Working Worries

April 11, 2021

by Steve Stofka

Early Saturday morning came the news that Amazon workers at the Bessemer, Alabama plant had rejected a union by more than 2-1. The strength of the rejection surprised analysts and advocates. Companies who offer competitive wages and generous benefit packages often win against union adoption elections.

Amazon workers at Bessemer start at $15 an hour; adjusted for relative cost of living, it is $17.30, slightly below the national median warehouse wage of $17.77. In addition, Amazon offers comparatively generous medical benefits. In a 2020 study, Antonios Chantziaras at the Durham University Business School and two professors at Greek business colleges found that auditing fees are higher for U.S. companies that have unions, an indication of the complexity of union work rules (2020). It makes economic sense for companies to pay workers enough to dissuade any organizing efforts.

The Amazon workers who would be receptive to union organizing are those in Los Angeles, where the starting pay is the same $15 hour. According to the BEA, the cost of living in L.A. is 40% higher than in Bessemer. The starting pay of $15 is above California’s minimum wage of $14, but indexed to the nation as a whole, that $15 per hour in L.A. is worth only $11 per hour.

Bernie Sanders and others campaigned in Bessemer to show support for union organizers. Instead of trying to organize where workers would be motivated to join a union, workers in Amazon’s 230 warehouses have been waiting to see the results of the Bessemer election. Why does organized labor and the politicians who support them campaign with the most effort in those geographic areas that are the least likely to succeed?

According to many analysts the economy is on a coiled spring, ready for explosive growth. There are many positive signs but the contradictions are puzzling. For two consecutive weeks, initial jobless claims have risen. However, the Bureau of Labor Statistics reports that the 4-week average of unemployment claims has not risen (FRED Series CC4WSA). The past two weeks may be data noise or a seasonal shift in the workforce, but that is not the sign of an economy poised to leap into action. In March, the 4-week average of claims was almost double the number of claims in March 2020, as the nation went into lockdown.

The Covid pandemic has uncovered startling disparities in our economy. According to the Bureau of Labor Statistics, those who kept their jobs this past year have seen a 4% increase in weekly wages (FRED Series CES0500000011). The other half of that story is ugly. Those service businesses who are open may offer jobs at lower wages. With many businesses still closed, job applicants have what economists call low bargaining power and are willing to take less pay.

The Relief Act and the recent stimulus checks have helped many. Let’s hope that these worrying signs are just noise and that the country is back to full recovery.


Photo by Christopher Burns on Unsplash

BEA. (2019). Cost of living calculator. Retrieved April 11, 2021, from

Chantziaras, A., Dedoulis, E., & Leventis, S. (2020). The impact of labor unionization on monitoring costs. European Management Journal, 38(2), 288-307. doi:10.1016/j.emj.2019.09.004. Retrieved from!

The View From Here

May 17, 2020

by Steve Stofka

The editorial page of the Wall St Journal criticized the provision in the CARES act that paid an additional $600 in unemployment benefits to working people told to stay home by their state and local governments (WSJ, 2020). An attack on a policy that supports people during this historic crisis is a personal attack on working families. Some workers are earning more in benefits than they did when working. This offends elitist sympathies. As families overwhelm the resources of food banks nationwide, the country club set worry about the moral hazard of providing an income of basic sustenance to those forced to stay home. What level of hell birthed such sentiments?

When governments order people to stop working, they have a responsibility for monetary damages as well as some compensation for pain and suffering. Some in our country’s aristocracy prefer a system that makes people desperate to work in order to eat and pay their bills. Such workers will be more inclined to compromise their safety and return to work. Who will clean the bathrooms and offices of the executives that own America?

Almost a hundred years ago the German director Fritz Lang painted a dystopian account of social and economic classes in his film “Metropolis.” Each day the workers descended into the underground to keep the machinery of the city running. Above ground, the sons of the elite enjoyed sporting contests and idle pleasures. 

In a past century the elite wore powdered wigs and flared waistcoats to distinguish themselves from the commoners. On the jogging paths in Central Park they might be indistinguishable from other runners. Unlike aliens from another planet the patrician class look human. Their attitudes are not.

State and local governments mandated business closures. Losing a job includes the loss of someone’s employer-sponsored insurance. The $1200 stimulus payment covered one month of COBRA replacement insurance for a family (Garfield, 2020). The elite write these barbaric rules.

To protect themselves, the elite left their tony neighborhoods in crowded Manhattan and Brooklyn (Quealy, 2020). Are they spending quality time at their homes in the Hamptons? The social and economic hierarchy of this world has changed little from the century old society that F. Scott Fitzgerald captured in The Great Gatsby.

As Fitzgerald wrote, the privileged believe that they deserve their entitlements. To criticize such thinking is Socialism or Communism. The elite claim to be the moral standard bearers of the country, the high priests of a religion they call Capitalism. Whatever serves their self-interest is enfolded into that religion. Whatever does not serve their interests is an ism that is un-American. To appease their god, the priests need the sacrifice of thousands of families. Let the subservient workers shed their concerns for their safety and shuffle to their daily toil. So sayeth the precious persons of privilege.


Photo by Alex Blăjan on Unsplash

Garfield, R., Claxton, G., Damico, A., & Levitt, L. (2020, May 12). Eligibility for ACA Health Coverage Following Job Loss. Kaiser Family Foundation. Retrieved from Key highlights by one of the authors

Quealy, K. (2020, May 15). The Richest Neighborhoods Emptied Out Most as Coronavirus Hit New York City. NY Times. Retrieved from

WSJ Editorial Board. (2020, May 14). Opinion | Pelosi’s Presidential Platform. Wall St. Journal.  Retrieved from (Paywall).


April 1, 2018

by Steve Stofka

This week I’ll look at several aspects of work, from cryptocurrencies like Bitcoin, to the minimum wage.

What is work? In general science or physics, the subject of “work” pictured a horse hitched to a pulley lifting a weight (an example). In one minute, the horse could lift so many pounds a foot in the air and that equaled so much horsepower. Thus we could reduce our definition of work to three components: weight, distance and time.

