I admire the effort, but not the approach to problem-solving

There was an ad on TV this morning for OASAS. They pronounced it oasis (because that's just the way things are these days). The catch-phrase that got my attention was "harm reduction strategies".

I looked em up. OASAS is the NYS Office of Addiction Services and Supports. Their mission is to improve people's lives.

There are TONS of similar agencies and groups and even individuals also, working to improve people's lives. And I should say first, that this is admirable work. But it sure would be nice if we didn't need so much of it.

Google turns up almost 9 billion results, for a world of less than 8 billion people:

 

Economic troubles that are widespread and spreading, persistent and growing worse are indications that the cause is macroeconomic in nature. Our world is full of such troubles. We try to solve them by treating them as microeconomic troubles, trying to make the world a better place, one person at a time.

I applaud the effort. But the success would be greater if we would fix things from the macroeconomic end as well.

The memorable boy

Adam Smith, The Wealth of Nations, Book 1, Chapter 1, from Project Gutenberg:

Men are much more likely to discover easier and readier methods of attaining any object, when the whole attention of their minds is directed towards that single object, than when it is dissipated among a great variety of things. But, in consequence of the division of labour, the whole of every man’s attention comes naturally to be directed towards some one very simple object. It is naturally to be expected, therefore, that some one or other of those who are employed in each particular branch of labour should soon find out easier and readier methods of performing their own particular work, whenever the nature of it admits of such improvement. A great part of the machines made use of in those manufactures in which labour is most subdivided, were originally the invention of common workmen, who, being each of them employed in some very simple operation, naturally turned their thoughts towards finding out easier and readier methods of performing it. 

Whoever has been much accustomed to visit such manufactures, must frequently have been shewn very pretty machines, which were the inventions of such workmen, in order to facilitate and quicken their own particular part of the work. In the first fire engines {this was the current designation for steam engines}, a boy was constantly employed to open and shut alternately the communication between the boiler and the cylinder, according as the piston either ascended or descended. One of those boys, who loved to play with his companions, observed that, by tying a string from the handle of the valve which opened this communication to another part of the machine, the valve would open and shut without his assistance, and leave him at liberty to divert himself with his play-fellows. One of the greatest improvements that has been made upon this machine, since it was first invented, was in this manner the discovery of a boy who wanted to save his own labour.

This is what I'm doing about it

Yesterday I showed a graph of two FRED datasets with exactly the same name: "Monetary interest paid: Government: Federal". The names are the same, but the numbers differ substantially. What to do, what to do?

The series with lower numbers starts in 1960, same as the "Monetary interest paid" (in total) series. When the components of interest paid are added up, it is probably this series (with lower numbers) that are used for interest paid by the federal government. However, as I pointed out yesterday, both datasets are current. It's not that one is the "old" data and the other is "new". Both sets of numbers are reported annually.

I prefer the series that starts before 1960. I always want all the data I can get. 

Also (without knowing the facts) I prefer the series with the higher numbers because it is probably more honest. 

Yesterday I was frustrated because I couldn't find out why there were two different sets of numbers. Today I'm using my judgement. If that's not good enough, then they should provide better documentation. I looked. I didn't find any documentation at all. I didn't even find anybody wondering which series to use when.

Anyway, here's what I did. I put FRED's interest paid (in total) on a graph, a fat blue line. Then I added a thin red line showing federal government interest paid (using the low-numbers data). Both these datasets start in 1960 -- that's how I know this must be the federal interest data that they use when they figure the total. Then I added the interest paid by state-and-local-governments, by households, by U.S. business, and by "the rest of the world" to US creditors. Here is the result:

Graph #1: The FRED series that starts in 1960 (blue);
the Sum of Components (red) gives a good match

I made the red line thin so I could see the blue line behind it. The red is centered on the blue from start to finish. So I'm satisfied that I have the right components, and all of them.

