As a rule it is a problem when cost is too high, but not when income is too high. To the recipient there is no such thing as income being too high. Excessive cost, however, can bring transactions to a dead stop.
Cost is a problem. Income is not. And yet, one person's income is another person's cost. If there is any limit to income, it is because every dollar of income is somebody's cost. In other words, the limit to income is a cost-side limit.
When cost is widely distributed, and income narrowly, the cost-side limit to income is less effective. The larger the market for your product, the less effective is the limit to your income. Markets allow inequality of income. Larger markets allow greater inequality.
Now you know why the wealthy favor globalization.
Tuesday, May 15, 2018
Sunday, May 13, 2018
The 10-year average 10 years out
Springtime. Time for mowing the lawn every fourth day. Between that and binge-watching with the wife, who has time for blogging? Expect these posts to be intermittent ...
On the 10th I showed this graph of RGDP growth ("Gordon growth" I called it) and some other stuff:
Today I keep the blue line and drop the rest.
In that earlier post I said
The RGDP data I've been using in these "Gordon growth" posts is Real Gross Domestic Product, Percent Change from Preceding Period, Quarterly, Seasonally Adjusted Annual Rate. The last data item is 2.3, for 2018Q1, preliminary and subject to change. I'll go with that number, a 2.3% annual rate of economic growth.
If the economy stays at the 2.3% growth rate, it is higher than growth during the recession. The blue line will go up. Assuming growth stays constant at 2.3% for ten years -- that's not a prediction, just a number to work with -- the blue line will follow the path shown here in red:
In the near term, at the start, the red line rises rapidly. But after a couple years it is already close to the 2.3% level, and after that there is not much change.
Point of interest: On this graph the sudden change in the red line (from mostly rising to mostly flat) occurs at 2020Q1, half a year or so before the next Presidential election. Of course, it also takes time for the data to be reported. So if the economy suddenly goes flat near 2.3% as shown here, we're not going to know about it until after the election.
In another hypothetical future, economic growth increases at 0.1% per quarter, from 2.3% in 2018Q1, to 2.4% in 2018Q2, to 2.5% in Q3 and like that, until it reaches a 3.1% annual rate, and then remains at 3.1%. Again, the red line shows the future path:
Here the red line rises rapidly at first, as the Great Recession falls out of the 10-year period. Then it rises more slowly, until the average approaches the 3.1% level. But there is a definite difference between this graph and the previous one.
I used the unfortunate term "prediction" to identify data on the graphs. In the spreadsheet, the word meant that some other data was the actual data. But on the graphs, it looks like a prediction. That was not my intent. I just wanted to see how the numbers affect the average as time passes.
And I missed my 4AM deadline.
On the 10th I showed this graph of RGDP growth ("Gordon growth" I called it) and some other stuff:
 |
| Graph #1: Gordon Growth and Productivity -- Incremental 10-Year Periods |
In that earlier post I said
That last little tic it shows, from 2017 to 2018, is an uptick. Ooh ooh Trump.But it isn't Trump, I said. The old data is gradually dropping out of the 10-year average. And the old data happens to be from 2007, 2008, 2009, the time of the Great Recession. The blue line shows an uptick at the end because 2007 dropped out of the 2018 average. And over the next couple years, the rest of the low numbers from the recession will drop out of the average as current data is added in. So, if current growth is at all higher than growth was during that recession, the blue line will go up more.
The RGDP data I've been using in these "Gordon growth" posts is Real Gross Domestic Product, Percent Change from Preceding Period, Quarterly, Seasonally Adjusted Annual Rate. The last data item is 2.3, for 2018Q1, preliminary and subject to change. I'll go with that number, a 2.3% annual rate of economic growth.
If the economy stays at the 2.3% growth rate, it is higher than growth during the recession. The blue line will go up. Assuming growth stays constant at 2.3% for ten years -- that's not a prediction, just a number to work with -- the blue line will follow the path shown here in red:
 |
| Graph #2: How 10 Years of 2.3% Growth Affects the Average |
Point of interest: On this graph the sudden change in the red line (from mostly rising to mostly flat) occurs at 2020Q1, half a year or so before the next Presidential election. Of course, it also takes time for the data to be reported. So if the economy suddenly goes flat near 2.3% as shown here, we're not going to know about it until after the election.
