Saturday, March 25, 2017

"there seems evidence that interest rates follow nominal GDP"


The title is a quote from Richard Werner.

If I have it right, he means that interest rates follow the growth rate of nominal GDP. Now I have a problem, because the growth rate of nominal GDP is a bullshit measure. When you are looking at economic growth you look at inflation-adjusted values, not nominal values. Always.

So maybe Werner is not looking at economic growth?

Clearly. But say he has a reason for using nominal values. What then? Then of course interest rates follow GDP, because when inflation makes nominal GDP go up, the Fed responds by making interest rates go up. And then, when high interest rates bring inflation and nominal GDP growth down, the Fed responds by bringing interest rates down. So interest rates follow nominal GDP growth on the way up, and interest rates follow nominal GDP growth on the way down, because that is the way monetary policy works.

Richard Werner seems not to know this. He sees the way monetary policy works, and he says interest rates follow GDP, and therefore (he says) interest rates cannot be the main tool of monetary policy:

Thus instead of the central banking narrative that lower rates lead to higher growth, the empirical and verifiable reality is that higher growth leads to higher rates and lower growth leads to lower rates. If rates are the result of growth, they cannot be the cause.

Monetary policy works by raising rates when inflation raises (or threatens to raise) nominal GDP growth. That's how it works. Werner sees interest rates following nominal GDP and says because they follow, rates have no influence on growth. I have to say it again: bullshit.

So much for nominal. Here's what happens with interest rates and real GDP growth:

Graph #1: RGDP Growth (blue), the Interest Rate (red), and High-Side Trends
Not much "following" going on there, is there.

Friday, March 24, 2017

The Federal Funds Rate and Economic Growth


"By lowering rates, central banks accelerate growth and by raising rates, they slow it". That's standard practice. But Richard Werner says central banks have it all wrong.

Werner says central bank policy depends on a negative correlation between interest rates and economic growth. It doesn't work that way, he says. "If you plot the nominal GDP growth rate against nominal interest rates, say, a scatter plot, you will find a positive correlation." A positive correlation, he says, not negative. If Werner is right, this is a major conceptual shift.

I watched a Werner interview two weeks ago, and did some reading. Every day since, I've been drawing his scatterplot. It fascinates me. I've started writing about it half a dozen times. Until now, my response has died every time. It is a difficult response to write, due to both the "major conceptual shift" and the "if Werner is right".

For starters, Werner's choice of data troubles me. If you plot the nominal GDP growth rate and nominal interest rates, you see both going high during the Great Inflation because of the great inflation. You see both going low after the financial crisis because of the financial crisis.

Nominal GDP grew rapidly during the Great Inflation, because of inflation. At the same time, policy (and creditors) pushed interest rates up to very high levels because of inflation. Inflation caused both growth and interest rates to rise to high levels, and then to fall when inflation receded. Movement in the same direction. That's a positive correlation.

More recently, a different set of special circumstances arose. The financial crisis and the Great Recession drove economic growth to unusually low levels. In response, our central bank dropped interest rates to the floor. Again, unusual circumstances created a positive correlation -- this time, low growth and low rates.

These positive correlations arise from sources other than the relation between economic growth and interest rates. If you mix such times with normal times, in a single picture of the economy, you distort the norm and create a hotbed of doubtful GDP/interest rate correlations. To add an overall trend line to such a mix of data would be absurd.

To be sure, I don't see Richard Werner showing trend lines on his scatterplots. But I do see him proclaim

the scatter plots on the left-hand side of the graph show a distinct positive correlation.

I do see him proclaim

The positive correlation of both curves is obvious.

And I do see him proclaim

instead of the proclaimed negative correlation, interest rates and economic growth are positively correlated.

Werner doesn't need to show a trend line. The positive correlation is obvious, he says. He doesn't need to show the trend line to see it. But he does not by his power of vision manage to escape the absurd.

Me? Yeah, I show the trendlines.

