Gordon's Way

Graph #1: The Unemployment Rate (blue) and RGDP Growth

According to the NBER blurb that we saw yesterday for Robert J. Gordon's paper,

Measured between quarters with identical unemployment rates, U. S. economic growth slowed by more than half from 3.2 percent per year during 1970-2006 to only 1.4 percent during 2006-16...

Measured between quarters with identical unemployment rates: I thought that might be an interesting way to look at growth.

I used UNRATE, with the frequency changed to quarterly (the average of monthly values), and A191RL1Q225SBEA, a measure of Real GDP growth that shows the percent change from preceding quarter at a seasonally adjusted annual rate.

That sentence from NBER finishes up with these words:

... and only half of this GDP growth slowdown is accounted for diminished productivity growth.

An important afterthought. But I want to leave productivity out of it, at least until I see if I can duplicate Robert Gordon's 3.2% and 1.4% numbers.

Close. I'll be happy if I just come close to his numbers.

The RGDP growth numbers come from FRED with one decimal place. But the unemployment numbers have more decimal places than I can count. I'll be comparing growth numbers for dates that have "identical unemployment rates" but damn few of them will be identical if all those decimal places have to match. I started a new column of data with =TEXT(B13,"0.0") and copied it down to create numbers with one decimal place.

How'm I going to compare 1970-2006 to 2006-2016? I can sort 'em by one-digit UnRate. I can sort 'em, but first I have to make two separate batches of numbers. Then I can sort 1970-2006 by unemployment rate, and separately sort 2006-2016 by the unemployment rate. I'm thinking I can plot the two separate batches as two lines on a scatter graph, with unemployment on the horizontal and growth on the vertical. I should get two jiggy lines and, I expect to see the 2006-2016 line reliably lower than the 1970-2006 line.

So I made two copies of the data and eliminated items from before 2006 from the one, and items from after 2006 from the other. Then I sorted them on my =TEXT values. Excel challenged me on the sort, saying that it "may not sort as expected because it contains some numbers formatted as text". (Yeah, I know.) But Excel offered to "sort anything that looks like a number, as a number", and that's what I wanted.

Graph #2: First Try

Well that graph didn't come out right. For one thing, all of the 2006-2016 values are clustered on the left side, as if the unemployment rates were all low. They should be scattered across the full width of the graph, more or less.

For another thing, what the hell are those numbers on the X axis? They're supposed to be my unemployment rate numbers to one decimal place. Four percent, maybe, or 8% or 10%. But definitely not zero, and definitely not 160%. Wow.

Maybe my one-decimal-place conversion is the problem. Excel thinks my numbers are not numbers. I'll try rounding instead.

Graph #3

Oh yeah, that makes a difference already. The unemployment values run from about 4% to about 10%. And the later years are scattered about as widely as the early years on the graph. This is promising.

I cleaned the graph up some to make it easier to look at:

Graph #4

And now (hopefully) it gets interesting. Now I put a trend line on the early years, and a trend line on the late years:

Graph #5

I just used linear (straight line) trend lines, Excel's default, because they are close to flat and they obviously run at different levels. The heavy blue trend line for the early years is definitely higher than the heavy red trend line for the later years. As expected.

The blue trend line runs very slightly uphill (it is higher on the right than on the left) and the red one runs very slightly downhill (it is lower on the right than the left). I know, because the red trendline equation begins with a minus sign, and the blue one doesn't.

I know the slopes are very slight because I can see it, and because 0.0261 and -0.0347 are very small numbers, compared to the numbers on the Y axis.

The values 3.0212 and 1.7214 in the trendline equations are the Y-intercept values. Extend the trend lines leftward, off the graph, to the point where the X-axis value is zero, I think that will be the spot where the trend lines have the values shown in the equations. On the graph, where we actually see the lines, the blue will be more than 3.0212 (because the line slopes up) and the red will be something less than 1.7214 (because the line slopes down).

What were Robert Gordon's numbers again? 3.2 percent and 1.4 percent. More than 3.0212, the one, and less than 1.7214, the other. So I'm definitely in the ballpark.


I increased the number of decimal places in the trendline equations to 8 (whether I need to do that or not for linear trends, I don't know) and used those equations to figure values for those lines.

The blue (1970-2006) values run from 3.12 to 3.30, with an average of 3.18.

The red (2006-2016) values run from 1.57 to 1.38, with an average of 1.49.

If I round my averages to one decimal place, I get 3.2 for the early years, the same as Robert Gordon. And I get 1.5 for the later years, compared to Gordon's 1.4. Close enough.

I'm happy now.

The Missing Word

Like partners in a dance

Credit Card Delinquency (blue) and Household Debt Service

Micro micro micro micro micro micro micro

I'd guess I'm at least 80% right about this:

Noah Smith says

Economists study gender relations in the workplace, racial gaps, changes in labor contracts, early childhood education, minimum-wage policy, regional opportunity gaps, automation and the future of jobs, and a vast array of other highly important, immediately relevant topics.

