I usually try to avoid political commentary in this space, because it has become so personal to so many people. If I point out that a particular program of the “left” is smart, or cleverly put together, then half of my readership is annoyed; if I point out the same about the right, then half of my readership is angry. It doesn’t really make sense to waste article space except on those occasions when a policy has a clear effect on inflation over time, such as when the structure of the ACA made it clear that it would put upward pressure on inflation (as I pointed out in 2013) or in response to someone else’s flawed analysis of a policy, as I did last year when I tackled the San Francisco Fed for their weak argument about how the ACA would hold down inflation because the government would demand lower prices. Actually, there is no policy I have written about more than the ACA over the years – but again, this was economic commentary and not political commentary.
This article will be short, but different in that I am writing it to express frustration with the absolute lack of intellectual clarity on the part of the Republicans in making a particular argument that immediately impacts the debate over health care but also extends far into other policies. And, because the argument is simple, direct, and has tremendous empirical support, I couldn’t restrain myself. I expect this article will not be picked up and syndicated in its usual channels since it isn’t directly about economics or markets, but it needed to be said.
I’ve been stewing about this topic since Tuesday (March 14th), when I happened to catch part of the daily White House press briefing. Press Secretary Sean Spicer was asked a question about the President’s health care proposal, and tap danced away from the question:
Q Thanks, Sean. You mentioned the call with the CEO of Anthem Health. Can you tell me what this proposal of the President means for health insurance companies? Will their profits go up or down under the President’s proposal?
SPICER: Well, I don’t think that’s been the focus of the President’s proposal. It’s not about them, it’s about patients. But I think what it means for them is that they finally get to create more choice and more plans and allow people to choose a plan that fits them. Right now, they don’t have that choice. And, frankly, in more and more markets, companies like Anthem, UnitedHealth, Signa are pulling out — Aetna — because they don’t have the choice and because of the government mandate. I think what we want to do is allow competition and choice to exist so that they can offer more options for the American people.
Q But will those companies make more money under the President’s plan or less?
SPICER: I don’t know the answer to that. That’s not been the focus of what we’re doing now. And at the end of the day, right now they’re pulling out of market after market, leaving the American people with fewer and fewer choices. So right now it’s not a question of — from the last I checked, I think many of them were doing pretty well, but it’s the American people and its patients that are losing under the current system. So I think that there’s a way you can do a little of both.
Spicer’s response was the usual drivel that the Republicans have adopted when they run in fear from any question that includes the word “profits.” To summarize, the question was basically, “you’re doing this to throw a sop to fat-cat insurance companies, aren’t you?” and the answer was “we don’t think about that. No idea. Profits? Who said anything about profits? It’s about patients and choice. And, if anyone gets more profits, it wasn’t on purpose and we didn’t have anything to do with it.”
But this was actually a softball question, and the answer ought to have been something like this:
Q But will those companies make more money under the President’s plan or less?
BIZARRO SPICER: Well, I hope so. After all, the insurance companies want every person in America to have health care – which is the same thing that we want – because the more people they sell their product to, the more money they can make. The insurance companies want to sell insurance to every person in the U.S. The insurance companies also want costs to be lower, and constantly strive to lower the cost of care, because the lower that costs are, the more profit they can make in the short run. But they don’t want lower costs at the expense of health – clearly, the best outcome for their profits is that most people covered by insurance are healthy and so don’t require the insurance they’ve paid for. So, if we just get out of the way and let companies strive for better profits, we are likely to get more coverage, lower costs, and a healthier population, and that is the goal of the President’s plan.
The reason we don’t already have these things is that laws we have previously passed don’t allow insurance companies to offer certain plans, to certain people, which both sides want but which politicians think are “unfair” for one reason or another. Trying to create a certain preconceived Utopian outcome while limiting profits of insurance companies is what caused this mess in the first place.
If you want to beautify gardens in this city, does it make sense to limit the amount of money that gardeners can make? If you did, you would find fewer gardens got tended, and gardeners would not strive to make improvements that they didn’t get paid for. We can see this clearly with gardeners. Why is it so hard to understand with the companies that tend to the nation’s health? Next question.
For some reason, Republicans think that saying “profits are good” is the same thing as saying “greed is good” and leads to caricatures of conservatives as cigar-smoking industrialists. But while at some level it is the desire for a better material outcome – which I suppose is greed, but aren’t there degrees of greed? – that drives the desire for profit, we cannot dismiss the power of self-interest as a motive force that has the effect of improving societal outcomes. “It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest,” after all.
Of course, Republicans must also remember that profit without competition is a different animal. If an insurance company creates an innovation that lowers medical care costs, but does not face competitive pressure, then the benefit of the innovation accrues to the company alone. There is no pressure in such circumstances for the company to lower the price to the customer. But consider what happened to air fares after the deregulation of 1978, or to the cost of telephone service when the AT&T monopoly was broken up in 1984, as competition was allowed and even encouraged. Competition, and the more brutal the better, is what causes companies to strive for an edge through innovation, and it’s also what causes the benefit of that edge to eventually be accrued by the end customer. The government didn’t invent cell phones. Motorola did, in order to try and gain an edge against AT&T, but until the telephone monopoly was broken up there were no commercial versions of the cell phone. The first cell phones cost $10,000 in 1983, about $25,000 in today’s dollars, but now they are ubiquitous and cost about 2% as much in real terms. But this didn’t happen because of a government program to drive down the cost of cell phones. It was the profit motive, combined with competition. All that government did was create the conditions that allowed innovation and competition to happen. And wouldn’t we like health care to be as ubiquitous and cheap as cell phones are?
