Tuesday, August 23, 2016

BIS on the connection between Debt and Labor Productivity

At BIS, from When the financial becomes real:

Financial booms typically go hand in hand with significant resource misallocations. In particular, labour is diverted to booming sectors with relatively low future productivity growth...

The impact of these misallocations became even larger in subsequent years, once the boom turned to bust... Thus, the fallout from credit booms may well have exacerbated the trend decline in productivity growth in advanced economies. By the same token, lower productivity growth in recent years need not be permanent.

... need not be permanent. In other words, it ain't secular stagnation, it's crisis-related. And maybe, the bank is saying, maybe we shouldn't be surprised if we see an improvement in productivity in the next couple three years.

Where have you heard that before?

Also this, remarkable from a bank:

Credit expansions may still boost output growth through higher demand and investment, but not productivity growth. To gain a sense of the economic significance, consider the US experience. Between 2004 and 2007, labour productivity grew by 1.2% per year, but labour reallocations made a negative 0.3 percentage point contribution. Over the same period, private credit to GDP grew by 4.5% per year. Taking the estimates at face value, if credit to GDP had grown by only 1.5%, the drag on productivity growth would have been eliminated.

They're saying we used too much credit. BIS -- one bank to rule them all -- BIS says private credit use was excessive. BIS says private debt was excessive. BIS.

This is big.

Monday, August 22, 2016

Debt Service and Labor Productivity Projections

Here's the graph I couldn't get right for yesterday's post. (X-axis was messed up.)

The blue line shows household debt service, 1980 thru 2015. The black line is a debt service trend line showing the future debt service that I anticipate; same as yesterday.

The brown line shows labor productivity, 1980 thru Q2 2016. The bright red line shows my general expectation for future productivity, Q2 2016 thru Q4 2020. Also bright red, the productivity  data for Q4 1993 thru Q2 1998 -- the data I copied and showed again as future productivity.

Graph #1: Debt Service and Labor Productivity Projections
By the time we get to 2020, the economy will be great. The person we elect President in 2016 will be easily re-elected in 2020. And we'll all be happy again for a while -- until debt goes too high once again and we have another financial disaster.

Anything else?

// The Excel file

Sunday, August 21, 2016

Potential Productivity

"Since 2007, the rate of productivity growth has been disappointing", John Cassidy writes in The New Yorker. "Since 2010, it has been extremely disappointing."

Here's a close-up of productivity growth since the start of 2011:

Graph #1: Productivity Growth 2011 Q1 thru 2016 Q2
The linear trend line is very flat at 0.5 percent. Productivity is low and not improving. What's more, the last few readings show a downward trend. Extremely disappointing, as John Cassidy says.

But we do not know where the red line will go next. It was lower in mid-2013 than it is now, and it went low more quickly. Then it turned around and went up even faster. So you never know.

Here's a close-up of productivity growth in the quiet time before the Goldilocks years of the 1990s:

Graph #2: Productivity Growth 1993 Q1 thru 1995 Q1
The linear trend line is very flat at 0.5 percent. Productivity, low and not improving. The last few readings show a downward trend. Productivity growth was disappointing. Just like the first graph.

Here's a close-up that picks up where Graph #2 leaves off:

Graph #3: Productivity Growth 1995 Q1 thru 1997 Q1
The linear trend rises from 0.5 percent to nearly 3% in two years.

You never know.

To my way of thinking, Graph #1 (our time) is very much the same as Graph #2 (the early 1990s). But I think we are at the end of Graph #2 and ready to start Graph #3. That makes all the difference.

Oh come on, you are saying. Graph #2 shows only a couple years. Graph #1 shows almost six years. There's no comparison. The slump is endless this time.

It's not endless. That's the point. The quiet time before the vigor is longer this time -- about 2½ times as long, my guess. I'm telling you we are at the end of the quiet period. Soon we will see productivity start to climb, just as on Graph #3.

