavor to figure out why economies stumble and how future downturns can be restrained if not avoided altogether. The source of the economy’s to and fro through the decades has been attributed to everything from sunspots to blunders by central bankers. The Marxist interpretation simply warns that capitalism is inherently unstable and so a steady run of turmoil is fate. No matter your view on Karl and his political legacy, his defeatist view isn’t too far from the truth, or so the historical record seems to indicate.
Such narratives are only the beginning, of course. You could spend the better part of a lifetime cataloguing the spectrum of theories that claim to uncover the reasons for the business cycle’s persistence. But don’t confuse an abundance of explanations with enlightenment. Despite countless studies intent on finding the truth, it’s still debatable if anyone truly understands the big picture. Perhaps that’s why recessions are a recurring menace.
In any case, the slumps keep coming, as they have for more than two centuries, and there’s no reason for thinking that the future will be any different. “I devoutly hope our next downturn won’t come for quite some time, but it surely will come eventually,” noted Richard Fisher, president of the Federal Reserve Bank of Dallas, in 2011.3 As macroeconomic prophecies go, that’s a keeper.
Recessions are no closer to extinction in the 21st century than they were in 1950—or 1850. Some say it’s simply the essence of capitalism, or human nature’s influence over matters economic. It’s been the same whether it’s an economy linked to a gold standard or fiat monetary systems; with or without a central bank running the show. The use of heavy regulation vs. something closer to a free-market ideal doesn’t matter much either in terms of affecting the durability of broad economic fluctuations.
Macroeconomic theory may not have a satisfying answer for why these events roll on, but the profession isn’t a total bust. Dismal scientists have learned a thing or two about economic volatility over the years. The future’s still uncertain and always will be. It’s safe to say that there’s never a shortage of analysts who are caught napping at the start of a new downturn. Yet it’s shortsighted to ignore the advances in recession analytics because some economists didn’t recognize the warning signs the last time around.
Imagining a world that delivers steady progress toward kinder, gentler economic cycles seemed as plausible in 2004 as it is absurd today. Yet the Great Moderation was no illusion. Bernanke and the legions of economists who agreed with him weren’t delusional in that halcyon period, before the worst recession in 80 years struck in early 2008. Ahead of that fateful slump, economic volatility did moderate and recessions did retreat in frequency and magnitude. The mistake was thinking that the trend heralded an era of permanently diminished macroeconomic risk.
It’s hardly the first time that economic volatility was underestimated by the experts (nor is it likely to be the last). In 1960, the economist Arthur Burns, one of the 20th century’s early pioneers of macroeconomic analysis, declared that “the business cycle is unlikely to be as disturbing or troublesome to our children as it was to us or our fathers.” 4 In the following decade, Burns would eat those words. Appointed chairman of the Federal Reserve in 1970, he led the central bank through the turmoil of the 1973-1974 recession, the deepest up to that point since the Great Depression of the 1930s.
Perhaps it’s human nature to think optimistically, a habit that eventually colors expectations for even the most objective of dismal scientists. Nonetheless, the business cycle endures. As of 2014, there have been 33 recessions since 1857, according to the National Bureau of Economic Research, the official score keeper of turning points in the U.S. economy. No one can afford to assume that this ignominious tally won’t continue to climb in the years ahead, yet hope springs eternal.
Before the Great Recession, macroeconomists were congratulating themselves on the long stretch of shallow and infrequent recessions. And for a time, it looked like the business cycle had been conquered. But it all came crashing down in 2008. The arrival of the deepest recession in nearly a century has challenged the notion that economic risk can be engineered down to a manageable level through enlightened policy. Everything works in macroeconomics until it doesn’t. Topics long considered settled terrain have recently been revived for a new generation of debate and research. Students of economic history will find parallels in contemporary discussions with the dialogues of the 1930s that included such luminaries as John Maynard Keynes, Friedrich von Hayek, and Irving Fisher. What’s old is new in macro.
But let’s keep our criticism in perspective. There’s precious little opportunity for experimental research in macroeconomics. Testing the validity of one theory vs. another in a controlled setting is impossible. There are no laboratories to run trials and sort out the results. There’s only one historical sample to dissect and it’s burdened by a limited data set, questionable rules for interpretation, and an excess of mitigating circumstances. Even when new and presumably improved economic policies are implemented, it’s never entirely clear if there’s a direct connection between the adjustment and the economic outcome. There are too many moving parts in a modern economy to isolate specifics in the search of cause and effect to speak authoritatively.
