Relevant and even prescient commentary on news, politics and the economy.

Paul Krugman is Very, Very Wrong

by Mike Kimel

Update …Since this post has gotten a lot of attention, jump here for my
final word
on this topic.

I’m sure I’m missing something here, because Paul Krugman is so often extremely perceptive, but I think here he is very, very wrong. He writes:

The naive (or deliberately misleading) version of Fed policy is the claim that Ben Bernanke is “giving money” to the banks. What it actually does, of course, is buy stuff, usually short-term government debt but nowadays sometimes other stuff. It’s not a gift.

To claim that it’s effectively a gift you have to claim that the prices the Fed is paying are artificially high, or equivalently that interest rates are being pushed artificially low. And you do in fact see assertions to that effect all the time. But if you think about it for even a minute, that claim is truly bizarre.

Um, I dunno. Perhaps on specific day to day operations Ben B. is not giving money to the banks, but things look very different with a 30,000 foot view. (I suspect “the banks” most people mean if they say there are giveaways going on are not all banks but rather a small subset of basket cases.) Remember the toxic asset purchase? When the Fed spends over a trillion bucks paying the face value for securities whose real worth has declined to a fraction of that face value, to me that is both an expansion of the money supply and a give-away to those from whom one “purchases” those assets. There have been any number of similar, er, programs the Fed has run in the last few years which have had the same purpose: injecting money into a small number of entities that made extremely bad lending decisions in ways that specifically avoid making those entities pay any sort of market or reasonable price for that money.

That isn’t the only error in Krugman’s post. He also tells us this:

Furthermore, Fed efforts to do this probably tend on average to hurt, not help, bankers. Banks are largely in the business of borrowing short and lending long; anything that compresses the spread between short rates and long rates is likely to be bad for their profits. And the things the Fed is trying to do are in fact largely about compressing that spread, either by persuading investors that it will keep short rates at zero for a longer time or by going out and buying long-term assets. These are actions you would expect to make bankers angry, not happy — and that’s what has actually happened.

Yes, the Fed is sending a message that it well keep short rates at zero for a while longer. But which short rates and which long rates is Krugman talking about? Because banks can borrow at one rate – the effective federal funds rate, and they loan money to the public at a number of other rates.

I wandered over to FRED, the economic database of the St. Louis Fed and downloaded the Effective Federal Funds rate and the Average 30-Year Mortgage rate, which should be a good representation of a long rate used in loans by banks to the public.

The thirty-year mortgage is first reported on 5/7/1976 and is reported weekly thereafter. The FF tends to be reported a day or two earlier or later depending on the week, holiday schedules, and the like. Here’s what the 30-year Mortgage less the Fed Funds rate looks going back that far:

As is evident from the graph, whatever the Fed has been doing since the recession began in December of 2007, it isn’t compressing the spread between the 30-year mortgage rate and the Fed Funds rate.

Perhaps things might look different if the Fed followed more of a Banco do Brasil model, where the public could borrow directly from the Central Bank. But as things stand, pace Krugman, the Fed’s interventions since the recession began have only increased the spread between the rate at which banks can borrow and the rate at which they can loan out money.

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The Opposite of Bankrupt

By Noni Mausa

The Opposite of Bankrupt

Some time ago I wrote about dollars as bizarre IOUs, with no names,
dates or specific obligations. They are free-floating promises, which
can be used to command the efforts of the other people who accept them
as valid.

I give you ten promises, and you give me a sack of potatoes. The ten
promises I give you fragment to a fine dust and disperse backwards in
time to command the efforts of growers, shippers, plastic bag
producers, potato breeders, researchers, and a vast pyramid of all the
people whose efforts, minor or major, permit a sack of potatoes to sit
there waiting for me when I enter the store.

Where did my ten promises come from in the first place?

Generally, I have them because I have spent time, exerted effort, and
focused my attention upon some task. In return, I received
promise-tokens, which I can use to command the fractional efforts of
other people. They may be near or far, known or unknown to me, in the
past or in the future, but these promises are nothing without their
ability to command the efforts of others and especially, to command
that effort anonymously.

Let’s look at bubbles and crashes with that in mind.

Trillions of promises evaporated practically overnight in the wake of
the 2008 real estate, stock market and investment collapses. But real
wealth — in the form of homes, land, crops, buildings, human skills
and knowledge, and the myriad other desirable and necessary goods –
was practically untouched. This created several important effects.

