When Is the Next Recession Coming? Don’t Ask the Fed
Monday, September 17, 2018 17:41
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“Don’t Be Fooled by Good Economic Numbers”
By Jim Rickards
“The Trump administration’s initiatives on the U.S. economy are notable and mostly positive. Regulations have been cut. Taxes have been cut. Trump is aggressively seeking better trade deals. The stock market is back to all-time highs and consumer sentiment is off the charts. Second-quarter U.S. GDP growth was over 4% and projections for the third quarter are also strong.
What’s not to like? The problem is we’ve seen all this before. Obama had several quarters of 4% or greater growth during the long recovery from 2009–2016. Stocks may be higher but not much higher than they were last January. Consumer sentiment doesn’t tell us much because it’s highly correlated to the stock market.
So Trump is having a good stretch, but it’s too early to say that the U.S. economy has broken out of its weak recovery performance or that sustainable above-trend growth has been achieved. In fact, there’s good reason to believe the Trump economy is no different than the Obama economy, which is to say weak growth with occasional spikes and occasional dips down to zero.
The U.S. trade deficit spiked in July, according to the latest data. That’s a drag on third-quarter GDP growth. It’s also a reflection of the impact of a strong dollar (due to Fed rate hikes) and the trade war that is ongoing. Strong growth in the second and perhaps third quarters could follow a pattern seen in the past nine years of short-term spikes followed by a return to subpar growth. We may not be in a recession, not yet anyway, but there’s no reason to believe we are seeing a genuine boom.
The Fed is raising interest rates 1% per year in four separate 0.25% hikes each March, June, September and December. The Fed is also slashing its balance sheet about $600 billion per year at its current tempo. The equivalent rate hike impact of this balance sheet reduction is uncertain because this kind of shrinkage has never been done before in the 105-year history of the Fed. However, the best estimates are that the impact is roughly equivalent to another 1% rate hike per year.
Combining the actual rate hikes with the implied rate hikes of balance sheet reduction means the Fed is raising nominal rates about 2% per year starting from a zero rate level in late 2015. Actual inflation has risen slightly, but not more than about 0.50% per year over the past six months. The bottom line is that real rates (net of inflation) are going up about 1.5% per year under current policy. From a zero base line, that’s a huge increase.
Those rate hikes would be fine if the economy were fundamentally strong, but it’s not. Real growth in Q2 2018 was 4.1%, but over 4.7% of that real growth was consumption, fixed investment (mostly commercial) and higher exports (getting ahead of tariffs). Q2 growth looks temporary and artificially bunched in a single quarter. Lower growth and a leveling out seem likely in the quarters ahead.
The Fed seems oblivious to these possibilities. The Fed has extended its growth forecasts to yield 2.27% for Q3 and Q4, and expects 2.71% for 2018 as a whole. That’s a significant boost from the 2.19% average real growth since the end of the last recession in June 2009. By itself, that forecast offers no opening for a pause in planned Fed rate hikes or balance sheet reduction. The Fed is on track for more rate hikes, a reduced balance sheet and no turning away from its current plans.
But the Fed’s assumptions may be wishful thinking. Real annualized U.S. GDP growth exceeded 4% four times in the past nine years only to head for near-zero or even negative real growth in the months that followed. There’s no compelling reason to conclude that Q2 2018 will be any different. Data indicating performance close to recession levels will likely emerge in the next few months. With Fed tightening and a weak economy on a collision course, the result might well be a recession.
Toward the end of this quarter, the full extent of a global slowdown will be apparent even to the Fed. In that case, get ready for a Fed “pause” on rate hikes in December, a weaker dollar, a stock market correction and increased tension in the trade wars. In the meantime, the Fed will almost certainly raise rates in less than two weeks as the Fed sleepwalks into another recession. Below, I show you why the Fed will be clueless when the next recession strikes. As you’ll see, the problem is the Fed’s models. What models should the Fed adopt instead? Read on.”
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“When Is the Next Recession Coming? Don’t Ask the Fed”
By Jim Rickards
There are plenty of models and lots of ways of looking at the same data to draw conclusions about the economy and make forecasts. Sometimes the model differences are more superficial than not. Other times the model differences are profound. But for a few who actually explain their models (including a typical Fed mathfest around their dynamic stochastic general equilibrium, or DSGE, models), most differences don’t matter because the analysts are too busy shouting their conclusions and not patient enough to offer a deeper explanation to genuinely interested parties. In any case, followers latch onto their favorites and re-shout the conclusions and life goes on with no resolution of which models work and which don’t.
The Fed DSGE models (also used by the IMF and others) are straightforward. They begin with the assumption that dynamic economic systems are equilibrium-based. There’s no actual evidence for this, but it’s a convenient economic assumption. The model also assumes that events in a sequence are stochastic. This means “random,” but not in a path-dependent way. Random for this purpose is more like a coin toss, card draw or roll of the dice where an individual outcome is not predictable, but a long-term series of outcomes is highly predictable i.e., where 1,000 coin tosses will come close to 500 heads and 500 tails every time.
Once one assumes DSGE models are correct (I don’t), it follows that the overall economy is generally in balance and the long-term path of key variables is predictable, despite short-term variance. Then there is relatively little for central banks to do except avoid changes in expectations, mostly about inflation or deflation.
The result is that expectations and real variables (interest rates, unemployment, growth, etc.) are optimized and in balance. The only time the Fed needs to intervene is when expectations or real variables fall out of balance and some nudge, usually via interest rates, is needed from the Fed to restore those factors to balance.