In another hypothetical future, economic growth increases at 0.1% per quarter, from 2.3% in 2018Q1, to 2.4% in 2018Q2, to 2.5% in Q3 and like that, until it reaches a 3.1% annual rate, and then remains at 3.1%. Again, the red line shows the future path:
 |
| Graph #3: How 10 Years of Rising Growth Affects the Average |
I used the unfortunate term "prediction" to identify data on the graphs. In the spreadsheet, the word meant that some other data was the actual data. But on the graphs, it looks like a prediction. That was not my intent. I just wanted to see how the numbers affect the average as time passes.
And I missed my 4AM deadline.
Friday, May 11, 2018
No early warning? Of course there's an early warning.
Anticipating recession, John Mauldin writes:
The economy was hitting on all cylinders in late 2006? Depends what numbers you look at.
The growth of Household Debt peaked in the first quarter of 2006. It was seriously downhill from there to the recession. And come to think of it, household debt peaked in the first quarter of 2000, a year or more before the 2001 recession. So I don't buy Mauldin's story that the numbers are all great and then suddenly there's a recession. I don't buy that.
By the way, the most recent data FRED provides at the moment is for the last quarter of 2017. It shows increase. It shows a trend of increase. No indication of recession.
As indicators go, the yield curve Mauldin discusses may be a little more "leading" than the change in household debt. But at the moment, the debt numbers give no indication of impending recession.
Nor do the Change in Employment numbers suggest impending recession:
After running pretty flat (jiggy, but flat) from 1997 to 2000, the change in employment suddenly started dropping. A year or so later, recession.
After showing increase since the 2001 recession, the change in employment peaked in 2005 and started dropping. Two and a half years later, recession.
Since climbing out of the 2008-09 recession, the change in employment has run rather flat. You might see a hint of an S-curve in the trend. But there is definitely no dropping off. There is no indication of recession at this time.
Capacity Utilization wanders a lot. But it goes downhill fast during recessions. It tends to fall or to run flat for six months or more before a recession. but sometimes the "downhill fast" starts even before the recession. Notice, though, that Capacity Utilization is never going uphill fast when a recession starts.
At the moment, Capacity Utilization is going uphill fast.
My conclusions: No impending recession. And there are always early warnings.
Look around at all the great economic news. I’m aware of it. But the economy was hitting on all cylinders in early 2000 and late 2006, too. The numbers always look great right before a recession. Then it all rolls over at once.I'll throw the challenge flag.
The economy was hitting on all cylinders in late 2006? Depends what numbers you look at.
 |
| Graph #1: Household Debt, Quarterly Change in Billions |
By the way, the most recent data FRED provides at the moment is for the last quarter of 2017. It shows increase. It shows a trend of increase. No indication of recession.
As indicators go, the yield curve Mauldin discusses may be a little more "leading" than the change in household debt. But at the moment, the debt numbers give no indication of impending recession.
Nor do the Change in Employment numbers suggest impending recession:
 |
| Graph #2: Change in Employment |
After showing increase since the 2001 recession, the change in employment peaked in 2005 and started dropping. Two and a half years later, recession.
Since climbing out of the 2008-09 recession, the change in employment has run rather flat. You might see a hint of an S-curve in the trend. But there is definitely no dropping off. There is no indication of recession at this time.
Capacity Utilization wanders a lot. But it goes downhill fast during recessions. It tends to fall or to run flat for six months or more before a recession. but sometimes the "downhill fast" starts even before the recession. Notice, though, that Capacity Utilization is never going uphill fast when a recession starts.
 |
| Graph #3: Capacity Utilization |
My conclusions: No impending recession. And there are always early warnings.
Thursday, May 10, 2018
The moment we've been waiting for!
What I'm now calling "Gordon Growth" is a comparison of time periods, where GDP growth is "measured between quarters with identical unemployment rates". I figure it by making a scatterplot showing the time periods with unemployment on the X-axis and RGDP growth on the Y-axis, then comparing the linear trend lines created by Excel.
