Archive for the ‘Good One’ Category

Seasonal Adjustment and Springtime Inflation

April 14, 2014 1 comment

On Tuesday, the Bureau of Labor Statistics will report the CPI index (along with endless other data) for March. Currently, the consensus estimate calls for +0.1%, and +0.1% ex-food-and-energy. This release will generate the usual irritation among conspiracy theorists who believe the government is monkeying with the inflation numbers for their own nefarious ends. I have previously explained why it is that inflation tends to feel faster than it actually is, and I have regularly debunked the claim by certain conspiracy-minded individuals that inflation has been running about 5% faster than the “official” mark since the early 1980s.[1] However, today I want to point out another reason that right now we will have a tendency to recognize that inflation is not rising at 0.1% per month, and that involves the issue of seasonal adjustment.

The point of seasonal adjustment is to remove regular, cyclical influences so that we can see if the underlying trend is doing anything interesting. Consider temperature. Is it particularly helpful for you as a meteorologist to know that the average temperature in April has been higher than the average temperature in January? Of course not, because we know that April is always warmer than January. Hence, with temperature we ask whether April was warmer than a typical April.

Closer to the point, consider gasoline. The national average gasoline price has risen in 61 of the last 66 days, as the chart below (Source: Bloomberg) illustrates.


Yes, if you’re noticing that gasoline prices have been rising you are not alone, and it is not an illusion! But should we worry about this rapid acceleration in gasoline? Does this necessarily presage spiraling inflation? Bloomberg offers an easy way to look at the seasonality question (we formerly had to do this by hand). The following chart shows the change in gasoline prices (in cents) since December 31st for each of the last four years, for the 5-year average (the heavy, yellow line) and for this year (the white line).


You can see that the rise from late January into April is not only normal, but the scale of the increase is just about the same this year as for the prior four years – what was unusual was that prices didn’t start rising until February.

Now, this particular seasonal pattern is important to inflation-watchers and TIPS traders because the volatility of gasoline prices is an important part of volatility in the overall price dynamic. In fact, it is important enough that if I take the average line from the gasoline chart above and overlay it with the official CPI seasonal adjustment factors from the BLS, you can see the ghost of the former in the latter (see chart, source Enduring Investments).


Now, the seasonal adjustment factors for the CPI as a whole are less dramatic (closer to 1, in the chart above, if you look at the right-hand scale compared to the left-hand scale) than are the factors for gasoline, but that makes sense since gasoline is only a small part – albeit a really important part – of the consumption basket of the average consumer. And the BLS methodology is a lot more sophisticated than the simple average-of-the-last-x-years approach I have taken here. But this should be good enough for you to grasp the intuition.

What this means is that when the BLS reports tomorrow that gasoline prices didn’t add anything to overall inflation in March, you should recognize that that does not mean that gasoline prices didn’t rise in March. It means that they didn’t rise significantly more or less than the average factor the BLS is assuming. Most of all, it doesn’t mean that the BLS is monkeying with the data to make it seem lower. The product of the seasonal adjustment factors is (approximately) 1.0, which means that what the BLS takes away in the springtime, to report inflation numbers lower than would be anticipated given a raw sampling of store prices, they will give back in the late fall and winter, and report inflation numbers higher than would be anticipated given a cursory glance of store shelves. What is left, hopefully, is a more-unbiased view of what is happening with the price level generally.

Where you can see this effect most clearly is in the difference between the seasonally-adjusted number that is reported and the rise in the NSA figure that is used to adjust inflation-indexed bonds like TIPS. While the consensus calls for a +0.1% rise in headline CPI, the forecasts expect the NSA CPI (the price level) to rise from 234.781 to 236.017, which is a rise of +0.5%. So yes – if it feels like inflation is suddenly rising at a 6% annualized pace, that is because it is. But fear not, because that will slow down later in the year. Probably.


[1] The summary of that argument: we know that wages have increased roughly 142% since the early 1980s – average hourly earnings was $8.45 in April 1984 and is $20.47 now, and this “feels about right” to most people. Against this, the CPI has risen 128%, meaning that our standard of living “should” have improved a little bit since then, but not much (although any individual may be doing somewhat better or worse). But if prices instead of rising at 2.8%/year had risen at 7.8%/year, prices in aggregate would have risen 851% versus a 142% increase in wages, and we would all be living in absolute squalor compared to our parents. This is offensively and obviously wrong.

Categories: CPI, Good One, Theory Tags: , ,

What Do You Care What Other People Think?

February 18, 2014 3 comments

In reflecting, over this weekend, about the markets of the last week, I wonder if we haven’t seen a subtle – and subtly disturbing – shift in the markets’ behavior.

Before the Fed began the taper, and even after the Fed began the taper but before we were really sure they intended to maintain it through at least mild economic wiggles, bad news was treated as good news in the markets (both stocks and bonds) because it implied more QE, or a longer QE, or a slower taper. This was lamentable because it suggested that the Fed was more important than global market fundamentals, but understandable at some level. All other forces summed to just about zero, so one big institution with a very big hammer was able to make the market vibrate the way policymakers wanted it to. So, while lamentable, this behavior was at least understandable.

But recently, as the Fed has started ever-so-slowly receding to the back pages, we have started to see behavior that is less unusual, but still not “normal.” Over the last couple of weeks, despite manifestly weak data – from the Employment report to Thursday’s surprisingly weak Retail Sales data and Friday’s weak Industrial Production data (which would have been even weaker if it hadn’t been for the utilities sector humming away) – the stock market has continued a marked rally. However, this is something we’ve seen before: a rally not because weak data would precipitate bullish policy, but because the weak data had a ready excuse in poor winter weather. In this sort of environment, good news is really good news, and bad news can be discounted (even if the cause to do so is sketchy).

There also is some “kitchen sinking” going on even among economists. “Kitchen sinking” refers to when a company takes advantage of a bad quarter to write off all sorts of expenses, all attributed to the “one time event” whether due to it in fact or not. This makes it far easier to score great earnings in the future. It’s understandable (if of questionable legality) in corporate accounting, but when economists do it then we should look askance. Without my naming names: on Friday one well-known macroeconomic advisor told clients that cold weather in November, December, and January will lower Q1 GDP by 0.4%. I am not sure how November’s weather would lower GDP in Q1…in fact, it seems to me that by lowering Q4 GDP, bad weather in December would tend to increase GDP in Q1 because it would be building from a lower base. Whatever the reason for the forecast, though, it certainly lowers the bar for the actual Q1 GDP report and increases the odds of a stock market-bullish surprise (although that’s way out in April).