Next, I switched the federal government component from the one that starts in 1960 to the one that starts before 1960. Here's the result:

Graph #2: The sum of components (red) now runs on the high side.

The red line is no longer centered on the blue.

Obviously, FRED has all the data. They still track it all. I just don't know why they go with the lower number for interest paid by the federal government.

No matter. I can use the higher number and make my own version of total Monetary interest paid. I can have two versions of it, just like there are two versions of the "Government: Federal" data set at FRED.

Anyway, the gap between red and blue is not so big on the graph.

I don't know what to do with this

Graph #1: Two Measures of Interest on the Federal Debt. They can't both be right.

Two measures of interest on the federal debt:

• The blue one is https://fred.stlouisfed.org/series/A091RC1A027NBEA
  
• The red one is https://fred.stlouisfed.org/series/Y669RC1A027NBEA

It's not like one of them was discontinued. It's not an old version and a new version. It is two current versions. Two sets of books. If that's what they want to do, fine, but I want to know which one would be more useful to me. I want to know what they're leaving out of the one and including in the other. I find nothing on that.

If you look at the big number, the total Monetary Interest Paid data for all sectors including "Government: Federal", it starts at 1960 like the red one on the graph above. All the other components of the big number go back to 1946. It looks to me like they use the federal one that starts in 1960, our red one, when they figure the big number. And all the years before 1960 drop out of the picture.

Why use the federal measure that starts in 1960? I was assuming that it is the more recently created measure -- you know, the one they would say is more accurate. But now I'm not sure about that. I added one more series to the graph, the "current expenditures" version of federal government interest paid:

Graph #2

The new line (green) is a good match to the blue line and not the red. Green is quarterly data, blue is annual; this probably accounts for the small differences between these two. And the green one has the most current data of them all.

So I would say that of the three, the green one is the best one to use, the blue one is second best, and the red one is least worth using. And, since I find no information on the differences between red and blue, I can only confirm my opinion that the red one is the least worth using.

So you see, it doesn't make any sense to me that the red one is the one they use when they add up all the components of interest paid to get total interest paid. I'm at a loss here.

 

I know, this is not the kind of thing you usually find on the internet, when people talk about the interest on government debt. Can't be helped.

What would I be thinkin, to show you this?

Graph #1: Federal Interest Paid (red) and Total Domestic Interest Paid (blue)

Everything you know about Labor Share is wrong

9:44 AM: Hey, I found this on my Test & Development blog, dated January 2020. But I don't find it on this blog, so I'm posting it now. It's like getting one for free.

Is it too early for a sip of single malt?

Ever since Kaldor (1957, 1961) documented his growth facts, the constancy of the share of income that flows to labor has been taken to be one of the quintessential stylized facts of macroeconomics.

-- Michael Elsby et al

If you want to compare one year's GDP to another to see how the size of the economy has changed, it is necessary to use inflation-adjusted values. If you want to see changes in the size of the economy, it is necessary to distinguish between changes in size and changes in the unit of measurement.

But what if you want consider the change in size of some portion of GDP? For example, labor's share of GDP: Would you still want to use inflation-adjusted values? Just thinking about it, here, as an alternative you could look at a ratio of values that are not adjusted for inflation. Inflation cancels itself out of the ratio, and you end up with the equivalent of an "inflation-adjusted" comparison.

Here is the ratio of Compensation of Employees to Gross Domestic Income -- which should look a lot like a graph of labor share:

Graph #1: Compensation of Employees as a Percent of Gross Domestic Income

Something is fishy, though. Graph #1 doesn't look much like this graph of Labor Share:

Note, 3 October 22: One is labor share of business sector output, and the other is labor share of GDI. This could explain why the graphs look different.

Graph #2: Business Sector: Labor Share  (Source: BLS)

The first graph shows one downtrend from 1953 to 2014. The second displays a gradual downward trend from the mid-1950s to the mid-90s, then rapid downward trend from 2001 to 2012.

//

What do experts say about the path of labor share?

