Ramin Toloui on QE

David Beckworth directed me to a new paper by Ramin Toloui, which examines the various transmission mechanisms for quantitative easing. This might be the single best paper I’ve read on the effects of Fed policy during the Great Recession and its aftermath.

In the past, I’ve often criticized people who judge the effectiveness of QE by looking at the impact on interest rates. Toloui does a nice job explaining why macroeconomists should avoid reasoning from a price change:

First, evaluating the effectiveness of quantitative easing by focusing solely on realized bond yields is inherently flawed. The conventional narrative for QE’s transmission mechanism to the broader economy focuses on the causal chain whereby central bank purchases boost bond prices, thus stimulating investment and consumption via the intermediate channel of lower bond yields. But this ignores the powerful expectations channel through which central bank policy operates. If central bank actions positively shock expectations for future economic prospects, that may directly shift the willingness of businesses and households to invest and consume. Success in breaking deflationary expectations can catalyze increased consumption and investment.

But such a shift toward reflationary expectations—higher growth, higher inflation—also tends to increase bond yields! In theory, therefore, the impact of “successful” central bank balance sheet policy on realized risk-free yields is ambiguous. At minimum, any central bank success in generating reflationary expectations would mitigate observed downward effects on yields, understate the full impact of QE policies, and help account for why bond yields increased during some implementation periods cited by QE skeptics.

Then Toloui develops a very clever way to address the identification problem:

First, this study explicitly models how changes in Fed balance sheet policy shifted market expectations for the Fed’s future policy reaction function. It achieves this by using a Taylor Rule-based framework to model the market’s future expected policy rate as a function of the market’s expectations for future inflation and output. Controlling for these variables makes it possible to identify periods when the market perceives there to be outright shifts in the central bank’s future policy reaction function—that is, when the market expects that the central bank will select a different policy rate in the future than it would have previously given the identical expectations for inflation and output.

It is useful to illustrate this concept with an example. Assume that the month before a Federal Open Market Committee (FOMC) meeting, the market expects that the policy rate three years in the future will be 2 percent, expected inflation will be 1½ percent, and the expected output gap will be zero. The FOMC then meets, leaving the policy rate unchanged but taking other actions. In the month after the FOMC meeting, the market shifts its expected policy rate to 1¼ percent while the market’s expectation for inflation and the output gap remain unchanged at 1½ percent and zero, respectively. This indicates that the market anticipates that there has been an accommodative shift in the central bank’s future policy reaction function—i.e., the market expects the Fed to choose a policy rate that is ¾ percentage points lower than before, despite identical inflation and output gap expectations.

This is indirectly related to a point I’ve made about “forecast targeting”.  The point is not to get the market forecast of inflation, or the market forecast of future levels of the fed funds rate; rather you want the market forecast of the fed funds rate that is likely to lead to on-target inflation.

Toloui also understands that any evaluation of interest rates should be conditional on the state of the economy.  Instead of using this approach to identify the optimal policy rate, he uses it to identify the impact of monetary policy.  He finds that the effect of QE on interest rates is even greater than estimated in previous studies, when conditioned on the state of the economy.

He also has some very interesting things to say about the impact of Fed policy on riskier assets:

But that is where the future Fed reaction function becomes important. To the extent that the market believes that the Fed will be more quiescent in face of future inflationary pressures, the risk that the punch bowl will be removed diminishes and prospects for a boisterous party increase. The market’s expectation for the Fed’s future policy reaction thus affects the attractiveness of a wide range of financial assets, not just U.S. Treasury bonds.

It is worth emphasizing this point, since investment committees around the world were focusing intensively on Federal Reserve policy during the post-crisis period. The interest of investors in new policy announcements was not limited to the technical dimensions of particular initiative. Rather, market participants were looking for what these announcements revealed about the character of the central bank. Was the Federal Reserve willing to do “whatever it takes” to secure a recovery and clip the tail risk of a deflation scenario? If so, portfolio managers would have a “green light” for investing in riskier assets that would benefit from a reflationary scenario. Each additional policy innovation provided more information about the Fed’s attitudes.

Lots of people have in mind a model where monetary stimulus inflates asset prices by lowering interest rates.  But that’s not actually what’s going on.  Asset prices plunged during 2008-09 even as interest rates were cut to zero.