To which I respond:

Micro micro micro micro micro micro micro, and a vast array of other micro.

Noah says

... many theorists now prefer to work with game theory [which] can encompass things like wage bargaining, fraud and lots of other things ...

Micro micro and lots of other micro.

Noah says

Auction theory, random-utility models, matching theory, gravity-trade models, and some other mathematical theories have enjoyed enormous quantitative predictive success ...

I'm gonna make a guess here and say: Micro micro micro micro and some other micro.

And Noah says

... a version of consumer theory ... is very useful and powerfully predictive for all sorts of real-world applications, from transportation planning to marketing to disaster planning and more.

From micro to micro to micro, and more.

Hey, disaster planning could be pretty damn important. Even I can see that. But it's not economics. At least, it isn't macro. When the shit hit the fan a decade back we got a financial crisis, a "great" recession, and double-digit unemployment. Macro, macro, and macro.

You can't tell, with him

"Him" is Brad DeLong.

Among links at Economist's View I find

What Does Economics Need to Learn Next? - Brad DeLong

Okay.

At the link:

What Does Economics Need to Learn Next?

Prospect Magazine: Back to school: top economists on what their subject needs to learn next: Learn to prevent—we’re out of cure:

The crisis and its aftermath showed that the North Atlantic economies could not maintain full employment by following the Keynesian road. The idea that when the private sector sits down the public sector should stand up—that consistent durable prosperity can be achieved by having government step in as a spender of last resort—proved unsustainable.

Whoa! Whose conclusion is that? With DeLong you never know.

His own? Or somebody at Prospect magazine? Now I gotta go look.

Oh good. At Prospect I can

Register today and access any 7 articles on the Prospect’s website for FREE in the next 30 days.. 

Yeah. Thanks. No thanks. I should just close the page, but that would end this post.

Oh, okay. The part I quoted above is part of DeLong's two cents at the Prospect page. There are several others quoted there too. DeLong quotes a bunch of them on his page. More than you wanted to know. More than I wanted to know.

Anyway, it's Brad DeLong's conclusion. DeLong says //

No, I won't repeat it again. But apparently he thinks we were "following the Keynesian road." You know: Deficits be damned.

We did the Keynesian thing and it didn't work, DeLong says. We're out of cure, he says. Our only choice is to prevent the problem from arising again, he says. I guess he's out of ideas.

Shit, he never even had an idea. He was using Keynes's idea.

And I don't know why, if the one idea he thought would work didn't actually work and he has no other ideas, I don't know why he thinks we'll be able to prevent the problem from arising again.

Anyway, he didn't even get to Step One yet. Step One is Understand the problem.


DeLong's buddy Krugman, back in 2010, was saying things like

American households have to bring their debt levels down.

and

I think it’s fair to say that a majority of economists believe that excessive private debt played a key role in getting us into this economic mess, and is playing a key role in preventing us from getting out.

He was right about debt. And it's still true. But more recently Krugman says things like

The problem with private debt is that we have good reason to believe that in very wide-open financial systems people get irrationally exuberant, lending and borrowing to an extent that they eventually realize was excessive — and that there are huge negative externalities when everyone tries to deleverage at once.

So, far as I can tell, Krugman now thinks the problem is exuberance, not debt. He used to know how to fix the problem. Now he doesn't.


Look, it's not complicated. The problem is not excessive "lending and borrowing". The problem is the cost of the debt. If you have to spend money to pay for financing, that's money you don't get to spend on output.

Need I say more?

Little Dipper, Big Dipper

Graph #1 (Markup not intended to look like Amazon smiles!)

Blue:	(TCMDO-FGTCMDODNS)/FYGFD
Red:	TDSP/3
Green:	TCMDO/M1SL

After the little dipper of the 1990s, the economy was for a time rather good.

After the big dipper we are currently in, the economy again will be rather good. Probably for a longer time than with the little dipper, and maybe more than rather good.

Not marked up on the graph, the early years of the blue line (up to the mid-1970s) show what happened as our economy emerged from the monster dipper that goes back to the Great Depression. The economy was really good. But debt accumulated, and eventually it caused problems. We must contain finance.

We must contain finance but not growth. I am therefore forced to conclude that raising interest rates is the wrong way to contain finance.

Forget about Sumner

Rummaging thru my old posts this morning I noticed a pretty neat graph of debt growth, then moved on. An hour later I noticed myself quoting Scott Sumner:

Krugman makes the basic mistake of just looking at time series evidence, and only two data points: US growth before and after 1980. Growth has been slower, but that’s true almost everywhere.

Sumner disputes the significance of Krugman's statement. But he agrees that US economic growth has been slower since 1980. When I saw that, the bell went off in my head again. Backtracking, I was lucky enough to find the graph I saw earlier:

Breaking the 54-year period into two equal parts --

Total (Public and Private) Debt relative to GDP

A 25% increase in the first period, and a 100% increase in the second period. Debt grew four times as fast in the more recent period. Relative to GDP.

Maybe it was the growth of debt that caused the slowing of economic growth.

Nah. Sumner says forget about debt.