Even this mechanical definition of work illustrates a problem. If the horse lifted the weight, then let it down again, how would we know that the horse did any work? Should we give the horse a few cups of oats, or have we got a lazy horse?

A variation on that problem – I cut my lawn. My neighbor looks at my lawn and sees that work was done. In a week or two the grass has grown and time has erased any sign that I did work.

Thus, we need a way of recording work done. The product of the work performed may serve as a record. A big pyramid sitting on a desert is a permanent record that work was done. If workers dig holes in the ground, then fill the holes, how do we know any work was done? If they have dug up gold from those holes.

Bitcoin and other cryptocurrencies (crypto) are assets like gold. They recognize that some work was done. Equipment, technology and workers were needed to dig up gold. Likewise, electricity was an important resource needed to generate a bitcoin, and even more electricity will be needed to generate a replacement bitcoin if one were lost.

This Politico article is an account of a crypto mining boom in a rural area in Washington state. The electricity consumed is enormous. The mighty Columbia River nearby provides electricity at a fifth of the average cost in the country. By the end of this year, there will be enough electrical capacity in this small area to power the equivalent of a tenth of the homes in Los Angeles. Shipping containers house computer servers which generate so much heat that the exhausted air melts the snow around the containers. As gold records the digging of dirt, a bitcoin records the expenditure of some quantity of electricity.

Assets can represent past work, future work, or a combination of the two. Precious metals, jewels, books and artistic works represent work done in the past. On the other hand, a machine represents future work. Other assets include stocks and bonds, both of which are claims on future work. A bond is a fixed limit claim on a company’s assets. In contrast, a share of stock is an undying claim on a portion of a company’s assets.

The blockchain algorithm behind crypto requires agreement among many parties to confirm a property right to the crypto. The recording of property rights might seem rather ordinary to a reader in the U.S. In some countries, however, property deeds are more easily altered by those in power. In contrast, a blockchain system of recording property rights prevents forgery and alteration.

As a record of work done, money relies on a relatively stable value. High inflation damages the money record of work done. Consequently, high inflation can fracture the social bonds among people. As an example, I cut someone’s lawn on Saturday and am paid. When I spend the money on Sunday, it is worth half the amount. In effect, the money has only recorded that I cut half a lawn. Examples of this hyper-inflation are Zimbabwe in the 2000s, and Yugoslavia in the 1990s (Wikipedia article). Look no further than Venezuela for a current example of the destruction that inflationary policies can have on a society.

Let’s turn from the recording of work done to the doing of it. New unemployment claims are at a 45 year low. A decade ago, job seekers despaired. In contrast, employees today are confident they will quickly find new employment. To illustrate, the quit rate is at the same pace as the mid-2000s, at the height of the housing boom. As a percent of the labor force, new unemployment claims are the lowest ever recorded. Last week’s numbers broke the record set in April 2000 at the height of the dot-com boom.

Equally important to the strength of a job market is the fate of marginal workers who are most vulnerable to the shifting tides of the economy. This includes disabled people who want to work. During the recession, the unemployment rate for disabled men of working age reached almost 20%. Today it is half that.

Let’s turn to another disadvantaged sector of the job market – those who work for minimum wage. The 1930s depression put many employers at an advantage in the job market. The Fair Labor Standards Act of 1938 (FLSA) enacted a wage floor, but many workers were not subject to the new law. In 1955, almost twenty years after passage of the law, “retail workers, service workers, agricultural workers, and construction workers were still not required to be paid at least the minimum wage” (article).

The minimum wage affects many lower paid workers who are making more than minimum wage. In some union jobs, starting wages for helpers are set by contract at a percentage above minimum wage. The understanding may be non-written in some cases. In 1966, the rate was increased from $1.25 per hour to $1.60 per hour. Non-union clerks at a NYC hospital who had been making $1.70 per hour now complained that they were making minimum wage. As a result of their pressure on management, they got a raise within a few months.

Here’s a chart showing the annual increases in the minimum wage for each period since 1950.


In the three decades after World War 2, annual increases in the minimum wage exceeded inflation. Since 1977, the minimum wage standard has not kept pace with inflation.


If Congress truly represented all of their constituents, they would make the minimum wage adjust automatically with inflation. On the contrary, Congress represents only a small portion of their constituents, and the minimum wage is used as a political football.

Finally, there is the destruction of the record of past work by war. Every minute of every day, living requires calories, another measure of work. Therefore, each of us is a record of work done.  War destroys too many human records, and the unliving records of work like buildings, roads and bridges. Perhaps one day we will fight our battles in video games and stop destroying all those work records.

GDP, Unemployment, Wage Growth

Feb. 1st, 2015


The first estimate of 4th quarter GDP growth was 2.6%.  This figure is truly a guesstimate and is sometimes heavily revised in the following months. Last October, the first estimate of third quarter GDP growth was 3.5%.  As data continued to roll in, that estimate was revised upwards by a whopping 42% to 5.0%.

The year over year growth in inflation-adjusted, or real GDP was 2.5%, more or less following a trend that is four years old.

On a per capita basis, GDP growth is near 2%, the average rate of growth since World War 2.

Let’s get in the wayback machine and look at per capita GDP growth over the past four decades.  Reagan and Clinton groupies can leave the room now.  The adults are going to talk.  The 1970s and first half of the 1980s were a period of high inflation and erratic growth – up 5%, then down 3%.

Growth above 3% for any length of time leads to distortions in investment and the labor market which generates a subsequent downward correction lasting several years.  Above average growth in the late 1980s was followed by a three year period of below average growth in the early 1990s.  The strong growth of the late 1990s was fueled by a boom in dot-com investment and telecom coupled with ever rising house prices.  The above 3% growth of those years sparked an inevitable correction lasting three years, bringing us back to the 2% average.

The housing boom of the 2000s generated above average growth followed yet again by a three year correcting downturn. For those families who have struggled to recover from the recession, average growth may be too slow and too small.  On the other hand, average growth is less likely to lead to a rebalancing recession.



Much ado this week when the Labor Dept announced that new claims for unemployment dropped more than 40,000 to 265,000.  The week after the Martin Luther holiday is typically volatile each year with little consensus on the reasons.  The somewhat erratic weekly numbers are smoothed by using the four week average of new claims.  That average has been just below 300,000 since September.

