Monday, April 9, 2018

"the hedonic method"

I'm reading Karl Whelan's A Guide to the Use of Chain Aggregated NIPA Data PDF. Menzie Chinn linked to it, and Justin Fox, regarding errors in the use of "chain-weighted" inflation-adjusted data.

I need some background on "hedonics":

Source: OECD

Source: Abstract, The Hedonic Method by Laura O. Taylor at Springer Link

In economics, hedonic regression or hedonic demand theory is a revealed preference method of estimating demand or value. It breaks down the item being researched into its constituent characteristics, and obtains estimates of the contributory value of each characteristic....
Hedonic models are commonly used in real estate appraisal, real estate economics, and consumer price index (CPI) calculations. In CPI calculations, hedonic regression is used to control the effect of changes in product quality. Price changes that are due to substitution effects are subject to hedonic quality adjustments.
Source: Wikipedia, Hedonic regression

Whelan describes the problem with the old "fixed-weight" method, the problem which led to the adoption of the "chain-weight" method:
... for a given base year, the growth rate of a fixed-weight quantity index tends to increase over time as the output bundle becomes increasingly expensive when measured in terms of the base year's prices. This problem became more severe after the mid-1980s because of BEA's decision to measure computer prices according to the hedonic method pioneered by Zvi Griliches (1961). This approach revealed enormous declines in the quality-adjusted price of computing power and the introduction of these prices accentuated the tendency of fixed-weight GDP to accelerate over time.

"The quality-adjusted price of computing power". That's the "hedonics" thing.

OECD describes quality adjustment:
The process - or the result of the process - of estimating what the market price of a replacement product would be if it had the characteristics of the product it replaces and with whose price its price is to be compared.

BLS explains it less objectively:
The CPI is calculated using prices for a fixed basket of goods and services through time. While the basket is periodically revised to reflect changing consumer expenditures, some items being priced in the sample come and go from the marketplace, making collection of these prices from month to month difficult. When an item is no longer available in the marketplace, a similar replacement item is selected. Often there are no similar items from which to choose, and as a result, a less comparable item is selected, potentially introducing quality change and an associated price differential into the index. The hedonic quality adjustment method removes any price differential attributed to a change in quality by adding or subtracting the estimated value of that change from the price of the old item.

consumerpriceillusion has a different take:
Ostensibly, the CPI is a linear combination of the “prices” of things/stuff consumers could actually purchase weighted by a percentage that the “ideal consumer” spends on any particular stuff/thing in his “ideal” basket. The main problem here is that the “prices” used are not the prices a consumer would actually pay; instead the real price for an item is scaled by what the BLS calls a “Hedonic Quality Adjustment (HQA)”. The HQA was designed to solve a real world problem economists face: the market keeps pumping out new and better devices. In practice the HQA is used to artificially depress the prices used in the calculation of the CPI.

For me... Well, let me tell you about my experience with computers. When I bought my first modem it cost me $150. It was a 300 baud modem. Several years later I bought a 56K modem. It cost me $150. For me, $150 was an acceptable price for a modem.

My first hard drive cost me $400. It was a 40-meg drive. Several years later I bought another hard drive: 400 gig. It cost me $400. For me, $400 was an acceptable price for a hard drive.

In my experience, the price of modems and hard drives didn't go up at all. But if you used hedonics to "adjust" those prices for quality, the prices would have fallen. A lot.

But the prices didn't fall. The technology got better, but the prices didn't fall.

"In practice the HQA is used to artificially depress the prices used in the calculation of the CPI."

Yup.


Oh. The reason this comes up. There is a lot of noise these days about low productivity, and how productivity "really" isn't low. It's just not counted right, they say. Or it's not countable. Or some other story. It's all noise.

It is noise that will eventually lead to a revision in the way productivity is calculated. A revision that makes productivity look better than it is today. A bullshit revision, another one, like not counting people who are unemployed and like using hedonic adjustment to "reduce" inflation.

I object.

Sunday, April 8, 2018

The whole is not equal to the sum of its parts? Really?

Menzie Chinn, in Assessing Trends in Real Shares at Econbrowser brings up a problem: "Chain-weighted" real numbers don't add up. Chinn links to Justin Fox's Friends Don't Let Friends Calculate Shares of Real GDP. Both of them link to Karl Whelan's A Guide to the Use of Chain Aggregated NIPA Data (PDF).

Chinn quotes Fox: "the different components of real GDP can no longer be added together. That is, they can be added together but, except in the base year, they don't add up to real GDP." Pretty clear.

Fox also says:
The BEA's remedy to the problem is to put up warnings against doing share-of-real-GDP calculations all over its website.
That's pretty funny. Also true, as even I have noticed those warnings.

But I'm having an awful lot of trouble understanding the problem. To use the example both Chinn and Fox use, consider manufacturing as a share of GDP. If you figure Nominal Value Added (for manufacturing only ) relative to Nominal Value Added (for all of GDP) you are okay. But maybe you think your result is unsatisfactory because prices have gone up more slowly for manufacturing than for all of GDP ("think health care", Justin Fox says). The nominals don't give you a good picture of manufacturing's share of real output over time. But that's not the error.