This is not a hard thing to get right. It isn’t hard for people to understand. But for some reason, it seems incredibly hard for politicians to believe.
Note that nothing I have written here should be construed as an opinion about the President’s health care plan, which I have not read. My remarks are only meant to reflect on the utter inability of Republicans to properly convey the reasons that a different approach – one where the government’s involvement is lessened, rather than increased – would make more sense.
 The first cell phone call was made by the inventor, Martin Cooper at Motorola, who called his competition with it: the head of the cellular program at AT&T. According to him, he said “Joel, I’m calling you from a cellular phone, a real cellular phone, a handheld, portable, real cellular phone” and he said it got really quiet on the other end of the line.
I have recently begun to spend a fair amount of time explaining the difference between a “good model” and a “bad model;” it seemed to me that this was a reasonable topic to put on the blog.
The difference between a good model and a bad model isn’t as obvious as it seems. Many people think that a “good model” is one that makes correct predictions, and a “bad model” is one that makes bad predictions. But that is not the case, and understanding why it isn’t the case is important for economists and econometricians. Frankly, I suspect that many economists can’t articulate the difference between a good model and a bad model…and that’s why we have so many bad models floating around.
The definition is simple. A good model is one which makes good predictions if high-quality inputs are given to the model; a bad model is one in which even the correct inputs doesn’t result in good predictions. At the limit, a model that produces predictions that are insensitive to the quality of the inputs – that is, whose predictions are just as accurate no matter what the inputs are – is pure superstition.
For example, a model of the weather that depends on casting chicken bones and rat entrails is a pretty bad model since the arrangement of such articles is not likely to bear upon the likelihood of rain. On the other hand, a model used to forecast the price of oil in five years as a function of the supply and demand of oil in five years is probably an excellent model, even though it isn’t likely to be accurate because those are difficult inputs to know. One feature of a good model, then, is that the forecaster’s attention should shift to the forecasting of the inputs.
This distinction is relevant to the current state of practical economics because of the enormous difference in the quality of “Keynesian” models (such as the expectations-augmented Phillips curve approach) and of monetarist models. The simplest such monetarist model is shown below. It relates the GDP-adjusted quantity of money to the level of prices.
This chart does not incorporate changes in money velocity (which show up as deviations between the two lines), and yet you can see the quality of the model: if you had known in 1948 the size of the economy in 2008, and the quantity of M2 money there would be in 2008, then you would have had a very accurate prediction of the cumulative rate of inflation over that 60-year period. We can improve further on this model by noting that velocity is not random, but rather is causally related to interest rates. And so we can state the following: if we had known in 2007 that the Fed was going to vastly expand its balance sheet, causing money supply to grow at nearly a 10% rate y/y in mid-2009, but at the same time 5-year interest rates would be forced from 5% to 1.2% in late 2010, then we would have forecast inflation to decline sharply over that period. The chart below shows a forecast of the GDP deflator, based on a simple model of money velocity that was calibrated on 1977-1997 (so that this is all out-of-sample).
That’s a good model. Now, even solid monetarists didn’t forecast that inflation would fall as far as it did – but that’s not a failure of the model but a failure of imagination. In 2007, no one suspected that 5-year interest rates would be scraping 1% before long!
Contrariwise, the E-A-Phillips Curve model has a truly disastrous forecasting history. I wrote an article in 2012 in which I highlighted Goldman Sachs’ massive miss from such a model, and their attempts to resuscitate it. In that article, I quoted these ivory tower economists as saying:
“Economic principles suggest that core inflation is driven by two main factors. First, actual inflation depends on inflation expectations, which might have both a forward-looking and a backward-looking component. Second, inflation depends on the extent of slack (or spare capacity) in the economy. This is most intuitive in the labor market: high unemployment means that many workers are looking for jobs, which in turn tends to weigh on wages and prices. This relationship between inflation, expectations of inflation and slack is called the “Phillips curve.”
You may recognize these two “main factors” as being the two that were thoroughly debunked by the five economists earlier this month, but the article I wrote is worth re-reading because it describes how the economists re-calibrated. Note that the economists were not changing the model inputs, or saying that the forecasted inputs were wrong. The problem was that even with the right inputs, they got the wrong output…and that meant in their minds that the model should be recalibrated.
But that’s the wrong conclusion. It isn’t that a good model gave bad projections; in this case the model is a bad model. Even having the actual data – knowing that the economy had massive slack and there had been sharp declines in inflation expectations – the model completely missed the upturn in inflation that actually happened because that outcome was inconsistent with the model.
It is probably unfair of me to continue to beat on this topic, because the question has been settled. However, I suspect that many economists will continue to resist the conclusion, and will continue to rely on bad, and indeed discredited, models. And that takes the “bad model” issue one step deeper. If the production of bad predictions even given good inputs means the model is bad, then perhaps relying on bad models when better ones are available means the economist is bad?
A new paper that was presented last week at the 2017 U.S. Monetary Policy Forum has garnered, rightly, a lot of attention. The paper, entitled “Deflating Inflation Expectations: The Implications of Inflation’s Simple Dynamics,” has spawned news articles such as “Research undercuts Fed’s two favorite U.S. inflation tools”(Reuters) and “Everything the Market Thinks About Inflation Might Be Wrong,”(Wall Street Journal) the titles of which are a pretty decent summary of the impact of the article. I should note, because the WSJ didn’t, that the “five top economists” are Stephen Cecchetti, Michael Feroli, Peter Hooper, Anil Kashyap, and Kermit Schoenholtz, and the authors themselves summarize their work on the FiveThirtyEight blog here.