Does a positive correlation exist in the "normal" economy? Perhaps. But if we're going to look into it, we should exclude the data since the financial crisis, and we ought to strip inflation out of the numbers we will be looking at. For starters.

Now you know what we're doing today.


I thought I might be confused about what Werner is saying, so I checked: He is not speaking of what people in general think about central bank operations. He refers explicitly to the views expressed and the actions taken by central bankers:

Recently, central banks have been lowering rates, while proclaiming that this is a measure to stimulate the economy.

He disputes their story:

To the contrary, empirical evidence shows that ... interest rates and economic growth are positively correlated.

Werner uses a scatterplot to show correlation. Oddly, however, his scatterplot of U.S. data does not use the short-term interest rate that our central bank uses to influence the economy. Werner uses a long-term rate in his scatter. To test the idea that central banks influence growth by changing rates, it seems to me the scatterplot should use the same short-term rate that is used by the Fed.

Granted, the scatterplot might show a positive correlation for any interest rate you pick. But if you're going to challenge the Federal Reserve on interest rate policy, shouldn't you use the same interest rate that the Federal Reserve uses?

For my scatterplot data, then, I will use Real GDP and the inflation-adjusted FedFunds rate. My inflation-adjusted FedFunds calculation is similar to Bill McBride's from a dozen years back. I'll use the Effective Federal Funds Rate less "percent change from year ago" of the CPI:

Graph #1: FEDFUNDS (blue) and Inflation-Adjusted FEDFUNDS (red). Quarterly Data
The area between the red and blue lines, that's all inflation
These days the Fed prefers PCE to CPI. But I'll be cutting "these days" off the chart. And the Fed only switched from the CPI to the PCE in 2000. My scatter data goes back to the 1950s. I'm sticking with CPI for this calculation.

Here, then, is the source data for my scatter plot:

Graph #2: Quarterly Growth of RGDP (blue) and the Inflation-Adjusted Federal Funds Rate (red)
The graph runs from 1953 (before the FEDFUNDS data starts) to the end of 2008. I'll trim it down a little more in Excel when I can see the data.

On second thought, I'll grab all of the data for download, in case I have a use for it.


To see the path of the data but eliminate the jiggies, I'm figuring Hodrick-Prescott values for the two data sets. My objective is to preserve the "shape" of the data but make that shape more readable. So my smoothing constants are low, non-standard values. Here are the smoothed data (red) and the original values (gray):

Graph #3: Smoothing the Real FEDFUNDS data
Graph #3 shows the interest rate. The source data is gray. The smoothed data is red. The value of the smoothing constant is 4, as the legend indicates. The same details apply to Graph #4:

Graph #4: Smoothing the RGDP data
I put the two smoothed series together in a scatterplot, with GDP on the horizontal and interest on the vertical. Tried to make the dots pretty. Connected them with thin gray lines. And added a linear trend line, in black. Here is the result:

Graph #5: RGDP and the Real FedFunds Rate with a Linear Trend Line (smoothed data)
The RGDP values shown on the horizontal axis are for quarterly data. The center of the dot cluster (call it the average growth rate) appears to be somewhere between 0.5 and 1.0. It's a low number because it is a quarterly rate. Annual rates would be, ballpark, four times bigger. That would give an average real growth rate between 2% and 4% per year, which sounds about right.

The straight black trend line tilts upward to the right. Doesn't look like much, but it probably slopes more than you think. The trendline formula says the slope is 0.4876. That's almost 0.5. If the slope was 0.5, Y would go up by half of X, and the trend line would go up six inches for each foot it goes to the right. That's almost as steep as a flight of stairs. Steeper than it looks.

For some reason whenever I see a trend line on a scatterplot, the trend line is straight. A glance at the scattered dots should tell you there's no chance the trend is a straight line. But straight-line trends are commonly used on scatterplots. Maybe that has to do with the way economists think.

I made a copy of Graph #5 and changed the trend line to something other than a straight line, just to see how it looks. It looks like Poirot's moustache:

Graph #6: RGDP and the Real FedFunds Rate with a Polynomial Trend Line
The trend line is in the same place, and it still slopes up to the right. But along the way, it curves up and down. I can't tell you much of what those curves might mean, but I can tell you the trend is not a straight line.