Much more than the former mode of taking weak data as good because it implied more liquidity from the Fed, this sort of thing – kitchen sinking by economists, and markets taking all news as either neutral or good – is a signature of unhealthy bullishness. The concern is that when the reasons to ignore bad news have passed, the market will not be priced at a level that can sustain actual bad news. And, unlike the QE-baiting, it is something we have seen before. It is a weaker signature, and it’s entirely emotional rather than the twisted but at least debatable reasoning that investors employed when bad news was Fed-good.

It seems almost unfair to continue to list anecdotal signs of frothy behavior, because it’s so easy to do so these days. One that sprang into view last week was the incredibly vitriolic response to the chart that has been making the rounds showing the parallel in equity market action between 1928-29 and 2012-14. For example, here was one objection, which was perhaps a reasonable objection … but note the tone. And this was just one example among many.

Come on, is it really so horrible, such a threat to civilization, to have someone trot out this chart? I will take either side of the argument with no acrimony. Personally, I don’t think it’s almost ever useful to think of the past as an exact roadmap (although if I ignored this chart, and the market did crash, I hate to think of how I would explain that insouciance to my clients after-the-fact), but I also don’t care if someone else does do so. Especially if it leads them to the right conclusion, and I happen to think that if investors start being cautious right now it is the right result, whether it happens because they were scared of a spooky chart or because they understand market valuation metrics.

But again: who cares? This is not a fact which is right or wrong – unlike, say, the claim that the government made a change to the CPI in the early 1980s which subtracts 5% from CPI every year. That is a verifiable statement, and it is demonstrably false. But saying “chart A looks like chart B” can’t possibly be wrong…it’s opinion! My concern isn’t about the chart; it is about the vehemence with which some people are attacking that opinion.

It is like I tell my daughter when someone calls her a dunderhead, or whatever the 7-year-old equivalent is these days. I ask “well, are you a dunderhead?” If the answer is yes, then you have bigger problems than what they’re calling you. If the answer is no, then as Feynman said what do you care what other people think? Similarly, if you’re bullish, what do you care if someone runs that chart? If it’s right, then you have bigger problems than the fact they’re running the chart. And if it’s wrong, then what do you care what they think?

The Marie Antoinette Rule

February 11, 2014 5 comments

The biggest surprise of the day on Tuesday did not come from new Fed Chairman Janet Yellen, nor from the fact that she didn’t offer dovish surprises. Many observers had expected that after a mildly weak recent equity market and slightly soft Employment data, Yellen (who has historically been, admittedly, quite a dove) would hold out the chance that the “taper” may be delayed. But actually, she seemed to suggest that nothing has changed about the plan to incrementally taper Fed purchases of Treasuries and mortgages. I had thought that would be the likely outcome, and said so yesterday when I supposed “she will be reluctant to be a dove right out of the gate.”

The surprise came in the market reaction. Since there had been no other major (equity) bullish influences over the last week, I assumed that the stock market rally had been predicated on the presumption that Yellen would give some solace to the bulls. When she did not, I thought stocks would have difficulty – and on that, I was utterly wrong. Now, whether that means the market thinks Yellen is lying, or whether there is some other reason stocks are rallying, or whether they are rallying for no reason whatsoever, I haven’t a clue.

I do know though that the DJ-UBS commodity index reached its highest closing level in five months, and that commodities are still comfortably ahead of stocks in 2014 even with this latest equity rally. This rally has been driven by energy and livestock, with some precious metals improvements thrown in. So, lest we be tempted to say that the rally in commodities is confirming some underlying economic strength, reflect that industrial metals remain near 5-year lows (see chart, source Bloomberg, of the DJUBS Industrial Metals Subindex).


One of the reasons I write these articles is to get feedback from readers, who forward me all sorts of articles and observations related to inflation. Even though I have access to many of these same sources, I don’t always see every article, so it’s helpful to get a heads up this way. A case in point is the article that was on Business Insider yesterday, detailing another quirky inflation-related report from Goldman Sachs.

Now, I really like much of what Jan Hatzius does, but on inflation the economics team at Goldman is basically adrift. It may be that the author of this article doesn’t have the correct story, but if he does then here is the basic argument from Goldman: the Fed shouldn’t target inflation or employment, but rather on wage growth, because wage growth is a better measure of the “employment gap” and will tie unemployment and inflation together better.

The reason the economists need to make this argument is because “price inflation is not very responsive to the employment gap at low levels of inflation,” which is a point I have made often and most recently in my December “re-blog” series.

But, as has happened so often with Goldman’s economists when it comes to inflation, they take a perfectly reasonable observation and draw a nonsensical conclusion from it. The obvious conclusion, given the absolute failure of the “employment gap” to forecast core price inflation over the last five years, is that the employment gap and price inflation are not particularly related. The experimental evidence of that period makes the argument that they are – which is a perversion of Phillips’ original argument, which related wages and unemployment – extremely difficult to support. Hatzius et. al. clearly now recognize this, but they draw the wrong conclusion.

There is no need to tie unemployment and inflation together …unless you are a member of the bow-tied set, and really need to calibrate parameters for the Taylor Rule. So it isn’t at all a concern that they aren’t, unless you really want your employment gap models to spit out useful forecasts. Okay, so if you can’t forecast prices, then use the same models and call it a wage forecast!

But the absurdity goes a bit farther. By suggesting that the Fed set policy on the basis of wage inflation, these economists are proposing a truly abhorrent policy of raising interest rates simply because people are making more money. Wage inflation is a good thing; end product price inflation is a bad thing. Under the Goldman rule, if wages were rising smartly but price inflation was subdued, then the Fed should tighten. But why tighten just because real wages are increasing at a solid pace? That is, after all, one of society’s goals! If the real wage increase came about because of an increase in productivity, or because of a decrease in labor supply, then it does not call for a tightening of monetary policy. In such cases, it is eminently reasonable that laborers take home a larger share of the real gains from manufacture and trade.

On the other hand, if low nominal wage growth was coupled with high price inflation, the Goldman rule would call for an easing of monetary policy…even though that would tend to increase price inflation while doing nothing for wages. In short, the Goldman rule should probably be called the Marie Antoinette rule. It will tend to beat down wage earners.