Low numbers for the newly unemployed is good, right?!  As with GDP, too much of a good thing for a period of time may be a precursor to an offsetting period of not so good.  Such is the law of averages.  As a percent of the labor force, new claims are at the same low level as in mid-2000 and late 2006.

As the demand for labor increases, employers make compromising decisions out of necessity.  They hold onto low productivity workers. Workers who are let go can more readily find new jobs.  The number of new claims remains low.  Re-entrants into the job market help to reduce the pressure for wage increases but eventually wages begin to move upward.  Employers may cut margins to pay workers more than their productivity is worth.  Real wage growth climbs as the percentage of new unemployment claims remains low.

In the graph above I have highlighted two previous periods where new unemployment claims were low as real wage growth climbed.  The graph below illustrates the point a bit clearer.  It is based on the Employment Cost Index, a relatively new series about ten years old, that tracks the total employment cost, including benefits and required employment taxes and insurance.

Historical data suggests that a growing divergence between these two factors may play some part in generating an imbalanced economic environment – one that, unfortunately, soon rights itself.


Market Timing

The link to Doug Short’s blog is on the right side of this page but in case you might miss it, here is Doug’s monthly update of moving averages and the simple allocation model of the Ivy Portfolio.    The 10 month simple moving average crossover is similar to the 50/200 day crossover system I have mentioned numerous times: i.e. the Golden Cross and Death Cross.  Either system will help a person avoid the worst of a protracted downturn as we saw in the early 2000s and 2008 – 2011, and capture the majority of a long term upswing.

For those of you who have not read it, the Ivy Portfolio is a keep-it-simple allocation and timing model of domestic and foreign stocks, real estate, commodities and bonds using low cost ETFs.

A Week In The Life

September 28, 2014

This past Monday George was out in the backyard when his wife Mabel came out on the back deck to announce that lunch was ready.  From the deciduous vines that grew on the backyard fence George was pulling leaves that had turned an autumn shade of red.

“George, what are you doing?”
“I thought I would pull these leaves off before they fall.  This way I won’t have to stoop so much a few weeks from now to pick them out of the rock garden.  The leaves are getting in the pond and clogging up the filter.”
“Well, come on, dear.  Lunch is ready.  I heard on the radio a little while ago that the market is down.  You know how I worry about that.”
“Oh, really?” George replied.  “It was down last Friday.  Did they give any reason?”
“Something about housing.  I’m sure you’ll find out all about it while you are eating.”

Mabel had set a nice lunch plate of panini bread, cheese and vegetables.  George was a tall man, a big boned man, prone to weight gain in retirement. Although George was fairly fit for his age, she worried about his health, particularly his heart, the male curse.  Mabel made sure that they both ate sensible, healthy meals.

Mabel took her lunch into the living room, leaving George alone in the kitchen.  He liked to check in on the stock market a few hours before the close to get a sense of the direction of the day’s action.  She would have chosen to keep all their savings in CDs and savings accounts but the interest rates were so low that living expenses would slowly erode their principle.

“We’ll put just 25% of our money in the market,” George had told her.  “I’ll watch it carefully and if anything like 2008 happens again, we can pull it out right away.  I’ll know what the signs are.”

George had studied a book on technical indicators which were supposed to help a person understand the direction of the market.  Despite her confidence in George’s ability and sensibility, Mabel still worried.  The stock market had always seemed to her like gambling.

At the kitchen table, George turned on the computer while he chewed his carrots and celery.  He had never been fond of vegetables but found that his likes and dislikes had mellowed with age.  He liked that Mabel cared.  The market helped distract him from the vegetables.  He paged through the daily calendar at Bloomberg, then checked out the headlines at Yahoo Finance. Existing home sales in August had fallen more than 5% from the previous August but that was a tough comparison because 2013 had been a pretty strong year.  Existing home sales were still above 5 million.

Before George had invested some of their savings in the stock market, he had bought several books on how to read financial statements but soon gave up when he realized that knowing the fundamentals of a company would not protect their savings in the case of another meltdown like the recent financial crisis.  Patient though she might be, Mabel would be extremely upset with him if he lost half of his investment in the market.

He then turned to the study of technical indicators which analyzed the behavior of other buyers and sellers in the stock market.  As an insurance adjuster, he had learned C programming back in the 1990s and found a charting program whose language was familiar to him.  As a former adjuster for the insurance of commercial buildings, he was used to making judgments based on a complex interplay of many factors.  He played with several indicators, found a few that seemed to be reliable, but got burned when the market melted down in the summer of 2011.  He got out quickly but not quickly enough for he had lost more than 10% of his investment in the market.  The market healed but at the time it seemed as though there might be a repeat of the 2008 crisis.  Had George and Mabel been younger, George could have just ridden out the storm.  Retirement had made him cautious and the 2011 downturn made George almost as leery of the market as Mabel.

Tuesday was a fine day in late September.  Mabel put her crochet down and made the two of them some soup, with fruit, crackers and cheese.  She took pride in the variety of food that she prepared.  When she walked out on the deck to call George in for lunch, a startled crow took to flight.  George was sitting on the edge of the deck where the crow had been.

“What are you doing, George?”
“I was teaching that little crow how to break open a peanut,” George replied. “I think they learn how to do stuff like that from their parents but I haven’t seen the flock in a few days and this guy was just wandering around the backyard looking for something to eat.  When I gave him a peanut, he didn’t seem to know what to do with it.  He’d pick it up in his beak, then drop it and stare at it.  He pecked at it a few times but that only made the peanut skitter away. “
George held up a branch.  “I carved a claw into the end of this branch and held down the peanut for him.”  George held up half a peanut shell.  “See, he got it figured out.  He flew off when the door opened but I’ll betcha he’ll be back.”
“Well, come on in then.  Lunch is ready.  The market is down again.  Something about housing again.”
“Hmmm,” George grunted and followed Mabel into the kitchen.  “Hmmm, that soup smells good.”
“A little beef vegetable that I doctored up a bit,” Mabel said with a smile.
George gave her a little hug. “I sure like your doctoring.”