Toloui has a much better explanation.  Monetary stimulus creates a macroeconomic environment (basically “prosperity”) where risk assets do well.  It has nothing to do with creating bubbles; it’s all about the fact that what’s good for America (in a macroeconomic sense) is more often than not also good for the stock market and credit spreads.

I strongly encourage younger academics to take a look at this paper, it provides lots of ideas that point the way toward future research opportunities.

Could’ve fooled me

Here’s the NYT:

The cumulative impact of a decade of austerity measures and Labour shifting the political center of gravity leftward on economic policy means that Mr. Johnson has been forced to promise more public spending if he wins the election. But make no mistake: In the long term his administration remains committed, as one Conservative-aligned think tank put it recently, to “rampant individualism” and “a small state.”

I was fooled by the fact that Trump, Johnson and other modern conservatives all over the world are both promising and delivering more public spending.  I thought that meant they no longer favored “a small state”.  My “mistake”.

Bartleby the central banker

The Reserve Bank of Australia has delivered 28 years of solid growth in NGDP. Unfortunately, its recent performance has been subpar. Even more worrying is the fact that its communication has been borderline incoherent:

In its quarterly monetary policy review earlier this month, the RBA downgraded a series of economic forecasts, including growth, wages, consumption and inflation, and warned “further easing could unintentionally convey an overly negative view of the economic outlook”.

It said it was prepared to cut rates again, if required, to stimulate growth but flagged the possible use of unconventional monetary policies. Philip Lowe, RBA governor, is due to deliver a speech later this month outlining options, which are likely to include negative interest rates and large-scale buying of government bonds.

Actually, it would be more accurate to say that making the statement, “further easing could unintentionally convey an overly negative view of the economic outlook” is itself likely to unintentionally create an overly negative view of the economic outlook.  Markets will look at that sort of statement and assume the RBA doesn’t know what it is doing.

This statement is just one more indication that the problem in central banking is not the zero lower bound, it’s a much deeper failure.  Central banks seem paralyzed for some reason that I don’t fully understand.  Ben Bernanke noticed this phenomenon way back in 1999.

As an analogy, we’ve all known someone who stayed in a dysfunctional relationship that they should have left.  To an outsider, it’s hard to understand why they stay in a relationship where they are subjected to continual abuse.

Similarly, people like Bernanke and I have trouble understanding why so many central banks clearly need to do something and yet hold back for some unknown reason.  Why?  It’s one of life’s great mysteries.

As a result of their paralysis, there are now calls for fiscal stimulus in Australia:

The Liberal-National government is now under increasing pressure to abandon its election pledge to return the budget to surplus for the first time in more than a decade and instead to unleash fiscal stimulus via tax cuts and infrastructure spending.

After all, it worked great in Japan:

Instrumental beliefs, prediction and reality

Note:  Feel free to skim past the philosophy to the discussion of monetary policy at the end.

In a recent podcast, Penn Jillette said something to the effect that people don’t believe conspiracy theories because they are true, rather because they are entertaining, like a good story or a good song.

The term ‘entertaining’ has a rather frivolous connotation, so lets make the concept more general and include beliefs that add deep and profound meaning to life, in areas such as art, religion, and politics.

There is another set of beliefs about the world that are more instrumental. If I believe the two objects in front of my eye are a hammer and nail, it’s not because I enjoy this belief, rather because this belief is useful. I know (or “predict”) that if I pick up the hammer I can drive the nail through a piece of wood. Similarly, I believe that New York City exists in the sense that I predict that if I traveled to that spot I’d see tall buildings, art galleries and yellow taxis.

So you might say that our view of reality is a set of beliefs that we find either directly rewarding or at least instrumentally useful. In the rest of this post I’ll mostly focus on the latter.

The sciences contain the most famous examples of instrumental beliefs. In principle, the laws of “physics” should be able to explain the behavior of the entire physical universe, or at least the non-random portion. But in practice, people use the term ‘physics’ to refer to the subset of physics problems that are very simple and easy to model. The term ‘chemistry’ refers to physics problems that are slightly messier and more complex, whereas geology, meteorology, ecology and economics refers to highly complex areas of physics—the motion of molecules in complex and chaotic environments.