The Fed found itself in a highly unbalanced economy in late 2007 and most of 2008 regarding deflationary expectations (much higher) and the path-dependence of bank failures. The Fed’s solution, first under Ben Bernanke and then Janet Yellen, was to first cut rates to zero (ZIRP). Then, blow up the Fed balance sheet through so-called QE, QE2 and QE3, bail out failing banks in the U.S. and Europe and reassure the general public that Bernanke, Yellen and the ECB’s Mario Draghi would do “whatever it takes” to keep the financial system going.
At that point, the Fed and ECB assumed the simple passage of time and continual reassurance would heal the wounds and return the economy to normalcy. This never happened. It’s true that a worse recession in 2008 was avoided, but there is no evidence at all that the expansion from 2009–2018 was more than a slow, modest claw-back of growth.
This nine-year expansion averaged real annual growth of 2.19%, significantly lower than the 3.22% average real annual growth for all expansions since 1980. The most recent quarter of 4.1% annual real growth was the fifth such quarter since 2009. All four prior 4%-plus quarterly expansions quickly compressed to growth below 1.0% or actual losses within six months.
Despite an abysmal record of forecasting economic growth and inflation over the past 10 years, markets still buy into the Fed’s plan of action. Today, markets are showing a 96.8% expectation of a rate hike at the Fed’s September meeting in less than two weeks. The reason actual Fed expectations have not been served is that their DSGE models bear little to no relationship to the real economy. The real economy is not an equilibrium system. It is a system of booms and busts, surges and sharp contractions, and misplaced reliance on government.
Assumptions about consumer and investor expectations are routinely disappointing, which leads to rapid reversals that are also disappointing. Each of these psychological reversals (disappointment, reversal, disappointment, reversal, etc.) is an example of an “emergent property,” a hallmark of complex dynamic systems.
A complex dynamic system, part of a larger branch of science called complexity theory, is much more in sync with how the real economy operates. A complex dynamic system is characterized by diversity (millions of perspectives), connectedness (diverse views have message traffic links), interaction (system participants conduct billions of transactions) and adaptive behavior (system losers change or close losing positions).
A city dweller who looks outside on a winter morning to see if locals are wearing sweaters (not too cold) or down parkas (below freezing) and adapts her dress accordingly is a willing participant in a complex dynamic system of which she may be only slightly aware.
Most experts in complexity theory and complex dynamic systems are only familiar with capital markets in superficial ways. They are more likely to be experts in physics, biology, seismology, meteorology and other branches of science where complexity is deeply rooted.
Complexity was discovered as a hard science in 1948 by Warren Weaver of the Rockefeller Foundation and was put on a more firm statistical footing by climatologist Edward N. Lorenz in 1963. Since the early 1960s and the advent of remarkably swift and inexpensive computing power, complexity theory has flourished in hard sciences, soft sciences and capital markets.
Complexity theory is an almost perfect description of actual behavior in capital markets (go here to learn how to make complexity theory and the world’s most powerful predictive tools work for you in the markets). The capital markets are four-for-four on the main criteria — diversity, connectedness, interaction and adaptive behavior.
Billions of investors wake up every day and adopt a posture of bull or bear, leveraged or unleveraged, aggressive or timid and so on. They connect through a myriad of networks over every channel, from Bloomberg to text. They interact to the extent of trillions of dollars in stocks, bonds, currencies, commodities and more. Finally, they adapt their behavior at warp speed or else expect to be removed from the trading floor, possibly feet first.
These conformance characteristics alone prove nothing, but they lay a strong basis for further analysis. The critical connection between complexity and capital markets is not just superficial behavior, although that’s an important starting point, but is based on the fact that humans themselves are models of complex behavior independent of the role of some in capital markets.
This makes human behavior in capital markets an exponentially complex adaptive arena. Without leaping to conclusions, there is an eminently sound foundation for the conclusion that capital markets are the most complex human arena for behavior alongside love and war.
Once your analysis has come this far, many hallmark behaviors from capital markets become easier to understand. Bull and bear markets are seen for what they are — psychological enthusiasm and psychological depression taking turns as the thème du jour.
Panics are also seen in the proper context — radical changes in investor attitudes toward real cash (“Where’s mine?”) versus pseudocash, which are stocks, bonds, real estate and other investments that are taken to be “cash,” up until the day they’re not.
These and many other instant behavioral changes are considered to be “emergent properties” of complex systems — a favored term for events no one sees coming until they land on your doorstep or brokerage account statement.
Name-tagging does not make forecasting easier but it does put forecasting in a proper context. The humble analyst, hopefully including your correspondent, would rather be approximately right than completely wrong.
Other paradigms abound, but DSGE (the Fed) and complexity theory (me and a few others) have staked out the high ground for which theory best explains behavior in capital markets. Many analysts favor DSGE because it’s mainstream, and taught from the first week of Intro to Economics.
The accuracy of predictive analytics favors complexity theory. In time, powerful predictive analytics falling from the application of complexity to capital markets will trump the sheer number of DSGE adherents. Yet there’s no reason to expect this to happen quickly.
Copernicus, with Kepler and Brahe hot on his heels, laid out the mathematical and empirical foundations of a heliocentric solar system by the mid-16th century. Yet the theological and scientific debate inside the Catholic Church raged on during the 17th century and was not finally put to rest in Copernicus’ favor until the early 19th century. Even the best ideas have high mountains to climb when they’re new.
Meanwhile, my readers will receive the fruits of complexity theory applied in predictive analytic form to capital markets. I’m happy if everyone receives them but not displeased if the audience is smaller… at least for the short run.”
Source: http://coyoteprime-runningcauseicantfly.blogspot.com/2018/09/when-is-next-recession-coming-dont-ask.html
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