I wanted a better look at changes in the scatterplot trend. I thought I might split the cluster down the middle, and get a trendline for each half. Then I got bold and decided to split economic growth into four overlapping subsets so I could see four overlapping trend lines.

I inserted four new columns into the spreadsheet, alongside the smoothed data. I used formulas to put values into these columns, based on growth rate limits I picked for each subset. This gave me the values in chronological order, with blank cells where the values were outside the limits.

Then I made a scatterplot, and it was garbage. Excel doesn't do what I expect when there are blank cells intermixed with the values. But I didn't know that yet. So I tried again. This time I subsetted the interest rate data instead of the growth rates.

This time, all the blank cells were interpreted as zero values. I got a whole lot of dots at the zero level, and I couldn't get rid of them. That's when I figured out the blank cells must be the problem.

The question then was how to convert one column of numbers into four columns based on specified value limits, without having blank cells mixed in with the data. The answer of course was VBA.

I wrote a routine to arrange the data in a way that satisfied both Excel and myself, and at last I got a look at the trends of the subsetted data:

Graph #7: The Scatter Data split out as Low Growth, High Growth, and Intermediate Levels
I got four overlapping trend lines. These lines occupy the same general location as the overall trend line shown on Graph #5. The trend lines, taken together, show a positive correlation similar to the overall trend: lower on the left, higher on the right. However, three of these four trend lines are downsloping. They show negative correlation. They contradict the overall trend, and they contradict Richard Werner.


After a pointless argument with myself that lasted much too long, I decided to write more VBA, to subset the scatter data on interest rate values this time rather than growth rate values.

The code writer complained that he already did the work and why should he have to do it again. The econ hobbyist pointed out that the central bank changes the interest rate on purpose, so the interest rate subsets must be more informative than the growth rate subsets and the code writer should have known which data to subset the first time around. The code writer gave us the finger. But he eventually admitted that his outrage was no more than a way to postpone the inevitable. The matter was finally settled when the blogger pointed out that he had to stop blogging so that the code writing could commence.

I looked at Graph #7 and divided up the vertical axis to make four overlapping groups. Then I copied the code I used to make Graph #7 and tweaked it for #8. The code revision took less time than the argument.

Here's what I got:

Graph #8: The Scatter Data split out as Low, High, and two Intermediate Interest Rate Ranges
This time, three of the four subsets show positive correlation. One shows negative.

I don't know, though. Take the high and low trendlines on Graph #8 and throw them away. Keep the two in the middle. They point up. The space between these two trendlines appears to be the same space where we find all four trendlines of Graph #7. But three of those four trendlines are pointing down. It looks like you could get any result you want, if you pick the right dots.

Something is wrong here. The trend is what it is. We must be doing something wrong if we can make the trend slope this way and that. We must be doing something very wrong.


I think I know what the problem is: The trends we've created here are long-run trends. They reduce  more than half a century to only "up" or "down". (The correlation is positive, not negative, Werner says.) Yes, we cut off the data at the crisis. Yes, we stripped away the inflation. But too much variation remains in our fifty-plus years of dots and data. Too much for one trend line. We still have the golden age, early on. And though we removed inflation, we still have the multiple recessions that occurred at the time of the Great Inflation. Then we have the changes in policy that began around 1980, and the change in the trend of interest rates from uphill to downhill. And we have the gradual but persistent slowing of economic growth for the full extent of our fifty-plus years. These factors and others throw monkey wrenches at our scatterplot trend.

I think we need shorter trends. We need to evaluate shorter time periods. To answer the obvious questions (How short? Where shall we start them and stop them? How can we justify our choices?) consider the data we are evaluating: It is economic growth, and the interest rates which may or may not affect that growth. It makes sense, I think, to base our time periods on the business cycle.