The Gordon Growth number is the average of trend line growth rates.
At this point I couldn't tell you how I managed to turn the phrase "measured between quarters with identical unemployment rates" into the process I'm using. But the process works, far as I can tell. So here we are.
I want to go back to that first sentence which has occupied my attention for three or four days now. This time, I'm going to start thinking about the second half of the sentence, and productivity:
This is related to "growth accounting": The GDP growth rate can be calculated as the growth rate of the labor force plus the growth rate of labor productivity, as Menzie Chinn shows. So I think the productivity that Robert Gordon's talking about is labor productivity. Real output per hour.
Using PRS85006092 I get an average productivity growth rate of 2.1% for 1970-2016, and an average of 1.2% for 2006-2016. The one minus the other is 0.9%, exactly the number we're looking for.
I put a new spreadsheet together, formatted better, with the info for each time period all in one column on the sheet. I tested the sheet by duplicating my own previous results. It was good.
I checked the productivity numbers too. The sheet was good.
Satisfied that the new worksheet is good, I made a copy of the sheet and gave it different time periods to evaluate. For the three time series I'm looking at, my data goes from 1948Q1 to 2018Q1. Seventy years of data. I figured I'd look at ten-year periods:
The blue dots show the Gordon Growth numbers by decade: numbers comparable to Robert Gordon's 3.2% for the 1970-2006 period. My dots for 1968-2008 are in that neighborhood. Gordon got 1.4% for the years 2006-2016. I get 1.5% (same as I got before), this time for the years 2008-2018.
There is a general downward trend in the Gordon Growth number on my graph.
The red dots show productivity by decade. There are high points at 1958-1968 and 1998-2008; these highs more or less agree with other histories of productivity that I have seen. The numbers I have are 2.1% for Robert Gordon's 1970-2006 and 1.2% for his 2006-2016. The latter is a good match to my 2008-2018 here, and the other looks about right as an average of the red dot values from 1968 to 2008. In the ballpark.
The green dots are blue minus red: Gordon Growth less Productivity Growth. To put it in the "growth accounting" framework, green shows growth attributable to things other than labor productivity.
Labor force size, maybe?
Maybe. But I don't like to close doors. If we attribute the green growth to labor force size, there is nothing left over that I can point to and say "it was caused by the growth of private debt". And I have to have something I can point to and talk about debt.
To me, breaking up 70 years into seven 10-year periods is much more informative than breaking it into two periods punctuated by a "great" recession. So I thought maybe I'd gain even more by breaking it into fourteen 5-year periods. But all I gained was messiness:
First guess, the blue dots now show the effects of recessions. I count four definite low points:
The red dots still show early and late high points, plus a smaller high in the 1980s.
The green is all up-and-down. It's indecipherable. But probably not closely tied to labor force size.
I want to go back to 10-year periods, to minimize the effects of recession. But this time I'll figure incremental, overlapping ten-year periods: 1948Q1-1958Q1, then 1949Q1-1959Q1, then 1950Q1-1960Q1, and like that. And instead of getting a "dot" for a ten year period, I'll have points on a line, where each point is the end of a ten-year period. I think that'll smooth out the picture, even better than the first graph did.
...
Here's the graph:
First impression? Didn't smooth things out at all. There's a lot of agitation in those lines. Way more than I expected. Remember, consecutive points on the line are only a year apart.
See what I did here? I put the Legend off to the right rather than up top with the title. With the Legend off to the right, the years of data are compressed into a smaller space. The agitation would look less severe if the lines could stretch out into the space where the Legend is. But hey, I'm just showing you the graph as I first saw it, with the Legend at right and the lines compressed.
This data deserves to be compressed. Look at that green line: It is up and down and up and down and up and down from start to finish. You don't want to hide that agitation.
The red line provides a pretty good display of productivity, I think, with peaks early and late, and listlessness between.
And the bright blue line, Gordon Growth, when I saw that line it reminded me of this graph from Fernando Martin of the St. Louis Fed:
Very similar to my blue line.