He sat down to eat, wondering what all the fuss in the market was.  Checking the Bloomberg Calendar, he saw that it was the House Price index from the Federal Housing Administration that had dampened spirits.  The monthly change was drifting down to zero, a sign of weakness.  Although housing prices were still rising, the rise was slowing down.

A disappointment, George thought, but not a catastrophe.  However, the market had been down for three days in a row.  He finished his lunch and went into the living room.  Mabel was reading a book.
“You know, Mabel, I think it’s just a short term thing.  The bankers from the developed countries met last week and they kinda put out a wake up call to the market.  I think there’s a bit more caution and common sense after that.”
“Well, as long as you’re watching it, dear.”
“You know, we did good this last year,” he reassured her.
“I just worry that it was too good.  We should have taken some of that out of the market and put it somewhere safe.”
 “Well, I’m keeping an eye on it,” he said.  “I checked CD rates last week and they are paying like 1% for a one year CD.  It just ain’t like it used to be. We just have to take some risk.”

They had a 3-year CD coming due in a month. He didn’t want to tell her that he was thinking about not rolling over the CD.  Maybe buy a bond fund.  She wouldn’t like that. For a time he had dabbled in some short to medium term trading but barely broke even.  He had lost sight of his original goal – to keep their savings safe while taking some risk with the money.  Fortunately, this insight had come to him toward the end of 2012.  The market had been mostly up since then, rewarding those who sat out the small downturns.

Late Wednesday morning, Mabel could hear George on the side of the house clearing brush or some such thing.  He said he was going to cut down an elm tree sapling that was growing near the house but when she went out to call him into lunch, he had cut everything but the elm sapling.

“I thought you were going to cut that down, dear.”
“Well, I was but the squirrels are using it to climb up to the old swamp cooler we have perched up there.  You remember the litter from early this spring?  Well, I think there’s another litter in there.  I haven’t seen any young ones but there’s a squirrel carrying twigs up that sapling to the cooler.  She’s even got a piece of one of my rags.  Must’ve fallen out of my pocket.”

Mabel looked up at the platform George had mounted to the side of the house years ago.  On top of the platform sat the old abandoned cooler.  George had meant to take it down and disassemble the platform but then the squirrels had used it as a nursery this winter and neither of them had been able to dismantle it while the little ones were scampering around in and out of the cooler.  Of course, George was supposed to take the cooler down during the summer but never got around to it.  Now she saw that he had tied a cord from the platform to the sapling to bend the sapling close to the platform, making it easier for the squirrel to get from the tree to the platform.

She shook her head and said “George Liscomb, I hope you don’t let that sapling get out of hand.  You know how elm trees are.  They grow faster than a puppy.”
“Well, the tree won’t grow much during the winter and I’ll cut it down in the spring.”
“Ok, well, come on it.  Lunch is ready.  I heard on the radio that the market is up a lot today.  Housing again.  Maybe you were right about it being short term.”
“Well, of course, I’m right,” he made a grand gesture.  “The squirrels will confirm that.”

His lunch plate held some broccoli spears and six, no more and no less, tater tots.  “I know you don’t particularly like broccoli so I thought a few tater tots might ease the pain,” Mabel said with a slightly sardonic smile.

He laughed.  “I’m married to a kind prison guard.”  He sat down at the table, wondering what could have buoyed the market so much.  Housing yet again.  “Holy moly!” he called out to Mabel. He went into the living room to tell her the good news. “Finally, after more than six years, new homes are selling at a rate of more than half a million a year.  That’s what’s got the market dancing.”

On Thursday, she found George working on the stream that he had built in the rock garden.  A few feet from George a squirrel cautiously sipped water from the stream.  The squirrel saw her and scampered up the nearby fence.  “It’s remarkable how comfortable they are with you,” she told him.  “I try to move slowly when I’m working,” George replied. “They seem to be less anxious.”
“What are you doing today?” she asked.
“Got a leak somewhere.  I’ve lost about 15 gallons since last night.  Still haven’t found it.”
“Well, you’re not going to like what going on in the market.  It’s way down today and it’s not about housing.”

He followed her into the house and broke into a big grin when he saw what was for lunch. “Tuna fish!”  Mabel had dressed up her famous tuna fish salad with lettuce, tomatoes, some green onions and put it open faced on some toasted bread.  It was scrumptious.  Not so the market.  The SP500 was down about 1-1/2% on several news releases.  The whopper was that Durable Goods Orders were down 18% in August from the previous month.  But most of that drop was a decline in aircraft orders after a surge in those same orders in July.  Aircraft orders were notoriously volatile. Year-over-year gains in non-defense capital goods, the core reading, were up almost 8%.

The weekly report of new unemployment claims had risen slightly but was still below 300,000.  September’s advance reading of the services sector, the PMI Services Flash, was slightly less than the robust reading of August but still very strong.  So what was causing these overreactions to news releases?  The short term traders execute buy or sell orders within seconds of a news release.  Computer algorithms trade within nanoseconds of the release.  If new unemployment claims are up even by 1, the word “up” or “rise” or some variation will occur within the release.  Sell.  New home sales up?  Up is good for this report.  Buy.  Why would the short-termers be so active this week?  Because they are trading against each other.  The mid and long termers, the portfolio managers, will take the stage at the beginning of next week to adjust their positions at quarter end when funds report their allocations.

Late Friday morning, Mabel stood out on the back deck, her mouth open at the sight of George hunched down as he came out of the shed in the backyard.  Hundreds of wasps swarmed above him.  He knelt down and closed the doors to the shed and hurried to her on the deck.