No, you know what? Between one recession and the next there is sometimes a low point of growth. Sometimes more than one low point. To shorten and simplify trend segments in the scatter, our subsets can stop at every low point. So let's not say business cycles. Let's say growth cycles instead -- or, not even cycles, but loops. Growth loops. That's it, growth loops.

I dug up an old spreadsheet and plugged in the data we've been developing here. Changed a few graph titles and some range names. Put Xs in the MinGrowth column at the low points of growth. And clicked a couple buttons to get some graphs. Here is the first one:

Graph #9: The Business Cycle of 1957-1960
Against a background showing the whole scatterplot, the graph highlights the data points of the period identified in the subtitle line. The first dot of the series is green and the rest are red. Red lines connect the highlighted dots in chronological order.

The black trend line for the highlighted dots shows a positive correlation (higher on the right) as Richard Werner says. But, oddly, what happens with the dots seems to contradict Werner. After the first three dots (green, red, red) the dots start to go higher, meaning the interest rate was rising. The horizontal distance between the dots gets smaller, meaning increases in the growth rate are getting smaller. Then, after the rightmost red dot, the RGDP growth rate falls as the dots step to the left.

Based on the data values shown here, interest rate increases after the third quarter of 1958 appear to have caused economic growth to slow. The story these dots tell matches the central bank narrative that Richard Werner rejects.

The trend line displays the positive correlation that Werner points out, but the dots behave as the central bank describes. The dots are saying that Werner's positive correlation is not relevant.

By the way... The same RGDP and the same real interest rate for the same dates we see on Graph #9, but without the smoothing the HP calculation provides, looks like this:

Graph #10: Same Data as Graph #9, but Without the Smoothing
A growth loop of sorts is still visible here, in red. But it's not the same. The smoothed data definitely makes the shape more visible. But if you want to say that I have not preserved the shape of the unsmoothed data, I refer you to Graphs #3 and #4.

The trend line for this unsmoothed data is high on the right, as for the smoothed data.What the dots have to say is less clear. But at low interest rates growth is increasing; rising rates put a halt to the increase; and high interest rates leave us with reduced growth. The dots reiterate the central bank narrative, despite the positive correlation shown by the trend line.



Not every smoothed growth loop has a trend line that agrees and dots that disagree with Werner, as the first one does. Many of them show small clusters or tight groups, and are difficult to read at all. Some of these might make better sense if combined with an adjacent growth loop. I didn't look into that.

I made 16 subsets of the "smoothed data" scatterplot. The subsets run from low to low of the smoothed RGDP growth rate, with the lows sometimes at recessions and sometimes between recessions. On each graph, the green dot indicates the start of the subset. The last of the red dots, then, becomes the green dot of the next graph. Here are all 16 subsets:

Graph #11: The 16 Subsets (MinGrowth to MinGrowth) of the Scatter
I could tell less by looking at the graphs than I expected. So I made a table listing the start date, end date, and slope of each subset, noted some features for each subset, and got total counts for each feature. Here's the table:


Sixteen subsets total. Half of them slope up to the right (positive correlation) and half slope down to the right (negative correlation). The average of all 16 slope values is -0.342, an overall negative correlation that stands in contradiction to the positive correlation Richard Werner finds in his scatter plots.

(Note that the positive correlation Werner finds in his scatterplots, like the trend line he does not draw, is based on the whole set of dots, not on sequential subsets of the dots. A trend line based on the whole collection by design ignores the economic forces that put any one dot in a different position than the preceding dot. It ignores economic forces, while pretending that economic forces are best described by the data set as a whole.

This problem arises not only here, but also with the Phillips curve and Okun's law. Anyone who bothers to look will discover the shapes and behaviors visible in sequential subsets of these datasets.)

The average of the negative slope values is -1.391, about twice as far from zero as the average of the positive slope values, which happens to be 0.707. (Oddly, too, the slope of the 1997Q4-2001Q2 period is 1.414.)