Whether or not the Goldman rule is an improvement over the Taylor Rule is not necessarily the right question either, because the Taylor Rule is not the right policy rule to begin with. Returning to the prior point: the employment gap has not demonstrated any useful predictive ability regarding inflation. Moreover, monetary policy has demonstrated almost no ability to make any impact on the unemployment rate. The correct conclusion here is a policy rule should not have an employment gap term. The Federal Reserve should be driven by prospective changes in the aggregate price level, which are in turn driven in the long run almost entirely by changes in the supply of money. So it isn’t surprising that the Goldman rule can improve on the Taylor rule – there are a huge number of rules that would do so.

Do Floating-Rate Notes (FRNs) Protect Against Inflation?

February 1, 2014 Leave a comment

Since the Treasury this week auctioned floating-rate notes (FRNs) for the first time, it seems that it is probably the right time for a brief discussion of whether FRNs protect against inflation.

The short answer is that FRNs protect against inflation slightly more than fixed-rate bonds, but not nearly as well as true TIPS-style bonds. This also goes, incidentally, for CPI-linked floaters that pay back par at maturity.

However, there are a number of advisors who advocate FRNs as an inflation hedge; my purpose here is to illustrate why this is not correct.

There are reasonable-sounding arguments to be made about the utility of FRNs as an inflation hedge. Where central bankers employ a Taylor-Rule-based approach, it is plausible to argue that short rates ought to be made to track inflation fairly explicitly, and even to outperform when inflation is rising as policymakers seek to establish positive real rates. And indeed, history shows this to be the case as LIBOR tracks CPI with some reasonable fidelity (the correlation between month-end 3m Libor and contemporaneous Y/Y CPI is 0.59 since 1985, see chart below, data sourced from Bloomberg).


It bears noting that the correlation of Libor with forward-looking inflation is not as strong, but these are still reasonable correlations for financial markets.

The correlation between inflation and T-Bills has a much longer history, and a higher correlation (0.69) as a result of tracking well through the ‘80s inflation (see chart below, source Bloomberg and


And, of course, the contemporaneous correlation of CPI to itself, if we are thinking about CPI-linked bonds, is 1.0 although the more-relevant correlation, given the lags involved with the way CPI floaters are structured, of last year’s CPI to next year’s CPI is only 0.63.

Still, these are good correlations, and might lead you to argue that FRNs are likely good hedges for inflation. Simulations of LIBOR-based bonds compared to inflation outcomes also appear to support the conclusion that these bonds are suitable alternatives to inflation-linked bonds (ILBs) like TIPS. I simulated the performance of two 10-year bonds:

Bond 1: Pays 1y Libor+100, 10y swaps at 2.5%.

Bond 2: Pays an annual TIPS-style coupon of 1.5%, with expected inflation at 2.0%.

Note that both bonds have an a priori expected nominal return of 3.5%, and an a priori expected real return of 1.5%.

I generated 250 random paths for inflation and correlated LIBOR outcomes. I took normalized inflation volatility to be 1.0%, in line with current markets for 10-year caps, and normalized LIBOR volatility to be 1.0% (about 6.25bp/day but it doesn’t make sense to be less than inflation, if LIBOR isn’t pegged anyway) with a correlation of 0.7, with means of 2% for expected inflation and 2.5% for expected LIBOR and no memory. For each path, I calculated the IRR of both bonds, and the results of this simulation are shown in the chart below.


You can see that the simulation produced a chart that seems to suggest that the nominal internal rates of return of nominal bonds and of inflation-linked bonds (like TIPS) are highly correlated, with a mean of about 3.5% in each case and a correlation of about 0.7 (which is the same as an r-squared, indicated on the chart, of 0.49).

Plugged into a mean-variance optimization routine, the allocation to one or the other will be largely influenced by the correlation of the particular bond returns with other parts of the investor’s portfolio. It should also be noted that the LIBOR-based bond may be more liquid in some cases than the TIPS-style bond, and that there may be opportunities for credit alpha if the analyst can select issuers that are trading at spreads which more than compensate for expected default losses.

The analysis so far certainly appears to validate the hypothesis that LIBOR bonds are nearly-equivalent inflation hedges, and perhaps even superior in certain ways, to explicitly indexed bonds. The simulation seems to suggest that LIBOR bonds should behave quite similarly to inflation-linked bonds. Since we know that inflation-linked bonds are good inflation hedges, it follows (or does it?) that FRNs are good inflation hedges, and so they are a reasonable substitute for TIPS. Right?

However, we are missing a crucial part of the story. Investors do not, in fact, seek to maximize nominal returns subject to limiting nominal risks, but rather seek to maximize real return subject to limiting real risks.[1]

If we run the same simulation, but this time calculate the Real IRRs, rather than the nominal IRRs, a very different picture emerges. It is summarized in the chart below.


The simulation produced the assumed equivalent average real returns of 1.5% for both the LIBOR bond and the TIPS-style bond. But the real story here is the relative variance. The TIPS-style bond had zero variance around the expected return, while the LIBOR bond had a non-zero variance. When these characteristics are fed into a mean-variance optimizer, the TIPS-style bond is likely to completely dominate the LIBOR bond as long as the investor isn’t risk-seeking. This significantly raises the hurdle for the expected return required if an investor is going to include LIBOR-based bonds in an inflation-aware portfolio.

So what is happening here? The problem is that while the coupons in this case are both roughly inflation-protected, since LIBOR (it is assumed) is highly correlated to inflation, there is a serious difference in the value of the capital returned at the maturity of the bond. In one case, the principal is fully inflation-protected: if there has been 25% inflation, then the inflation-linked bond will return $125 on an initial $100 investment. But the LIBOR-based bond in this case, and in all other cases, returns only $100. That $100 is worth, in real terms, a widely varying amount (I should note that the only reason the real IRR of the LIBOR-based bond is as constrained as it appears to be in this simulation is because I gave the process no memory – that is, I can’t get a 5% compounded inflation rate, but will usually get something close to the 2% assumed figure. So, in reality, the performance in real terms of a LIBOR bond is going to be even more variable than this simulation suggests.

The resolution of the conundrum is, therefore, this: if you have a floating rate annuity, with no terminal value, then that is passably decent protection for an inflation-linked annuity. But as soon as you add the principal paid at maturity, the TIPS-style bond dominates a similar LIBOR bond. “Hooray! I got a 15% coupon! Boo! That means my principal is worth 15% less!”

