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Another Look

Another Look

by

Ken Melvin

In the wake of riots following the Police murders of George Floyd, Breonna Taylor and too many other Black Americans, and Trump’s earlier installation  the likes of Jeff Sessions and Bill Barr as Attorney General; let US Cities find now to be a particularly good time to look anew at what they, the people, think should be the proper role of Police in America. It is time and time to rethink Policing in America. Any and all changes made need be made nationwide, else we would wind up forever dragging around this same Policing Model, a model purportedly somewhat based on some interpretation of the Old Testament of the Bible, a Model with ties to Slavery and Servitude. It is time and time that Policing in America broadly reflects current American values and thinking.

Police being an inclusive term; including all law enforcement agencies.

Much of what we now have was brought forward from 17th Century English Laws premised on protecting the property of the landed gentry, including the Monarch, since modified as required to allow for the added responsibility for public safety, … Today, many Police and Sheriff Departments are Economic and Political Fiefdoms. In December 2019, Barr said, “They have to start showing, more than they do, the respect and support that law enforcement deserves, … And if communities don’t give that support and respect, they may find themselves without the police protection they need.” Safe to assume that Sessions would have agreed. Here we are two generations into the Age of Technology with an Administration out of the 1960s and before. Taking off from Albert Camus’ Absurdism, we past Absurd quite a long ways back. Houston, we have hit bottom.

In times like these, the question must be: 

What should be the role of the Police?

 

Another Look at Drug Pricing, Costs, and Why

Median total costs Table for the most common prescriptions of each of the 49 high-volume brand-name drugs from 2012 through 2017 as detailed in JAMA Network Open’s “Trends in Prices of Popular Brand-Name Prescription Drugs in the United States” 2019.”

A Bit of A Summary: This particular table relates back to a post I wrote; Does Trump Read JAMA Network Open? which reviewed the latest JAMA findings (Trends in Prices of Popular Brand-Name Prescription Drugs in the United States) on pharmaceutical price increases from 2012 to 2017. It is another in a series of articles which have looked at the rising prices of pharmaceuticals. The World Health Organization (2018) findings reflected on R & D costs for cancer drugs and the amount of time needed to recoup those costs (median of 3 years for $750 million) with an average return of $14. 50 for every $1 invested in R & D for cancer drugs.  For the maximum estimated risk-adjusted cost of R&D (US$2.827 BN), the time to cost recovery was 5 years (range: 2 years; 10 years, n=56).

Click on the JAMA Table: Median Total Cost of Top-Selling Brand-Name Drugs 2012 – 2917 to enlarge and again to magnify if needed.

Taken “From the Trends in Prices of Popular Brand-Name Prescription Drugs in the United States” findings, substantial cost increases among these drugs was near universal, with a 76% median cost increase from January 2012 through December 2017, and almost all drugs (48 [98%]) displaying regular annual or biannual price increases. Of the 36 drugs available since 2012, 28 (78%) have seen an increase in insurer and out-of-pocket costs by more than 50%, and 16 (44%) have more than doubled in price. Insulins (ie, Novolog, Humalog, and Lantus) and tumor necrosis factor inhibitors (ie, Humira and Enbrel) demonstrated highly correlated price increases, coinciding with some of the largest increase in drug costs. Relative price changes did not differ between drugs that entered the market in the past 3 to 6 years (2012 – 2017)  and those having been on the market longer (number of drugs, 13 vs 36; median, 29% increase from January 2015 through December 2017; P = .81) nor between drugs with or without a Food and Drug Administration – approved therapeutic equivalent (number of drugs, 17 vs 32; median, 79% vs 73%; P = .21). Changes in prices paid were highly correlated with third-party estimates of changes in drug net prices (ρ = 0.55; P = 3.8 × 10−5), suggesting that the current rebate system, which incentivizes high list prices and greater reliance on rebates, increases overall costs.

The ICER Report (Unsupported Price Increase Report) compared the percentage increases in the  Wholesale Acquisition Cost (WAC – second Column)  to the increase in the Medical Care Consumer Price Index (CPI) over the same period and excluded those drugs with a WAC increase less than 7.32% or two times the increase in Medical Care CPI over the same period. The medical care CPI is one of eight major components of the CPI recorded and reported by the US Bureau of Labor Statistics .