That leaves economists to argue over the ideas that appear credible. But debates about theory aren’t easily resolved, if at all, by studying history. The business cycle unfolds slowly and there’s always doubt if the historical period in question is an exception to the rule, or even representative of how the system works generally. Indeed, this is a profession that still fiercely debates the catalysts of the Great Depression—more than eight decades and countless studies after the fact.
It’s fair to say that consensus isn’t about to break out in macroeconomics anytime soon. Perhaps the closest thing to harmony is the acceptance that economic output rises and falls through time. If we’re inclined to emphasize what’s conspicuous and beyond debate, we can agree that the cycle has the capacity to be something other than gentle at times. The inherently dynamic nature of capitalism endures, as Schumpeter warned, delivering a “perennial gale of creative destruction” through the course of history. 5
If we must plead some level of ignorance for explaining why there’s a cycle, much less curing it, we should still respect and study it, if only for self-defense. We can start with an easily confirmed fact, albeit one that’s too often ignored: fluctuations in the broad economy persist. That’s clear when looking backward. The problem, of course, is gazing ahead.
Inference & Error
Consistently predicting the timing of recessions with pinpoint accuracy is impossible, but that doesn’t mean there’s no hope for recognizing when the odds of a new downturn are elevated. Much of what’s been uncovered in the art/science of anticipating and recognizing recessions falls into the empirical corner of economics. History suggests that under condition x, there’s a higher likelihood of y. Economic theory helps us understand why there’s a relationship—or, why we should be skeptical of a relationship that appears to be relevant. Meanwhile, econometrics provides the tools for crunching the numbers and estimating the dynamic aspect of risk. If you need definitive answers and precise timetables, you’re out of luck. But if we relax our expectations a bit, there’s room for optimism about what can be achieved.
History isn’t a consistently reliable guide for what happens next, of course. No amount of statistical analysis can wipe away the perennial mystery about tomorrow. But quantitatively based risk estimation can help recognize the hazards that look particularly threatening at a given point in time. Recessions rarely if ever strike without some type of warning. History doesn’t repeat, but it’s been known to rhyme.
Even the Great Recession wasn’t all that unusual, aside from the depth of the downturn. The main set of factors that led to previous recessions conspired to bring us the 2008-2009 slump, according to professors James Stock of Harvard and Mark Watson of Princeton—two veterans of deciphering macro fluctuations. They found that “the same six factors which explained previous postwar recessions also explain the [start of the Great Recession]….” In particular, oil, monetary policy, productivity, uncertainty, liquidity/financial risk, and fiscal policy were the key elements:
Within the context of our model, the recession was associated with exceptionally large movements in these “old” factors, to which the economy responded predictably given historical experience. While there were new events and exceptional policy responses in the 2007 Q4 recession, the net effect of these new events and responses was not qualitatively different than past disturbances—just larger. We interpret these results as pointing towards a confluence of large shocks that have been seen before, not towards new shocks that produced unprecedented macroeconomic dynamics. 6
In other words, we’ve seen this movie… several times. You can never really prove anything in economics, but it’s hard not to notice the recurring features that accompany boom and bust across the broad sweep of history—stylized facts, as they’re called. “We have been here before,” a pair of economists wrote in an expansive review of financial crises through the centuries. “No matter how different the latest financial frenzy or crisis always appears, there are usually remarkable similarities with past experience from other countries and from history,” advised professors Carmen Reinhart and Kenneth Rogoff in their empirical masterwork This Time Is Different: Eight Centuries of Financial Folly.7
The naïve assumption is that recessions are random events that arrive with no warning—economic acts of God. If true, attempts at recognizing the conditions that lead to these events are doomed to failure. But as research by Stock and Watson, Reinhart and Rogoff, and many other economists suggest, the prospects are in fact encouraging for evaluating recession risk as it rises and falls. Why? Because there’s a recurring aspect to the economic conditions associated with slumps. The historical record clearly shows that economies don’t suddenly, inexplicably shift from growth to contraction overnight. Recessions typically take time to fester, and the festering is almost always visible… if you’re looking at the relevant indicators through a practically designed analytical prism. It’s not a perfect, symmetrical rise and fall; in some cases the deterioration arrives faster or slower compared with previous events. But the cyclical aspect of the process is noticeable if we monitor multiple indicators and aggregate the changes through time.