Well I'm almost out of things to say about Gordon Growth, at least for now. But first, look again at the blue line on Graph #3. That last little tic it shows, from 2017 to 2018, is an uptick.
Ooh ooh Trump. That was my first ball-bustin thought. It isn't, though. Isn't Trump. The graph shows ten-year averages.
The uptick from 2017Q1 to 2018Q1 is an uptick in 2008Q1-2018Q1 relative to 2007Q1-2017Q1. We see an uptick on Graph #3 because the year 2017 was okay and the year 2007 was horrible. It isn't Trump.
Here's FRED:
All the values from 2008Q1 to 2017Q1 are included in both of the last two points on my bright blue. The difference between those last two points exists entirely because of the difference between the first few points and the last few points on this FRED graph.
The change from 2007Q1 (where the graph starts) is a jump up to over 2.5%, then a slight fall, then a bigger fall, then a sharp drop into negative territory and the start of the Great Recession. All in all, a big downer.
The change from 2017Q1 (the bottom of the last "V", at the right) is a jump up to over 2.5%, then a slight increase, then a slight fall, then another slight fall as the line heads to a tentative 2.3% rate. All in all, fairly flat.
The difference in the last two bright blue points on my #3 is this: The next-to-last point includes RGDP falling into recession. The last point doesn't, so the last point goes up. I'm trying to avoid tiresome detail here. But people are going to be saying Ooh ooh Trump.
During the next couple years, the bright blue line is going to go up and up significantly, as time goes by and the "Great Recession" gradually drops out of the calculation.
So in the next few years, if you hear anybody say "The economy is great again!" and they hold up a graph of 10-year average growth, well, now you have evidence to shoot them down.
I for one still expect the economy to improve for a number of reasons. But I expect to see it in current data, not in ten-year averages.
The Gordon Growth number is the average of trend line growth rates.
At this point I couldn't tell you how I managed to turn the phrase "measured between quarters with identical unemployment rates" into the process I'm using. But the process works, far as I can tell. So here we are.
I want to go back to that first sentence which has occupied my attention for three or four days now. This time, I'm going to start thinking about the second half of the sentence, and productivity:
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, and only half of this GDP growth slowdown is accounted for diminished productivity growth.Growth slowed from 3.2% to 1.4%, a difference of 1.8%. And only half of this slowdown can be attributed to diminished productivity growth. So I want to look for a slowdown in productivity growth of 0.9% or so. I should find this slowdown by comparing the time periods noted in the quote.
This is related to "growth accounting": The GDP growth rate can be calculated as the growth rate of the labor force plus the growth rate of labor productivity, as Menzie Chinn shows. So I think the productivity that Robert Gordon's talking about is labor productivity. Real output per hour.
Using PRS85006092 I get an average productivity growth rate of 2.1% for 1970-2016, and an average of 1.2% for 2006-2016. The one minus the other is 0.9%, exactly the number we're looking for.
I put a new spreadsheet together, formatted better, with the info for each time period all in one column on the sheet. I tested the sheet by duplicating my own previous results. It was good.
I checked the productivity numbers too. The sheet was good.
Satisfied that the new worksheet is good, I made a copy of the sheet and gave it different time periods to evaluate. For the three time series I'm looking at, my data goes from 1948Q1 to 2018Q1. Seventy years of data. I figured I'd look at ten-year periods:
 |
| Graph #1: Gordon Growth and Productivity -- 10-Year Periods |
There is a general downward trend in the Gordon Growth number on my graph.
The red dots show productivity by decade. There are high points at 1958-1968 and 1998-2008; these highs more or less agree with other histories of productivity that I have seen. The numbers I have are 2.1% for Robert Gordon's 1970-2006 and 1.2% for his 2006-2016. The latter is a good match to my 2008-2018 here, and the other looks about right as an average of the red dot values from 1968 to 2008. In the ballpark.
The green dots are blue minus red: Gordon Growth less Productivity Growth. To put it in the "growth accounting" framework, green shows growth attributable to things other than labor productivity.
Labor force size, maybe?