CPI for Medical consists of medical care services (professional services, hospital and related services, and health insurance) and medical care commodities (medical drugs, equipment, and supplies). ICER using overall Medical CPI and not a lone services or commodity related one or subcomponent(s) of either or each was to reflect increases in drug prices relative to inflation in the overall price of medical care. The 77 drugs shown in the ICER Table 2.2 had an increase in Wholesale Acquisition Cost (WAC) greater than 7.32% over  the two-year period (4th quarter 2016 – 4th quarter 2018). The remaining 23 drugs were excluded from further analysis even though they may have been greater than one times CPI.

The ICER Table 2.3 depicting 9 drugs of the 77 shows  the percentage change in net price (Column 3) over the two-year period from the fourth quarter of 2016 to the fourth quarter of 2018, and the and the increase in drug spending during calendar years 2017 and 2018 and the 4th column depicts net revenue after discounts, rebates, concessions to wholesalers and distributors, and patient assistance programs same as Table 2.2 in the report. Only the ICER Table 2.3 is shown here (JAMA chart above).

The first seven drugs under assessment did not display evidence meeting the criteria accepted evidence grading system called GRADE. As a result, the seven are reported as having price increases “unsupported by new clinical evidence.” GRADE is a method used by systematic reviewers and guideline developers to assess the quality of evidence and decide whether to recommend and intervention.  GRADE differs from other appraisal tools for three reasons: (i) because it separates quality of evidence and strength of recommendation, (ii) the quality of evidence assessed for each outcome, and (iii) observational studies can be ‘upgraded’ if they meet certain criteria.

So What Does All of This Mean?

Other reports recognize similar. Healthcare costs are increasing at a much higher rate than inflation, enough so, JAMA is reporting patented pharmaceutical price increases to be 50% to 100% between 2007 and 2014, as are the generic versions, and those introduced during 2007 and 2014 have seen similar sizeable increase. The exhibited JAMA report details the increases.

The ICER report goes a bit further and establishes a benchmark of increase at twice Medical CPI and whether a price increase greater than the benchmark can be justified by the result of significant value brought to the market to account for the increase. At greater than a generous twice Medical CPI, the top nine drugs exceeded this benchmark and after investigation,  did not bring significant value to the market place following the 4 significant values claimed by pharmaceutical companies. This analysis was completed on  9 of 77 drugs having price increases greater than twice Medical CPI. Seven of the nine drugs were shown to have price increases for which additional value could not be substantiated. The remaining two had evidence of clinical value which could not be examined at this time. Then there is the balance of the 77 drugs which have had price increases greater also. Legit or not?

Remember, the ICER is the organization which justifies pricing for many of the new drugs coming to the market place.

The World Health Organization Report reviews the costs of R & D for Cancer Drugs which pharmaceutical companies blame as a the major factor for higher prices over the life of their patents. The WHO document reports the R & D costs are recouped in a median 3 to 5 years for R & D investments of $750 million to $2.8 Bn. Drug patents are significantly long than the recovery. Rent taking . . .

This is just pharma alone and I did not look at hospitals, clinics or hospital supplies. Briefly, “Health Affairs – Hospital Prices Grew Substantially Faster Than Physician Prices For Hospital-Based Care In 2007–14″ reports  inpatient care at hospital prices grew 42 percent, while physician prices grew 18 percent. Similarly, for hospital-based outpatient care, hospital prices grew 25 percent while physician prices grew 6 percent. Both this report and Kocher and Berwick’s “While Considering Medicare For All: Policies For Making Health Care In The United States Better: Health Affairs” point to increases in hospital care as the leading cause of increased healthcare insurance premiums.

The emphasis by politicians has been on the pricing of drugs without looking at the supply chain and the PBM’s influence on it; without looking at the costs of R & D, the return from sales revenue and how quickly those costs are recovered; and without looking at the exclusivity granted drugs through patents that allow the ability to increase pricing without a returning benefit clinically, socially, to the system, and most of all to the patient. The emphasis by government should be a review of drug costs to establish a fair market value/price. I do not see a foundation being established for the setting of pricing.

