Wednesday, May 25, 2016

Less aimless, a closer look

In the previous post I showed household debt as a portion of total private non-financial debt. About half, but it varies, and it varied higher on the approach to crisis. Back in the normal range now, high, but high in the normal range and trending down.

I highlighted two peaks that look similar. They show similar rates of increase on the approach to peak. They show similar rates of decrease on the decline from peak -- and faster decline than increase for both.

In addition, they both peak near 0.54 on the vertical scale. And they both occur during times of superior economic performance. I'm not saying anything about cause or effect or significance; it's far too soon for that. I'm just pointing out similarities.

Graph #1: Household Debt relative to Total Private Non-Financial Debt
highlighting similarity between the 1960s and the 1990s
Looking at it a little more, the peak in 1980 shows the same pattern of rapid increase followed by more rapid decline. This peak is obviously lower than the other two, and people don't often describe the 1976-1982 period, say, as a time of superior economic performance. Still, the pattern is similar.

So I thought I'd take a look at all three peaks. I started out by bring the FRED data -- the "total credit to private non-financial sector" series is copyright BIS (but FRED is down again so I can't get their preferred copyright claim) -- bringing it into Excel and using Kurt Annen's Hodrick-Prescott code to smooth out the jiggies:

Graph #2: Ratio of Household Debt to Total Private Non-Financial
Debt (blue) and the Hodrick-Prescott Trend (red)

Next I changed the blue FRED data to gray so it doesn't stand out. I changed the red Hodrick-Prescott line to blue, to make it our starting point. And in red I added three subsets of the H-P data, one for each of the three peaks discussed above.

Those peaks occur at 1964Q2, 1979Q4, and 1996Q3. Each red subset shows the peak, 16 quarters before the peak, and 10 quarters after.

Graph #3: Household-to-TPNF Debt, and Three Similar Subsets
Then I pulled out the subsets to take a closer look. The blue and green lines on the next graph are the peaks in the 1960s (blue) and the 1990s (green). The two are remarkably close.

The red line is the 1979Q4 peak. It shows the same general shape as the blue and green. But the red is significantly lower, just as the October 1979 peak is lower on Graph #3.

Graph#4: The Subsets Highlighted on Graph #3
Blue=1964 peak, Red=1979 peak, Green=1996 peak
On the X axis, Q is the peak quarter for each line. Q-16 is 16 quarters before peak. Q+10 is 10 quarters after peak.

I'll say it again: The blue and green lines, 30 years apart chronologically, are remarkably, remarkably close as a portion of total private non-financial debt. I'm not saying anything about cause or effect. But maybe there is something to be said for significance.

Monday, May 23, 2016

Aimlessly looking at economic data

Spend enough time aimlessly looking at economic data and eventually you'll find something interesting. I had total private non-financial debt on the screen, and suddenly wondered how it compares to consumer debt. Consumer debt is a subset of total private non-financial so it is worth a look.

Graph #1: Household Debt relative to Total Private Non-Financial Debt
First thing I notice: two big humps -- one in the 1990s and one in the 2000s.

Second thing: It is jiggy early, till around 1990, and smooth after that.

Third, it's about fifty-fifty. From 1950 to 2000, the curve is pretty well centered on the 0.50 line, and pretty well contained between 0.46 and 0.54. In other words, household debt runs between 45% and 55%  of private non-financial debt until just after the year 2000. Then household debt goes high, something I've heard other people say.

If the household portion of private non-financial debt is roughly half the total, that means the rest of private non-financial debt is also roughly half the total. Or again, was roughly half the total, until the year 2000. Something I didn't know.

Fourth, the peak in the mid-1960s and the peak in the mid-1990s both top out at about 54% (0.54 on the graph). That's quite a coincidence. In addition, the upslope in the 1960s is comparable to the upslope in the 1990s. The two downslopes are similar also:

Graph #2: Similarity in the 1960s and 1990s
What makes this interesting is that the 1960s and the 1990s are our two best decades of economic performance.

At the high point of the 1960s,

Apparently FRED is down.

Saturday, May 21, 2016

Self-correcting? What do you mean by that?

Syll quotes Krugman

... we do want, somewhere along the way, to get across the notion of the self-correcting economy, the notion that in the long run, we may all be dead, but that we also have a tendency to return to full employment via price flexibility

In response Syll offers "what Keynes himself wrote", here shortened:
On the one side were those who believed that the existing economic system is in the long run self-adjusting ...

Those on the other side of the gulf, however, rejected the idea that the existing economic system is, in any significant sense, self-adjusting.

The strength of the self-adjusting school ... has vast prestige and a more far-reaching influence than is obvious. For it lies behind the education and the habitual modes of thought, not only of economists but of bankers and business men and civil servants and politicians of all parties …

Thus, if the heretics on the other side of the gulf are to demolish the forces of nineteenth-century orthodoxy … they must attack them in their citadel … Now I range myself with the heretics.