Good thing, too, since ignoring the business cycle is a luxury that few of us can afford. Recession risk drives many if not most of the hazards that bedevil individuals, businesses, governments and society in general. We can’t neutralize this risk, but we can at least prepare for it when the storm clouds look particularly menacing. The only thing worse than a recession is a recession that arrives as a complete surprise. Fortunately, we can reduce the chances of finding ourselves in a state of ignorance by reading the cycle’s tea leaves.
Whether we’ll take advantage of what’s been uncovered on this front is another matter. Consider the signals from the Treasury market’s yield curve. It’s usually a sign of trouble in those rare instances when interest rates on short-maturity securities rise above long rates—an inverted yield curve, as it’s called. Inverted curves have dispatched early and generally accurate warnings about recession risk since the 1960s. No one should assume that this signal alone will tell us all that we need to know going forward. The yield curve may fail us the next time. The same can be said of any one indicator, no matter how impressive its track record. A responsible review of recession risk demands a broad review of indicators.
Still, when a predictor with an encouraging history flashes red, it deserves respect. “For over two decades, researchers have provided evidence that the yield curve, specifically the spread between long- and short-term interest rates, contains useful information for signaling future recessions,” a 2009 study noted. A useful sign, but “despite these findings forecasters appear to have generally placed too little weight on the yield spread when projecting declines in the aggregate economy. Indeed, we show that professional forecasters are worse at predicting recessions a few quarters ahead than a simple real-time forecasting model that is based on the yield spread.” 8
Perhaps the inclination to question the timeliness of even the strongest warnings of macro trouble is part of the human condition of embracing optimism, which is especially tempting when recession risk is generally higher, i.e., after a long period of growth. It seems that living through the good times can cloud our capacity for critical analysis. It’s now understood that our brains are susceptible to exaggerating recent experiences when anticipating the future. Cognitive biases bedevil us, according to the pioneering research from psychologists Daniel Kahneman and Amos Tversky. Their analyses show that it’s psychologically difficult to accept the idea that the recent past may be a poor guide to the near term. 9
We all want to believe that the good times will roll on. That’s understandable, but it’s a habit that’s sure to become dangerous every so often. Growth dominates in the long haul and so expecting more of the same fares pretty well as a general outlook. But that expectation is destined to be wrong at some point. Overlooking our tendency to downplay future turning points leaves us vulnerable to large negative surprises. That’s no trivial issue when you consider that recessions usually start during the best of economic times.
There are plenty of other factors bedeviling the search for reliable clues about the business cycle’s current state. Institutional biases, for instance, can skew the best guesses of professionals. Jeffrey Frankel at Harvard’s Kennedy School of Government demonstrated that official government forecasts in 33 countries showed a tendency for overstating the case for economic growth. 10 Politics may play a role, too. At least two studies found that the International Monetary Fund’s forecasts of growth were higher than the levels implied with basic economic evaluations. 11 Maybe that’s not entirely surprising in the wake of reports that revealed that accuracy alone isn’t always the sole or even primary motivation behind some macroeconomic predictions. 12
Nowcasting Recession Risk
Even if we avoid the obvious pitfalls, it’s easy to see the situation as bleak. History, after all, is littered with failure when it comes to business cycle analysis. But let’s not sink into defeatism. In contrast with Dante’s reaction when he approached the gates of hell, we needn’t abandon all hope. In fact, we start with a considerable advantage in knowing that there’s probably another recession out there somewhere. The real challenge isn’t predicting when it will arrive so much as developing solid intuition for recognizing when the threat is exceptionally high. Progress on the latter will provide insight into the former. The work begins by focusing on the tools and techniques that will tell us when a downturn has recently started. Forecasting may be a fool’s errand in economics, but looking for early indications that the cycle has entered the danger zone is something else entirely.
The distinction between predicting and nowcasting drives the logic of this book. That is, evaluating recession risk based on the latest economic indicators as opposed to predicting how the numbers will stack up down the road, which invariably runs up against a familiar obstacle: uncertainty. That doesn’t mean we should always and forever refrain from forecasting. A disciplined, well-designed methodology of estimating what looks likely in the near-term future can be productive. But the world is awash in such efforts, and the results overall aren’t terribly encouraging, which is why we need an alternative to the standard approach.