First, and inevitably, the real value of each surviving promise
ballooned – currency deflated drastically and almost instantaneously.

Huh? Isn’t inflation still piddling along at one or two percent? We
are warned about deflation and we have seen some, but not the steep
slither into the abyss that we saw in the 20s and 30s worldwide.

But the math is simple. If 10% of your paper wealth suddenly
vanishes, deflation (fewer dollars for the same goods) must happen,
it’s a definitional truth. But the key is that the dollar was
drastically inflated before the bubble, but the inflated bit was in
storage, not in circulation where it could inflate prices and require
wheelbarrows for trips to the grocery store. It doesn’t matter if
Marty (“The Artist”) Billingham prints up thousands of hundred dollar
bills, if he then buries them or burns them. These promises only
exist in circulation.

So, when the bubble popped, the potential value of each dollar
grew. If this maneuver had been executed by the Fed, perhaps to
help the federal budget by having to mint fewer coins and bills,
nothing would have changed. Pay would be less, prices would be less,
but proportionality would be preserved.

But no. Proportionality went all to hell, because of whose promises
got liquidated.

The rising tide lifting boats is a lousy metaphor because all boats
sit on the top of the water, at the same level. Imagine instead that
your wealth measures how far offshore you are. When the tide rises,
all boats are lifted, but when it falls some are beached right away,
while others float serenely. Even though the ocean liners technically
have 20 feet less water to float in, the difference is not important.

So when our currency deflated, whose hulls were stove in?

Well, we know that. Property values stayed the same, insofar as value
means “a warm dry place that isn’t a cave,” but ownership skipped from
homeowners to the promise merchants, who can now command the efforts
of new buyers. The equity in those homes is gone, whoever buys them
now has to start over and pay the cost-plus-interest from scratch.
Either the owners, or their heirs, take the hit for that tangle of
broken promises.

Pension plans took a big hit also. Wages and benefits, already
weakened, are still being hacked away at the roots.

In short, the effect of the bubble and crash was not to destroy
wealth, since all that wealth is still present or could be very
quickly rebuilt.

No, the real effect was to further shift the “ability to command the
fractional efforts of people” from the working majority to a
commanding minority. And so long as money is accepted, so long as
currency can be used to command that effort anonymously, the majority
is in a pickle.

Bankruptcy is the loss of liquidity, the loss of abstract leverage to
command the efforts of other people. Generally, this is a voluntary
process in which you confess you will never be able to provide
sufficient effort to compensate for the loans extended to you, and so
shed those obligations. It pushes you off the rocks and, hopefully,
back into a few feet of water where you can begin again.

What do you call the opposite – the ownership of more IOUs than you
could have ever earned, which can be deployed anonymously, which
multiply over time, and which can be created out of thin air if you
know the magic words? Who are you when you’re permanently anchored
over a Mariana Trench of money where no tide, however terrible, can
touch you?

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The money quandary

The Federal Reserve, the Bank of England, and the Bank of Japan are considering further quantitative easing. It’s an explicit statement, as with the Federal Reserve and the Bank of England, or implied by the fact that the foreign exchange intervention will eventually be sterilized if the policy rule is not changed, as with the Bank of Japan. Why more easing?

In response to this question, BCA Research (article not available) presented a version of the quantity theory of money. They looked at the simple linear relationship between the average rate of money supply growth (M2) and nominal GDP growth (P*Y).

The chart is a reproduction of that in the BCA paper, but with a sample back to 1959 (they went back to the 1920’s when M2 was not measured). The relationship illustrates the 5-yr compounded annual growth rate of money (M2) against that of nominal GDP, and has an R2 equal to 50% – okay, but not perfect.

Nevertheless, the implication is pretty simple: the current annual growth rate of M2, 2.8% in August 2010, corresponds to an average annual income growth just shy of 4%. Sitting beneath a behemoth pile of debt relative to income, 4% nominal GDP growth is unlikely provide sufficient nominal gains for households to deleverage quickly or “safely“.

However, notice the 2000-2005 and 2005-2009 points, where the relationship between M2 and nominal GDP growth deviated away from the average “quantity theory” relationship. Would a broader measure of money account for the weak(ish) relationship in the chart above? Yes, partially. (Note: the relationship almost fully breaks down at an annual frequency.)