Maybe. But I don't like to close doors. If we attribute the green growth to labor force size, there is nothing left over that I can point to and say "it was caused by the growth of private debt". And I have to have something I can point to and talk about debt.
To me, breaking up 70 years into seven 10-year periods is much more informative than breaking it into two periods punctuated by a "great" recession. So I thought maybe I'd gain even more by breaking it into fourteen 5-year periods. But all I gained was messiness:
 |
| Graph #2: Gordon Growth and Productivity -- 5-Year Periods |
- 1953-1958: (2) recessions
- 1978-1983: (2) recessions
- 1988-1993: (1) recession
- 2008-2013: (1) "great" recession
The red dots still show early and late high points, plus a smaller high in the 1980s.
The green is all up-and-down. It's indecipherable. But probably not closely tied to labor force size.
I want to go back to 10-year periods, to minimize the effects of recession. But this time I'll figure incremental, overlapping ten-year periods: 1948Q1-1958Q1, then 1949Q1-1959Q1, then 1950Q1-1960Q1, and like that. And instead of getting a "dot" for a ten year period, I'll have points on a line, where each point is the end of a ten-year period. I think that'll smooth out the picture, even better than the first graph did.
...
Here's the graph:
|
| Graph #3: Gordon Growth and Productivity -- Incremental 10-Year Periods |
See what I did here? I put the Legend off to the right rather than up top with the title. With the Legend off to the right, the years of data are compressed into a smaller space. The agitation would look less severe if the lines could stretch out into the space where the Legend is. But hey, I'm just showing you the graph as I first saw it, with the Legend at right and the lines compressed.
This data deserves to be compressed. Look at that green line: It is up and down and up and down and up and down from start to finish. You don't want to hide that agitation.
The red line provides a pretty good display of productivity, I think, with peaks early and late, and listlessness between.
And the bright blue line, Gordon Growth, when I saw that line it reminded me of this graph from Fernando Martin of the St. Louis Fed:
 |
| Graph #4: From Why Does Economic Growth Keep Slowing Down? by Fernando Martin |
Well I'm almost out of things to say about Gordon Growth, at least for now. But first, look again at the blue line on Graph #3. That last little tic it shows, from 2017 to 2018, is an uptick.
Ooh ooh Trump. That was my first ball-bustin thought. It isn't, though. Isn't Trump. The graph shows ten-year averages.
The uptick from 2017Q1 to 2018Q1 is an uptick in 2008Q1-2018Q1 relative to 2007Q1-2017Q1. We see an uptick on Graph #3 because the year 2017 was okay and the year 2007 was horrible. It isn't Trump.
Here's FRED:
 |
| Graph #5: 2007Q1 to a Still-Preliminary 2018Q1, Quarterly (The Same Data I've Been Using) |
The change from 2007Q1 (where the graph starts) is a jump up to over 2.5%, then a slight fall, then a bigger fall, then a sharp drop into negative territory and the start of the Great Recession. All in all, a big downer.
The change from 2017Q1 (the bottom of the last "V", at the right) is a jump up to over 2.5%, then a slight increase, then a slight fall, then another slight fall as the line heads to a tentative 2.3% rate. All in all, fairly flat.
The difference in the last two bright blue points on my #3 is this: The next-to-last point includes RGDP falling into recession. The last point doesn't, so the last point goes up. I'm trying to avoid tiresome detail here. But people are going to be saying Ooh ooh Trump.
During the next couple years, the bright blue line is going to go up and up significantly, as time goes by and the "Great Recession" gradually drops out of the calculation.
So in the next few years, if you hear anybody say "The economy is great again!" and they hold up a graph of 10-year average growth, well, now you have evidence to shoot them down.
I for one still expect the economy to improve for a number of reasons. But I expect to see it in current data, not in ten-year averages.
Wednesday, May 9, 2018
Acuppla things
Here's my graph based on Robert Gordon's description, from Sunday: The unemployment rate, sorted, on the X axis. Real GDP growth on the Y axis:
Here's the same data, in chronological order:
The jiggy lines are different now. But the trend lines are unchanged, as are the numbers in the trend line equations.