On Friday I showed productivity growth with bright red circles around the two quiet times -- the recent years, and the early 1990s. Our low productivity has lasted much longer than that of the 1990s:

Graph #4: Productivity and Debt Service
Yes, and it shows that the "bottom" in the dull red "debt service" curve has also lasted much longer this time. But you can see from the shape of that curve that it wants to go up.

And you can see from the early 1990s that when the debt service curve goes up it goes up quickly, and productivity goes up with it. And the economy becomes vigorous.

I expect that debt service will soon rise sharply. Productivity will improve, just as happened in the mid-1990s. And the economy will again be vigorous.

Graph #5: The Recent Years
If we want to understand the productivity problem, we have to look at it in context. What context? I suggest we use household debt service for context.

The recent years of debt service show a remarkable drop from the late-2007 peak. Debt service fell rapidly, to a sharp down-spike at the end of 2012.

After the bounce-back from that down-spike, the path of debt service was different. The rapid decline had ended. It had reached a bottom. It was running flat.

If you look, you can see that debt service since the beginning of 2013 shows a fairly smooth curve. The curve bottoms out just at the end of 2014, then starts to rise.

To my eye, debt service drifted downward less quickly in 2014 than 2013, then turned and started drifting upward in 2015. Started drifting upward last year.

Curse the luck, the debt service data ends with 2015. We don't have first- and second-quarter 2016 numbers that let us see what's really happening. But I think 2016 will drift upward a little more than 2015, continuing the pattern that began at the start of 2013.

And I think that after 2016 debt service will rise even faster. That's when we'll start to feel the vigor. That's when we'll see the improved productivity. Here: I mirrored the curve on this next graph to show the kind of future I expect:

Graph #6: Our Near Future?
Just to give you an idea.

I should say, though, that if debt service rises as far and as fast as this graph suggests, then the recession bar after 2025 will be even wider than what the graph shows, and the recession more severe than the last one.

But you take my point: If the debt service curve is going down, then going down more slowly, then going up instead of down, then going up more quickly, this is what the graph must look like. And if debt service goes up and up, productivity will improve and the economy will show vigor -- for a while at least.

I took the eight data values for 2014 and 2015 -- the slowly-down-and-slowly-up drift in the curve -- and used those eight values to create a trend line in Excel. The trend line runs into the past and future, to show where debt service will be (and where it would have been) if those eight values determined the path of debt service:

Graph #7: Household Debt Service and the 2014-2015 Trend
The original eight values are shown in red at the end of the blue line, just at the bottom of the U-shaped trend line. Going forward, the U-shaped trend provides an estimate of the future path of the blue line, the future path of household debt service.

Going backward, the U-shaped line is not an exact match to the blue line during its rapid 2007-2013 fall. But the lines are close enough to make you stop and think. And that means the right side of the U-curve, the side that imagines the future, is likely also a pretty good estimate.

Time will tell. In the meanwhile I have to look. I have to see if I understand what's going on. I have to see if I understand the economy.

I made a screen capture of household debt service in the 1990s so we can look at the "dip, bottom, and recovery" (DBR) of that time. It is shown here in place (in the 1990s) as a dotted green line in a black box, overlaid on the original blue line:

Graph #8: Capturing the "Dip, Bottom, and Recovery" of the 1990s
I took that image of the 1990s, with the green dots there, took that image and scaled it up by a factor of 2.5: that is, 2.5 times as tall and 2.5 times as wide. Then I moved it so that the "dip" of the 1990s lines up with the 2007-2013 dip on the blue line:

Graph #9: Looking at Current Conditions as 2½ times the size of the 1990s Conditions
The green dots -- the 1990s data, scaled up by a factor of 2.5 -- the green dots make a very good match to the 2007-2013 downtrend of the blue line. A very good match.

The green dots also suggest that the debt service "recovery" will happen sooner than Excel's U-curve says. This makes me stop and think. Excel's U-curve is based on the most recent two years of debt service data. Only two years of it, but the most recent two years.