“My God, George!  Are you all right?”
“Oh, yeah, no worries.  Anything on me?” he asked.
“No.”  There were just a few wasps visible outside the closed doors.  “What on earth?!”
“Well, they’ve really built themselves a city since I was in there last,” George explained.  He sat down on the deck.  The shed was where they kept old tax records and camping gear that they hadn’t used in quite a long time but hadn’t given away or sold – just in case they went camping again.  “I should have sprayed them earlier in the summer but it was such a small hive.  Those doors get sun most of the day so they like it in there.  They’re right above the doorway so they’re not bothering any of our stuff and I was able to stand up in the shed and they just left me alone.”
“I don’t care. What if I had gone out there to get something?!” she said angrily.
“Yeh, you’re right.  I’ll take care of them this weekend.  I was kinda waiting for the cold weather to do its job.”  He held up his hands a couple of feet apart from each other.  “That hive is like this, strung out along the studs that frame the doorway.”
“Why were you out there?” she asked.
“Well, I wanted to see if we still had the box that the TV came in a few years ago.”
“Didn’t you throw it out?” she asked.
“Well, I thought that in case we had trouble with the TV but then the box was behind a bunch of stuff and it was hard to get to and I guess I forgot,” he admitted.
“Well, come on it and eat your lunch.  The market is up again today, I heard them say.”

George settled down at the kitchen table.  A few salami slices, some macaroni salad, carrots, olives and crackers sat on the plate.  “Working man’s antipasto, hey?”
“There are some sardines in there, too” she said.
“I have the best wife and cook in the world.  Anthony Bourdain, move ovah!  Mah honey’s takin’ ovah!”
Mabel laughed.  “Now let me get back to my book.  Second to last chapter and I think the niece did it.  I haven’t trusted her since the first chapter.”

The 3rd estimate of 2nd quarter GDP had been revised up from 4.2% to 4.6%, helping to compensate for the weak first quarter.  Good stuff, thought George.  The U. of Michigan Consumer Sentiment Survey had risen in September to 84.6 from August’s 82.5.  Confident consumers buy stuff, a good sign.  Anything above 80 was welcome and more was better.  To round out the daily trifecta of news releases, corporate profits for the second quarter were revised upward.  The year over year gain without inventory and depreciation adjustments was 12.5%.  Not spectacular but solid.

Even with Friday’s triply good news, the market closed below what it opened at the previous day.  This was usually an indication that the short term downward trend in the market might have a little way to run.  Then he promised Mabel that he would get rid of the wasps this weekend, and yes, he would be careful.  Did she remember seeing the wasp spray that he bought earlier that summer?

GDP and Education

June 29, 2014

This week I’ll review some of this week’s headlines in GDP, personal income, spending and debt, housing and unemployment.  Then I’ll take a look at some trends in education, including state and local spending.

Gross Domestic Product First Quarter 2014

The headline this week was the third and final estimate of GDP growth in the first quarter, revised downward from -1% to -2.9%.  This headline number is the quarterly growth rate, or the growth rate over the preceding quarter.  A year over year comparison, matching 2014 first quarter GDP with 2013 first quarter GDP, shows an annual real growth rate of 1.5%, below the 2.5 to 3.0% growth of the past fifty years.  The largest contributor to the sluggish GDP growth was an almost 5% drop in defense spending.  Simon Kuznets, the economist who developed the GDP concept, did not include defense spending in the GDP calculation.

Contributing to the quarterly drop was the 1.7% decline in inventories.  Businesses had built up inventories a bit much in the latter half of 2013 in anticipation of sales growth only to see those expectations dashed by the severe winter weather.  Final Sales of Domestic Product is a way of calculating current GDP growth and does not include changes in inventory.  Let’s look at a graph of the annual growth in Real (Inflation-Adjusted) GDP and Real Final Sales of Domestic Product to see the differences in the two series.

Note that Real GDP growth (dark red line) leads Final Sales (blue line) as businesses build and reduce their inventory levels in anticipation of future demand and in reaction to current and past demand.
The Big Pic: if we look at these two series since WW2, we see that ALL recessions, except one, are marked by a year over year percent decline in real GDP.  The 2001 recession was the exception.

Secondly, note that in half of the recessions, y-o-y growth in Final Sales, the blue line in the graph, does not dip below zero.  We can identify two trends to recession: 1) businesses are too optimistic and overbuild inventories in anticipation of demand, then correct to the downside, causing a reduction in employment and a lagging reduction in consumer spending; 2) consumers are too optimistic and take on too much debt – selling an inventory of future earnings to creditors, so to speak – then correct to the downside and reduce their consumption, causing businesses to cut back their growth plans.  In case #1, a decrease in consumer spending follows the cutbacks by businesses.  In case #2, businesses cut back following a downturn in consumer spending.

In this past quarter, employment was rising as businesses cut back inventory growth, indicating more of a rebalancing of resources by businesses rather than a correction.  Consumer spending may have weakened during the first quarter but, importantly, did not decline.  We have two hunting dogs and neither is pointing at a downturn.

For a succinct description of the various components of GDP, check out this article written for by Kimberly Amadeo.  Probably written in the first quarter of 2014, her concerns about the inventory buildup in 2013 were proved accurate.


Income and Spending

Personal Income rose almost 5% on an annualized basis in May but consumer spending rose at only half that pace,  2.4%.  The spending growth is only slightly more than the 1.8% inflation rate calculated by the Bureau of Economic Analysis, revealing that consumers are still cautious.

I heard recently a good example of how data can be presented out of context, leading a listener or reader to come to a wrong conclusion.  Data point: the dollar value of consumer loans outstanding has risen 45% since the start of the recession in late 2007. Consumer loans do not include mortgages or most student loan debt. If I were selling a book, physical gold, or a variable annuity with a minimum return guarantee, I could say:

My friends, this shows that many consumers have not learned any lessons from the recession.  They are living beyond their means, running up debts that they will not be able to pay. Soon, very soon, people will start defaulting on their debts and the economy will collapse.  This country will suffer a depression that will make the 1930s depression look tame.  Now is the time to protect yourself and your loved ones before the coming crash.

Data is little more than an opportunity to spread one’s political message.  Data should never lead us to reconsider our message, our point of view.  If I were penning a politically liberal message, I could write:

The families in our country are desperate.  Without enough income to satisfy their basic needs, they are forced to borrow, falling ever deeper into debt while the 1% get richer.  We need policies that will help families, not the financial fat cats on Wall Street.  We need a tax structure that will ensure that the 1% pay their fair share and not have the burden fall on the shoulders of most of the working Americans in this country.