There are two basic ways to wrestle with recession risk. One is to forecast it; the other is to develop a high-confidence assessment of whether it’s currently squeezing the economy. The world is teeming with guesses about the future, and they come with all the usual caveats. It doesn’t help that some fatally flawed systems are occasionally accurate. Even if you’re skilled at figuring out who’s truly talented on this front—no mean feat—the uncertainty problem remains sizable. By contrast, identifying the start of major downturns in the economy in real time, using what we know today instead of what we think will happen tomorrow, is far less precarious (if the process is intelligently designed).
Eventually, all becomes clear… if you wait long enough. The gold standard on this front is the National Bureau of Economic Research’s official announcements on the dating of recessions. Because NBER is striving for a high level of accuracy that will stand the test of time, these announcements arrive well after the fact. The cyclical peak of December 2007, for instance, was identified 12 months after the recession started. 13
The advantage of the slow-moving NBER methodology is that you don’t have to worry about revisions. When the group says the cycle peaked, it’s virtually certain that they’re right and that everyone will agree with the conclusion today, tomorrow, and in the years ahead. But must we wait so long for clarity? The tradeoff in the pursuit of more timely signals is that earlier calls on cyclical peaks may suffer with accuracy. The earlier you declare a peak, the higher the possibility that you could be wrong.
The challenge is figuring out how to keep a lid on error while making relatively high-confidence assessments—as early as possible. It wouldn’t hurt if the process that brings us closer to this optimal sweet spot is transparent, intuitive, and draws on free, publicly available data. Highly parameterized models with lots of moving parts, by contrast, may impress folks in academia. But the record on complex systems isn’t terribly encouraging in business cycle analysis.
All of which inspires searching for a reasonable compromise that concentrates on timely judgments of the key economic variables. That’s an inherently subjective task, but it’s essential for interpreting the business cycle’s patterns. The true business cycle, after all, is unobservable—it’s a concept, an idea, rather than one number or a single index. We can see the outcome of what we call the business cycle through the synchronized movements of various economic metrics—employment, industrial production, consumer spending, etc. The true underlying source (or sources) that drive the synchronization, however, is a debatable topic at best. The most we can hope for is calculating a reasonable proxy that captures the economy’s broad fluctuations. Decades of research offer a guideline, but there’s no substitute for getting our hands dirty with the numbers. The economic gods have left mere mortals with the unpleasant work of conducting trial-and-error tests to figure out what is, or isn’t, relevant.
Our handicap is sizable but it’s not overwhelming, as we’ll discover in the chapters ahead. There are no short cuts that will transform us into oracles, but standing on the shoulders of giants in the field of economic research can lead us to a useful group of indicators that dispatch relatively reliable warnings of when the economy is susceptible to a new round of contraction—particularly when we look at these indicators in a holistic manner, as opposed to the natural tendency to focus on a handful of numbers one at a time.
Overall, there’s reason to think that 1) we can identify broad deterioration that’s already in progress in the economic cycle; and 2) do so earlier relative to when the crowd recognizes that another downturn has become destiny. We can start by adjusting expectations based on key lessons uncovered by economic researchers and focusing on what’s probable—as opposed to reaching for the stars by fooling ourselves that we can know what will unfold in the future.
We also have an edge that wasn’t available to previous generations: access to the numbers. It’s no small advantage that economic data is now plentiful and quite a lot of it is published on the Internet. What’s more, you can often find what you’re looking for at no charge. In addition, economists have made substantial progress in mapping the connections between the various indicators and so there’s greater opportunity for interpreting the data and using it wisely.
Keep in mind too that anticipating the risk of a general economic contraction is a somewhat easier task compared with the professional economist’s burden, which is often one of routinely predicting everything from the future path of industrial production to the economy’s quarterly gross domestic product. The goal on the following pages, however, is considerably less ambitious but far more practical: identifying those times when the odds appear elevated that a new recession has started.
“Most recessions remain undetected until they are well underway,” noted a 2009 International Monetary Fund study that reviewed forecasters’ track records. 14 Another review of predictions from private and government forecasters for the 20 years through 2006 concluded that “if past performance is a reasonable guide to the accuracy of future forecasts, considerable uncertainty surrounds all macroeconomic projections….” 15
Surely we can do no worse than the average forecaster, although with a bit of effort it’s possible and perhaps even likely that we can do slightly better. By focusing on the relevant data and using economic research to develop a simple but intuitive model to assess recession risk, we have a good chance of modestly enhancing our strategic intelligence. Given what’s at stake, even a small degree of improvement will bring substantial advantages.