Perhaps the debt service recovery will not come as quickly this time as it did in the 1990s. That seems a reasonable conjecture. Excel's U-curve seems to me a better bet than my scaled-up green dots from the 1990s. So I grabbed the image of the 1990s again and stretched it, still 2.5 times as tall but this time 3 times as wide. Three times the duration.

I fitted the green overlay to the blue line as before:

Graph #10: Looking at Current Conditions as 3 times the Duration of the 1990s Conditions
The scaled-up green dots from the 1990s align with the 2007-2013 fall of the blue line as before. And this time, the green dots of the 1990s recovery align quite nicely with Excel's U-curve.

What does it mean, really? Really, it means nothing: It's a prediction. Still, if the prediction turns out to have been correct, it means maybe I do have a pretty good handle on the economy. Time will tell.

It all comes down to prediction on my part.

You don't expect the economy to pick up. You don't expect vigor. You don't expect productivity to rise. I look at debt service in the '90s and say "That pattern is being repeated right now."

"No," you say. "The economy is different since the crisis." And you are right: Different it is. Maybe things won't pick up this time. Maybe the economy will stay as flat as my recent Blogger stats.

But everything I read tells me that people are tired of this washed-out recovery, which is less a recovery than a continuing depression. People are tired of it. People are ready for recovery. Nobody believes me when I say "vigor", but everybody's ready for it.

It will happen. It won't happen because of my charm and wit, but it will happen.

It will happen because people are ready for it. Nobody was ready yet, in 2010. Everybody wanted it, but everybody knew vigor was unrealistic. Today, people don't say vigor is realistic, but everybody wants it. We're not saying vigor is possible, but we're hungry for it.

You know what that is? That's expectations.

Expectations have turned. Can vigor be far behind?

Friday, August 19, 2016

Productivity and Debt Service

This graph shows productivity. I have circled the low productivity of the past few years, and also the low productivity of the 1990s in the years before "Goldilocks".

Graph #1: Productivity
When I take that graph and add household debt service to it, you can see that the circled years of low productivity are quite obviously related to the lows in debt service:

Graph #2: Productivity and Debt Service
Need I say more?

Thursday, August 18, 2016

Low Debt Service plus Growing Debt equals Productivity

The red line is productivity, shown as percent change from year ago.

Graph #1: Household Debt & Debt Service (blue) and Productivity (red)
The blue line combines the household debt service ratio and the growth of household debt.

The two lines don't always match, mostly because of the big spike in productivity that we typically get after recessions. But set those spikes aside, and the lines do at least hint at similarity.

The red oval mid-graph highlights productivity and debt conditions during the "Goldilocks years".

The red oval on the right shows debt conditions even lower now than during 1993-1995, so there is plenty of room for things to go up.

Productivity has been low since 2011, as the graph shows. But productivity was also low after debt conditions bottomed out in the early 1990s, just before the Goldilocks years.

Productivity is going to pick up soon.

Wednesday, August 17, 2016

Illicit use of the Hodrick-Prescott?

The Hodrick and Prescott (1980, 1997) filter (hereafter, the HP filter) has become a standard method for removing trend movements in the business cycle literature.

I'm reading Notes on Adjusting the Hodrick-Prescott Filter for the Frequency of Observations, a short PDF by Morten O. Ravn and Harald Uhlig. The paper is © 2002 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology, so they're probably right.

Most applications of this filter have been to quarterly data, but data is often available only at the annual frequency, whereas in other cases monthly data might be published. This raises the question of how one can adjust the HP filter to the frequency of the observations so that the main properties of the results are conserved across alternative sampling frequencies.

Their topic is tweaking the HP calculation to allow for different data frequencies.

I use Kurt Annen's VBA code in Excel to do the HP calculation. The code creates a function named HP( ) that does all the work. All you have to give it is the range of source data and a constant.

The constant is how you allow for different data frequencies. Changing the constant changes the amount of "smoothing" you get when you graph the results. The trick is to use the right value for the constant.