• "A detailed description of labor's share of national income in 16 industrialized democracies from 1960 to 2005 uncovers two long-term trends: an increase in labor's share in the aftermath of World War II, followed by a decrease since the early 1980s." -- Tali Kristal
• "Over the past quarter century, labor’s share of income in the United States has trended downward, reaching its lowest level in the postwar period after the Great Recession." -- Michael Elsby et al
• "Figure 1 shows the ... slow and steady decline during the latter half of the 20th century—followed by the sharper decline over the 15 years since then" -- BLS
• "... the BLS measure has a much stronger long-run downward trend than the measure we use." -- EPI [EPI's Figure 2 show uptrend from 1947 to the early 1990s, then downtrend comparable to BLS.]
• "The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain." -- David Autor et al

Tabulated comparison:

Kristal:	Increase before 1980	Decrease since the early '80s
Elsby:		Decrease since the late 1980s
BLS:	Slow decrease 1947-2000	Rapid decrease 2001-2016
EPI:	Moderate increase 1947-1990	Rapid decrease 1992-
Autor:		Decrease "in recent decades"

It's difficult to pin 'em down, but there doesn't seem to be a lot of agreement. And none of them agree with Graph #1 above. However, there is a point of similarity: All of these studies find a sharp decline beginning in the 1980s or later, as we see on Graph #2.

//

I discovered quite by accident that you can duplicate Labor Share for the business sector by taking the ratio of compensation to current dollar output:

Graph #3: Compensation relative to Nominal Output, (red) and Labor Share (blue)

 

 

It is a ratio of nominals that looks exactly like Labor Share.

Just for the heck of it, let's see what it looks like as a ratio of reals. Actually, I looked at this before. I don't remember why. Maybe it didn't occur to me that the ratio of reals should be the same as the ratio of nominals. Anyway, let's do it again.

FRED has the output number. I can use Business Sector: Real Output in place of Business Sector: Current Dollar Output. But I don't find an inflation-adjusted versions of Business Sector: Compensation. Have to make one.

Conveniently, FRED provides Business Sector: Real Compensation Per Hour and Business Sector: Compensation Per Hour. The one relative to the other makes a price index -- the perfect price index to use for deflating compensation.

Here is Business Sector: Labor Share as a ratio of reals:

Graph #4: Business Sector Labor Share as a Ratio of Reals

It's all downhill from the mid-1950s. No sharp decline starting in the early '80s, or the late '80s or the early '90s or the early 2000s. It's all downhill since Kaldor. Sharp downhill.

It's interesting also that the big, jagged movements have disappeared from Graph #4.

The only thing different about the calculation of graph #4 is that it uses inflation-adjusted values. Nothing else in the calculation has changed. So the graph is different because it is a ratio of reals.

But if the Compensation price index was the same as the Output price index, graph #4 would have come out exactly like the Labor Share graph, graph #2. Graph #4 is different because the price indexes are different.

Is it reasonable to have different price indexes for different things? Probably, yeah.

Okay.

Since we have these different price indexes for a reason, it must be okay to use them when the need arises.

When does the need arise? The need arises when you're looking at a ratio of nominals -- a ratio such as Labor Share -- where each data series has its own price index.

If you don't go with the ratio of reals, your graph will be incorrect. If you just assume that inflation cancels itself out of a ratio of nominals, but there are two different price indexes involved, your graph will be incorrect.

If no one uses the ratio of reals when they figure Labor Share, then everyone is wrong. No, no that's not true. The ratio of nominals is valid for micro or for the individual firm. But it is not valid as a macroeconomic evaluation.

In the world of macro, using the ratio of reals, it turns out that Labor Share has fallen faster and farther than we thought.

Okay, go back to your television now.

The peace to end all wars

"But if nations can learn to provide themselves with full employment by their domestic policy (and, we must add, if they can also attain equilibrium in the trend of their population), there need be no important economic forces calculated to set the interest of one country against that of its neighbours."