The main conclusion – but read the FiveThirtyEight summary to get it in their own words – is that the momentum of the inflation process is the most important variable (last year’s core inflation is the best predictor of this year’s core inflation), which is generally known, but after that they say that the exchange rate, M2 money supply growth, total nonfinancial credit growth, and U.S. financial conditions more broadly all matter more than labor market slack and inflation expectations.
Whoops! Who farted in the Fed’s elevator?
The Fed and other central banks have, for many years, relied predominantly on an understanding that inflation was caused by an economy running “too hot,” in that capacity utilization was too high and/or the unemployment rate too low. And, at least since the financial crisis, this understanding has been (like Lehman, actually) utterly bankrupt and obviously so. The chart below is a plain refutation of the notion that slack matters – although much less robust than the argument from the top economists. If slack matters, then why didn’t the greatest slack in a hundred years cause deflation in core prices? Or even get us at least close to deflation?
I’ve been talking about this for a long time. If you’ve been reading this blog for a while, you know that! Chapters 7-10 of my book “What’s Wrong With Money?: The Biggest Bubble of All” concerns the disconnect between models that work and the models the Fed (and most Wall Street economists) insist on using. In fact, the chart above is from page 91. I have talked about this at conferences and in front of clients until I am blue in the face, and have become accustomed to people in the audience staring at me like I have two heads. But the evidence is, and has long been, incontrovertible: the standard “expectations-augmented-Phillips-Curve” makes crappy predictions. And that means that it is a stupid way to manage monetary policy.
I am not alone in having this view, but until this paper came out there weren’t too many reputable people who agreed.
Now, I don’t agree with everything in this paper, and the authors acknowledge that since their analysis covers 1984-present, a period of mostly quiescent inflation, it may essentially overstate the persistence of inflation. I think that’s very likely; inflation seems to have long tails in that once it starts to rise, it tends to rise for some time. This isn’t mysterious if you use a monetary model that incorporates the feedback loop from interest rates to velocity, but the authors of this paper didn’t go that far. However, they went far enough. Hopefully, this stink bomb will at last cause some reflection in the halls of the Eccles building – reflection that has been resisted institutionally for a very long time.
 And that, my friends, is the first time I have ever used “crap” and “fart” in the same article – and hopefully the last. But my blood pressure is up, so cut me some slack.
Pension Fund Perils: Why Conventional Pairing of LDI with De-risking Glide Paths Produces Inferior Outcomes
Combined use of traditional Liability Driven Investment (LDI) and funded status responsive de-risking strategies should be decoupled or rebuilt. Embedded inconsistencies in the treatment of risks in these two elements of what has become a popular pension strategy cause irreconcilable conflicts in their execution and imperils the positive pension fund outcome.
This article provides a critique of the combined LDI / De-risking Glide Path strategy as currently implemented by many pension plan managers and also provides an example of an alternative solution that better improves pension plan outcomes.
Approaches to pension risk management have passed though many phases over the past 40+ years. Higher rate environments of the 1980s made liability immunization programs with treasuries very attractive, but traditional 60/40 or balanced fund strategies persisted as the dominant strategy for pensions. As rates began their secular decline, funding levels continued to deteriorate and while liability-driven investing became popular again in the beginning of the new millennium, significant levels of underfunding prevented most pensions from fully matching their assets and liabilities. A variety of partial risk mitigation solutions began to emerge as the lower rate environment of the past 20 years forced institutional investors to be exposed to higher levels of market risk. New asset classes were introduced into pension plan portfolios in order to achieve higher returns and higher levels of diversification. Adverse market volatility was further reduced through creative solutions that incorporated smart beta and risk allocation strategies that delivered lower-volatility at similar levels of long term return. Other strategies sold liquidity back to the market in order to generate additional return in a low yielding environment. Some risk-based approaches also introduced interest rate derivative overlay programs to extend interest rate duration of total assets along with equity risk reduction programs to reduce equity market risk. Finally, de-risking glide paths – and ultimately liability risk transfer to insurance companies – became in vogue as companies continued to struggle with their asset-liability risk and found it expedient to pay insurance companies to assume the problem for them.
In recent years, much has been written about whether pension funds have sufficient assets to support their liabilities, and clearly the source of much of this angst is that…many of them don’t. One thing that is clear is that after decades of chasing new and creative solutions, the problem of underfunded pension plans is still here and the debate about who should manage the assets, and how they should be managed, continues with ever-increasing urgency.
This article represents our contribution to this debate, with a special focus on the asset allocation requirements for cost effective pension plan de-risking.
Two Shortcomings of Traditional LDI and De-risking Strategies, as Combined
Type of risk
At this point it is important to differentiate the assets that function as liability hedges and those assets that better assist with the process of de-risking as the plan glides towards a fully hedged status. Long duration bonds function as the best hedge for the liabilities, and as the plan’s funded status improves and the de-risking process proceeds, the allocation to bonds increases. While bonds and bond-like derivatives are a core staple of liability-driven investing (LDI) strategies, for most underfunded plans that have a goal of full funding with some help from asset performance it is economically infeasible to allocate 100% of the assets to the liability-matching portfolio. A gradual increase in bond assets over time as funding status increases is part of the de-risking asset allocation process. This is an important distinction between LDI and the process of de-risking. If the liability-matching assets allow the plan to better lock in the current funded status level, then it is only the remaining assets that allow that plan to reach the next funded status threshold in order for the plan to de-risk further. Traditionally, these non-LDI assets are exposed to a significant amount of equity beta, as the long-term expected compensation from taking equity risk is positive. While it is thought to be true that, in the long term, equity beta risk is well compensated, the trouble is that in the shorter time horizon of de-risking process the equity beta is very much dependent on market valuations that are not related to the valuation of the pension liabilities. Therefore, it becomes a tactical rather than a strategic decision to hold equities for a de-risking plan.