That's what I expected to see. But I had to look.
//
Next, how does the graph look if I use the original unemployment values instead of rounding them to one decimal place? Like this:
Compare this graph to Graph #1. Or for that matter, you can compare the numbers in the trendline equations to those in Graph #2 (which has the same numbers as #1). With rounding omitted, the numbers are different.
No noticeable change in the trend lines, though. It's not a big change.
//
I wonder... Remember, at the end of Sunday's post, the average of my trend line values for 1970-2006 was 3.2%, the same number Robert Gordon got. But my average for 2006-2016 was a little off. I got 1.5%. He got 1.4%. I wonder if that difference goes away when the rounding goes away.
Nope. I get 3.2% and 1.5%, same as before.
 |
| Graph #1: Data in Each Period Sorted by Unemployment Rate |
Here's the same data, in chronological order:
 |
| Graph #2: Data in Chronological Order |
That's what I expected to see. But I had to look.
//
Next, how does the graph look if I use the original unemployment values instead of rounding them to one decimal place? Like this:
 |
| Graph #3: Data not Rounded |
No noticeable change in the trend lines, though. It's not a big change.
//
I wonder... Remember, at the end of Sunday's post, the average of my trend line values for 1970-2006 was 3.2%, the same number Robert Gordon got. But my average for 2006-2016 was a little off. I got 1.5%. He got 1.4%. I wonder if that difference goes away when the rounding goes away.
Nope. I get 3.2% and 1.5%, same as before.
Tuesday, May 8, 2018
Notes on my Gordon's Way calcs
Yesterday I said
Next time, no rounding.
As part of the process of creating my "Gordon" scatter plots, after I made subsets of the data for selected time periods, I sorted them. For each subset I sorted three columns (unemployment rate, RGDP growth rate, and date) on the unemployment column. The sort puts my X-axis values in sequence, lowest to highest, the way they would be if I was putting date values on that axis.
(I didn't need the "date" column for the graph. I needed it to improve my confidence in my work.)
What happens if I don't sort the data? I found out when I forgot to do the sort. It looked like a cluster or spiral or something. I knew right away when I saw it that I did something wrong, and I fixed it right away. I didn't stop to look at it. So I want to graph the unsorted data again -- and look at it this time:
Not a spiral. Maybe a "scatter". If you follow along the blue line from dot to dot, you arrive at the dots in chronological order. Uh, the dots are in chronological order, not you.
But looking at it, I get the impression that the dots are grouped, with empty space between the groups. Look at the dot closest to the upper-left corner: There are no dots below it! Three dots off to the left, maybe five to the right, but there is a big space with no dots below that upper-left one.
And look at the two highest dots, the ones above the 15.0 level. Below each of them is a broad white strip with few scattered dots in it. A little off to the left, a little off to the right, the dots are more tightly packed together. Odd, isn't it?
Maybe that's "random": unexpected groupings separated by unexpected empty space.
Then I remembered that I rounded the values. I ran into that problem before, where the dots got packed into groups by the rounding. I did the graph over right away, using the original, unrounded data:
Looks almost the same.
... ?
Oh, of course: Rounded to one decimal place, I could have nine dots side-by-side between 4.0 and 5.0 on the X-axis, with the dots separated by gaps only about the size of a dot. The grouping isn't from the rounding.
Then you get these strange ideas, like maybe there is some relation between unemployment and growth which favors certain places on the graph over other places.
... Nah.
But you have to think about those things, you know? Because one of those ideas could lead to the light bulb that works.
I want to use Robert Gordon's method of evaluating economic conditions... I'm not doing it by throwing away all the data where there is no identical unemployment rate in both time periods. The way I'm doing it is by putting linear trend lines on scatterplots, and compare the trends.Proofreading that, looks like I should have said "comparing the trends." Also, I realized that since I'm not "doing it by throwing data away", I don't have to round the unemployment numbers to one decimal place.
Next time, no rounding.
As part of the process of creating my "Gordon" scatter plots, after I made subsets of the data for selected time periods, I sorted them. For each subset I sorted three columns (unemployment rate, RGDP growth rate, and date) on the unemployment column. The sort puts my X-axis values in sequence, lowest to highest, the way they would be if I was putting date values on that axis.