These days it’s all about credit. I’m sitting in Cosi right now – bought a sandwich and charged the bill on my credit card. Actually, I prefer to use cards. But M2 doesn’t account for this transaction as money if the balance is never paid in full. M2 is essentially currency, checking deposits, saving and small-denomination time deposits, and readily available retail money-market funds (see Federal Reserve release).

One can argue about the merits of including credit cards balances as “money”, per se. However, the sharp reversal of revolving consumer credit, and likely through default (see the still growing chargeoff rates for credit card loans), would never be captured in M2. The hangover from the last decade of households using their homes as ATM’s (i.e., home equity withdrawal) and running up credit card balances to serve as a medium of exchange is dragging nominal income growth via a sharp drop in aggregate demand.

The Federal Reserve discontinued its release of M3 in 2006, which among other things included bank repurchase agreements (repos). Including M3, rather than M2, in the estimation improves the the R2 over 30 percentage points (to 81%).


This is a very small sample, and removing the latest data point from the original estimation improves the R2 slightly to 64%; but clearly there’s something going on here. I think that it’s fair to say that we may be disappointed by the M2 implied average nominal GDP growth rate over the next 5 years (4%).

According to John Williams’ Shadow Statistics website, M3 is still contracting at (roughly because I don’t subscribe to the data) 4% over the year. The relationship in the second chart implies that nominal GDP will fall, on average, about 4.5% per year. Japan’s nominal GDP never contracted more than 2.08% annually during its lost decade, but the implication is that “things” may not be as rosy as the M2 measure of money suggests.

Rebecca Wilder

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The Non-Relationship Between Interest Rates and the Money Supply, Part 2

by Mike Kimel

The Non-Relationship Between Interest Rates and the Money Supply, Part 2
Cross-posted at the Presimetrics Blog.

This post is a bit less about Presidents than usual, but its a follow-up to last week’s post on the non-relationship between the money supply and interest rates. (That post appeared both at the Presimetrics and Angry Bear blogs. In that post, I noted that the Federal Reserve tends to move the money supply monthly and seasonally with no corresponding change in the fed funds rate. For example, the Fed will increase the money supply in December to make sure there’s adequate money in circulation for the Christmas shopping season, and yet interest rates don’t move at all.

This week, I want to expand on that, and point out that I wasn’t entirely accurate. There actually is a relationship between interest rates and the money supply, but its not the the one taught in textbooks. The textbook relationship, as I noted last week, can be described like this:

The Fed determines what the Federal Funds interest rate should be. If the Fed wants to reduce interest rates, it will create money out of thin air and use it to buy bonds. Because there is more money competing to buy bonds, the interest rate bonds have to pay falls. At the same time, the added money sloshing around becomes cheaper for anyone to borrow, whether they’re issuing bonds or not. On the flip side, if the Fed wants to raise interest rates, it sells bonds. That forces anyone else trying to sell bonds to raise interest rates to compete. Additionally, because the Fed retires the money it gets paid for the bonds it sells, that process reduces the amount of money available in the economy, making it harder to come by and hence more costly.

In other words, the money supply and interest rates are negatively correlated. An increase in money supply leads to a decrease in interest rates, and a decrease in the money supply leads to an increase in interest rates. There is an alternative story, but it only applies to high inflation environments. If you’re in Argentina in 1982, for example, the money supply is increasing so fast that any little bit of new money translates immediately into inflation and higher interest rates.

So there’s the theory, what everyone knows is true. But what really happens? For that, as always, we cut to the data. The Federal Reserve’s Economic Database (FRED) reports the federal funds rate going back to July of 1954. For the money supply, we used M1 from 1959 to the present, and the money stock for years before that.

The graph below shows the correlation between the 12 Month Percent Change in M1 and the Fed Funds rate in the same period, one month later, two months later, etc.:


Figure 1

The graph shows that the correlation between the percentage change in M1 over a year ending in a given month and the Fed Funds rate in the same month is about 14%. The correlation between the annual percent change in M1 and the Fed Funds rate in the next month rises to 16%, and so forth. The 1 year change in M1 has a higher correlation with the Fed Funds rate 36 months later than with any lag on the Fed Funds rate. In plain English, increases in M1 lead to increases in the Fed Funds rate, and decreases in M1 lead to decreases in the Fed Funds rate. That doesn’t sound at all the textbooks tell us we should expect in a world that isn’t suffering from hyperinflation.