While all pension models focus on longer-term horizons, pensions in a de-risking mode have a much lower risk tolerance in the short term. This has caused many pensions to allocate assets to a variety of alternative investments in order to diversify away from equity beta risk. However, this practice also introduces other risks to the plan, some of which are illiquidity, currency, and/or additional credit default risk. So there is an inconsistency: while pension funds are known for taking the very long view when it comes to illiquidity, if the sponsors are pursuing an LDI/de-risking strategy the additional illiquidity is counterintuitive, given the objective to be dynamic and nimble in the de-risking process.
But assuming that potential illiquidity is at least somewhat of a concern to a pension fund manager, then the Hobson’s choice between equity risk or illiquidity likely means that underfunded pension plans that are pursuing joint LDI/de-risking strategies are still carrying too much equity beta risk, or are slowing down the de-risking process while equity risk is mitigated through other less liquid investments, or both. Pension fund managers and their advisors sense this, but tend to reach a type of asset allocation compromise where pension returns may be less optimal and de-risking results are less effective.
So if equity beta isn’t desirable as unrelated to the liability, and illiquidity of many other alternatives make them less-desirable for dynamic rebalancing into LDI assets, what is the most effective way to replace the equity beta for a de-risking plan? What other forms of beta and/or alpha are appropriate in aiding in the process of de-risking? From the standpoint of Markowitz efficient frontier generation, risk is a function of return variance and the covariance of the returns of the eligible portfolio elements. Beyond that, to the optimization routine risk is risk. That is, it doesn’t matter whether the risk comes from beta or from alpha. From the standpoint of the de-risking process, when it comes to the non-LDI assets or return generating assets, alpha is preferred to most beta since alpha is more process-dependent as opposed to market-dependent. In the shorter-term horizon of de-risking, non-LDI beta introduces more risk. So our only choice seems to be some combination of liquid alpha and/or well compensated liquid beta that has some correlation to liabilities. This particular beta may be different from how the liability matching or LDI assets are invested and doesn’t need to match the performance of the liabilities, but should have a positive correlation with liability performance. That’s a tall order.
Some of the more publicized alpha alternatives are hedge funds, private investments in equity or debt of corporations, or real estate. We don’t intend to dive into the merits and disadvantages of these or other alternative investments on a stand-alone basis but will only superficially observe their fit in a de-risking framework. Many hedge funds return as much beta as alpha – indeed, the fact that there are successful hedge-fund replication techniques is virtual proof that many hedge funds are actually beta masquerading as alpha. The obvious visual correlation between hedge fund returns and equity returns, too, should make one suspicious that hedge funds are a pure source of alpha (see Chart, source Bloomberg, comparing the HFRI Fund of Funds Composite Index to the S&P 500).
While those hedge funds or private investments that have a higher correlation to fixed income beta may benefit plans with a long time horizon, they suffer from varying degrees of illiquidity, which impedes the de-rising process as previously discussed.
While there may be other examples for a better alternative, we can provide one strategic example that better fits the combined LDI / de-risking criteria we have discussed in this article.
The Better Alternative
We have addressed above the type of risk that pension funds do not want to have. But it behooves us as well to point out one type of risk that pension funds really ought to have, and yet tend to be underinvested in: inflation exposure, or more accurately real interest rates.
There is a competent literature about the importance of inflation-linked assets to the pension plan. Importantly, inflation-linked assets are relevant even if the pension benefits are not themselves inflation-linked, since for most pension plans the formula which links the work history of active participants to their future retirement benefits implicitly means that pension benefit accruals for a particular employee are higher the more that employee earns. Since wages generally rise at least partly because of inflation, this implies that any pension fund with active participants still accruing benefits does in fact have some inflation exposure.
But the importance of inflation to the pension plan goes beyond that liability-side insight. Additionally, pension assets are exposed to inflation – and, especially, large changes in inflation – because on the asset side the majority of the assets of most plans are invested in equities and nominal fixed-income. Both of these asset classes are terribly exposed to increases in inflation, especially when inflation rises above 3-4%.
We can go still further. While the effects just mentioned are well-established in the literature, one additional benefit from owning inflation-linked assets has not been discussed as far as we can tell, and that is this: the relative value of inflation-linked bonds, compared to nominal bonds, is related to the business cycle and/or level of interest rates level in the same way that corporate spreads are – but without default risk. The chart below (source: Bloomberg data) highlights the connection between credit spreads and 10-year breakevens. This is important because for most pension funds, the relevant interest rate for discounting liabilities is not the risk-free Treasury rate, but a risky corporate rate; therefore, the liability has credit spread risk and an asset that co-moves with credit spreads – especially without actually having credit risk – is valuable.
In our opinion, given a choice between equity beta and inflation/real rate beta, there is no choice: inflation-linked assets are clearly the more valuable risk for a pension fund to own.