The error comes in when you switch to inflation-adjusted data. Since the mid-1990s, inflation-adjusted values have been figured by the "chain-weighted" method. Because they use this new method, when you take the inflation-adjusted components of GDP and add them up, the total doesn't come out equal to inflation-adjusted GDP. Here's Whelan:
A crucial feature of this chain aggregation methodology is that the real aggregate of X and Y will generally not equal the arithmetic sum of the real series for X and Y.
For chain-weighted values, the whole is not equal to the sum of its parts. That's the problem. That much I get, but that's where I lose it.

It just doesn't make any sense to me. Y=C+I+G+NX, but only if they're nominal values? I have to ruminate on this for a while.

Saturday, April 7, 2018

A critique of Andolfatto and Spewak's Debt Monetization: Then and Now

Debt Monetization: Then and Now by David Andolfatto and Andrew Spewak at On the Economy. Andolfatto and Spewak (A&S) show this graph of the monetization rate:

Graph #1, from Andolfatto and Spewak
Their graph shows "the percent of [Federal] debt held by the Federal Reserve—the monetization rate—against personal consumption expenditures (PCE) inflation." In a note they add:
We excluded intragovernmental holdings from our definition of debt. However, the conclusions of our analysis would not change significantly if we included these holdings.
To start, I want to duplicate the graph. From the note, I know they are looking at debt "held by the public" and not the "gross" Federal debt. So I know where to begin.

The Debt Held By the Federal Reserve, there are two series for that: an older one and a newer one. I need both. A search of FRED for federal debt held by the public turned up only one series that goes back as far as 1953. But it is called "Gross Federal Debt Held by the Public" which seems a contradiction in terms. To me, at least, "gross" means all of it, and "held by the public" means only part of it. Anyway, that series is annual. The A&S graph is quarterly. So I knew my first attempt would not look right:

Graph #2: Old (blue) and New (red) Federal Reserve Holdings as a Percent of the Federal Debt
(You'd have to ask the Fed how they got "Holdings" wrong and why they had to change it.)
The annual data is too smooth. Plus, my numbers are too high. I peak above 22 .5% in the mid-1970s. They peak near 20%. So I switched out the denominator for the blue line. I went with the Federal government component of TCMDO instead:

Graph #3
The numbers came down some, and are quarterly. Not sure why the two measures of debt are so different. But now my blue line looks like what A&S show. So I changed the red line also, and added PCE Inflation for the hell of it:

Graph #4: Yeah, that looks like what they show
I used the first "PCE Inflation" I found that had quarterly data going back at least to 1953.

Then, since Adolfatto and Spewak say
From 1953 to 1974, the monetization rate increased hand-in-hand with inflation, with both peaking near the end of 1974.
I put the 1953-1974 data into the Data Analysis "Regression" form in Excel. First time I used that. I got an R square value of 0.60. So I'm thinkin' that point six oh (or more) means "hand-in-hand".


I'm dropping inflation from my graph. I just want to look at Federal Reserve holdings of Federal debt. I want to compare the A&S version, Fed Holdings as a percent of the Federal Debt, to my version, Fed Holdings as a percent of the rest of the debt: The "non-Federal" debt, I call it. The part of TCMDO that A&S ignore.

Graph #5: Fed Holdings of Federal Debt as a Percent of the Federal Debt (blue & red)
and as a Percent of Debt Other than Federal (green & purple)
Relative to the Federal debt, Fed holdings are high and variable. Relative to debt other than Federal, Fed holdings are low, and were falling until the crisis.

Just before the crisis, Fed holdings relative to Federal debt were near the middle of their historical range. That may have been high enough to cause inflation (A&S don't say) but it is not likely that Fed holdings in that range would have caused the crisis.

By way of contrast, just before the crisis Fed holdings relative to non-Federal debt were the lowest they had ever been. This could have caused the crisis. I'm not saying it did; not today, anyway. But I am saying the "relative to non-Federal debt" measure is at least as important as the "relative to Federal debt" measure.

And that means non-Federal debt is at least as important as the Federal debt when we're talking about the economy. I hope you'll keep that in mind when you are looking at debt, and when you see other people looking at debt.


Andolfatto and Spewak offer an explanation of inflation. In particular, they offer an explanation for why the 1953-1974 increase in Fed holdings of Federal debt was associated with inflation but the more rapid increase in the 2009-2017 period was not.

One can look at their graph and ponder a similar question about the increase of Fed holdings in the 1992-2003 period. As I indicated above, though, that increase is not discussed in their article.

The explanation of inflation that they offer has to do with banks' incentive to lend. A&S measure this incentive as a difference of interest rates: the interest rate on a one-year T-bill minus the interest rate paid on reserves.

Here they explain the inflation of the 1953-1974 period:
As the Fed ramped up its debt monetization during this span, the average rate of interest on a one-year Treasury bill was about 5 percent, and the interest rate paid on reserves was literally zero.