(I didn't need the "date" column for the graph. I needed it to improve my confidence in my work.)
What happens if I don't sort the data? I found out when I forgot to do the sort. It looked like a cluster or spiral or something. I knew right away when I saw it that I did something wrong, and I fixed it right away. I didn't stop to look at it. So I want to graph the unsorted data again -- and look at it this time:
 |
| Graph #1: Unemployment Rate (X-Axis) and RGDP Growth Rate (Y-Axis) |
But looking at it, I get the impression that the dots are grouped, with empty space between the groups. Look at the dot closest to the upper-left corner: There are no dots below it! Three dots off to the left, maybe five to the right, but there is a big space with no dots below that upper-left one.
And look at the two highest dots, the ones above the 15.0 level. Below each of them is a broad white strip with few scattered dots in it. A little off to the left, a little off to the right, the dots are more tightly packed together. Odd, isn't it?
Maybe that's "random": unexpected groupings separated by unexpected empty space.
Then I remembered that I rounded the values. I ran into that problem before, where the dots got packed into groups by the rounding. I did the graph over right away, using the original, unrounded data:
 |
| Graph #2 |
... ?
Oh, of course: Rounded to one decimal place, I could have nine dots side-by-side between 4.0 and 5.0 on the X-axis, with the dots separated by gaps only about the size of a dot. The grouping isn't from the rounding.
Then you get these strange ideas, like maybe there is some relation between unemployment and growth which favors certain places on the graph over other places.
... Nah.
But you have to think about those things, you know? Because one of those ideas could lead to the light bulb that works.
Monday, May 7, 2018
Using Robert Gordon's method
Since last we spoke, I figured out how to use the SLOPE() and INTERCEPT() functions in Excel. Better late than never, huh?
I want to use Robert Gordon's method of evaluating economic conditions, the method we looked at yesterday. I want to pick time periods that interest me this time, and compare economic growth in those periods his way: for "quarters with identical unemployment rates".
I'm not doing it by throwing away all the data where there is no identical unemployment rate in both time periods. The way I'm doing it is by putting linear trend lines on scatterplots, and compare the trends. Like I did yesterday. It's the method that makes sense to me. I don't know how Robert Gordon did it. But I figure he must have done it the same way, as it is the only way to do it that I thought of. :)
Anyway, now I can calculate the slope and intercept values. I don't have to make the graph and add the trend line and copy the values from the trend line equation. That'll save a lot of work.
Since we crawled out of the last recession, for the longest time people were talking about how economic growth was so much slower than before.
Does this mean we have to accept slow growth as normal? No, because that's a prediction. Predictions are not facts. The fact is that the economy has been slower since 2009 than it was before.
Now, about that "before" time, and the growth then: "It´s more or less recognized that US RGDP is trend stationary," Marcus Nunes told me, "with real growth averaging about 3.3% from the early 50s to 2007."
At Trading Economics I read that "GDP Growth Rate in the United States averaged 3.21 percent from 1947 until 2018". I know they want to simplify and have just one number, and that can be useful. But it's not useful if you want to see how growth trends have changed.
Marcus's method is better. He figures an average only thru 2007. There is data left over, so we can figure an average for the more recent years. Then we can compare the two averages and see how growth trends have changed.
Trading Economics figures the average from a 1947 start. That's what I would do. It uses all of the commonly available quarterly data. Marcus figures the average from 1952 "to avoid the post war adjustment". That makes sense, too.
What doesn't make sense to me is to lump all the years together and get one average value, if there was a change somewhere in the middle. Scott Sumner says "growth in US living standards slowed after 1973". Somewhere in the middle.
Ross Perot showed the same:
So maybe we want to look at economic growth from 1947 to 1973, and from 1973 to 2007, and since 2007. Three numbers. Three growth trends. Then we can look at all three, and compare them. That's the kind of thing that makes sense to me.