Now, pension plans that are pursuing de-risking along with LDI are typically loathe to replace equity risk, given its advantage (over a full cycle, although not necessarily at any given point) in expected return, with real interest rate risk. But inflation-linked markets have an additional benefit, at least in 2017 – they are inefficient, and produce myriad opportunities to generate alpha along with their useful beta. Indeed, we have designed an investment strategy that addresses all of these requirements:
- Historical return commensurate with equity returns, with slightly lower total risk
- Beta from inflation-linked bond markets, which is relevant to pension fund liabilities
- Risk sourced from useful beta, as well as alpha
- Implied credit spread exposure, without actual credit risks, which is relevant to pension fund liabilities
- Superior liquidity to “alts” such as real estate, private equity, or hedge funds – which is more consistent with the de-risking mandate
We call this strategy “Enhanced Systematic Real Return.” In a nutshell, this strategy holds the combination of inflation-linked bonds and breakevens that most efficiently adds inflation protection for a given level of interest rates, and adjusts these proportions based on the richness or cheapness of inflation-linked bonds to capture additional alpha.
Magnitude of risk
After determining a different, if not more efficient risk vehicle for the non-LDI assets we now turn to the discussion of how much of this risk should be taken at every point of the glide path. Should the risk allocation to return generating risk assets (i.e non-LDI assets) only depend on the dollars allocated to these investments or should the risk allocation be independent of dollars allocated and vary based on the level of leverage and/or asset composition?
Not All Risk is Bad
As we have already alluded, prudent risk has some place in the management of a pension fund on a glide path. Yet, as with the villain in the black hat, we have been conditioned to look at the word “risk” and recoil. But not all risk is bad. Certainly, with LDI approaches risk is a negative – after all, the goal of LDI is to maximize the funded status (difference between assets and liabilities), subject to a limit on the maximum volatility (risk) of the funded status. In that construction, there is no doubt that risk is bad, or anyway that less risk is better. But risk is not necessarily bad for de-risking.
This seems counter-intuitive. If we are trying to remove risk, doesn’t that imply that risk is bad? Yes – as we just said, risk is bad for the LDI-driven mandate. But the plan that takes less risk has fewer opportunities to reach de-risking thresholds. That is, the more that you de-risk the longer the next increment of de-risking takes. In this context, it is actually helpful to retain more rather than less risk in the non-LDI assets at each de-risking step.
Here is an analogy from basketball: consider the player who constantly heaves up three-point shots. He shoots a lower percentage from beyond the arc, and so the variance of his scoring is quite a bit higher than his variance shooting short jumpers or layups. Let us suppose that on average, he scores the same amount per game whether he shoots three-pointers or short jumpers. In an asset management context, we would say that this is a “non-optimized” shooter. He should aim for the same average scoring with lower volatility, right?
Now let us suppose that in a particular game, this player’s team is down by 18 points in the final quarter. The coach sends the player onto the court. If this coach is from the pension industry, he instructs his shooter to take only safe shots, because that is how he maximizes his Sharpe Ratio. But if this is actually a basketball coach, he orders his player to take as many three-pointers as he can. Why? He does this because in this situation, risk is good. A strategy of only taking safe shots is guaranteed to lose in this context; only a highly-volatile strategy has a chance of working.
In the same way, prudent addition of volatility as the plan is de-risking helps to de-risk a plan that is under water. So we can see that there is a tension here, and one that is routinely ignored in most LDI/de-risking plans: more volatility is helpful for de-risking, but hurtful inasmuch as it departs from the LDI mandate to maximize the return/risk tradeoff for the funded status. This leads to the phenomenon that is common today, of “hurry up and wait.” As we noted previously: the more that a fund has been de-risked, the longer the next increment of de-risking takes. Each reduction of the proportion of return generating assets to total assets significantly increases the average time until the next de-risking point is reached, as the table below, illustrates:
This is problematic. By de-risking, this plan is becoming too conservative as it approaches being fully funded. We can show that the plan reaches a fully-funded status more quickly when it prudently avoids full de-risking. What happens when we allow leverage, and maintain the total portfolio risk even as the bond allocation increases at each trigger? The following table shows the significant result:
Combining the Right Type, and the Right Magnitude, of Risk
When the pension plan pursues a strategy that focuses on risks sourced from alpha and the “right kinds” of beta sources that will tend to match the liability, and de-risks in a way that recognizes that some risk helps the de-risking task, then the combined result can be powerful. The chart below (Source: Enduring Intellectual Properties, Inc) compares this new approach with the “classic” LDI plus de-risking approach. The dashed lines represent the “classic” approach, while the solid lines represent an approach that uses our “Enhanced Systematic Real Return” strategy as a substitute for the equity risk of the traditional strategy. In each case, this imaginary pension fund starts year zero at 60% funded, and liabilities grow with the Bloomberg/Barclays/Lehman U.S. Long Government/Credit Index. Also in each case, the top line represents the 90th percentile outcome of the Monte Carlo simulation; the bottom line represents the 10th percentile, and the middle line represents the median outcome.
There are several facets of this chart worth noting.
Importantly, observe how the median outcome line is linear with our approach, but flattens out with the traditional de-risking approach. This phenomenon is the visual counterpart to Tables 1 and 2; it illustrates how the closer one gets to being fully funded with a traditional glide path, the slower the funded status converges. Our approach, as highlighted in Table 2, is designed to remove that effect. The benefits of that approach aren’t only felt on the median outcome, but are apparent on every path as the funded status moves above 75%.
Also, observe that the superior “good” outcomes aren’t “paid for” by much worse “bad” outcomes. After all, we could have had even better “good” outcomes if we took lots of extra risk. But in that case, the benefit would have come at a price, and we would see it manifesting in much worse “bad” outcomes. The outcomes here are actually skewed to the positive side.