With the spread between interest rates so large, banks had more incentive to use their newfound reserves to make loans than to hold onto them. These loans would then create money, which would boost the money supply and have inflationary effects. While several factors led to the Great Inflation of the 1970s, the gradual rise in the monetization rate was likely a significant one.
A&S compare two periods and find greater incentive to lend in the earlier period because the spread was greater. Because of this greater incentive, then, they see the "rise in the monetization rate" as a significant contributor to the Great Inflation of the 1970s.

It makes good sense to say that the greater "spread" increased banks' incentive to lend. But I think the low level of private debt and the economy's "golden age" vigor in the 1953-1974 period also increased banks' incentive to lend. And the high level of private debt and the residual trauma from "financial crisis" in the 2009-2017 period reduced banks' willingness to lend. Andolfatto and Spewak mention neither the vigor nor the lingering effects of the financial crisis. The vigor of one period, the trauma of the other, for A&S these somehow fall under ceteris paribus -- "all else equal".

Oddly, too, they emphasize the increase in monetization of debt in the early period, but de-emphasize the rise of interest rates that occurred concurrently. I expected Andolfatto and Spewak to give more weight to interest rates -- particularly in this case, as they note that "The larger the spread, the more profitable it is for a bank to lend". It is not the rise in monetization but the rising level of interest rates which supports their "greater incentive" argument.

During this time, however, with the interest rate on one-year Treasurys rising from one or two percent (in 1953) to eight or nine percent (in 1974), A&S refer only to "the average rate of interest on a one-year Treasury bill".

Emphasis added.


Let me regroup. Andolfatto and Spewak say that the increasing monetization rate, which increased reserves and the lending capacity of banks, was more likely to lead to inflation at a time when the incentive to lend (measured as an interest rate spread) was high. Lending was more likely to happen at the higher constant ("average") rate spread, as it would be more profitable.

Sure. But the rate of interest was not constant. It was rising. The interest rate spread was increasing. If the spread was increasing, surely the anticipated increase in bank profits would be more than if the spread was constant. Surely, the increase of interest rates was as significant as the increase in the monetization rate. Maybe more significant: Monetization provided an opportunity, but it was interest rates that provided the incentive.

Why then do A&S make the rising-monetization-rate argument, but smother the rising-interest-rate argument? I can't say. But even though they emphasize the monetization, their argument is that the interest rate spread led to the lending that led to the Great Inflation.

A&S argue that higher interest rates caused inflation by increasing the incentive to lend. I like this argument a lot; it fits my way of thinking. But somebody should point out that monetary policy uses higher interest rates as a way to fight inflation.


Andolfatto and Spewak argue that the increase in Federal Reserve holdings of Federal debt led to inflation in the 1950s and '60s and '70s but not after 2008 because the interest rate spread was different in the two periods. In the earlier period the spread was large, and in the latter it was small. In the earlier period the incentive to lend was large; in the latter it was small.

A&S consider the supply side of bank lending, but ignore the demand side. They consider the incentive to lend, but not the incentive to borrow. They present half a picture.

They ignore borrowers' interests. In essence they are saying that banks' incentive to lend was great enough in the early period that it caused the lending to happen. As if the borrowers were left saying to themselves: Well dammit, we borrowed all this money. Now what are we gonna do?

Friday, April 6, 2018

Productivity, smoothed


Quarterly data. "Annual rate" values would be about four times what's shown on the vertical scale.

Gray is the source data from FRED. ("PCH" is "Percent Change".)
Red is an undersmoothed Hodrick Prescott (smoothing factor 50).
Black is a sixth order polynomial trendline by Excel, based on the red.

A sixth order poly based on the gray looks identical to the one based on the red. I thought that was interesting.

As far as predicting what's next for productivity, I'm thinking: Look at the lows in the gray (quarterly) data. The last two lows are a lot higher than what came before. Could be a hint.

And remember: Productivity can rise quickly.

See also: Debt Service and Labor Productivity Projections from August 2016.

Thursday, April 5, 2018

Productivity can rise quickly

Productivity can rise quickly. Almost two percentage points in a year, for example:

Wednesday, April 4, 2018

Pascal Paul: Damned if you do, damned if you don't

In a recent FRBSF Economic Letter, Pascal Paul says
Recent research suggests that sustained accommodative monetary policy has the potential to increase financial instability. However, under some circumstances tighter monetary policy may increase financial fragility...

Can't win. Easy money increases instability. Tight money increases fragility.

Why? Because finance is big. Big, heavy, and quick to panic. You didn't see topics like Pascal Paul's back in the day finance was small. These days, every little flicker in the policy rate threatens our future.

The solution lies not in interest rate policy, but in reducing the size of finance.

Tuesday, April 3, 2018

It's Miller time

If your search phrase includes the word "debt" you turn up statements like this:
When government debt grows, private investment shrinks, lowering future growth and future wages.
Government debt is bad for growth.

If your search phrase includes the words "private debt" you turn up statements like this:
Private debt can slow the economy even in times of overall growth.
Private debt is bad for growth.

Why those two guys can't sit down, have a beer, and agree that debt is bad for growth, is beyond me.