Selling a political persuasion and selling a car brand often employ similar techniques.  Data should never lead us to question our loyalty to the brand.  If I were crafting a conservative message, I could write:

The misuse of credit indicates an immaturity fostered by cradle to grave social programs, which are eroding the very character of the American people, who come to rely less on their own resources and more on some agency in Washington to help them out.  People steadily lose their sense of personal responsibility, becoming more like children than self-reliant adults.

However, the facts behind the data point lead us to a different story. In the spring of 2010, consumer loans spiked, rising $382 billion in just two months.

That surge represents more than a $1000 in additional debt per person. Consumers did not suddenly go crazy.  Banks did not open their bank vaults in a spirit of generosity. Instead, banks implemented accounting rules FAS 166 and 167 that required them to show certain assets and liabilities on their books. $322 billion of the $382 billion increase in consumer loans during those two months in 2010 was the accounting change. If we subtract that accounting change from the current total, we find that real consumer loan debt increased only 5.5% in 6-1/2 years.  And that is the real story.  Never in the history of this series since WW2 have consumers restrained their borrowing habits as much as we have since December 2007.  We had to.  In the eight years before the financial crisis in 2008, real consumer debt rose 33%, an unsustainable pace.

About two years ago, loan balances stopped declining and since then consumers have added $80 billion, much of it to finance car purchases. $25 billion of that $80 billion increase has come only since the beginning of this year.  On a per capita, inflation adjusted basis, consumer loan balances are still rather flat.



New home sales in May were up almost 20% over April’s total, and over 6% on an annual basis.  Existing homes rose 5% above April’s pace but are down 5% on an annual basis.  Each year we hope that housing will finally contribute something to economic growth.  Like Cubs fans, we can hope that maybe this year….


Unemployment Claims

New unemployment claims continue to drift downward and the 4 week moving average is just below 315,000.  Our attention spans are rather short so it is important to keep in mind that the current level of claims is the same as what is was last September.

It has taken this economy six months to recover from the upward spike in claims last October.  The patient is recovering but still not healthy.


Minimum Wage

The number of workers directly affected by changes in the minimum wage are small.  We sympathize with those minimum wage workers who try to support a family.  The Good Samaritan impulse in many of us prompts us to say hey, come on, give these people a break and raise the minimum wage.  What we may forget are the implications of any minimum wage increase.  Older readers, stretch your imagination and remember those years gone by when you were younger. Workers in their early working years often see the minimum as a benchmark for comparison.  The much larger pool of younger workers who make above minimum wage may push for higher wages in response to increases in the minimum wage.

Fifty years ago, Congress could have made the minimum wage rise with inflation, ensuring that workers in low paid jobs would get at least a subsistence wage and that increases would be incremental.  Of course, there are some good arguments against any nationally set minimum wage.  $10 in Los Angeles buys far less than $10 in Grand Junction, Colorado.  Ikea recently announced that they will begin paying a minimum wage that is based on the livable wage in each area using the MIT living wage calculator .  Several cities have enacted minimum wage increases that will be phased in over several years but none that I know of are indexed to inflation as the MIT model does.

Congress could enact legislation that respects the differences in living costs across the nation.  For too long, Congress has chosen to use the minimum wage as a political football.  Social Security payments are indexed to inflation because older people put pressure on politicians to stop the nonsense.  There are not enough minimum wage workers to exert a similar amount of coordinated pressure on the folks in Washington so workers must rely on the fairness instinct of the larger pool of voters if any national legislation will be passed.



Demos, a liberal think tank, recently published a report recounting the impact of rising tuition costs on students and families.  Student debt has almost quadrupled from 2004 – 2012.  Wow, I thought.  State spending per student has declined 27%.  More wows.  How much has enrollment increased, I wondered?  Hmmm, not mentioned in the report.  Why not?

The National Center for Education Statistics, a division of the Dept. of Education, reports that full time college enrollment increased a whopping 38% in the decade from 2001-2011.  Part-time enrollment increased 23% during that time.  Together, they average a 32% increase in enrollment. Again, wow!  Ok, I thought, the states have been overwhelmed with the increase in enrollment, declining revenues because of the recession, etc.  Well, that’s part of the story.  Spending on education, including K-12, is at the same levels as it was a decade ago.

From 2002-2012, states have increased their spending on higher ed by 42%.  Some argue that the Federal government should step up and contribute more.  In 2010, total Federal spending on education at all levels was less than 1% ($8.5B out of $879B).  Others argue that the heavily subsidized educational system is bloated and inefficient.  As much cultural as they are educational institutions, colleges and universities have never been examples of efficiency.  Old buildings on college campuses that are expensive to heat and cool are largely empty at 4 P.M.  Legacy pension agreements, generously agreed to in earlier decades, further strain state budgets.  We may need to rethink how we can deliver a quality education but these are particularly thorny issues which ignite passions in state and local budget negotations.

Although state and local governments have increased spending on higher ed by 42% in the decade from 2002-2012, the base year used to calculate that percentage increase was particularly low, coming after 9-11 and the implosion of the dot-com boom.  Nor does it reflect the economic realities that students must get more education to compete for many jobs at the median level and above.

Let’s then go back to what was presumably a good year, 2000, the height of the dot-com boom.  State coffers were full.  In 2000, state and local governments spent 5.14% of GDP (Source).  By 2010, that share had grown to 5.82% of GDP (Source). That represents a 13% gain in resources devoted to education.  But that is barely above population growth, without accounting for the rush of enrollment in higher education during the decade.

Let’s take a broader view of educational spending, comparing the total of all spending on education, including K-12, to all the revenue that Federal, state and local governments bring in.  This includes social security taxes, property taxes, sales taxes, etc.  As a percent of all receipts, spending on education has declined from 30% to under 18%.

Many on the political left paint conservatives as being either against education or not supportive of education.  Census data shows that Republican dominated state legislatures, in general, devote more of their budget to education than Democratic legislatures.  W. Virginia, Mississippi, Michigan, S. Carolina, Alabama and Arkansas devote more than 7% of GDP to education, according to U.S. Census data compiled by  Only two states with predominantly Democrat legislatures, Vermont and New Mexico, join the plus-7% club (Wikipedia Party Strength for party control of state legislatures).