Trends in Prices of Popular Brand-Name Prescription Drugs in the United States, JAMA Network Open, Nathan E. Wineinger; Yunyue Zhang; Eric J. Topol, May 2019

Unsupported Price Increase Report, Institute for Clinical and Economic Review; David M. Rind, Foluso Agboola, Varun M. Kumar, Eric Borrelli, Steven D. Pearson; October 2019

Technical Report, Pricing of cancer medicines and its impacts; World Health Organization; 2019

While Considering Medicare For All: Policies For Making Health Care In The United States Better; Health Affairs; Kocher and Berwick; 2019

Health Affairs – Hospital Prices Grew Substantially Faster Than Physician Prices For Hospital-Based Care In 2007–14;” Health Affairs; Zack Cooper, Stuart Craig, Martin Gaynor, Nir J. Harish, Harlan M. Krumholz, and John Van Reenen; 2019

Run75441 (Bill H)

Another look at GDP

(Dan here….Lifted from comments here)

Spencer says:

You can download the most recent GDP in excell form directly from the BEA.

In the 2nd quarter exports accounted for 1.12 percentage points of the 4.1% surge in real GDP. That is almost 30% of growth.

Apparently the big jump in exports was due to large purchases of soy beans in May, before new tariffs were imposed. This was obviously a one time unusual event that will quickly reverse and dampen real GDP for the rest of the year.

The y/y growth in real GDP is now 2.8% VS 2.6% in the first quarter. Interestingly, from 2012 to 2016 under Obama there were 6 quarters when the y/y growth in real GDP exceeded 3%.

rjs says:

Soybean sales would be in exhibit 7 of the trade report:

https://www.bea.gov/newsreleases/international/trade/2018/pdf/trad0518.pdf

there was a $1,956 million increase to $4,142 million in our exports of soybeans…
i’d note that there were concurrent big decreases in our exports of oil & oil products which could reverse as well…

meanwhile, an inflation adjusted $58.2 billion downward swing in inventory growth subtracted 1% from the 2nd quarter’s growth rate…the -27.9 bilion Q2 inventory figure was the worst contraction going back at least 6 years (looking at the extent of the pdf table)…so just a modest increase in inventory growth in Q3 could add that 1% right back…that would cover the expected reversal of your exports…so other components being equal then, we could see another +4% in Q3…

to clarify; my inventory GDP numbers are at an annual rate, soybeans are unadjusted for May only…

I’m Buried, but This Deserves Another Look

Erik Loomis at LG&M notes that Forbes is attempting to encourage age discrimination (no we’re not; wink, wink, nod, nod).

And it made me think of this post from Lance Mannion, which deserves to be read every day you can:

You get up for a stretch, wander out onto the floor to get a cup of coffee, give people the eye, remind them you’re here, still the boss. Not that they need the reminding. Good people. Hard workers. You hardly have to say a word to some of them. Work their asses off for half the money, which, you know, you’d like to pay them. Business is good, as in ok, but it’s not like you’re making the bucks so fast you can’t find space to put it all, it’s piling up so fast….

Sid. Look at him. Geezus. Five years younger than you and looks like he could be your father. Ok. That’s a bit of an exaggeration. But he’s not looking too good these days, is he? Too bad. He used to be such a dynamo. Worked like a hero. Put in seven days a week if you’d let him. Best you had. Then he turned sixty-five and it was like he hit a wall. Bam. Just knocked him flat and he’s never been able to get up again, not really. Mostly, for the past year, he comes in, goes through the motions. He’s become a real drag on the business. He really should hang it up. But what’s he gonna do? You always paid him a fair chunk of change. Never was going to make him rich, but he got by pretty well. But 2007, 2008. Everybody’s 401(k) took a big hit, then his wife got sick, and their house went under water. He’s going to need to collect full benefits on his Social Security. He needs to stick it out for one more year.

Oh wait. It’s 2020 now, isn’t it? They raised the retirement age for people Sid’s age back in 2011. He can’t collect full benefits until he’s 69. So he’s going to stick around for three more years!

Three?

Think about it. His wife’s health is shaky. Sid’s is none too good. No way he can make up for the difference in medical costs for what the vouchers won’t cover. Sid needs to work here till he drops just for the medical plan, which is no great shakes, it costs you both an arm and a leg, but it’s not like it’s suddenly got cheaper to go the doctor’s. Even a simple check-up dings you, never mind if you need something big taken care of.

No, Sid’s here for life, unless…

Nah, you couldn’t do that to Sid. Not after all the years he’s put in.