A degree in medicine isn’t required for making informed decisions on health matters and you don’t need years of training in meteorology to recognize when there’s a storm coming. Similarly, intelligent evaluation of recession risk isn’t solely dependent on holding a Ph.D. in macroeconomics. That’s no slur against dismal scientists—some of my best friends are formally trained economists. But let’s face it—monitoring the mother of all risk factors is too important to be left to “the professionals.”
That’s an invitation for us to take some responsibility for thinking clearly about recession risk. The motivation requires no explanation. As the American engineer C. F. Kettering reportedly said, “My interest is in the future because I am going to spend the rest of my life there.”
The rest of the book is a journey—a journey of exploring how we can develop a deeper understanding of the business cycle in order to identify, as early and confidently as possible, those times when a recession is upon us. The model isn’t particularly complicated—feel free to skip ahead to the final chapter for a summary on how to assess recession risk—but it is practical and, so far, has proven to be quite valuable in quantifying the big-picture trend.
To understand what’s behind it all, you’ll want to review the chapters that precede the strategic finale. Chapter 1 offers a short review of the evolution of business cycle analysis. Although economic research that’s been published in recent years suggests a path for our analysis, a bit of historical context on the topic of economic theory is useful before we dive into studying the details of the economy’s broad swings. I begin with a recap of theory across the broad sweep of time. Where did the idea of analyzing the business cycle come from and how has it evolved?
In Chapter 2, I focus on the historical record of U.S. recessions and consider (briefly) some of the empirical efforts over the years that seek to put these events into perspective for anticipating the next round of contraction. If we’re going to analyze recessions in detail, a primer on defining and profiling these events is a useful foundation.
For Chapters 3 through 11, the focus turns to studying each of the indicators that comprise the recession risk model that’s presented at the end of the book. Yes, volumes could be (and have been) written about these indicators. But fear not, the goal here is merely a cursory introduction to the various data sets to provide a basic level of understanding for why these measures of economic and financial activity are on our short list.
Our journey concludes in Chapter 12 with a practical-minded review of a simple model for interpreting the various indicators that are discussed in the preceding chapters. I’ll also point you to a free, publicly available business cycle index that can be used to compare and contrast with the book’s model.
Yes, there are a lot of moving parts with analyzing recession risk. But after several years of study and trial-and-error analysis, I’m confident that I’ve developed a modest but powerful process for estimating macro danger. It’s only natural—and intellectually healthy—that readers will be skeptical at this point. By the end of the book, however, I trust that quite a lot of the doubts will fade.
The true test of any system of economic evaluation is the one that unfolds in real time, and so only time can dispense the definitive conclusion. But as a preview, I’ve been running tests in recent years and the results are encouraging. For an ongoing update, visit my web site: CapitalSpectator.com, where I discuss strategic-minded economic and financial subjects—including the monthly signals dispensed by the model that’s outlined in this book. 16
Without further ado, let’s begin… at the beginning, of course.
1. “Remarks by Governor Ben S. Bernanke. At the meetings of the Eastern Economic Association, Washington, DC, February 20, 2004. ‘The Great Moderation’”: www.federalreserve.gov/BOARDDOCS/SPEECHES/2004/20040220/default.htm
3. “Speech by Richard W. Fisher. Washington, D.C., March 7, 2011. ‘Churchill, Baruch, Lindsay Lohan, Congress and the Fed.’ Remarks at the Institute of International Bankers Annual Washington Conference”:
4. Burns (1960), p. 17.
5. Schumpeter ( 1950), p. 84.
6. Stock and Watson (2012), p. 2.
7. Reinhart and Rogoff (2009b), p. xxv.
8. Rudebusch and Williams (2009), p. 492.
9. See, for example, Kahneman and Tversky (1973), Tversky and Kahneman (1974), and Kahneman (1999).
10. Frankel (2011), which includes a bibliography of related studies.
11. Aldenhoff (2007) and Dreher, et al. (2007).
12. See Lamont (2002) and Laster, et al. (1999), for instance.
13. NBER issued a press release on Dec. 1, 2008 that stated: “The committee determined that a peak in economic activity occurred in the U.S. economy in December 2007”: www.nber.org/cycles/dec2008.html
14. Loungani and Tamirisa (2009), p. 3.
15. Reifschneider and Tulip (2007).
16. See the author’s web site (CapitalSpectator.com) and search for “US Economic Profile.”
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Copyright © 2014 by James Picerno. All rights reserved.