For the whole 16 subsets, I count nine that support the central bank narrative, where a rising interest rate is associated with slowing economic growth. The relation is sometimes concurrent and sometimes sequential. For the whole 16 I count five that contradict the central bank narrative, either a falling interest rate associated with slowing growth, or a rising rate with rising growth. I count two subsets which neither support nor contradict the narrative.

Of the nine subsets that support the central bank narrative, four show a positive and five a negative trend slope. Of the five that do not support the narrative, three show positive and two show negative slope.

I could not resist splitting the 16 subsets into "first 8" and "last 8". The first half ends and the second half begins with 1980Q2. The first half runs 22½ years, if my fingers were up to the counting of it, and the second half 26½ years. From start to finish, each half has nine growth minimums. Okay, that makes sense, as the subsets begin and end at growth minimums.

For the first half, the average slope of the trend lines is 0.265. For the second half, -0.949. For the first half, there are six positive and two negative slopes. For the second half, just the reverse. For the first half, a rising interest rate leads to slowing growth 6 times out of 8. For the second half, 3 times. For the first half, a rising interest rate leads to rising growth once. For the second half, a falling interest rate leads to slowing growth four times.

That's all the stats I have.

Conclusion? Policy may not be as simple as "By lowering rates, central banks accelerate growth and by raising rates, they slow it." But central banks surely do not have it all wrong.

Thursday, March 23, 2017

How could I say such a thing?


Couple weeks ago I showed this graph:

Graph #1
I said

"Growth definitely slowed when the interest rate went up. Growth slowed because the interest rate went up."

Commenting on the post, Jim quoted me and said

I can't understand how you can look at that graph and make such a statement. It seems pretty obvious to me that Fed interest rates are lagging behind GDP which suggests the correct conclusion is that the economy is driving Fed interest rates.

Well...

Graph #2, Recreated from Scratch to Match Graph #1, and marked up

Like that.

Blue accelerated out of the 1954 recession. Red noticed, and went up faster in early 1955.

Blue slowed slightly then, but not enough. Red went up faster again in the second half of 1955.

Blue slowed more, and ran parallel with red until 1957.

Growth definitely slowed when the interest rate went up. Growth slowed because the interest rate went up.

Wednesday, March 22, 2017

When did the Federal Reserve switch from CPI to PCE?


PCE and CPI Inflation: What’s the Difference? at the Federal Reserve Bank of Cleveland:

The Federal Reserve, however, states its goal for inflation in terms of the PCE.

//

Two Measures of Inflation and Fed Policy by Jill Mislinski:

The Fed is on record as using Core PCE data for its primary inflation gauge.

//

I say CPI, you say PCE by Phil Davies. At the Federal Reserve Bank of Minneapolis:

The Fed switched from the CPI to the PCE in 2000.

//

Now we know.

Saturday, March 18, 2017

Notes on the Measurement of Unemployment


The Persistence of Memory

i saw...
somebody said the calculation of unemployment has not changed.
they said it vaguely, so that it wasn't quite a lie.
but it is not true.
3:16 AM 3/16/2017
a couple days ago I saw it.

// Here it is:

The White House Takes Its Attacks On Jobs Data To A New (And Dangerous) Level
by Ben Casselman at five thirty eight
filed under Data Integrity
:)

https://fivethirtyeight.com/features/the-white-house-takes-its-attacks-on-jobs-data-to-a-new-and-dangerous-level/

"(When pressed by Tapper, Mulvaney acknowledged that he didn’t think the Bureau of Labor Statistics had changed the way it collected jobs data since Trump took office.)"

"... there is no conspiracy here. Obama didn’t change the definition of unemployment, which has been essentially unchanged for decades."

The words "essentially unchanged for decades" link to
https://www.bls.gov/cps/faq.htm#Ques12

Ques12 is "Have there been any changes in the definition of unemployment?"

The answer is
"The concepts and definitions underlying the labor force data have been modified, but not substantially altered, even though they have been under almost continuous review by interagency governmental groups, congressional committees, and private groups since the inception of the Current Population Survey."

So yes, there have been changes. But the answer is not specific as to what those changes were.