Could you?

There are many reasons I say people should hit his tip jar–he’s too good to be one of the people Brad DeLong but this one keeps coming back as one of the best, one of the two best posts ever on the Internet about working.* Read the whole thing. And hit his tip jar if you can.

*The other is Mark Thoma’s description of what it’s like to be downsized in a Company Town and have to look for a new job. Which, as usual, I haven’t been able to find recently.

ANOTHER LOOK AT CBO REPORT FOR THOSE FOREVER YOUNG

by Dale Coberly

REALITY 101

ANOTHER LOOK AT CBO REPORT

FOR THOSE FOREVER YOUNG

I wrote a post the other day trying to explain what the CBO’s number
meant when they said it might be necessary to raise the payroll tax
an extra 3.5% to pay for Social Security for the next seventy five
years. I was very disappointed, frightened even, by the responses I
got. Here is another way to try to explain it.

The following is a fairy tale. The numbers are made up to be made
simple. But they are meant to be realistic.

Our grandparents, or maybe your great-grandparents lived on incomes
of about 25 thousand dollars a year… in “our” dollars. That is,
they got by on about half of what we have in “real” dollars. Out of
this 25 thousand, they tried to save about ten percent for when they
got old. There was no Social Security. They hoped to earn enough
interest on their savings to keep up with inflation.

Another look at Spending and Revenues

This is more or less relevant to Beverly’s post from earlier today.

How many times have you heard Boehner, McConnell, Ryan or one of the legion of right-wing talking heads say, “We don’t have a revenue problem, we have a spending problem?”  I refuted that lie repeatedly in this AB post and at the included links.   But this is one of those zombie ideas that simply will not stay in the grave.  

Therefore, some prominent voices have found it necessary to sing out again against the lie. I will add my humble quavery baritone to the chorus.

Here in Graph 1 is Kevin Drum demonstrating how Real Government Expenditures per Capita have changed under the last three presidents.

What we have isn’t a spending problem. That’s under control. What we have is a problem with Republicans not wanting to pay the bills they themselves were largely responsible for running up.

 Graph 1, Real Government Expenditures per Capita

By using real [inflation adjusted] and per capita numbers, Drum has introduced a couple of denominators.  Real expenses per cap is a rational way to display the data, but not the only way. So lest someone cry out about that ol’ devil denominator, let’s have a different look.

Via Paul Krugman we get Graph 2 and Graph 3, from FRED, showing total Government expenditures and Federal Government expenditures, respectively, on log scales.

Graph 2. Government Total Expenditures
Graph 3, Federal Government Total Expenditures

Yes, you can argue that spending was growing too fast under Bush, although it’s funny how few deficit scolds saw fit to mention that at the time. Or you can say that you just want less spending, although as always people who say this tend to be short on specifics. But the narrative that says that spending has surged under Obama is just wrong – what we’ve actually seen is a slowdown at exactly the time when, for macroeconomic reasons, we should have been spending more.

Remember, a log scale represents constant growth as a straight line, and zero growth as a horizontal line.  So, in pure dollar numbers, spending hasn’t quite declined, but it has stagnated to almost zero growth.  Hence Drum’s decline in inflation adjusted, per capita terms.

In Graph 4, we get one more longer range look, using Krugman’s data series, this time on a linear scale.  Also presented is the difference between the two, which is the amount of spending by state and local governments.

 Graph 4, Government Spending at Different Levels

 The red line is total spending at all levels of governemnt, the blue line is federal only, and the green line is the difference, state and local spending.  Note that the green line flattens early in the recession

To bring things full circle, Graph 5 shows Federal Government current receipts.  Look at this and tell me we don’t have a revenue problem.

Graph 5, Federal Government Current Receipts

To drive this point home, Graph 6 shows Federal Receipts as a fraction of GDP.  The purpose of the ratio is to provide context, using GDP as a proxy for the size of the economy.

Graph 6, Federal Receipts as a fraction of GDP

As you can see, revenues/GDP are in a historically low range.

Conclusions:
– Federal spending is flat in nominal dollar terms.
– Federal spending is declining when adjusted for inflation and population growth.
– Federal revenues are far below trend lines based on any historical reference you chose.
– Federal revenues as a fraction of GDP are historically low.
– The Republican claim that we have a spending problem not a revenue problem is simply a lie, on both counts.
– Disproportional spending growth has only occurred under two presidents: Republicans Ronald Reagan and George W. Bush. 