Finally, although you cannot tell this from the illustration, you should know that this simulation assumes that stocks and bonds have expected returns that are somewhere near their historical mean returns. Unfortunately, presently this seems a generous assumption for the traditional approach. It seems more likely that, going forward, pension plans which are invested heavily in equities will be drawing from a distribution with worse-than-average characteristics due to the high starting valuations. Ditto, of course, for fixed-income…but at least bonds affect both sides of the LDI equation.
LDI and de-risking glide paths can be combined under certain conditions, but current implementation practices create inconsistencies in how risks are treated and do not facilitate achievement of strategic goals.
Asset beta risks that do not match liability beta risks are useful only in a tactical setting, and then only if they are associated with exceptional returns (that is, the market is cheap tactically).
More effort is required to search out new sources of liquid alpha and beta that facilitate the de-risking process. We have produced one that we believe is useful in this context.
As the plan de-risks along the glide path, the level of risk in the non-LDI assets should be adjusted to preserve a quantum of variance that is useful in the de-risking process, as opposed to just mechanically adjusting allocation dollars in a simple glide path.
 Milla Krasnopolsky is an investment strategist and investment manager. Milla held previous positions as a Managing Director of Fixed Income Markets and Strategic Solutions at General Motors Asset Management and as a Principal and Senior Investment Consultant at Mercer Investments. Michael Ashton is the Managing Principal of Enduring Investments and CEO of Enduring Intellectual Properties, Inc.
 For the iconic example, see Siegel and Waring, “TIPS, the Dual Duration, and the Pension Plan” (Financial Analysts Journal, September/October 2004).
 Remarkably, the myth that common stocks confer some inflation protection has survived decades of contrary experience, both before and after Zvi Bodie’s classic “Common Stocks as a Hedge Against Inflation” (Journal of Finance, Vol. 31, No. 2, May 1976), in which he concluded forcefully “The regression results…leads to the surprising and somewhat disturbing conclusion that to use common stocks as a hedge against inflation one must sell them short.”
 The 10-year simple “breakeven” is merely the yield difference between the 10-year nominal Treasury yield and the 10-year TIPS real yield; it represents roughly the amount of future inflation at which an investor would be indifferent between the two types of bonds.
 It would be inappropriate to discuss the fine details of this strategy in a thought piece such as this. However, we thought it important to point out that demand for a solution with these characteristics is not hopeless or uninformed. There does exist at least one such solution, and probably others!
 This idea isn’t exactly alien in finance: if you own an out-of-the-money option, a higher implied volatility increases your delta while if you own an in-the-money option, a higher implied volatility decreases your delta. It’s just alien in pension fund management.
 Both Table 1 and Table 2 represent simplified examples where LDI hedging assets and pension liabilities are proxied by the same long-duration bonds, and future pension contributions are excluded from the analysis.
 Table is based on a Monte Carlo simulation of a pension fund that begins with the indicated funding status and allocated as shown until it reaches the next de-risking trigger. Returns for stocks and bonds are simulated; the correlation from the last five years is used. The importance of the table isn’t derived from the precision of the assumptions, but from the illustration of the increased difficulty in reaching the next de-risking increment when the fund is already de-risked substantially.
One of the problems that inflation folks have is that the historical data series for many of the assets we use in our craft are fairly short, low-quality, or difficult to obtain. Anything in real estate is difficult: farmland, timber, commercial real estate. Even many commodities futures only go back to the early 1980s. But the really frustrating absence is the lack of a good history of real interest rates (interest rates on inflation-linked bonds). The UK has had inflation-linked bonds since the early 1980s, but the US didn’t launch TIPS until 1997 and most other issuers of ILBs started well after that.
This isn’t just a problem for asset-allocation studies, although it is that. The lack of a good history of real interest rates is problematic to economists and financial theoreticians as well. These practitioners have been forced to use sub-optimal “solutions” instead. One popular method of creating a past history of “real interest rates” is to use a nominal interest rate and adjust it by current inflation. This is obvious nonsense. A 10-year nominal interest rate consists of 10-year real interest rates and 10-year forward inflation expectations. The assumption – usually explicit in studies of this kind – is that “investors assume the next ten years of inflation will be the same as the most-recent year’s inflation.”
We now have plenty of data to prove that isn’t how expectations work – and, not to mention, a complete curve of real interest rates given by TIPS yields – but it is still a popular way for lazy economists to talk about real rates. Here is what the historical record looks like if you take 10-year Treasury rates and deflate them by trailing 1-year inflation:
This is ridiculously implausible volatility for 10-year real rates, and a range that is unreasonable. Sure, nominal rates were very high in the early 1980s, but 10%? And can it be that real rates – the cost of 10-year money, adjusted for forward inflation expectations – were -4.6% in 1980 and +9.6% in 1984? This hypothetical history is clearly so unlikely as to be useless.
In 2000, Jay Shanken and S.P. Kothari wrote a paper called “Asset Allocation with Conventional and Indexed Bonds.” To make this paper possible, they had to back-fill returns from hypothetical inflation-linked bonds. Their method was better than the method mentioned above, but still produced an unreasonably volatile stream. The chart below shows a series, in red, that is derived from their series of hypothetical annual real returns on 5-year inflation-indexed bonds, and backing into the real yields implied by those returns. I have narrowed the historical range to focus better on the range of dates in the Shanken/Kothari paper.
You can see the volatility of the real yield series is much more reasonable, but still produces a very high spike in the early 1980s.