Myself, I like to say that if we want to fix the economy we have to give it what it wants. People don't seem to like that for some reason. Personifying the economy maybe? Pffft.

The economy is a system. Push on it here, and it moves over there. Economics is the attempt to explain why that happens. I prefer to say: economics is the attempt to understand why it happens.

I say things like: Jobs? You think 'jobs' is the problem?? Okay. But it's our problem. A problem for people. It's not a problem for the economy. If you want jobs from the economy, you have to give the economy what it wants.

I say things like: The economy does not care about inflation or unemployment. Those are not problems for the economy. They are problems for people. For the economy, they are simply ways to correct imbalances.

I say things like: We should use policy to keep the ratio of private debt to public debt at a low level, a level where the economy constantly wants to grow vigorously.

So yes, I think the economy is self-correcting. But not in the way most people think. I think the economy self-corrects to rectify imbalances that the economy doesn't like. For example, if you put too much money in the economy, the economy doesn't like it. Prices go up until there isn't too much money any more, and then prices stop going up.

Some people say the economy is self-correcting. They mean unemployment will go down all by itself without government intervention.

Some people say the economy is not self-correcting. They mean unemployment won't go down by itself, and government intervention is needed.

Both sides use the phrase "self-correcting" to refer to things we want from the economy. To me, any discussion about whether the economy is self-correcting can only refer to problems that the economy recognizes as problems, and whether the economy can rectify those kinds of problems.

The answer is: The economy will attempt to rectify those problems. But it may be hindered by policies imposed by people who design policies to fix things that people see as problems, rather than fixing things that are problems for the economy.

Friday, May 20, 2016

An economist praying to the Natural Rate of Unemployment (?)

Happened to take a look at the so-called Natural Rate of Unemployment at FRED:

Graph #1
It's all steppy! I don't remember that. Found an old version at Wikia:

Thursday, May 19, 2016

In the '60s, they thought four percent.

One of those times when I blurted a number from memory instead of checking it first. The 4% number in the title of this post, stated in yesterday's remarks: Four percent unemployment is 'Full Employment'. Now I'm checking it.

I thought I got it from an old Statistical Abstract, from the '70s.

Took a while to find it. I knew I looked at it before. Found a file on the old computer, a file from 2009.

But no. That was Potential GDP growth. Four percent annual growth. That would look like the red line here:

We're generally a little shy of that.

Grubbed around some more then, and ended up looking in my old Econ textbook (McConnell, Economics, sixth edition, 1975). Found the quote (page 194) that maybe put the 4% number in my head:
There is disagreement here. Some economists look back to the unemployment figures of the prosperous period from 1966 to 1969 and argue that unavoidable unemployment is only about 3.5 percent. Others contend that certain groups, such as those composed of women and young workers who traditionally have quite high unemployment rates, are becoming more important in the labor force. Therefore, the unavoidable minimum of unemployment should be revised upward to 4.5 or even 5 percent. We will settle for the 4 percent figure, recognizing that it is open to question.

Wednesday, May 18, 2016

Steppiness aside ...

Happened to take a look at the so-called Natural Rate of Unemployment at FRED:

Graph #1
It's all steppy! I don't remember that. Found an old version from 2011:

Graph #2
Heh, from even before FRED put their logo on their graphs. Tentative but not steppy.

I wanted to compare the two versions of the graph at ALFRED. Clicked the link from the FRED page to bring up NROU at ALFRED. It always comes up as a bar graph at ALFRED -- maybe so we know we're not in Kansas anymore. (Or wherever FRED is.)

I switched the setting to make it a line graph and ...

Graph #3
apparently the steppiness is new. This graph shows the two most recent vintages. The steppiness is the main difference. Otherwise the two lines are mostly the same, except the newer line is lower since 2007.

Let me say that again. The older line, the blue one, is from ten months ago. The newer line, the red, shows changes going back to 2007.

Well, I still want to compare the new one to the one from August 2011:

Graph #4
Yeah, back in 2011 they thought the natural rate would be high forever.

Since the subject has come round to questioning the NROU numbers, did you notice that on all these graphs a vigorous uptrend begins before 1960? I think the uptrend misrepresents the economic conditions of the time. Golden age, remember?

The Natural Rate of Unemployment is the lowest level of unemployment at which inflation remains stable. When they estimate the Natural Rate of Unemployment they take inflation into account. The NROU depends on unemployment and inflation.

If you add the unemployment rate and the inflation rate together to get the "misery index" and then compare the misery index to NROU ...

Graph #5
the Misery Index spikes briefly in 1958, then runs low and stable for near ten years. I think the NROU, which runs perfectly flat thru most of the 1950s, should have continued that same path into the latter half of the 1960s. Or lower. In the '60s, they thought four percent.

And then, in the latter 1990s, the Misery Index starts climbing and continues upward for a dozen years. Yet the NROU runs flat, then falls until it is forced upward by crisis and recession.