In the simpler branches of science, it is possible to do controlled experiments and reach a broad consensus about cause and effect. Two physicists will have similar predictions about the speed at which an object will fall if dropped in a vacuum at sea level. In contrast, in the more complex sciences even the experts will often disagree, as it is tough to do controlled experiments that replicate the specific empirical question you want answered. What controlled experiment would tell you the odds of an 8.0 earthquake in LA next year, or the odds of global temps rising by 2 degrees by 2100, or the odds of rhinos going extinct in the wild by 2100, or the odds of a recession in 2021?

So this raises an important question. How should “we” decide what to believe about reality in the areas where the systems are complex? If the “we” is policymakers, then Robin Hanson has argued that prediction markets are the best way to ascertain the truth. I agree.

But most people disagree and are skeptical of market forecasts; they would rather import the methods of the “hard sciences”. Let the experts decide. Let experts set monetary policy. If not all experts agree, then let a panel of 12 experts vote on the policy, majority rules. (Actually, not all FOMC members are experts.)

People often define fault lines in economics in terms of left/right, Keynesian/classical, Austrian/Marxist, etc. But the fault line that really matters is methodological. How do we decide what we know?

The standard view is that reality is best understood in terms of what the experts believe to be true. I see reality as what the markets believe to be true. Expert opinion is an input, but only one of many inputs, into market forecasts.

In the past, the Fed has tended to rely on the experts. (Albeit not exclusively, they have always paid some attention to markets.)

You might wonder why I spend so much time fighting against the asset price bubble view of markets. If bubbles exist, if they are a part of reality, then they are useful for making forecasts. (I’m ignoring the fact that people might get utility merely from believing in bubbles.) If they are useful, then market forecasts are not reliable, and that makes expert opinion relatively more valuable.  The fight over bubbles is a fight over the future of macroeconomics.

I’m actually not ideologically opposed to rule by experts—after all, I’m an expert on monetary policy. I’d like to be a ruler, to have others ask me where the Fed should set interest rates. But my reading of the evidence suggests that market forecasts are superior.  Thus I try to infer the market prediction of the interest rate most likely to achieve the Fed’s policy goal.

Robert Shiller is one of the most famous proponents of the view that asset price bubbles are important. Thus you’d also expect him to be skeptical of the view that markets can guide monetary policy. And that seems to be the case.

Consider the past 12 months, a good example of the difference between expertise and markets. Monetary policy experts tend to rely on Phillips curve type models, which suggest that very low unemployment is a sign the economy is in danger of overheating. Here’s a discussion of Robert Shiller’s ideas from July of this year:

Nobel-prize winning economist Robert Shiller sees justification for a quarter-point interest rate hike.

That’s right: A hike — not the cut Wall Street is expecting Wednesday from the Federal Reserve.

“We still have a very low unemployment rate. The economy is hot,” the Yale University professor told CNBC’s “Trading Nation” on Monday. “One could easily make a case for staying the course and doing another interest rate increase at this meeting to cool this economy.”

That’s an almost perfect example of the methodological split that I described earlier.  “Nobel-prize winning” vs. “Wall Street”.  The financial markets were suggesting that inflation would stay low even if the Fed cut interest rates; whereas Shiller worried that the economy would overheat, even without a rate cut.  Olivier Blanchard recently expressed similar concerns, although he later backed off a bit.

This year, the Fed decided to follow the markets and ignore the models constructed by experts.  That’s partly because even the experts are losing a bit of faith in Phillips curve models as a policy tool.  Even some of the experts are beginning to follow the markets.

The view that markets should guide monetary policy is just one part of a much broader agenda—markets should determine what is true, what is reality.  

Consider the following two cases:

Los Angeles policymakers decide to spend $300 million in a new high school, believing it will make LA better off.

A small town in New Hampshire holds a town meeting, and decides to spend $2 million remodeling an elementary school, believing if will make the small town better off.

I would argue that while neither decision is, strictly speaking, a market outcome, the New Hampshire town more closely mimics a market.  That’s because the decision-makers in LA have almost no personal stake in what happens.  They are engaged in “expressive voting”.  It makes them feel good to build a shiny new high school for mostly low-income students.  Sort of like when Penn Jillette’s acquaintances believe in conspiracy theories.  In the New Hampshire town, the residents who vote at the town meeting have a real stakes in the decision.  It will affect their property taxes and their children’s education.

[Yes, even LA policymakers pay property taxes, but the gains they personally derive from “big government” far outweigh the cost of their taxes going up.]

This also explains why Switzerland is more successful than most other countries; its policymaking apparatus more closely resembles a market outcome.