The key to deriving a smarter real yield series lies in this spike in the early 1980s. We need to understand that what drives very high nominal yields, such as we had at that time in the world, is not real yields. Since the real yield is essentially the real cost of money it should not ever be much higher than real potential economic growth. Very high nominal yields are, rather, driven by high inflation expectations. If we look at the UK experience, we can see from bona fide inflation-linked bonds that in the early 1980s real yields were not 10%, but actually under 5% despite those very high nominal yields. Conversely, very low interest rates tend to be caused by very pessimistic real growth outcomes, while inflation expectations behave as if there is some kind of floor.
We at Enduring Investments developed some time ago a model that describes realistically how real yields evolve given nominal yields. We discovered that this model fits not only the UK experience, but every developed country that has inflation-linked bonds. Moreover, it accurately predicted how real yields would behave when nominal yields fell below 2% as they did in 2012…even though yields like that were entirely out-of-sample when we developed the model. I can’t describe the model in great detail because the method is proprietary and is used in some of our investment approaches. But here is a chart of the Enduring Investments real yield series, with the “classic” series in blue and the “Shanken/Kothari” series in red:
This series has a much more reasonable relationship to the interest rate cycle and to nominal interest rates specifically. Incidentally, when I sat down to write this article I hadn’t ever looked at our series calculated that far back before, and hadn’t noticed that it actually fits a sine curve very well. Here is the same series, with a sine wave overlaid. (The wave has a frequency of 38 years and an amplitude of 2.9% – I mention this for the cycle theorists.)
This briefly excited me, but I stress briefly. It’s interesting but merely coincidental. When we extend this back to 1871 (using Shiller data) there is still a cycle but the amplitude is different.
So what is the implication of this chart? There is nothing predictive here; about all that we can (reasonably) say is what we already knew: real yields are not just low, but historically low. (Current 10-year TIPS yields are higher than our model expects them to be, but not by as much as they were earlier this year thanks to a furious rally in breakevens.) Money is historically cheap – again, we knew this – in a way it hasn’t been since the War effort when nominal interest rates were fixed by the Fed even though wartime inflation caused expectations to rise. With real yields that low, how did the war effort get funded? Who in the world lent money at negative real interest rates like banks awash in cash do today?
On Friday, I was on Bloomberg TV’s “What’d You Miss?” program to talk about the PCE inflation report from Friday morning. You can see most of the interview here.
I like the segment – Scarlet Fu, Oliver Renick, and Julie Hyman asked good questions – but we had to compress a fairly technical discussion into only 5 or 6 minutes. As a result, the segment might be a little “wonky” for some people, and I thought it might be helpful to present and expand the discussion here.
The PCE report itself was not surprising. Core PCE came in as-expected, at 1.7%. This is rising, but remains below the Fed’s 2% target for that index. I think it is interesting to look at how PCE differs from CPI to see why PCE remains below 2%. After all, core PCE is the only inflation index that is still below 2% (see chart, source Bloomberg). And, as we will see, this raises other questions about whether PCE is a reasonable target for Fed policy.
There are several differences between CPI and PCE, but the main reasons they differ can be summarized simply: the CPI measures what the consumer buys, out-of-pocket; the PCE measures not only household expenditures but also spending on behalf of consumers, including such things as employer-purchased insurance and some important government expenditures. As pointed out by the BEA on this helpful page, “the CPI is based on a survey of what households are buying; the PCE is based on surveys of what businesses are selling.”
This leads to two major types of differences: weight effects and scope effects.
Weight effects occur because the PCE is a broader index covering more economic activity. Consider housing, which is one of the more steady components of CPI. Primary rents and owners’-equivalent rent constitute together some 32% of the CPI and those two components have been rising at a blended rate of about 3.4% recently. However, the weight of rent-of-shelter in PCE is only 15.5%. This difference accounts for roughly half of the difference between core CPI and core PCE, and is persistent at the moment because of the strength in housing inflation.
However, more intriguing are the “scope” differences. These arise because certain products and services aren’t only bought in different quantities compared to what businesses sell (like in the case of housing), but because the two surveys include and exclude different items in the same categories. So, certain items are said to be “in scope” for CPI but “out of scope” for PCE, and vice-versa. One of the places this is most important is in the category of health care.
Most medical care is not paid for out-of-pocket by the consumer, and therefore is excluded from the CPI. For most people, medical care is paid for by insurance, which insurance is usually at least partly paid for by their employer. Also, the Federal government through Medicare and Medicaid provides a large quantity of medical care goods and services that are different from what consumers buy directly – at least, purchased at different prices than those available to consumers!).
This scope difference is enormously important, and over time accounts for much of the systematic difference between core CPI and core PCE. The chart below (source: BEA, BLS) illustrates that Health Care inflation in the PCE essentially always is lower than Medical Care inflation in the CPI.
Moreover, thanks in part to Obamacare the divergence between the medical care that the government buys and the medical care consumers buy directly has been widening. The following chart shows the spread between the two lines above:
It is important to realize that this is not coincidental, but likely causal. It is because Medicare and other ACA control structures are restraining prices in certain areas (and paid by certain parties) that prices to the consumer are rising more rapidly. Thus, while all of these inflation measures are likely to continue higher, the spread between core CPI and core PCE is probably going to stay wider than normal for a while.
Now we get to the most interesting question of all. Why do we care about PCE in the first place? We care because the Fed uses core PCE as a policy target, rather than the CPI (despite the fact that it has ways to measure market CPI expectations, but no way to measure PCE expectations). They do so because the PCE covers a wider swath of the economy. To the Fed, this means the PCE is more useful as a broader measure.