It seems to me that a lot of wishful thinking is involved in the calculation of the Natural Rate of Unemployment.

Tuesday, May 17, 2016

Seeing things

As I noted before, I'm trying to develop the VBA code to "lag" data on a graph in Excel. But after working for a week and a half on it, I got so bogged down that I decided to set the whole thing aside and start fresh. Maybe what I've learned so far will lead me down a better path this time.

Part of the trouble I'm having is that I have to see what I want to do before I actually do it. To help me see what I want, I decided to write about it. So here we are.

At the moment I have this graph:

which is based on this made-up data:

There's another column on the sheet, for "Lagged" data. When I put numbers there I get a blue line on the graph. Right now that column is blank, so there is no blue line. I want to take the gray line numbers, "lag" them, and put them in the blank column. The graph will then have a blue line showing the lagged data.

But it's easier said than done.

I also have a table of Lag Dates:

This is where I describe the lagging I want to do. For example, the high point of the red line on the graph is at 2007. The high point of the gray line is 2006. I want to lag the 2006 data one year to make the blue line peak in 2007 with the red. Likewise, I lag the low gray point from 2010 to 2011 for the blue line.

I did a couple other things to make it interesting. The table doesn't say anything about lagging after 2011, even though the data goes out to 2015. (And yes, the lag-able data stop at 2015 even though the graph continues on to 2016.)

And in the first row of the table, the lag-able data begins in 2002, but I lag it back to 2001. I can picture that. But what would happen if I did it, and there was already data for 2001? The original 2001 data would get pushed off the graph. That's how I see it, anyway. And like I said, I have to see it before I can make it happen.

According to my table of lag dates, I want to take the value for 2002 and move it back to 2001. And I want to take the value from 2006 and move it forward to 2007. So data from the five-year period 2002-2006 has to stretch out to cover the seven-year period 2001-2007. I have to figure seven equally-spaced values that give me a line that looks like the line I get from from the five "given" values I started with. It's a little messy, but I did have that working.

According to that table also, five values for 2006-2010 move as a group to the five years 2007-2011. There's no stretching this time. I can just copy the values from the "given" column to the "lagged" column.

Now we're at the end of the Lag Dates table. But we are still in the midst of the data. How do I handle the remaining data? Maybe I should shift all the remaining values, lagging them one year as 2010 is lagged to 2011.

Or maybe I should assume that the last given value does not move, because the lag table does not tell me to move it. Then I will have to squeeze the 2010-2015 data into the years 2011-2015. That means I have to calculate values again. Yeah, this is the way to go, even though it is more work.

I can't justify lagging data when a lag is not specified in the Lag Dates table. If I want to move the 2010-2015 data to 2011-2016, all I have to do is add a couple dates to the table. So I can do it that way if I want. But if I don't specify any lag, the code shouldn't create any lag. The code shouldn't take the initiative.

At least, that's how I see it.

The interesting thing doesn't happen until after I get the lag code working. At that point I'll start using actual econ data and I may end up with a dozen or more lines in my Lag Dates table.

The interesting thing will be to make a graph of the lag times, to see how the lag changes over time. I expect to find that some lags are related to the level of private debt. I expect to find that a changing lag describes the changing metabolism of the economy. I expect to find all kinds of fascinating things.

Time to go write code.

Monday, May 16, 2016

"... all that stands between a future for mankind and the end of civilization."

Required reading: Open Borders for Capitalism by Mathijs Koenraadt.

via Reddit.

From Latifundia at
A latifundium is a large piece of contiguous land that belongs to a single individual or family.

From the beginning, latifundia were commercial enterprises dedicated primarily to growing produce and livestock for profit, both for distant and nearby urban markets.

Ancestors of slave plantations, the ancient Roman latifundia have been described as the model for imperialism, colonialism, and modern slavery.

In Nero's time (37–68 CE), Pliny tells us, half the land of the North African province was divided up among six patricians and organized in huge latifundia farmed by slaves and native peasants.

In the final years of the Roman Empire, these slave workers were replaced by coloni, small tenant farmers who became permanently attached to the estates (glebae adscripti ) and evolved eventually into feudal serfs. Latifundia persisted in Italy, Gaul, Spain, southern Britain, along the Rhine, and in the eastern Byzantine Empire for centuries after the fall of Rome
You get the idea.

Saturday, May 14, 2016

'Soros retorted with a different strategy: “Go for the jugular.”'

From The Trade of the Century: When George Soros Broke the British Pound at Priceonomics:
In 1992, George Soros brought the Bank of England to its knees. In the process, he pocketed over a billion dollars. Making a billion dollars is by all accounts pretty cool. But demolishing the monetary system of Great Britain in a single day with an elegantly constructed bet against its currency? That’s the stuff of legends.

A small tax on currency exchange would be a practical measure.

It's a very good article, by the way.