I've always used the values 100 for annual data, 1600 for quarterly data, and 14400 for monthly data. Something I picked up from the EViews User Forum a while back. I have some old notes on it.

I shouldn't say I always use those values. I always start with those values. Sometimes I change them. For examples of how changing the value of the smoothing constant affects the results, see this old post.

In this recent post I show why, for one graph of monthly data, I abandoned my usual monthly constant of 14400 in favor of my default annual value 100. The larger value smoothed all the information out of the result -- like Kruger smoothing the head off a statue on Seinfeld.

For quarterly data, Ravn and Uhlig say, the value 1600 is commonly used. (It seems 1600 is the value Mr. Hodrick and Mr. Prescott used in the article that introduced the HP filter.) But for annual data Ravn and Uhlig note four different values: 100, 400, 10, and their own personal favorite, 6.25:
We then show that our recommendations work extremely well on U.S. GDP data: using a value of the smoothing parameter of 6.25 for annual data and 1600 for quarterly data produces almost exactly the same trend. This leads us to reconsider the business cycle “facts” reported in earlier studies. As an example, we cast doubt on a finding by Backus and Kehoe (1992) ...

Using a constant of 6.25 rather than 100 for annual data, the authors produce "almost exactly the same trend" that they get for quarterly data with a constant of 1600. Sounds good. But let me ask: Do you really want to get the same HP trend for the two series on this graph?

Graph #1: Quarterly (blue) and Annual (red) RGDP
I don't think so. The quarterly trend should show more detail.

Maybe if I'm looking at 50 years of data I'd want to think of "the" trend for the data, and it should be the same for both annual and quarterly. But if I'm focused on only a few years of data, it's probably because I'm looking for more subtle differences and I'd want to see more wiggle in the trend for the more wiggly line. I'm not looking at the 50-year trend. I'm looking at what's happened since the crisis.

Sometimes there's good reason to want the same trend from data with different frequencies. But sometimes there's good reason to want different trends.

Here are the two graphs from my "recent" post linked above, and my thoughts at the time:
Today I want to look at the monthly GDP data from Macroeconomic Advisers. I have their data thru May now:

Graph #2: Monthly RGDP since Jan 2009 with an Unresponsive H-P Constant
The blue line shows RGDP growth from 12 months prior. The red line is the Hodrick-Prescott using the constant I'd normally use for monthly data. I think this constant makes the red line a little too unresponsive, there being only about seven years of data.

Here is the same graph with a more responsive Hodrick-Prescott:

Graph #3: Monthly RGDP since Jan 2009 using a More Responsive H-P Constant
Now the red line follows the blue more closely. It helps us see the up-and-down pattern in the jiggy blue data. We are at a low spot now, and evidently RGDP growth has been trending down since the end of 2014.

Graph #2 shows a trend that is essentially flat. Graph #3 shows that RGDP growth has been trending down for a year and a half. Graph #3 is much more informative, and its trend line clearly does a better job of showing the path of RGDP than does Graph #2. But the thing of it is, Graph #3 uses the "wrong" smoothing constant. It uses my default annual value on monthly data!

I chose the annual value on purpose, because I wanted about as much smoothing on the monthly data as I normally get on annual data. It worked.

PS: I went out of my way to find monthly data for Graphs #2 and #3. Monthly, because it shows more variation. It would make no sense to smooth the monthly trend down till it showed as little variation as the annual!

Tuesday, August 16, 2016

The Relation Between Debt Service and RGDP Growth

Showing Hodrick-Prescott curves for Household Debt Service and Real GDP Growth:

1980-83: A low level of debt service (blue) allows rapid increase in RGDP growth.
1984-86: Rising debt service hinders growth. The red line peaks and turns downward.
1986-89: Reduced growth and reduced borrowing allow debt service to fall.
1990-93: Falling debt service encourages growth. The red line bottoms and turns upward.
1994-97: Rising growth leads to increasing debt service.
1997-99: Rising debt service hinders growth. The red line peaks and turns downward.
2000-06: Reduced growth and increased borrowing keep debt service rising.
2006-08: Reduced growth and reduced borrowing allow debt service to fall.
2008-10: Falling debt service encourages growth. The red line bottoms and turns upward.
2010-13: Falling debt service encourages growth. The red line rises.
2013-16: The fall in debt service slows. The increase in growth also slows.