So I made a graph like the last one I did yesterday, using Robert Gordon's method, but showing the three growth trends:
Forget the thin, jiggy lines. Forget all those dots. Focus on the three thick trend lines. The highest one, the blue one, is for the years 1948 thru 1973. (1947 got lost somewhere.)
The red line is lower. The economic growth is lower. This line shows the trend for the years 1973 thru 2007.
The green line is lower yet. Economic growth is lower yet. This line shows the trend for 2007 thru 2017.
The average growth rate of the 1948-1973 line is 4.1%. The average for the 1973-2007 line is 3.1%. The average for 2007-2017 is 1.5%.
I want to use Robert Gordon's method of evaluating economic conditions, the method we looked at yesterday. I want to pick time periods that interest me this time, and compare economic growth in those periods his way: for "quarters with identical unemployment rates".
I'm not doing it by throwing away all the data where there is no identical unemployment rate in both time periods. The way I'm doing it is by putting linear trend lines on scatterplots, and compare the trends. Like I did yesterday. It's the method that makes sense to me. I don't know how Robert Gordon did it. But I figure he must have done it the same way, as it is the only way to do it that I thought of. :)
Anyway, now I can calculate the slope and intercept values. I don't have to make the graph and add the trend line and copy the values from the trend line equation. That'll save a lot of work.
Since we crawled out of the last recession, for the longest time people were talking about how economic growth was so much slower than before.
- Julian Brookes in Rolling Stone, 2012: "Four years after the start of the Great Recession, nobody would mistake U.S. economy for a thrumming engine of growth, prosperity, and human flourishing."
- Chris Matthews in Fortune, 2014: "GDP growth has been tepid since 2009 (just 2.1% per year, below the post-war average and far below the average for previous recoveries)..."
- James Hamilton at EconBrowser, 2017: "The Bureau of Economic Analysis announced yesterday that U.S. real GDP grew at a 1.9% annual rate in the fourth quarter, well below the historical average of 3.1% per year, but close to the 2.1% average since the recovery from the Great Recession began in 2009:Q3."
Does this mean we have to accept slow growth as normal? No, because that's a prediction. Predictions are not facts. The fact is that the economy has been slower since 2009 than it was before.
Now, about that "before" time, and the growth then: "It´s more or less recognized that US RGDP is trend stationary," Marcus Nunes told me, "with real growth averaging about 3.3% from the early 50s to 2007."
At Trading Economics I read that "GDP Growth Rate in the United States averaged 3.21 percent from 1947 until 2018". I know they want to simplify and have just one number, and that can be useful. But it's not useful if you want to see how growth trends have changed.
Marcus's method is better. He figures an average only thru 2007. There is data left over, so we can figure an average for the more recent years. Then we can compare the two averages and see how growth trends have changed.
Trading Economics figures the average from a 1947 start. That's what I would do. It uses all of the commonly available quarterly data. Marcus figures the average from 1952 "to avoid the post war adjustment". That makes sense, too.
What doesn't make sense to me is to lump all the years together and get one average value, if there was a change somewhere in the middle. Scott Sumner says "growth in US living standards slowed after 1973". Somewhere in the middle.
Ross Perot showed the same:
 |
| Graph #1 Source: Ross Perot, United We Stand (from when Perot was running for President in 1992) |
So maybe we want to look at economic growth from 1947 to 1973, and from 1973 to 2007, and since 2007. Three numbers. Three growth trends. Then we can look at all three, and compare them. That's the kind of thing that makes sense to me.
So I made a graph like the last one I did yesterday, using Robert Gordon's method, but showing the three growth trends:
 |
| Graph #2: Progressive Decline in Trend Growth Unemployment on the X Axis. RGDP Growth on the Y Axis. |
The red line is lower. The economic growth is lower. This line shows the trend for the years 1973 thru 2007.
The green line is lower yet. Economic growth is lower yet. This line shows the trend for 2007 thru 2017.
The average growth rate of the 1948-1973 line is 4.1%. The average for the 1973-2007 line is 3.1%. The average for 2007-2017 is 1.5%.
 |
| Graph #3: Average Growth Rate by Period |
 |
| Graph #4: Average Unemployment Rate by Period |
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