Now, you may be thinking to yourself… maybe that relationship is a function of the fed trying to react to a slowing economy.

Strip out months in which the economy is in recession, plus the three months leading up to and the 3 months leading out of the recession, and the graph looks like this:


Figure 2.

Notice… the correlation drops a wee bit, but the shape of the curve is pretty much the same. Once again, it is fairly evident that this does not conform in any way to the classic textbook story.

So what is going on? My guess is that in the U.S., for the period for which we have data, in general:

1. changing the money supply has had no direct relationship on the Fed Funds rate
2. changing the money supply has had a direct effect on the economy; increasing M1 (actually, real M1 per capita) causes the economy to grow more rapidly, and decreasing the real money supply causes the economy to grow more slowly or contract
3. because increases in the (real) money supply cause the economy to grow more rapidly, eventually an increase in the money supply will lead the Fed to raise interest rates in an attempt to slow the economy (to avoid inflation). On the other hand, because reductions in the (real) money supply lead to slower economic growth or economic contraction, these reductions will eventually lead the Fed to lower interest rates to try to get the economy to grow more quickly.

Step 2 is something we cover in the book, but I hope to write another post showing that soon.

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The Non-Relationship Between Interest Rates and the Money Supply

by Mike Kimel

This piece has been cross-posted at The Presimetrics Blog.

The Non-Relationship Between Interest Rates and the Money Supply


Figure 1

The graph shows that all but one recession since 1948 was preceded by a big drop in the real money supply per person over the length of a year. The exception – July of 1953 – wasn’t much of an exception; the 12 month change in the real money stock per capita went negative in August of 1953 and remained negative throughout the length of that recession.

Now, I use real M1 per capita a lot in my posts; I think it’s a largely unused but very good (in part because it is largely unused) measure of monetary policy, and its one Michael Kanell and I use in Presimetrics. For instance, we discuss how it affects economic growth, and we look at how much real M1 per capita increased over the length of each administration. (Note – the change in real M1 per capita, like other measures of monetary policy, is under the control of the Federal Reserve, not the executive branch.)

But because it isn’t used much, every time I do use it, I find there is a bit of confusion. And because it is so useful, I think it is worth spending a bit of time covering it.

I’d like to start with a question I get asked a lot, which will be the topic of this post: what sense does it make to use real M1 per capita (or any other measure of the money supply) as a way to monitor the Fed’s monetary policy? After all, what the Fed does is set interest rates, or rather, one interest rate in particular: the Federal Funds rate. And when it does that, the money supply gets set by default. A fair number of college seniors majoring in econ, when pressed, could probably tell you a story like this:

The Fed determines what the Federal Funds interest rate should be. If the Fed wants to reduce interest rates, it will create money out of thin air and use it to buy bonds. Because there is more money competing to buy bonds, the interest rate bonds have to pay falls. At the same time, the added money sloshing around becomes cheaper for anyone to borrow, whether they’re issuing bonds or not. On the flip side, if the Fed wants to raise interest rates, it sells bonds. That forces anyone else trying to sell bonds to raise interest rates to compete. Additionally, because the Fed retires the money it gets paid for the bonds it sells, that process reduces the amount of money available in the economy, making it harder to come by and hence more costly.

It’s a nice story, and like many others that is taught in economics classes across the country, it works fine in theory. It may even apply in a lot of real world situations. As I will show below, however, it doesn’t have much if anything to do with the way the U.S. economy operates.

Now, I’ve got a lot of ground to cover today, and being charge of watching the newborn while the wife is out and about, I don’t have a whole heck of a lot of time, so whereas I’d normally be throwing up a lot of graphs to show what I mean, instead I’m going to tell a little story and then show you that the folks responsible for setting the money supply agree with the story.

Here’s the story: Americans like to shop, and they seem to really like to shop in December. (Apologies for the lack of a graph, but you can find one example of the data here.) Shopping is easier when there’s more liquidity in the system – that is to say, when money is looser and easier to come by – so the Fed should be expected to loosen the real money supply somewhat to accommodate the end –of-year shopping season. On the other hand, as anyone who watches the news can tell you, the Fed doesn’t exactly move interest rates around in a way that would suggest any loosening around December each year with a subsequent tightening up early in the next year. Which means either: a) the Fed does nothing to accommodate the end –of-year shopping season or b) the money supply and the interest rates, at least within some not-so-narrow range, have very little to do with each other.