The simple fact is we have a revenue problem, not a spending problem.

Why do Republicans lie?

The truth is hostile to their agenda.  PK Explains.

Cross posted at Retirement Blues

Another Look at Wealth and Consumption – Pt 2

Correlations and Slopes Over Time

In Part 1, we looked at the ratio of consumption spending to net worth, and how it changed over time.  This time we’ll look at the correlation between net worth and consumption.

Here is the big picture: personal consumption expenditures (FRED Series PCE) plotted against Net Worth (FRED series TNWBSHNO) Data is per calendar quarter.

Graph 1  Consumption vs Net Worth, 1959 – 2011

The data set is divided into two segments, with a break point at the beginning of 1997, with net worth at $30,315 and consumption at $5,467.  In a close up view, there is a clear slope change there.  Still, the selection is a bit arbitrary, since the high point of Q3, 1994, could also have been chosen, with net worth at $25291, and PCE at $4856.  But that is a detail, and no other reasonable breaks stand out.

Notably, both the slope of the data line and R^2 are significantly less after the break.  Visually, it’s obvious that in the later data, there is a lot more scatter.  Also note that that big data moves post 1997 return to the continuation of the best fit line, pre-1997.
Slope and R^2 measurements for the entire data set and the two segments are presented in Table 1. These numbers were generated using the linear trendline function in Excel.

 Table 1
 

Not so visually obvious are the declining slopes during the earlier portion of the data set.  Table 2 presents the same characteristics for data chunks of approximately 20 year duration.

Table 2

We saw in part 1 of this series that the relationship of consumption to net worth was not stable, so this result is not surprising.  And we can now see that as net worth increases, the sensitivity of consumption to increasing net worth decreases.

I can think of two contributing factors.  As wealth increases, the need to spend on basic necessities captures a smaller portion of that wealth, so the propensity to spend decreases.  I’ll defer consideration of the other factor for now.

Here is a detailed look at how the slope of the PCE vs net worth line varied over time.  Graph 2 shows the 34 quarter slope values for the data points of graph 1.  The slope is plotted in dark blue, with certain time spans highlighted in contrasting colors: recessions are in orange, and the stock market and housing bubbles are in yellow.

Graph 2 Slope of Consumption vs Net Worth

Observations:
1) Except for the bubbles and the spike in the post-bubble recession of 2008, the values are mostly contained between a low of 0.168 and a high 0.246.
2) There was an upward trend that ended in the mid-70’s, underscored with a blue line.
3) Values after the mid-70’s, including the two bubbles, are contained in a down-sloping channel, outlined in green.
4)  Except for the early 80’s and 90’s events, recessions are marked by sharp, temporary slope increases.
5) The average slope is 0.184, with a standard deviation of .038
6) The bubbles highlighted in yellow in Graph 2 correspond exactly to the data points in Graph 1 that fall below the red best fit line.
7) The post-bubble recessions brought the slope back into the range described in Observation 1.  This is illustrated in Graph 1 by the returns to the blue best fit line.

If the normal relationship between net worth and consumption is described by a slope in the range of around 0.17 to 0.25, what is there about bubbles that causes drops into the range of 0.11 to 0.12 at the peaks?  I think the answer is the second factor that I defered until now.  The stock bubble and the housing bubble represented wealth increases that were not shared equally across the population.  Specifically, as I pointed out earlier, these assets are mostly owned by the richest population segment, and growth in wealth has excessively favored the top 1% of the population.   They have the least propensity to spend, and this tendency drives the PCE slope into the low range.

This FRED graph illustrates the point in a different way.

Graph 3 PCE, Net Worth and Disposable Income

There are four lines, Net Worth in green (divided by 5 to put it on the same scale); Disposable Income in purple, PCE in red, and Disposible Income multiplied by 0.931 in blue.  Note that the last two overlap almost perfectly, as I also pointed out earlier (see link above.)