The moral of the story is that if your advisor doesn’t understand this nuance, they don’t understand how inflation operates on nominal values in an investor’s portfolio. I am sorry if that sounds harsh, but what is even worse than the fact that so many advisors don’t know this is that many of those advisors don’t know that they don’t know it!

[1] N.b. Of course, they seek to maximize after-tax real returns and risks, but since the tax treatments of ILBs and Libor floaters are essentially identical we can abstract from this detail.

RE-BLOG: Some Useful Charts And Thoughts About Personal Investing

December 30, 2013 1 comment

Note: The following blog post originally appeared on March 12th, 2013 and is part of a continuing year-end ‘best of’ series, calling up old posts that some readers may have not seen before. I have removed some of the references to then-current market movements and otherwise cut the article down to the interesting bits. You can read the original post here.


I just finished a paper called “Managing Laurels: Liability-Driven Investment for Professional Athletes,” and I thought that one or two of the charts might be interesting for readers in this space.

An athlete’s investing challenge is actually much more like that of a pension fund than it is of a typical retiree, because of the extremely long planning horizon he or she faces. While a typical retiree at the age of 65 faces the need to plan for two or three decades, an athlete who finishes a career at 30 or 35 years of age may have to harvest investments for fifty or sixty years! This is, in some ways, closer to the endowment’s model of a perpetual life than it is to a normal retiree’s challenge, and it follows that by making investing decisions in the same way that a pension fund or endowment makes them (optimally, anyway) an athlete may be better served than by following the routine “withdrawal rules” approach.

In the paper, I demonstrate that an athlete can have both good downside protection and preserve upside tail performance if he or she follows certain LDI (liability-driven investing) principles. This is true to some extent for every investor, but what I really want to do here is to look at those “withdrawal rules” and where they break down. A withdrawal policy describes how the investor will draw on the portfolio over time. It is usually phrased as a proportion of the original portfolio value, and may be considered either a level nominal dollar amount or adjusted for inflation (a real amount).

For many years, the “four percent rule” said that an investor can take 4% of his original portfolio value, adjusted for inflation every year, and almost surely not run out of money. This analysis, based on a study by Bengen (1994) and treated more thoroughly by Cooley, Hubbard, and Walz in the famous “Trinity Study” in 1998, was to use historical sampling methods to determine the range of outcomes that would historically have resulted from a particular combination of asset allocation and withdrawal policies. For example, Cooley et. al. established that given a portfolio mix of 75% stocks and 25% bonds and a withdrawal rate of 6% of the initial portfolio value, for a thirty-year holding period (over the historical interval covered by the study) the portfolio would have failed 32% of the time for, conversely, a 68% success rate.

The Trinity Study produced a nice chart that is replicated below, showing the success rates for various investment allocations for various investing periods and various withdrawal rates.


Now, the problem with this method is that the period studied by the authors ended in 1995, and started in 1926, meaning that it started from a period of low valuations and ended in a period of high valuations. The simple, uncompounded average nominal return to equities over that period was 12.5%, or roughly 9% over inflation for the same period. Guess what: that’s far above any sustainable return for a developed economy’s stock market, and is an artifact of the measurement period.

I replicated the Trinity Study’s success rates (roughly) using a Monte Carlo simulation, but then replaced the return estimates with something more rational: a 4.5% long-term real return for equities (but see yesterday’s article for whether the market is currently priced for that), and 2% real for nominal bonds (later I added 2% for inflation-indexed bonds…again, these are long-term, in equilibrium numbers, not what’s available now which is a different investing question). I re-ran the simulations, and took the horizons out to 50 years, and the chart below is the result.

50yrs pic

Especially with respect to equity-heavy portfolios, the realistic portfolio success rates are dramatically lower than those based on the “historical record” (when that historical record happened to be during a very cheerful investing environment). It is all very well and good to be optimistic, but the consequences of assuming a 7.2% real return sustained over 50 years when only a 4.5% return is realistic may be incredibly damaging to our clients’ long-term well-being and increase the chances of financial ruin to an unacceptably-high figure.

Notice that a 4% (real) withdrawal rate produces only a 68% success rate at the 30 year horizon for the all-equity portfolio! But the reality is worse than that, because a “success rate” doesn’t distinguish between the portfolios that failed at 30 years and those that failed spectacularly early on. It turns out that fully 10% of the all-equity portfolios in this simulation have been exhausted by year 19. Conversely, 90% of the portfolios of 80% TIPS and 20% equities made it at least as far as year 30 (this isn’t shown on the chart above, which doesn’t include TIPS). True, those portfolios had only a fraction of the upside an equity-heavy portfolio would have in the “lucky” case, but two further observations can be made:

  1. Shuffling off the mortal coil thirty years from now with an extra million bucks in the bank isn’t nearly as rewarding as it sounds like, while running out of money when you have ten years left to lift truly sucks; and
  2. By applying LDI concepts, some investors (depending on initial endowment) can preserve many of the features of “safe” portfolios while capturing a significant part of the upside of “risky” portfolios.

The chart below shows two “cones” that correspond to two different strategies. For each cone, the upper line corresponds to the 90th percentile Monte Carlo outcome for that strategy and portfolio, at each point in time; the lower line corresponds to the 10th percentile outcome; the dashed line represents the median. Put another way, the cones represent a trimmed-range of outcomes for the two strategies, over a 50-year time period (the x-axis is time). The blue lines represent an investor who maintains 80% in TIPS, 20% in stocks, over the investing horizon with a withdrawal rate of 2.5%. The red lines represent the same investor, with the same withdrawal rates, using “LDI” concepts.


While this paper concerned investors such as athletes who have very long investing lives and don’t have ongoing wages that are large in proportion to their investment portfolios (most 35-year-old investors do, which tends to decrease their inflation risk), the basic concepts can be applied to many types of investors in many situations.

And they should be.


You can follow me @inflation_guy, or subscribe to receive these articles by email here.

Categories: Good One, Investing, Re-Blog, Theory

RE-BLOG: Keynes, Marx, and Bernanke

December 27, 2013 1 comment

Note: The following blog post originally appeared on April 4th, 2012 and is part of a continuing year-end ‘best of’ series, calling up old posts that some readers may have not seen before. I have removed some of the references to then-current market movements and otherwise cut the article down to the interesting bits. You can read the original post here.


I routinely deride economists who rely on the discredited notion that growth in excess of a nation’s productive capacity is what causes inflation – and, conversely, a surplus of productive capacity is what causes deflation. See, for example, here, here, and here. And that is just in the last month!