In the early part of the twentieth century, a high school education was higher education.  In the early part of this century, college may be the new high school, a minimum requirement for a job applicant seeking a mid level career.  What are our priorities?  In any discussion of priorities, the subject of taxes arises like Godzilla out of the watery depths.  People scramble in terror as Taxzilla devours the city. Older people on fixed incomes and wealthy house owners resist property tax increases.  Just about everyone resists sales tax increases.  Proposals to raise income taxes are difficult to incorporate in a campaign strategy for state and local politicians running for election.

Let’s disregard for a moment the ideological argument over Federal funding or control of education.  Let’s ask ourselves one question:  does this declining level of total revenues reflect our priorities or acknowledge the geopolitical realities of today’s economy?



Reductions in defense spending, inventory reductions and a severe winter that curtailed consumer spending accounts for much of the sluggishness in first quarter GDP growth.

A surge in new home sales is a sign of both rising incomes and greater confidence in the future.

Consumer spending growth is about half of healthy income gains.

Spending on education has grown a bit more than population growth and is not keeping up with surging enrollment in higher education.

Labor’s Journey

January 12th, 2014

A dramatic decrease in new orders, mostly for export, for the non-manufacturing sector of the economy offset other positives in the December ISM report.  The composite non-manufacturing index dropped slightly but is still growing.  A blend of the manufacturing and non-manufacturing indexes, what I call the CWI, declined from its peak as expected. A month ago I noted the cyclic pattern in this index, and the shorter time between peaks as the economy has formed a stronger base of growth. Most businesses are reporting expansion, or strong growth.  Some respondents to the survey noted that the severe winter weather in December had an impact on their business.


Ringing in the New Year, the private payroll firm ADP issued a strong report of employment growth before the release of the BLS figures on Friday.  The reported gain in jobs was above the best of expectations.  In the past few months,  several reports in production and now in employment have exceeded expectations or come in at the upper bounds of estimates.


Wells Fargo announced that they will be offering non-conforming mortgages to selected buyers who present a low risk.  Non-conforming mortgages may be interest only, or have loan to values that don’t meet guidelines. Reminiscent of the “old days,” Wells Fargo intends to hold onto the mortgages instead of selling the paper in the secondary market.

The Gallup organization announced their monthy percentage of adults who are working full time, what Gallup calls the P2P.  I call this the “Carry the Load” folks, those people whose taxes are supporting the rest of the population.  At 42.9%, it is down a percentage point or two from previous winters.

The 4 week average of new unemployment claims is still below 350,000 but 20,000 higher than a month ago.  As I mentioned last week, this metric will be watched closely by traders in the coming weeks.  Although there is little statistical significance between a 349,000 average and a 355,000 average, for example, there is a psychological boundary marked in 50,000 increments.

Friday I woke up and found that somebody stole the ‘1’s at the Bureau of Labor Statistics.  The BLS reported net job gains were 74,000 and I thought that there was a smudge on my computer screen blocking the ‘1’ of 174,000 and reached out to wipe it off.  There was no smudge.  It is difficult to interpret the discrepancy between the ADP report and the BLS report.  Some say that the particularly harsh winter weather in the midwest and east caused many people to stop looking for work or that many businesses returned their BLS survey late.  If so, we may see some healthy upward revisions to the employment data when the February report comes out. Here’s a look at total private employment as reported by BLS and ADP.

As you can see there is a growing divergence between the two series.  As a percentage of 120 million or so employed in private industry, the divergence of a few hundred thousand is slight.  The BLS assumes a statistical error estimate of 100,000.  But people closely watch the monthly change in employment as a forecast of developing trends in the overall economy, changes in corporate profits and consequently the price of stocks.  Here is a chart of the difference in private employment as measured by the BLS and that measured by ADP.  A positive number means that the BLS is reporting more employment than ADP.

As with any estimates, I tend to average the estimates to get what I feel is a more accurate estimate.  This averaging works well when bidding construction jobs and some statistical experiments have proven the method reliable.  Averaging the two estimates for private payrolls gives us an estimate of job growth that is still above the replacement threshold of about 150,000 net job gains per month needed to keep up with population growth.

The figures above do not include 22 million government employees, or about 14% of total employment.  Flat or declining employment in this sector has dragged down the headline job gains each month.  Adding in net job gains or losses in the government sector gives us a net job gain of about 150,000 in December.

For those of you interested in more analysis of the employment report, Robert Oak at the Economic Populist presents a number of employment charts similar to the ones I have been doing in past months.

For the past 5 – 10 years, much has been written about the growth in income inequality during the past 30 to 40 years. I’ll call income inequality “Aye-Aye” because the abbreviation  “II” looks like the Roman numeral for “2” and because Ricky Ricardo used to exclaim “Aye, Aye, Lucy!” on that much loved comedy series.  Those on the left blame former President Reagan,  British Prime Minister Thatcher, and deregulation for Aye-Aye.  Those on the right blame increasing regulation that disincentivises businesses from taking chances, from making capital and people investments to pursue robust growth. The expansion of social welfare programs makes people ever more dependent on government and less likely to take jobs that they don’t want.  Economists cite the aging of the population as a cause of the growth of Aye-Aye.  Few I know of seriously challenge the idea that Aye-Aye has been happening.  The argument is over the causes and the solutions.

Thomas Piketty’s Capital in the 21st Century will add to the debate.  The English translation will be published in March.  A book review in the Economist outlines some of the ideas in the book.  Piketty’s analysis of almost 150 years of data from several countries indicates that the slower an economy grows, the more unequal the distribution of income.  One might think that the U.S. would have the most unequal income distribution, but Piketty reveals that it is France that tops the list.

Piketty’s rule of thumb is that the savings rate divided by a country’s growth rate will approximate the ratio of capital wealth to gross income.  As this ratio increases, more of the national income goes to those with capital wealth. So, if the savings rate is 8% and the growth rate is 2%, then capital wealth will be about four times gross national income.  Furthermore, he finds that population growth accounts for about half of economic growth over the past century and half.  Slowing population growth in the developed nations therefore leads to greater inequality of income.  If this rule of thumb is fairly accurate, stronger economic growth is the only way to lessen the inequality of income that has grown steadily over the past thirty to forty years.