At the Fed, some people feel good when they vote in a “dovish” or “hawkish” direction.  They have a lot invested in their ideology.  Contrast that with Wall Street.  In 1932, New York financiers voted for Herbert Hoover.  But in 1933, the financial markets “voted” that FDR’s policies were likely to boost prices and output.  Markets are unsentimental, and hence more likely to produce useful predictions, useful maps of “reality”.

Unlike markets, Fed officials are reluctant to reverse course soon after a major decision, as it makes them look bad—to most people, not to me.  I have a higher opinion of Powell after he reversed course on interest rates.  I believe the Fed was right to raise rates in 2017-18, and right to cut them this year.  Why? Because the outcome was good.

PS.  The question of whether reality is actually “out there” or is merely a mental construct is not important for the purposes of this post, or indeed for any other purpose.

Recessions in a post-inflation world

The Financial Times has an article pointing out that inverted yield curves are not a foolproof predictor of recessions, a point I’ve frequently made. (It’s actually a pretty good forecasting tool, just not perfect.)

In the article, Gillian Tett cites BIS research:

But as this inversion-watching game intensifies, it is worth reading a recent paper from the Bank for International Settlements, the central banks’ bank in Basel. It suggests that term spreads — what the shape of the yield curve measures — are not as good at predicting downturns as widely assumed and that there are other, better indices that economists and central bankers could (and should) use.

The authors start from the belief that the nature of business cycles has subtly shifted recently. In decades past, downturns were often sparked by rising inflation. But today, consumer price inflation seems increasingly benign, if not downright boring. They write that “there has been a shift from inflation-induced to financial cycle-induced recessions”. For this argument, the BIS staff define financial cycle as “the self-reinforcing interactions between perceptions of value and risk, risk-taking, and financing constraints”. The 2008 financial crisis is a case in point: a boom-to-bust financial cycle sparked a recession.

Obviously I don’t agree with that.  But there is a real change in the nature of recessions now that inflation is no longer a major problem.

In the past, some recessions were at least partly intentional. When inflation rose to unacceptable levels, the Fed tightened monetary policy to slow NGDP growth. A recession occurred. Even in 2008, inflation played a role, as the Fed was reluctant to cut rates during the late spring and summer months because of inflation fears.

Nonetheless, I do believe that financial cycles now play a bigger relative role, but not in the way the BIS assumes. (Recall that this institution was consistently wrong about monetary policy during the decade after 2007.)

Financial cycles do not directly cause recessions, but they may indirectly do so if they lead interest rate-targeting central bankers astray. When a financial cycle enters a downturn, the natural rate of interest falls sharply. If the central bank doesn’t respond in a timely fashion (by keeping its eye of forward looking market indicators), then money will get too tight and a recession will occur.

If the central bankers of the 1950s were in charge of the Fed during 2019 then we would now be in recession. Because they did not place enough weight on market indicators, we had 4 recessions between 1949 and 1960. We also had 4 recessions between 1970 and 1982. That’s way too many.

In another post I pointed out that central bankers following Phillips curve-type Keynesian models would have pushed the US into recession in 2019, as the very low unemployment rate suggests (in those models) that the economy was in danger of overheating.

Instead, the Fed looked at market indicators and did an abrupt shift from raising rates to lowering rates. There was no recession in 2019, and most forecasts now call for no recession in 2020. The longest expansion in US history is likely to go on for at least a few more years.

Because most developed countries have inflation under control, recessions caused by tight money aimed at restraining inflation will become very infrequent. By itself, this suggests that we will have fewer recessions than in the past. If the Fed continues to pay increasing attention to market signals, we will also have fewer recessions caused by the Fed not responding quickly enough to financial cycle-induced changes in the natural rate of interest.

I was taught that the average business cycle in the US lasts about 4 years. If I’m right (and I am pretty sure that I am right), then in the 21st century the average business cycle will last much more than 4 years, at least 15 to 20 years. Unfortunately, I won’t live long enough to know whether I am right.

PS. This made me laugh:

Four months ago, the yield on long-term US Treasury bonds fell below that for short-term ones, creating what is known as an “inverted yield curve”.

This sparked jitters, given that yield curve inversions preceded “seven of the last seven recessions”, with a lag of “8-60 months”, according to a recent Bank of America Merrill Lynch client note.

60 months? Why not 120 months, then the prediction would be even more reliable.