I want to point out that it isn’t that I don’t believe in microeconomics (where an increase in supply causes prices to fall and a decrease in supply causes prices to rise). I believe deeply in the supply-demand construct.

But the problem with applying these ideas to the macroeconomy is that people get confused with real and nominal quantities, and they think of the “productive frontier” of an economy as being one thing rather than a multi-dimensional construct.

When an economy reaches “productive capacity,” it isn’t because it has used up all of its resources. It is because it has used up the scarcest resource. Theory says that what should happen isn’t that all prices should rise, but that the price of the scarce resource should rise relative to the prices of other resources. For example, when labor is plentiful relative to capital, then what should happen is that real wages should stagnate while real margins increase – that is, because productivity is constrained by the scarce resource of capital, more of the economy’s gains should accrue to capital. And so Marx was right, in this sort of circumstance: the “industrial reserve army of the unemployed” should indeed increase the share of the economic spoils that go to the kapitalists.

And that is exactly what is happening now. In the banking crisis, the nation’s productive capacity declined because of a paucity of available capital, in particular because banks were forced to de-lever. Output declined, and after the shock adjustments the margins of corporate America rose sharply (which I recently illustrated here), near record levels from earlier in the decade of the 00s. And real wages stagnated. Be very clear on this point: it is real wages which are supposed to stagnate when labor is plentiful, not nominal wages.

Now, what should happen next in a free market system is that the real cost of capital should decline, or real wages should increase, or both, as labor is substituted for capital because of the shortage of capital. We indeed see that the real cost of capital is declining, because real rates are sharply negative out to 10 years and equities are trading at lusty multiples. But real wages are stagnating, going exactly nowhere over the last 36 months. Why is the adjustment only occurring on the capital side, with bull markets in bonds and stocks?

We can thank central bankers, and especially Dr. Bernanke and the Federal Reserve, for working assiduously to lower the cost of capital – also known as supporting the markets for capital. This has the effect, hopefully unintended, of lowering the level at which the convergence between real wages and the real cost of capital happens; and of course, it obviously also favors the existing owners of capital. By defending the owners of capital (and, among other things, refusing to let any of them go out of business), the Fed is actually helping to hold down real wages since there is no reason to substitute away from capital to labor!

But all of this happens in real space. One way that the real cost of capital and the real wage can stay low is to increase the price level, which is exactly what is happening. We call this inflation.


You can follow me @inflation_guy, or subscribe to receive these articles by email here.


RE-BLOG: Side Bet With Ben?

December 26, 2013 1 comment

Note: The following blog post originally appeared on June 14, 2012 and is part of a continuing year-end ‘best of’ series, calling up old posts that some readers may have not seen before. I have removed some of the references to then-current market movements and otherwise cut the article down to the interesting bits. You can read the original post here.


That said, there could be some signs that core CPI is flattening out. Of the eight ‘major-groups’, only Medical Care, Education & Communication, and Other saw their rates of rise accelerate (and those groups only total 18.9% of the consumption basket) while Food & Beverages, Housing, Apparel, Transportation, and Recreation (81.1%) all accelerated. However, the deceleration in Housing was entirely due to “Fuels and Utilities,” which is energy again. The Shelter subcategory accelerated a bit, and if you put that to the “accelerating” side of the ledger we end up with a 50-50 split. So perhaps this is encouraging?

The problem is that there is, as yet, no sign of deceleration in core prices overall, while money growth continues to grow apace. I spend a lot of time in this space writing about how important money growth is, and how growth doesn’t drive inflation. I recently found a simple and elegant illustration of the point, in a 1999 article from the Federal Reserve Board of Atlanta’s Economic Review entitled “Are Money Growth and Inflation Still Related?” Their conclusion is pretty straightforward:

“…substantial changes in inflation in a country are associated with changes in the growth of money relative to real income…the evidence in the charts is inconsistent with any suggestion that inflation is unrelated to the growth of money relative to real income. On the contrary, there appears to be substantial support for a positive, proportional relationship between the price level and money relative to income.”[1]

But the power of the argument was in the charts. Out of curiosity, I updated their chart of U.S. prices (the GDP deflator) versus M2 relative to income to include the last 14 years (see Chart, sources: for M2 Friedman & Schwartz, Rasche, and St. Louis Fed, and Measuring Worth for the GDP and price series). Note the chart is logarithmic on the y-axis, and the series are scaled in such a way that you can see how they parallel each other.

That’s a pretty impressive correlation over a long period of time starting from the year the Federal Reserve was founded. When the authors produced their version of this chart, they were addressing the question of why inflation had stayed above zero even though M2/GDP had flattened out, and they noted that after a brief transition of a couple of years the latter line had resumed growing at the same pace (because it’s a logarithmic chart, the slope tells you the percentage rate of change). Obviously, this is a question of why changes in velocity happen, since any difference in slopes implies that the assumption of unchanged velocity must not hold. We’ve talked about how leverage and velocity are related before, but an important point is that the wiggles in velocity only matter if the level of inflation is pretty low.

A related point I have made is that at low levels of inflation, it is hard to disentangle growth and money effects on inflation – an observation that Fama made about thirty years ago. But at high levels of inflation, there’s no confusion. Clearly, money is far and away the most important driver of inflation at the levels of inflation we actually care about (say, above 4%!). The article contained this chart, showing the same relationship for Brazil and Chile as in the chart updated above:

That was pretty instructive, but the authors also looked across countries to see whether 5-year changes in M2/GDP was correlated with 5-year changes in inflation (GDP deflator) for two windows. In the chart below, the cluster of points around a 45-degree line indicates that if X is the rate of increase in M2/GDP for a given 5-year period, then X is also the best guess of the rate of inflation over the same 5-year period. Moreover, the further out on the line you go, the better the fit is (they left off one point on each chart which was so far out it would have made the rest of the chart a smudge – but which in each case was right on the 45-degree line).

That’s pretty powerful evidence, apparently forgotten by the current Federal Reserve. But what does it mean for us? The chart below shows non-overlapping 5-year periods since 1951 in the U.S., ending with 2011. The arrow points to where we would be for the 5-year period ending 2012, assuming M2 continues to grow for the rest of this year at 9% and the economy is able to achieve a 2% growth rate for the year.

So the Fed, in short, has gotten very lucky to date that velocity really did respond as they expected – plunging in 2008-09. Had that not happened, then instead of prices rising about 10% over the last five years, they would have risen about 37%.