If you are familiar enough with French, you can read a preview here or pre-order the English version here.  The book is sure to spark some lively discussion between those in the economic growth camp and those in the demographic camp.  The topic has long been a topic of discussion in emerging economies.  I will quote from an Asian Pacific policy journal published in 2003, “The most important determinant of inequality is not [emphasis mine] economic growth, however, but rather changes in demographic age structure.”

Continuing Unemployment Claims

July 21st, 2013

Since I’m on the road this will be a short piece.  Every week the Bureau of Labor Statistics (BLS) releases their estimate of new unemployment claims based on a compilation of state filings for unemployment.  Labor market analysts pay more attention to the 4 week moving average of this series because the weekly numbers can be volatile or affected by weather and holidays.

Each month the BLS releases their estimate of the number of unemployed and the percent of unemployment but this figure comes from a survey of households.  People surveyed report that they are unemployed and BLS interviewers substantiate responses by asking additional questions. However, there really is no independent verification that someone who says they are unemployed is actually unemployed.

As the states update their tally of those unemployed who continue to claim benefits, the BLS reports the number as Continuing Unemployment Claims.  While no number is entirely accurate, there is a greater degree of accuracy in this number of unemployed.  It does not include those who have not filed for unemployment or those who have run out their benefit period and are no longer eligible for benefits.

I wanted to compare this fairly reliable number with another somewhat reliable number – the number of employed from the Establishment survey.  This total is based on a survey of companies who report the number of employees on their payroll.  While this total has some problems it has proven to be more reliable than the employed number from the Household Survey.

Below is the number of continuing unemployment claims.  Four years after the official end of the recession in June 2009, continuing claims are still at levels seen in the earlier two recessions.  This indicates the persistent underlying weakness in the labor market.

Comparing continuing claims to the total employed reveals some surprises.

This metric shows the severity of unemployment in the recession of the early 1980s; the percentage surpassed the peak in this past recession.  We can see that current levels are high but not dangerously so.  We have seen higher levels during periods of robust growth in the mid to late 1980s and in the recovery years in the mid 1990s.  What we want to see is a continued decline in this percentage.

Capital Goods and New Claims

March 3rd, 2013

This past week came a number of positive economic reports.  The first one I will look at is the Durable Goods Orders, which indicate a willingness by consumers and businesses to commit money now to buy stuff that will last for several years.  A critical component of this index is capital goods, durable goods like machinery which produce more goods and services.  As a key indicator of business confidence in the future, it is one of the trends I watch. (See Predictions and Indicators)

Until the past few months, this component has been particularly weak, warning of recession.  Resolution of the “fiscal cliff” issue at the beginning of the year has sparked more optimism and it shows in the new orders for capital goods.  This deep a decline in the year over year percentage change has been followed with an uptick in the past, only to fall into recession.

When we smooth out the monthly data with quarterly averages, the trend is still in negative territory.

Every week the Bureau of Labor Statistics issues a report on the number of New Unemployment Claims.  This past week, the BLS reported a lower than expected number of 341,000, a drop of 22,000 from the week before. Numbers of more than 400,000 are a major concern.  The weekly series can be volatile; most analysts look at the 4 week moving average to get a better gauge of the trend. 

As with many data series, I am interested in the year over year (y-o-y) percentage change in the data.  Because the SP500 index is a volatile series, I’ve smoothed out the data to a 6 month average to show the negative correlation between stock prices and  new unemployment claims. 

In other words, when unemployment claims go up, the stock market goes down.  This particular data series is good when it is low, bad when it is high so I reverse the percentage change to show its correlation with the SP500. 

On a quarterly basis, this negative correlation has proved to be a reliable trading signal for the longer term investor.  When the y-o-y percentage change in new unemployment claims crosses above the SP500 change, sell.  When the claims change crosses below the SP500 change, it’s safe to buy.

Again, this strategy is for the long term investor who is more concerned with major structural changes in the economy that can cause a significant dent in her savings.  Using this strategy she will not maximize her gains but she will avoid major losses and it does not require that she check her stock portfolio more than four times a year.  An investor using this strategy for the past twenty something years would have bought in the first week of Oct. 1990 and been in the market during the 1990s as the index climbed, then stalled in the mid 1990s, then climbed again.  She would have sold in the first week of Jan. 2001, missing most of the market drop for the next several years.  She would have re-entered the market in the first week of October 2003 and sold again in the first week of April 2008, just before the financial meltdown in September of that year.  She would have bought again in the first week of January 2010 and would still be in the market.

For the long term investor who does not want to devote a part of their lives to reading financial news or watching CNBC, it is often difficult to separate the “noise” – the weekly headlines and economic reports – from the real motion or trend.  This indicator is a low maintenance signal for that investor.

P.S.  You can get this report yourself without much trouble. 
Enter “Fred New Claims” into your browser’s search bar. 
The first link should be “Unemployment Insurance Weekly Claims Report – FRED” at the Federal Reserve.

Click the link, then select the first series “4-Week Moving Average of Initial Claims”. 
When the graph displays, click Edit Graph in the lower left below the graph.
Select the 10 Years range radio button. 
In the Frequency field below the graph, select “Quarterly” and leave the Aggregation method at the default setting of “Average”. 
In the Units field below that, select “Percent Change From Year Ago”. 

(Adding the SP500 stock market index)
Below the “Redraw Graph” button, select the blue bar Add Data Series
Leave the New Line button selected.
In the Search field, type SP500 and select the default SP500 index.  The graph will redraw automatically but it will make little sense at this point until we edit the settings for the SP500 index. 
Select the 10 Year range button for the SP500.  Make sure you are editing the SP500 data graph and not the New Claims indicator. 
Change the Frequency field to “Quarterly” just as you did for the New Claims. 
Change the Units field to  “Percent Change From Year Ago” just as you did with New Claims. 
Click the Redraw Graph button and voila!