If memory serves, under Clinton they added the condition that if you stop looking for work, you are no longer counted as unemployed. Clinton or Reagan, I forget. I think Reagan changed the inflation calculation and Clinton changed the unemployment calc.

Here you go:
"Yes, there have been modest shifts through the decades in how unemployment is defined, the last ones in 1994." -- Justin Fox at Bloomberg

Clinton.

What I can't figure out is why there is no discontinuity in the data at 1994. Can't see one on a graph. I've looked.

//

The Bloomberg article starts out very interesting, then drops off to asking
"Does this mean that the unemployment rate is some sort of “big lie” or “hoax...?”
(Can't you just deal with the economics? If you are addressing the question of the 'big lie' then you are NOT doing economics)
Then it gets interesting again.

The article challenges my memory:
"And when the U.S. government finally started measuring unemployment on a monthly basis in 1940 it was with a similar understanding that you didn’t count as unemployed unless you really wanted to work."

The "similar understanding" is a reference to "men who would have liked to work if they could have found a job that paid as much as they had been earning before."

But no, that's not really the same as no longer looking for work...

Recommended reading: What's Really Wrong With the Unemployment Rate by Justin Fox at Bloomberg. It gets specific about those changes in the unemployment calculation.

But I remember that NY Times article I read back in the '90s...

Friday, March 17, 2017

Suddenly it's the 1870s again


Justin Fox at Bloomberg on Carroll D. Wright in the 1870s:
As David Leonhardt explained in a great New York Times column in 2008, this all started in the U.S. with Carroll D. Wright, who as head of the Massachusetts Bureau of the Statistics of Labor during the economic hard times of the 1870s set out to measure joblessness while excluding people he considered malingerers:

The survey asked town assessors to estimate the number of local people out of work. Wright, however, added a crucial qualification. He wanted the assessors to count only adult men who “really want employment,” according to the historian Alexander Keyssar. By doing this, Wright said he understood that he was excluding a large number of men who would have liked to work if they could have found a job that paid as much as they had been earning before.
Wright went on to become the first commissioner of what is now the BLS.

...if they could have found a job that paid as much as they had been earning before.

Yeh.


Maynard Keynes in 1936:

If, indeed, it were true that the existing real wage is a minimum below which more labour than is now employed will not be forthcoming in any circumstances, involuntary unemployment, apart from frictional unemployment, would be non-existent. But to suppose that this is invariably the case would be absurd.

... if they could find a job that paid less, they would take it. They wouldn't prefer it, but if nothing else was available...



Scott Sumner in 2015:

I think they were unemployed because of sticky wages, and that if workers collectively accepted lower wages then we would have had full employment in 1936.

... they refused to work for less...

Thursday, March 16, 2017

Why the sudden change?


Central Bank Assets as a Percent of GDP:

Graph #1: Running Close to 5% Until the Big Surprise
(Annual data. Last date shown is 2014.)
The first question has to be Why? Why the sudden change?

My answer: The central bank suddenly felt the need to "catch up".

The line runs flat
Central bank assets ran flat from 1960 to 2008: a little higher at the end, a little lower in the middle. Central bank assets ran flat because the Fed was controlling things. The big surprise in 2008 was the discovery that they were not controlling the right things. And suddenly, there was a lot of catching-up to do.

You should be asking: Catching up to what?

Good question. The purpose of controlling central bank assets is to put a limit on the availability of money. And, from 1960 to 2008, they kept the limit around 5% of GDP. But that doesn't mean the money supply was 5% of GDP, because the money supply expands above the base provided by the central bank -- like dough rising to make bread.

The money supply increases when we borrow money. So you can imagine our borrowings must have some relation to the Central Bank Assets graph.

Note that our borrowings continue to exist until we pay back the borrowed money. The accumulation of borrowings is called "debt". So you may imagine that our debt must have some relation to the Central Bank Assets graph.