The conclusions I’m drawing are
1) Since the bubbles increased wealth in a highly skewed fashion, the relationship between average wealth and consumption broke down.
2) When the bubbles burst, the normal relationship between wealth and consumption reasserted itself.
3) The underlying cause is that during the bubbles the relationship between wealth and income broke down, and afterwards reasserted itself.
4) The relationship between disposable income and consumption is robust across time and most extraordinary financial events.
5) All the foregoing suggest that if wealth distribution were more even across the population (and thus more closely tied to disposable income,) then the relationship between wealth and consumption would be more robust.

Cross-posted at Retirement Blues.

Another Look at Wealth and Consumption – Pt 1

 Part 1 – Spending as a fraction of Net Worth

Tim Duy weighed in on the output gap debate – not my topic, but he presented this chart of net worth as a percentage of GDP.

Graph 1 Net worth as a Percentage of GDP 

That got me thinking again about the issue of whether consumption spending is determined by income or wealth. Specifically, if consumption is determined by wealth, there should be peaks in consumption corresponding to the dot-com and housing bubbles shown on Graph 1.  However, as Graph 2 shows, there were no such peaks.

Graph 2 Personal Consumption Expenditures

I’ve argued already that, contrary to standard economic thought, consumption is directly determined by income.  (Posted at RB and at AB.) One observation was that consumption, as a fraction of income, didn’t vary much over time, averaging 90.1% with a standard deviation of 2.1%. 

I took a similar look at consumption and net worth, data from Fred.  The next three graphs show personal consumption expenditures (PCE) as a decimal fraction of net worth (blue, left scale) along with net worth (NW) (red, right scale) over different time spans.

Graph 3A  Expenditures/Net Worth and Net worth, 1959-79,

Graph 3A spans from 1959 – the beginning of the data set – to 1979.  Net worth rises exponentially as the population grows.  Adjusting for population growth does not change the shape of the net worth curve, so, in the aggregate, we were becoming richer during those years.  Note that PCE/NW follows a generally similar, though far bumpier trajectory.  As I pointed out in the prior post, the personal savings rate also increased during this period, so the average worker was able to both save and spend more.

Graph 3B  Expenditures/Net Worth and Net worth, 1975-90

Graph 3B spans from 1975 to 1990.  Net worth continues on its exponential track.  But, after about 1979, PCE/NW drops, reversing the prior trend.  By 1990, PCE/NW is no greater than it was in the early 1960’s.  Meanwhile, the personal savings rate also dropped – to a range below that of the early 60’s.

Graph 3C  Expenditures/Net Worth and Net worth, 1989-2011

Graph 3C spans from 1989 through October, 2011.  The exponential growth of net worth falters before and during the two most recent recessions.  After about 1994, PCE/NW is a roller coaster ride.  Of particular interest is the exactly contrary motion at a detail level between NW and PCE/NW, after about 1998.  During the housing bubble of mid-last decade, PCE/NW hit an all time low.

What narrative makes sense of these three graphs?  Here’s my attempt.

Through the 60’s and 70’s, the standard of living was increasing, as incomes and net worth rose together.  This allowed more discretionary spending, and therefore, the fraction of NW that was spent increased.

In the 80’s, aggregate net worth continued to rise, but consumption spending, quite dramatically, failed to keep pace.  Lane Kenworthy has repeatedly pointed out that middle class income growth has decoupled from general economic growth as the upper income percentiles have captured an increasing slice of total income.  As the wealthy grew wealthier and the middle class fell behind, the fraction of NW that was spent declined – exactly the opposite of what should happen if increasing wealth determined spending.  But exactly what should happen if increased wealth is diverted to the already wealthy who have less of a propensity to consume.

During the 90’s, growth in median family income and GDP per capita were close to parallel (see graph at the Kenworthy link)  so there was a lull in the decoupling.  For most of that decade, PCE/NW was close to constant at 0.18-.19.  But while spending was kept level, the personal savings rate continued to fall. 

During the current century, median family income has flat-lined, while GDP/Capita has continued to increase. The decoupling has resumed and the wealth disparity has widened.   During the two wealth bubbles, PCE/NW declined dramatically.  When the bubbles burst and net worth declined, PCE/NW increased  back into the 0.18-.19 range.  Most strikingly, from about 1998 on, the two lines in graph 3C exhibit exactly contrary motion at a detail level.

Conclusions:

There was a tight relationship between Net Worth and consumption through the 60’s and the 70’s, when earnings growth kept up with GDP and wealth disparity was slight by current standards.