Easier to follow if you print out the page and mark it up.

// The Excel file (contains VBA code)

Monday, August 15, 2016

Debt service and economic growth

Some generalizations:

Debt service is a financial cost imposed on the non-financial sector -- on production and consumption. To the extent that debt service moves money from the non-financial to the financial sector, it hinders production and undermines consumption.

The data on debt service is for households. So I will confine my remarks to household expenditure, to consumption.

When debt service is low, consumers have more money left over for other things. When debt service is high, consumers have less money left over for other things.

When debt service is rising, it is an indication that consumer debt is high or that consumer borrowing is on the rise. If borrowing is on the rise, GDP is probably on the rise. If debt is high, maybe not.

When debt service is falling, it is an indication that debt has been falling or has been rising more slowly than usual. If the latter, GDP may be on the rise. If the former, maybe not.

Sunday, August 14, 2016

Reverse Engineering the Household Debt Service Ratio

Looking at household debt service as a percent of disposable personal income. Wondering how income affects the data, how debt affects it, and how saving affects it.

At FRED, the debt service number is given as "percent of disposable personal income". I figured saving the same way, and put the two together on a graph:

Graph #1: Debt Service (blue) and Household Saving (red) relative to DPI
My first impression was that the two lines tend to move in opposite directions: away from each other before the 1982 recession, but toward each other after it... away from each other after the 1991 recession and then toward each other again... and then away from each other from the late 1990s to the crisis, and then toward and past each other.

So then I took and put a minus sign in front of the formula for the red line, to turn it upside down:

Graph #2: Debt Service (blue) and Saving with a Minus Sign (red)
With the red line other-side-up, the red and blue do show signs of matching. I got low and then high from 1985 to 1990... low and then high again... then higher from 2000 to the crisis, and then low. The lines don't match well, but do show signs of matching. Makes me wonder what I can do to make them match better.

I thought about adding consumer debt (relative to disposable personal income) to the calculation of the red line. And then I remembered seeing those formulas that add two terms together after assigning a weight to each. And I said Yeah I can do that.

Ended up using "change in household debt" relative to DPI. And I just guessed some weights until I got something that looked somewhat like the debt service line. And I added a constant to push the red line up closer to the blue. Here is the result:

Graph #3: Using Savings and Household Debt to Reverse Engineer the Debt Service Ratio
Oh, was I pleased with myself!

The red line is very jiggy compared to the blue. But I expect I can smooth it out by using a Hodrick-Prescott calculation on it. Now I'm picturing a red line that looks even more like the blue, except everything happens about two years early. So I can lag the red line about two years to  make the lines more similar.

What that means is I'll get a peek into the future. My most recent data, from Q1 2016, will show up as a prediction of debt service for 2018! Now it's getting interesting.

I have to bring the data from FRED to Excel to do the lagging and the Hodrick-Prescott. I got all the data, which will let me calculate a number back to 1952 instead of 1980. I love this stuff.

Long story short, I figured the Hodrick-Prescott, tweaked the "weight" values a bit (by eye), and lagged my calculated numbers 8 quarters. Here's the result, back to 1980:

Graph #4: Not Perfect, but Not Bad!
The two-year lag is just about perfect for the high area (from 2000 to 2009). For the early years the red line should be lagged a little less.

But look at that big drop after 2008 Q1. At the peak the red line is a perfect match to the blue. At the bottom, by 2012, the lines have crossed. The economy slowed down during the big drop. I would need a longer lag there at the bottom, to push the red line more to the right.

But the most interesting thing on this graph, I think, is that it makes a prediction about the path the debt service ratio will take. It's going to go up. The blue line, like the red, is going to go up.

// The Excel file