Yeah:

Graph #2: Central Bank Assets (blue) and Private Non-Financial Borrowings (red)
Our accumulated borrowings increased more or less continuously, all the while the central bank was "controlling" things. Then suddenly, something snapped. Borrowings started to fall. And the central bank had to make a quick adjustment to bring its assets back in line with borrowings.

The problem (in case you missed it) is that the central bank was keeping its assets in line with GDP but what we really needed was to have those assets more in line with our borrowings. Here is assets relative to borrowings:

Graph #3: Central Bank Assets relative to Private Non-Financial Borrowings
This one looks a lot like the first graph except, if you notice, the "flat from 1960 to 2008" is now a decline. In 1970, central bank assets were around 6% of our borrowings, the same level you see on graph #1 for assets relative to GDP. But by the time of the crisis, that asset level had fallen to not much more than 3% of accumulated borrowings. Half as much.

This graph starts near the 6% level. But if the data was available, I expect you'd see the ratio much higher in the 1950s. That would make the recent high look less daunting. And you would see that the central bank "backing" behind private bank assets was quite high early on, but fell over the years to a low in our moment of crisis. Then in 2008 the central bank suddenly seemed to discover something it should have known all along, and started pushing its assets up, relative to private borrowings.

This next graph uses different data to tell the same story. And it goes back to the 1950s, so you can see the ratio was much higher then:

Graph #4: Fed Holdings of Federal Debt relative to Private Borrowings
On this graph the debt measure is bigger because it includes financial as well as non-financial debt. And the central bank asset measure is smaller, as it includes only the central bank holdings of Federal debt. But the downtrend since 1970 is visible just the same. And the early years show an even bigger downtrend from an even higher level. The ratio was much higher in the 1950s than it is at present.

The Fed was "controlling" things all along. But it was looking at the wrong things. It was looking at assets relative to GDP. It should have been looking at assets relative to the private-sector money that was built upon those assets. It should have been looking at its assets relative to private sector debt.

To prevent the decline that ended in disaster, the Fed would have had to increase its assets faster than it did since the 1970s, or reduce the growth of private sector debt. Since the 1970s or earlier. But nobody likes either of those options. Increasing the assets is associated with inflation. Decreasing private borrowing is associated with economic stagnation.

What to do, what to do.

We need a judicious combination of the two options. A well-designed policy could have increased central bank assets and restrained private debt growth to keep the ratio as stable as the ratio we saw on graph #1. Policymakers do have the ability to keep such ratios stable. They just don't know which ratio to stabilize.

With less borrowing, we'd have less growth. But with more central bank assets we'd have more growth.

With more central bank assets, we'd have more inflation. But with less borrowing, we'd have less inflation.

Meanwhile, there would be less private debt in our economy. There would be less financial cost competing for dollars with wages and profits. Finance -- or "rent" as people call it -- would be reduced. So the cost of our output would include less financial cost. Our output would be a better bargain as a result: more value per dollar. This would allow wages and profits to rise. And it would make us more competitive in world markets.

See how it works? It's a "euthanasia of the rentier" thing. But you knew that.

Wednesday, March 15, 2017

From 40% of GDP to 140%


Stock market capitalization as a percent of GDP:

Graph #1: "Total value of all listed shares in a stock market as a percentage of GDP."
This series used to run close to 40% of GDP. These days, the swings are 40% of GDP.

Tuesday, March 14, 2017

A wish


The most that the natural-rate hypothesis can tell us is that if an economy is operating at its natural rate of unemployment, monetary expansion cannot permanently reduce the rate of unemployment below that natural rate. Eventually — once economic agents come to expect that the monetary expansion and the correspondingly higher rate of inflation will be maintained indefinitely — the unemployment rate must revert to the natural rate.

I wish economists would stop focusing on "monetary expansion" and start focusing on the ratio of accumulated debt to circulating money. Because changing that ratio changes the natural rate.

Or, to change the wording a bit and use Richard Werner's wording:

I wish economists would stop focusing on "monetary expansion" and start focusing on the ratio of accumulated debt to the quantity of credit creation. Because changing that ratio changes the natural rate.