Are we willing to bet that this time is not only different, but permanently different, from all of the previous experience, across dozens of countries for decades, in all sorts of monetary regimes? Like it or not, that is the bet we currently have on. To be bullish on bonds over a medium-term horizon, to be bullish on equity valuations over a medium-term horizon, to be bearish on commodities over a medium-term horizon, you have to recognize that you are stacking your chips alongside Chairman Bernanke’s chips, and making a big side bet with long odds against you.

I do not expect core inflation to begin to fall any time soon. [Editor's Note: While core inflation in fact began to decelerate in the months after this post, median inflation has basically been flat from 2.2% to just above 2.0% since then. The reason for the stark difference, I have noted in more-recent commentaries, involves large changes in some fairly small segments of CPI, most notably Medical Care, and so the median is a better measure of the central tendency of price changes. Or, put another way, a bet in June 2012 that core inflation was about to decline from 2.3% to 1.6% only won because Medical Care inflation unexpectedly plunged, while broader inflation did not. So, while I was wrong in suggesting that core inflation would not begin to fall any time soon, I wasn't as wrong as it looks like if you focus only on core inflation!]

[1] The reference of “money relative to income” comes from manipulation of the monetary identity, MV≡PQ. If V is constant, then P≡M/Q, which is money relative to real output, and real output equals income.

RE-BLOG: My Two Cents On Nonsense

December 24, 2013 5 comments

Note: The following blog post originally appeared on March 13, 2012 and is part of a continuing year-end ‘best of’ series, calling up old posts that some readers may have not seen before. I have removed some of the references to then-current market movements and otherwise cut the article down to the interesting bits. You can read the original post here.


I had not planned to write tonight, but there was too much that happened today, and too much that is likely to be misunderstood and misinterpreted. Not, necessarily, that what follows will help that situation, but I felt a need to add my two cents (which, don’t forget, is two cents more than you paid for it, so you’re two cents ahead no matter what).

And this takes us to the final, and most interesting, event of the day. It began when JP Morgan trumpeted a nickel increase in its dividend and a $15bln stock buyback. My first reaction was that this is not a phenomenon you tend to see in bear markets or early in bull markets, but rather in mature bull markets. Firms have a marked tendency to buy stock back when it’s expensive, not when it’s cheap, and an even more marked tendency to announce a buyback when they want a stock price supported. An announcement of a buyback program is not a promise to buy, and often no stock is actually bought. It is only an announcement of an intention to buy, which the firm need not honor. And this is a bank. Anyone with even a passing knowledge of Basel III knows that banks are going to be raising Tier 1 capital – especially in Europe, but in the U.S. as well – for a while. There is no way that banks, whether or not they feel overcapitalized by 2000s standards or not, are actually going to be buying back large chunks of stock. So my second thought was “wow, are they actually going to scare up the stock so that they can sell more? That can’t be legal.”

Moments later, we found out what the real point was. It seems the Fed had completed the stress tests and informed all of the banks a couple of days ago (it’s unclear when), and were going to make a public announcement on Thursday.

Sidebar: This is why people think that Wall Street is run by a bunch of crooks. The moment that banks had this information, they were in possession of material nonpublic information that should have been immediately released if the banks were going to prepare any offering in their own securities. Whether the Fed says they can or can’t, the information must be released. And here is one positive checkmark for JPM: they announced that the Fed had approved their buyback and dividend plans in the context of passing the stress test. But thanks a lot, Fed, for putting banks in the awkward position of having to choose between ticking off the Fed, or ticking off the SEC. And great job, bank managements, for mostly choosing to keep a secret that makes you look like a member of an elite club/secret cabal, rather than choosing to release the information. Good job, JPM. (But I’m not done with you yet).

So, the Fed decided that they needed to immediately release the stress tests results, early. Well, not immediately; they decided to wait until 4:30ET, after the markets closed to retail investors, because golly it would be too much to ask to let people get the information when the markets were open. Sidebar: this is why people think the Fed is run by a bunch of crooks who are in bed with the Wall Street crooks. Who is running the PR at the Fed?

Bank of America bravely followed JP Morgan through the breach to announce that they, too, had passed the stress tests. US Bank announced a share buyback, dividend hike, and a passing stress test grade. (Quick quiz, with the answer to be given later: are the banks announcing share buybacks likely to be the strong banks or the weak banks with respect to the stress test? Write down your answer and we’ll come back to it.) Volume on the exchange spiked, with better than 50% of the day’s volume coming in the last hour of trading, and almost 30% in the last 7 minutes before the bell.

The stress test results were released, and four financials failed: Ally Financial, SunTrust, MetLife, and Citigroup. Well, good luck raising capital now, Citi. (Important Disclosure: I am expressing no opinion on any of these individual equities or any of the other securities of these companies. I neither own, nor intend to buy, nor sell, any of their securities in the near future. My negative opinion on banks generally is well-known, but I do not have any position, positive or negative, on the banking sector, nor do I plan to make such a sector bet in the near future).

Now, initially the press coverage listed three of the four firms that failed, but not MetLife, so I was forced to go skimming through the “CCAR” report to find the fourth one. If I hadn’t done that, I almost certainly would not have noticed Figure 7, which is reproduced below for your easy reference.

You can see the four banks which failed are the shortest bars on this chart, so you can easily pick out Ally, Sun Trust, Citi, and with a straightedge you can conclude that MetLife is the fourth. But then it’s a really close race for fifth-worst with KeyCorp, US Bank, Morgan Stanley, and… JP Morgan. It must be great to be JP Morgan. When you wonder why they drew the line where they did, you might imagine the counterfactual situation where JP Morgan came out on the other side of the line. JP Morgan, which was the Fed before there was a Fed, and will probably be the Fed after the Fed is gone. JP Morgan, which the Fed called on multiple times during the crisis to save the world (for example, by serving as a lending conduit to entities which the Fed could not directly lend to). I wonder what the odds are that JP Morgan would be allowed to fail? I’m going to speculate: zero. And that’s why the line is where it is.

Now, it is interesting to see which banks scored very highly. They’re banks that don’t have exposure to as many of the blow-up areas that were tested by the Fed (which is not to say they aren’t exposed to blow-ups: just that they’re not the ones that the Fed tested).