Now, if the Fed is trying to loosen the money spigot to help the shopping season along every year, it isn’t doing it with interest rates. Interest rates don’t seem to display much of a pattern when it comes to the calendar. You don’t hear anyone say, “I’m waiting until to December to refinance the house since rates are always lower then.”

What about real M1 per capita? Well, there we see a pattern. Using data from January of 1948 to December of 2008, we can construct 721 blocks made up of 12 consecutive months. The first of these blocks runs from January of 1948 to December of 1948, the second from February of 1948 to January of 1948, and so forth, until January of 2008 through December of 2008.

The graph below shows the percentage of these blocks in which each month had the highest real M1 per capita. For example, the percent of blocks for which the peak real M1 per capita for the block occurred in January is shown in the first bar, the percent of blocks for which the peak real M1 per capita for the block occurred in February is shown in the second bar, etc. So look what happens:


Figure 2.

Clearly, by far, the real money supply per capita is looser in December than any other month, and by a degree well outside the range that anything resembling chance would support. The fact that January comes in second is probably a function of spillover from December – the Fed doesn’t always drain out the money supply as quickly as it might otherwise like.

So… to sum up what we have… the Fed has a reason to loosen the money supply in December. Interest rates don’t show any pattern that works with the Fed’s goals, but real M1 per capita does. This indicates that unless there’s some really big coincidence going on, interest rates and real M1 per capita do not move together and the Fed is/seems to be using real M1 per capita (or something very similar) to accomplish many of its liquidity goals.

While I tend to let data speak for itself, I’d like share a couple of quotes. Here’s the first

Because of these difficulties in achieving a subtle response of the Federal funds rate to changes in the amount of borrowing, achieving the degree of reserve pressures specified in the directive has been interpreted since the late 1980s to mean creating conditions consistent with the FOMC’s desired Federal funds rate. That rate has generally been apparent to the banks; since 1994 it has been announced formally and in prior years it was clearly indicated through an open market operation. The rate has tended to move to the new, preferred level as soon as the banks knew the intended rate, with little or no change in the amount of borrowing allowed for when constructing the path for nonborrowed reserves (described below).

I bolded a key sentence in the above paragraph; it indicates that the Federal funds rate is set not by the buying and selling of bonds, as textbooks will tell us, but rather by the Fed’s wish. Since 1994, the Fed has announced its target rate, and the rate starts moving in that direction immediately upon the announcement, not waiting for open market operations. Prior to 1994, the target rate wasn’t announced, but banks tried to get figure out that target through statements made by Fed officials and head to that rate anyhow.

A second quote from the same source:

A prominent seasonal factor affecting deposits is the buildup in balances to accommodate the extra transactions during the holiday period, stretching from late November to early January (and the sharp reversal during January). A shorter term seasonal pattern arises from the payment of social security benefits on the third of each month; most recipients allow their cash balances to rise initially, then gradually work down the deposits as they pay their bills. (The Treasury’s total cash position might show offsetting movements, but most Treasury cash is not subject to reserve requirements.3)

This quote indicates that the Fed does, indeed, try to accommodate additional seasonal liquidity (including those in December I noted in Figure 2).

So, these quotes match the data I described and support my conclusion. Which is to say, I’ve found another heathen who refuses to accept the standard textbook monetary policy story about how the money supply and interest rates behave. So where do these quotes come from, you ask?

You’ll find the quotes I cited on pp. 141 – 142 and p. 142, respectively, of the chapter on Open Market Operations in a textbook on monetary policy produced by the New York Fed. That is to say – the people directly responsible for the buying and selling of bonds on behalf of the Federal Reserve aren’t don’t seem to feel that their activities have anything to do with the setting of interest rates. But what does it say about the economics profession that the rest of us are under the misimpression that it does?

I’ll have at least one more post soon on real M1 per capita and its effect on the economy.


Data Sources

FRED, the Federal Reserve Database, was the source for most of the data used to compute real M1 per capita: population from 1952 to the present , M1 from 1958 on and M1 from 1958 on.

Quarterly data on real GDP per capita and population. Note – the quarterly population figures were used to extrapolate monthly population for 1947 to 1952.

Finally, money stock figures were substituted in for M1 from 1947 to 1957. Those were copied by hand from this document at the

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