But hang on! The extra parts that PCE covers are, substantially, in parts of the economy which are not competitive. Medicare-bought prices are determined, at least in the medium-term, by government fiat. The free market does not operate where the government treads in this way. The more-poignant implication is that there is no reason to suspect that these prices would respond to monetary policy! Ergo, it seems crazy to focus on PCE, rather than CPI (or one of the many more-useful flavors of CPI), when setting monetary policy. This is one case where I think the Fed isn’t being malicious; they’re just not being thoughtful enough.
Every “core” inflation indicator, including the ones above (and you can throw in wages and the Employment Cost Index as well!), is at or above the Fed’s target even accounting for the typical spread between the CPI and PCE. Not only that, they are above the target and rising. The Fed is most definitely “behind the curve.” Now, as I have noted before in this space I don’t think there’s anything the Fed can do about it, as raising rates without restraining reserves will only serve to accelerate inflation further since it will not entail a slowing of money supply growth. But it seems to me that, for starters, monetary policymakers should focus on indices that are at least in principle (and in normal times) more responsive to monetary policy!
Recently I’ve been thinking a lot about what might happen in the event of a banking crisis redux. While I’m not very concerned about US banks these days, there is a ‘developing situation’ in China that could well eventually lead to crisis (although the state might prevent outright collapses), and of course ongoing gnashing of teeth over Deutsche Bank’s capital situation if it is fined as heavily as some have suggested they will be.
I am not yet really worried about the banking side of things. But there are plenty of sovereign issuers who are clearly heading down unsustainable paths (not least of these is the US, especially if either of the leading Presidential candidates really implements the high-cost programs they are declaring they will), and when sovereigns tremble it is often banks that bear the direct brunt. After all, you can’t form a line outside of the sovereign to withdraw your money.
But, in a spirit of looking forward to anticipate potential crises, let us pretend we are confronting another banking crisis. The question I often hear next is, “how deflationary would it be to have another crisis when inflation is already low?”
Unpeeling the onion, there are several reasons this doesn’t concern me much. First, inflation is stable or rising in most developed nations. Yes, headline inflation is still sagging due to energy prices, but median inflation is 2.6% in the US and core inflation is 0.8% in Europe and 1.3% in the UK. To be sure, all of those are lower than they were in mid-2008. But remember that in 2009 and 2010, median (or core) inflation never got below 0.5% in the US, 0.8% in Europe, and 2.7% in the UK. Japan of course experienced deflation, but that wasn’t the fault of the crisis – as I’ve pointed out before, Japan has been in long-running deflation due to the BOJ’s inability or unwillingness to grow the money supply.
So, if the worst crisis in 100 years didn’t take core inflation negative – a major, major failure of Keynesian predictions – then I’m not aflutter about it happening this time. Heck, in 2009 and 2010 core inflation wouldn’t even have been as low as it was, had the cause of the crisis not been the bursting of the housing bubble. The chart below (source: Bloomberg) shows the Atlanta Fed’s “sticky” CPI (another way to measure the underlying inflation trend) ex-shelter. Note that in 2010, the low in this measure was about 1.25%…it was actually lower in 2014 and 2015.
But we can go further than that. One reason that inflation decelerated in 2009 and 2010 was because money velocity dropped sharply. As I’ve shown before, and argued in my book, the decline in money velocity was not particularly unusual given the decline in interest rates. That is, if you had known what was going to happen to interest rates, you would have had a very good forecast of money velocity and, hence, core inflation.
Back in 2008, I never dreamed that interest rates would go so low, or stay so low for so long. Few of us did! But the outcome, in the event, was consistent with the monetarist model while being completely inconsistent with the Keynesian model. And here’s the point, when thinking about the next crisis: interest rates are already at incredibly low levels, lower even than the 36-year downtrend channel would have them (see chart, source Bloomberg).
With the wisdom of experience, I would never be so cavalier as to say that interest rates cannot go lower from here! But in 2008, 10-year rates were around 3.80% and they’re 1.60% now (in the US, and lower elsewhere). Real rates were around 2% at the 10-year point; they are at 0% now. It is difficult to imagine how rates can have another dramatic move as they did in 2008-09.
It is important to understand, that is, just why inflation tends to fall in recessions. It is not, as the Keynesians would have it, that a growing “output gap” reduces the pressure on resources and relieves price increases. It is because slack demand for credit causes interest rates to decline, which leads to lower money velocity and hence, lower inflation. If the central bank responds in a timely manner to increase money supply growth by increasing reserves, then inflation doesn’t fall very far. In the last crisis, the Fed and other central banks added enough liquidity to ramp up M2 growth, and that kept the decline in money velocity from causing outright deflation (then, they kept adding reserves for a few more years, which led to the situation we are in now – too many reserves in the system, so that central banks no longer control the marginal dollar that goes into the money supply).
So, in the next crisis I expect central banks will add still more reserves to the pile of excess reserves, which will be meaningless but will make them feel better. Interest rates will decline, but not by as much as they did in the last crisis, and money velocity will fall. So, in a real serious crisis, inflation will decline – however, it will not decline very much.
That is the world we are now living in: higher highs to inflation on each subsequent peak, and higher lows in each subsequent trough. The vicious cycle counterpart to the virtuous cycle we have enjoyed for 35 years. This is true, I think, whether or not we get a crisis or just a garden-variety recession.
I should be clear that I think that such a crisis would be horrible for growth. That is, our current weak growth in global GDP would turn negative again, and possibly even more painful. And times would be truly bad in the stock market. But inflation will not follow, just as it didn’t follow in 2009-2010, and turn into deflation.