By the way, don’t let anyone tell you “well, this was a really severe test, and so these banks are actually in really good shape.” Yes, this test is much more stringent than the cotton-candy version the European regulators put their banks through last year, but it only measures expected reactions to broad macroeconomic events, and not the interaction of the entire system under such a stressful scenario. That reaction is non-linear, and it is very difficult to model. Moreover, we can’t model the unknown: a rogue trader, a $65billion Ponzi scheme, a tsunami and nuclear meltdown in Japan, a terrorist attack in New York. As Roseanne Roseannadanna used to say, “It’s always something.”

When all is said and done, are we better off that the Fed did these stress tests? I suppose the answer is yes, if only because it means the regulators actually took some interest in looking at these businesses and their risks. But if it creates a false sense of comfort, or reverses the trend towards greater capital cushions, then probably not. Time will tell.

I am about ranted out for today, and there are no important economic releases tomorrow. It will be interesting to see how the spin machines work on Citigroup and JP Morgan, which are after all separated by only a thin line on Figure 7, but by a huge gulf in reputation.


You can follow me @inflation_guy, or subscribe to receive these articles by email here.

RE-BLOG: U.S. Wages and Egyptian President Employment

December 23, 2013 2 comments

Note: The following blog post originally appeared on February 3, 2011 (with an additional reference that was referred to in a February 17, 2012 post) and is part of a continuing year-end ‘best of’ series, calling up old posts that some readers may have not seen before. I have removed some of the references to then-current market movements and otherwise cut the article down to the interesting bits. You can read the original post here.


Rising energy prices, if they rise for demand-related reasons, needn’t be a major concern. Such a price rise acts as one of the “automatic stabilizers” and, while it pushes up consumer prices, it also acts to slow the economy. This helps reduce the need for the monetary authority to meddle (not that anything has stopped them any time recently). It doesn’t need to respond to higher (demand-induced) energy prices, because those higher prices are serving the usual rationing function of higher prices vis a vis scarce resources.

But when energy prices (or, to a lesser extent, food prices) rise because of supply-side constraints – say, reduced traffic through the Suez Canal, or fewer oil workers manning the pumps in a major oil exporting region – then that’s extremely difficult for the central bank to deal with. More-costly energy will slow the economy inordinately, and higher prices also translate into higher inflation readings so that if the central bank responds to the economic slowdown they risk adding to the inflationary pressures.

One of the ways that we can restrain ourselves from getting too excited, too soon, about the upturn in employment is to reflect on the fact that surveys still indicate considerable uncertainty and pessimism among the people who are vying for those jobs (or clinging to the ones they have, hoping they don’t have to compete for those scarce openings). This is illustrated by the apparent puzzle that Unit Labor Costs (reported yesterday) remain under serious pressure and Productivity continues to rise at the same time that profit margins are already extremely fat. Rising productivity is normal early in an expansion, but the bullish economists tell us that the expansion started a year and a half ago. We’re about halfway through the duration of the average economic expansion (if you believe the bulls). And fat profit margins are not as normal early in an expansion.

Now, we don’t measure Productivity and Unit Labor Costs very well at all. Former Fed Chairman Greenspan used to say that we need 5 years of data before we can spot a change in trend, and he may be low. But it seems plausible that there remains downward pressure on wages. Call it the “industrial reserve army of the unemployed” effect. While job prospects are improving, they are apparently not improving enough yet for employed people to start pressing their corporate overlords to spread more of the profits around to the proletariat.

Fear not, however, that this restrains inflation. The evidence that wage pressures lead to price pressures (and conversely, the absence of wage pressures suggest an absence of price pressures) is basically non-existent. Let me present two quick charts that make the point simply.

No surprise: tighter conditions in the labor market tend to be associate with wage inflation.

The chart above (Source for data: Bloomberg) shows the relationship between the Unemployment Rate and the (contemporaneous) year-on-year rise in Average Hourly Earnings. I have divided the chart into four phases: 1975-1982 (a period which runs from roughly the end of wage-and-price controls in mid-1974 until the abandoning of the monetarist experiment near the end of 1982), a “transition period” of 1983-1984, the period of 1985-2007 (the “modern pre-crisis experience”), and a rump period of the crisis until now. Several interesting results obtain.

First of all, there should be no surprise that that the supply curve for labor has the shape it does: when the pool of available labor is low, the price of that labor rises more rapidly; when the pool of available labor is high, the price of that labor rises more slowly. Labor is like any other good or service; it gets cheaper if there’s more of it for sale! What is interesting as well is that abstracting from the “transition period,” the slopes of these two regressions are very similar: in each case, a 1% decline in the Unemployment Rate increases wage gains by about ½% per annum. Including the rump period changes the slope of the relationship slightly, but not the sign. This may well be another “transition” period leading to a permanent shift in the tradeoff of Unemployment versus wage inflation.

But clearly, then, when Unemployment is high we can safely conclude that since there are no wage pressures there should be no price pressures, right?

The Phillips Blob

The second chart puts paid to that myth. It shows the same periods, but plots changes in core CPI, rather than Hourly Earnings, as a function of the Unemployment Rate. This is the famous “Phillips Curve” that postulates an inverse relationship between unemployment and inflation. The problem with this elegant and intuitive theory is that the facts, inconveniently, refuse to provide much support. [Note: the above chart is very similar to one appearing in this excellent article by economist John Cochrane, which appeared in the Fall of 2011.]

Why does it make sense that wages can be closely related to unemployment, but inflation is not? Well, labor is just one factor of production, and retail prices are not typically set on a labor-cost-plus basis but rather reflect (a) the cost of labor, (b) the cost of capital, (c) the proportion of labor to capital, and importantly (d) the rate of substitution between labor and capital. This last point is crucial, and it is important to realize that the rate of labor/capital substitution is not constant (nor even particularly stable). When capital behaves more like a substitute for labor, a plant owner can keep customer prices in check and sustain margins at the same time by deepening capital. This shows up as increased productivity, and causes the relationship between wages and end product prices to decouple. Indeed, in the second chart above the R2s for both periods is…zero!

This isn’t some discovery that no one has stumbled upon before. In a wonderful paper published in 2000, Gregory Hess and Mark Schweitzer at the Cleveland Fed wrote that

It turns out that the vast majority of the published evidence suggests that there is little reason to believe that wage inflation causes price inflation. In fact, it is more often found that price inflation causes wage inflation. Our recent research, which updates and expands on the current literature, also provides little support for the view that wage gains cause inflation. Moreover, wage inflation does a very poor job of predicting price inflation throughout the 1990s, while money growth and productivity growth sometimes do a better job. The policy conclusion to be drawn is that wage inflation, whether measured using labor compensation, wages, or unit-labor-costs growth, is not a reliable predictor of inflationary pressures. Inflation can strike unexpectedly without any evidence from the labor market.