This relationship broke down during the 80’s – though one could argue as early as the mid 70’s – as aggregate wealth and working class income decoupled.

Most recently, the relationship between NW and PCE/NW is inverse.  The big swings in NW that the bubbles provided also demonstrated that consumption spending does not depend on net worth.

As I indicated in the earlier post linked above, consumption spending does depend on disposable income, throughout the entire post war period.  A simple look at readily available data casts grave doubts on the idea that wealth, and not income, determines consumption spending.

For the longer perspective, here is the data of Graphs 3 A-C on a single graph.

 Graph 4  Expenditures/Net Worth and Net worth, 1959-2011

In part 2, we’ll look at how spending and Net Worth correlate.

Cross-posted at Retirement Blues.

Another Look at Keynesianism and the Great Stagnation

by Mike Kimel

Another Look at Keynesianism and the Great Stagnation

Cross-posted at the Presimetrics blog

Last week I had a post noting that the US government followed more or less naive Keynesian policies (whether on purpose or not I cannot say) from the early 1930s to the late 1960s. The post also notes that what Tyler Cowen calls The Great Stagnation, a period of relatively slow economic growth, began just about when the government moved from naive Keynesian policies to a regime that could mostly be described as “all deficits all the time.”

In this post, I’d like to present a couple of graphs that are pretty self-explanatory. The data in the graphs comes from the BEA’s NIPA Table 1.1.5 The black line runs from 1929 to 1967, and the gray line from 1968 to the present.


Figure 1


Figure 2

I’ll be coming back to this topic in future posts, but I’d like to make a few quick comments:

1. The Great Stagnation Tyler Cowen comments on seems to, at a minimum, coincide very strongly with the period where the government quit Keynesian policy, where the private sector’s share of the economy stopped shrinking and began growing, and where the government’s role in the economy stopped growing and started shrinking.

2.  Even if you assume the growth of the private sector or the shrinking of the government isn’t causing or contributing to the Great Stagnation, the data still leaves libertarian and conservative economic views at a loss.  After all – shouldn’t growth increase as the private sector becomes more important and the government shrinks in size? 

3.  Bear in mind that marginal tax rates – reduced in 1964 and then reduced again multiple times since then – were lower during the Great Stagnation period than they had been since the 1930s.  Needless to say, this is yet another fact that makes the data inconsistent with libertarian and conservative economic theory.

4.  As always, if you want my spreadsheet, drop me a line. I’m at my first name (mike) period my last name (one m only in my last name!!!) at gmail period com. And don’t forget which post your writing about.

Another look at the budget deficits

rdan

Another look at the budget deficit:

Discussions of the budget outlook typically begin with the budget “baseline”… In building the baseline, CBO follows rules that … generally assume that current laws affecting taxes and mandatory spending will continue without change.

Sometimes, however, current law diverges from current budget policies. This year, the official budget baseline incorporates several especially unrealistic assumptions. In particular, the latest baseline assumes that Congress will allow the 2001 and 2003 tax cuts, relief from the Alternative Minimum Tax, and other temporary tax provisions all to expire. It also assumes that the reductions in physician fees called for under Medicare’s sustainable growth rate formula — including a 20 percent reduction in 2010 — will actually take effect, even though Congress has stepped in to prevent such reductions since 2003. Finally, the baseline extrapolates enacted defense appropriations for 2009, which represent only a portion of the amount needed for operations in Iraq and Afghanistan this year and in coming years. …

Budget experts have been saying for a number of years that the official baseline departs sharply from reality. … In February 2009, CBO issued alternative budget scenarios that offered a more accurate representation of current budgetary policy. [2] We rely here on elements of those alternative budget projections and have updated them to be consistent with CBO’s new March 2009 baseline…

In our projection of the deficit under current budget policies, we adjust the official CBO baseline… These adjustments are detailed in the appendix table. Cumulatively, they point to deficits of $10.2 trillion over the next 10 years… CBO estimates that the cumulative deficit from 2010 to 2019 under the President’s proposals would total $9.3 trillion. Compared to our realistic baseline, the President’s proposals would reduce projected deficits by about $900 billion over the 2010-2019 period. [4] The deficit would be higher in 2009 and 2010, however, because the budget sets aside an additional $250 billion for stabilization of financial markets. …