The real mystery is why million-dollar economists, who have access to the exact same data, continue to propagate the myth that wage-push inflation exists. If it does, there is no evidence of it.


You can follow me @inflation_guy, or subscribe to receive these articles by email here.

RE-BLOG: Perfect Drugs From Perfect Pharmacists

December 20, 2013 1 comment

Note: The following blog post originally appeared on January 11th, 2011 and is part of a continuing year-end ‘best of’ series, calling up old posts that some readers may have not seen before. I have removed some of the references to then-current market movements and otherwise cut the article down to the interesting bits. You can read the original post here.


…Looking over the Atlantic, ECB President Trichet offered what some observers saw as a threat that the ECB would raise interest rates to combat inflation if energy-price increases pass through to broad price increases. The German bond market, and others, sold off on his “conditional warning”:

“We see evidence of short-term upward pressure on overall inflation, mainly owing to energy prices, but this has not so far affected our assessment that price developments will remain in line…Very close monitoring of price developments is warranted.”

This is an empty threat. There is no chance that the ECB will raise rates to combat inflation while they are simultaneously buying every bond in sight to try and lower borrowing costs for member nations (and especially the periphery countries). The ECB may be slightly more politically independent than the Fed, but tightening while member nations are trying feverishly to balance their budgets – with their only chance being either a strong resurgent economy or a cheapening of their nominal liabilities through inflation – is highly unlikely.

Trichet has more credibility, though, than our own domestic monetary policymakers. I have to take some time here to mention Fed Vice-Chair Janet Yellen’s speech from last weekend, since I have been meaning to for several days. It is important because the speech was an important defense of the Large Scale Asset Purchase (LSAP) program that the Fed has been conducting, and in that context we should be very afraid of what comes next. Because if this is the best thinking they have to share on the subject, then we are in a situation not unlike the baby who finds Daddy’s firearm in an unlocked position. Tragedy is likely to ensue.

In a nutshell, Dr. Yellen’s argument boils down to this:

  • The LSAP program is not affecting the dollar.
  • The LSAP program is not triggering “significant excesses or imbalances in the United States.”
  • The LSAP program does not risk markedly higher inflation because there is slack in the economy.
  • However, the LSAP program has had an enormous effect on jobs, adding about 3 million jobs to the economy.

So, the program has been hugely successful in the ways they needed it to be, without any side effects and no chance of anything going wrong. Does it make me a bad person that I am naturally suspicious of a drug that will make me immensely strong, lengthen my life, improve my love life, and cure hangovers but has no negative side effects? How about if that drug worked as intended the first time it was tested?

Incidentally, the claim that the LSAP program has created about 3 million jobs is interesting because the Administration claimed 2 million jobs were saved or created through fiscal stimulus. Each is not claiming that their policy in conjunction with other policies not under their control created jobs, so these must be additive. Fiscal policy, plus monetary policy, saved or created some 5 million jobs. Right now, the Civilian Labor Force is 153,690,000 and unemployment is 14,485,000 (9.4%), so these actions have prevented an Unemployment Rate of about 12.7%. This is interesting because no one was forecasting a 12.7% Unemployment Rate before these programs were put into place, so the people who are now telling us that the drug is working perfectly are the same people who had previously told us that no drug would be needed.

These results – the 2 million, 3 million jobs – are coming from time series regressions that are conducted with high mathematics and great rigor. But there are lots of reasons that econometric analysis should not be expected to work well in this case:

  1. The distributions you are trying to analyze are not static, which is a precondition for most time series analysis, nor normal. Indeed, you are actually trying to change the distributions with your policy.
  2. It is pretty plain that the model is not completely specified. That is, the people who were examining whether fiscal policy was effective didn’t include the separate effect of monetary policy, and vice-versa, so they both think it was their policy which worked. The fact that both of these policies are pushing in the same direction at roughly the same time also creates a problem of multicollinearity, a technical condition that basically means that with two people pulling on the same rope at the same time it is hard to tell who is pulling how much.
  3. The noise in the relationships far outweigh the signal, which means that all conclusions will (or should) have massive error bars on them.
  4. The analyst is analyzing the result of a single experiment. It is like trying to divine the laws of motion after hitting a cue ball a single time on the break of a game of billiards, except that the balls aren’t round, you can’t measure anything directly, and you have dirt in your eye. But in this case, the implications of reaching incorrect conclusions are far greater than if you were lining up your next shot in a game of pool.

Econometricians ought to be more guarded about conclusions such as this. Indeed, any reasonable experience with financial data sets tends to produce the realization that it is often hard to get any conclusive information out of them, although it is very easy to generate suggestive relationships that can’t be rejected simply because the error bars are too large to reject any particular hypothesis. It may be that the econometricians within the Fed who are actually doing the dirty work are providing the policymakers with all of the proper caveats, and warnings about the usefulness of the data, and that they policymakers are simply ignoring it. Or it may be that econometricians at the Fed feel pressure knowing that while 90% of the time there is nothing conclusive to say, it is hard to support your case for continued employment when your results most of the time are indistinguishable from not working.

The Fed continues to be especially cavalier about the end game. Yellen says the Fed remains “unwaveringly committed” to price stability, but says:

“I disagree with the notion that the large quantity of reserves resulting from our asset purchases poses some special barrier to removing policy stimulus when the right time comes. The FOMC will be able to increase short-term rates by raising the interest rate that we pay on excess reserves–currently 1/4 percent. That ability will allow us to manage short-term interest rates effectively and thus to tighten policy when needed, even if bank reserves remain high.”

Oh really? And you’ll be able to do that, politically, with unemployment at 9%? And you’re so sure that the effect will be immediate, perfectly calibrated, and won’t have any unanticipated side effects? She also suggests that they can withdraw stimulus by offering deposits to member institutions through a Term Deposit Facility, and also by selling portions of their holdings. The notion that you can have a huge effect by implementing a policy, but that reversing the policy will have little effect, is an offense against common sense. No, it’s an offense against financial physics. Yellen isn’t the first Fed official to make statements like this, and won’t be the last. And then, we’ll have several years of apologies when it doesn’t work out the way they said it would.


You can follow me @inflation_guy, or subscribe to receive these articles by email here.


Get every new post delivered to your Inbox.

Join 1,170 other followers

%d bloggers like this: