Political Calculations
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30 January 2015

How much should the Chief Executive Officer of a company be paid?

Before we attempt to answer that question, let's see how much CEOs are paid. Back on 15 April 2014, Forbes reported on a "study" released by the AFL-CIO, once a significant labor organization in the United States, but now mostly a political fundraising operation for leftist causes:

With CEO compensation analysis season in full swing, the AFL-CIO released data this morning stating that American CEOs in 2013 earned an average of $11.7 million–an eye-popping 331 times the average worker’s $35,293.

Though down from 2012's 354-to-1 CEO-to-worker pay ratio, the multiple more than doubles when compared to minimum wage workers; the average CEO in 2013 out-earned this group 774 times over.

We put "study" in quotes because the sample for the AFL-CIO's "research" consisted of 350 of the largest companies in the U.S., out of a total of 27,092,908 firms, which means they cherry-picked the available data for the CEOs of the largest and most successful firms with the most revenue. Meanwhile, the U.S. Bureau of Labor Statistics collected the data for some 248,760 CEOS at companies of all sizes and levels of success, finding that the average pay of a CEO was $178,400.

But that's quite a range for average values, isn't it? Whether its the average of $178,400 for 248,760 companies or $11,700,000 for 350 of the biggest companies doing business in the U.S., there has to be some objective way to determine just how much a given company's CEO job is worth.

The question of how much a CEO is really worth to a company is one that you might think would be difficult to answer, but which under special conditions turns out to be a lot easier than you might think. And by "special conditions", we're referring to the unique situation that happens at some companies when they announce a surprise change in their top leadership, where they replace their CEO.

There was one such example earlier this week, when McDonalds CEO Don Thompson announced he was stepping down after two years of running the fast food giant. The company had struggled under his leadership, with the company's revenues stuck in neutral and its stock barely treading water, even as the rest of the S&P 500 had risen by 47% in the same economic environment.

So when the news was announced before the stock market opened on 29 January 2015, it was very interesting to see that the company's shareholders reacted to the news that Johnson had resigned as CEO and would be replaced by Steve Easterbook by boosting the company's stock price from a closing value of $88.78 per share on the day before to $91.50 per share at the opening bell.

McDonalds Stock Price: 27 January 2015 through 29 January 2015

That represents a gain of $2.72 per share, which when multiplied by the company's outstanding 973,200,000 shares, suggests that they collectively believe that getting the right man to turn the company's fortunes around to do the CEO job at McDonalds is worth about $2.647 billion dollars.

McDonalds Workers Demand Higher Pay - Source: Senator Bernie Sanders - http://www.sanders.senate.gov/newsroom/recent-business/starvation-wages-for-fast-food-workers

By contrast, Thompson's total compensation in 2013 was $9.5 million. If McDonald's new CEO is paid twice that figure and succeeds in growing McDonald's business, it can be reasonably argued that he's being underpaid for the value he brings to the company.

And that's the thing - it's up to the CEO to deliver that kind of value to the owners of business. A CEO who doesn't deliver is almost always overpaid.

By the way, the exact same logic applies for the lowest paid employee on the company's payroll too. If they cannot deliver value to the company in excess of what they cost the company in pay, benefits and administrative expenses, they're overpaid.

The difference is that the responsibility of delivering the kind of value demanded of a CEO by the company's owners is something that is far beyond the job responsibilities of much lower ranking employees. Which is why they're paid so much in the first place.


28 January 2015

Going into Wednesday, 28 January 2015, investors had believed that the Fed was likely to indicate that the U.S. economy was performing solidly enough that it would begin to implement its plan to hike short term interest rates before the end of 2015-Q2 in June 2015.

In fact, when the Federal Reserve's Open Market Committee released its statement following the end of their two day meeting, that was the first impression that investors had, as stock prices spiked upward just after the statement was released at 2:00 PM.

But then, they kept reading past the first several sentences and reset their expectations accordingly given what the Fed was really saying....

S&P 500 on 28 January 2015

What the Fed was really saying is that they still expect to start hiking short term interest rates in 2015, but they won't start by the end of 2015-Q2 as they had previously indicated. Given their concern for the substantial decrease in the growing rate of inflation, the Fed effectively directed investors to refocus their rate hike expectations toward a more distant point of time in the future.

Fed Shifts Investors Attention to More Distant Future on 28 January 2015

And that's why stock prices fell, because the expectations that coincide with the Fed's decision to continue to be patient mean that the future they expect for the U.S. economy is not as bright as it would be if they were to begin hiking interest rates sooner.

In effect, the Fed has moved the goalposts for investor expectations. And in doing so, has sent stock prices to follow a lower trajectory than they otherwise would have followed.


In terms of affordability, 2014 became the worst year on record for the median price of new homes sold in the United States.

The chart below, showing the relationship between the trailing twelve month average of median new home sale prices and the trailing twelve month average of median household incomes reveals how new homes in the U.S. reached a record level of unaffordability for the typical American household.

U.S. Median New Home Sale Prices vs Median Household Income, 1999-Present (Monthly Data from December 2000 - December 2014)

In this chart, we're measuring the affordability of U.S. median new home sale prices against the trend that existed between these prices and median household income in the pre-housing bubble years from 1987 through 1999.

With that base for reference, we see that the previous record was reached in May 2006, when the trailing year average of median new home sale prices peaked at $242,658 in July 2006, which is 34% higher than the projected value of $181,000 that corresponds the same median household income of $46,700 if the stable trend that existed from 1987 through 1999 had held.

By contrast, the preliminary figures for December 2014 indicate that the median price of new homes in the U.S. exceeded that ratio, setting a new record. In December 2014, the trailing year average of median new home prices was $282,300, which is 37% above the figure of $206,000 that corresponds to the projection of the 1987-1999 trend at the same median household income level of $53,600.

To help put those figures in context, the chart below shows the major trends in the relationship between median new home sale prices and the median household income from 1967 through the present.

U.S. Median New Home Sale Prices vs Median Household Income, 1967-Present (Monthly Data from December 2000 - December 2014)

To put it bluntly, new homes have never been more out of reach for the typical American household for the 47 years for which we have both median new home sale price data and median household income data, given the typical level of affordability that existed in the nation's real estate markets before the U.S.' first housing bubble began to inflate in 2001.


Sentier Research. Household Income Trends: July 2014. [PDF Document]. Accessed 27 January 2015. [Note: We have converted all the older inflation-adjusted values presented in this source to be in terms of their original, nominal values (a.k.a. "current U.S. dollars") for use in our charts, which means that we have a true apples-to-apples basis for pairing this data with the median new home sale price data reported by the U.S. Census Bureau.]

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 27 January 2015.


27 January 2015

From our perspective, the most important and useful part of the Efficient Markets Hypothesis (EMH) is its assumption that asset prices change quickly to reflect the impact of new information upon the future expectations of investors.

So what does the ability of investors to collectively and efficiently absorb and assess new information and to communicate the changes in their outlook through asset prices tell us about what the U.S. Federal Reserve is likely to do with respect to its plans to hike short term interest rates?

Well, if we go by how U.S. stock prices responded after the European Central Bank (ECB) announced its Quantitative Easing (QE) program on 22 January 2015, the immediate assessment of U.S. investors was that the Fed will most likely implement its rate hike plans sooner rather than later. We can see that shift in the sudden change in the trajectory of the S&P 500, where it has gone from following the trajectory associated with an investor focus on 2015-Q4, which is consistent with what had been the growing consensus that the Fed would delay its rate hikes until then, to the nearer-term future associated with a forward-looking focus on 2015-Q2, which investors would now appear to consider to be more likely.

Shift in S&P 500 Stock Prices from 2015-Q4 Trajectory to 2015-Q2 Trajectory on 22 January 2015 following ECB Announcement of QE

That assessment will most likely be confirmed after the Federal Reserve's Open Market Committee concludes a two-day meeting on Wednesday, 28 January 2015 and issues a new policy statement. The Wall Street Journal explains why investor expectations would change in response to the ECB's decision in its schedule of economic news events for the week.

U.S.: 2:00 p.m. EST. Federal Open Market Committee’s monetary policy announcement:

After the ECB’s bombshell news of last week, all eyes now turn to the Fed. If it signals its continued intent to raise rates in the months ahead, this will likely drive even more fund flows into the dollar. How the Fed views that ECB move will be key. If it interprets it as an effective move to restore growth in the eurozone, it will see it as constructive to U.S. growth and likely want to stay the course and move toward higher rates sometime in the last spring or summer. If it instead focuses on the surge in the dollar that has come from the ECB move, it could be inclined toward holding back because of the disinflationary effect of that.

We already know that the Fed pays very close attention to the stock market in weighing their future actions, which we observed previously during their own QE programs. The reaction of the U.S. stock market to the ECB's action to initiate a QE program for the EU is such that the Fed is likely to hike short term interest rates in the US above their current 0-0.25% range by the end of 2015-Q2.

And that will hold until newer information might force the Fed to adapt its plans.

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26 January 2015
The Science of NFL Football - Source: National Science Foundation http://www.nsf.gov/news/special_reports/football/

Can physics explain what's wrong with Tom Brady's balls?

We're going to find out. Picking up on the speculation offered by a Boston sportswriter, who argued that weather alone was responsible for half of the underpressurization found in 11 of the 12 balls that the New England Patriots' offense brought with them to the 2015 AFC Championship game, we thought we'd check their math.

It's a good thing that we did, because they botched it. Badly.

We know that because of the physics that applies here, the combined gas law, which defines the relationship that exists between the internal pressure, volume and temperature of an enclosed vessel like a football will be a constant. That means that we can nearly perfectly predict how much the internal pressure, or inflation, of a football might change when the temperature of the ball changes from one point in time to another, using the following formula:

Combined Gas Law - Source: Wikipedia http://en.wikipedia.org/wiki/Combined_gas_law

We're going to do that math using the information we know about the situation. We'll assume that the footballs were inflated at a temperature of 68 degrees Fahrenheit, which is consistent with the interior thermostat setting recommended by the U.S. Department of Energy for optimal personal comfort and low energy consumption in the winter, the gametime temperature of 51 degrees Fahrenheit, the minimum acceptable inflated pressure specified by the NFL's rules of 12.5 pounds per square inch, and the approximate internal volume of the football of 258.5 cubic inches, which we'll assume is unchanged from the time when the footballs were filled and checked to when they were discovered to have deflated by roughly 2.0 pounds per square inch.

Enough talk - let's do some math using the tool we built just for that purpose!

Update 30 January 2015: We've added the standard sea level atmospheric pressure to the NFL's pressure gauge readings in the tool below, as per the New York Times' article proclaiming that the weather was responsible for the deflation of Tom Brady's balls. Judge for yourself just how well that explains the situation.

Football Inflation Data Before the Game
Input Data Values
Initial Measured Internal Pressure [psi]
Initial Volume [cubic inches]
Initial Temperature [degrees Fahrenheit]
Football Inflation Data at Halftime
Internal Pressure at Halftime [psi]
Volume at Halftime [cubic inches]
Temperature at Halftime [degrees Fahrenheit]

How Much of Football Deflation Is Explained by Weather?
Calculated Results Values
Expected Internal Pressure of Footballs at Halftime
Actual Internal Pressure of Footballs at Halftime
Percentage of Change in Pressure Explained by Change in Temperature
If you're reading this article on a site that republishes our RSS news feed, click here to access a working version of this tool!

So we find that, at best, the change in temperature in going from a room inside the stadium where the internal pressures of the footballs the New England Patriots brought to the game were inspected to on the field during the game can only, at best, explain 20% of the change in pressure that was measured.

We were curious to find out what of temperature would have to be held in order to produce the observed amount of deflation, and used trial and error in our tool above to find that Tom Brady's balls would have had to have been inflated and inspected at a temperature of 148.4 degrees Fahrenheit to account for a decrease in internal pressure from 12.5 psi to 10.5 psi.

That, of course, assumes that the volume of the bladder inside the football didn't change size. Going back to our initial temperature range, using trial and error in our tool once again, we found that it would have to expand to 297.85 cubic inches, or 115% of its initial volume, to account for the observed change in pressure.

That is something that might perhaps seem plausible, but a reality check indicates that would involve the footballs growing to be larger than the maximum dimensional specifications mandated by the NFL. It would have been incredibly easy for even the NFL's officials to determine that something was greatly amiss with the Patriots' footballs if that were the case.

Instead, the physics involved are such that it is clear that Tom Brady's balls achieved their deflated state through other means.

And if nothing else, we have perhaps demonstrated that one cannot trust either the scientific or mathematical claims made by a hack sportswriter from Boston.

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23 January 2015

There are more Boeing 737s flying in the skies of Earth today than any other model of commercial air transport. Back in 2000, to keep up with demand, the company began producing 737s at the then record rate of 1 per day, or rather, 30 per month. Ten years later, the company was producing 737's at a rate of 31.5 per month.

At that point in 2010, the company's orders were finally strong enough to justify speeding things up. By 2014, the company was producing 737s at a rate of 42 per month and now has plans to increase its production rate further with the goal of delivering 47 per month in 2017 and possibly as many as 52 per month in 2018.

The YouTube video below reveals some insights into how Boeing's mechanics do it.

To get an idea of how much the video has been speeded up, the assembly line shown after the wings are attached to the fuselage, where 737s are "flying" down the factory floor in single file, moves forward at a continuous rate of two inches per minute.

Altogether, the production of a Boeing 737 represents anywhere from 367,000 to 600,000 individual parts (depending on the exact model) that are assembled to fly together in close formation.


22 January 2015
Brent Crude Oil Price Projections - 1987-2040 - Source: AEO2014 EARLY RELEASE OVERVIEW, http://www.eia.gov/forecasts/aeo/er/early_prices.cfm

How much of a change in global oil prices can be attributed to changes in the relative demand for oil? And how much might be attributed to changes in the relative supply of oil?

Those are questions that we've asked and answered before, but now, for the first time, we can finally quantify the extent to which either of these economic factors may be driving the price!

We can do that math now thanks to the work of James Hamilton, who built a model of how much world oil prices change in response to changes in the prices of other commodities - ones that are particularly sensitive to changes in the demand for them: copper, U.S. dollars, and 10-Year Constant Maturity U.S. Treasuries.

Our tool below is built to do that math, with the default values being the values recorded for the week of 4 July 2014 (for the "Previous Values" and for the week of 12 December 2014 (for the "Current Values"), which Hamilton recommends because they smooth out some of the big swings in values that are recorded in the day-to-day data. If you want to do the math for the current day, here is where you can obtain the data for the "Current Values" to replace the default values we've entered in the tool below:

Got all that? Here's the tool....

Value of Global Demand Sensitive Commodities
Input Data Previous Values Current Values
Copper [USD/lb]
Trade Weighted U.S. Dollar Index
Constant Maturity 10-Year U.S. Treasury Yield [%]
Brent Crude Oil - Europe [USD/barrel]

Projected Price of Crude Oil Based on Demand Factors
Estimated Results Values
Expected Price of Brent Crude Oil If Only Affected by Global Demand Factors
Differences from Previous Price of Brent Crude Oil
Estimated Change in Price of Brent Crude Oil Due to Demand Factors
Actual Change in Price of Brent Crude Oil
Percentage of Actual Change in Brent Crude Oil Price Attributable to Demand or Supply Factors
Percentage of Change Attributable to Demand Factors
Percentage of Change Attributable to Supply Factors
If you're reading this article on a site that republishes our RSS news feed, click here to access a working version of this tool!

Using the default data, which applied for the week of 12 December 2014, we find that 42.8%, or $20.29 of the $47.45 per barrel change in Brent crude oil prices following the week of 4 July 2014 can be attributed to a negative change in global demand (from slowing national economies, particularly in Europe and Asia), while 57.2% might be attributed to the relative changes in the supply of crude oil (thanks largely to increases in U.S. oil production.)

And so, just like the recent discovery involving the causality associated with the chicken and egg dilemma, we now know not only whether its changes in demand or supply factors that are mostly driving changes in the price of oil in the world, but can now also determine tow what extent each factor is responsible!

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20 January 2015

With President Obama's 2015 State of the Union address now upon us, we thought we'd follow up on a 2011 post, which showed that the post-recession jobs recovery in the U.S. wasn't quite as good as claimed by the President's political supporters in the U.S. Congress.

Specifically, those supporters were claiming that the jobs recovery under President Obama were faster than those seen during the 1990 and 2001 recessions. Here's the chart we featured to show how things really stood at that time:

Percentage of Maximum Payroll Job Losses in Post WWII Recessions, Aligned at Maximum Job Losses, through December 2010

The jobs recovery from the 2007 recession was still a work in progress however, and in January 2011, even though it was the worst on record, it really wasn't too far out of sync with the typical payroll jobs recovery seen in every recession since the end of World War 2, where the typical recovery in jobs takes approximately the same number of months as it did for the maximum job loss to occur during each period of economic contraction.

Let's next reveal how the total nonfarm jobs recovery following the 2007 recession really played out.

Percentage of Maximum Payroll Job Losses in Post WWII Recessions, Aligned at Maximum Job Losses, through May 2014

Unlike every other recession since the end of World War 2, the jobs recovery from the 2007 recession was especially protracted, making it an atypical event, but also an asymmetric one.

That outcome is a direct result of the policies that were adopted during President Obama's tenure in office, particularly those that were implemented after 2010 through the President's phone and his pen, the net effect of which was to derail the jobs recovery from even coming anywhere close to following the typical pattern seen after every other recession in the modern era.

Which is why we call the recovery following the 2007 recession the worst recession jobs recovery ever.

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In the process of testing out and selecting a new color scheme for displaying complex data on a Microsoft Excel chart, we somehow managed to accurately forecast the overall trajectory of stock prices last week. Over a week in advance.

Here's how we did that. The complex data we were displaying was generated from our standard model of how stock prices work, which combines future-oriented data related to the amount of dividends expected in future quarters with historic stock prices, which our model uses as base reference points for projecting stock prices into the future.

Specifically, our standard model for forecasting stock prices incorporates the historic value of the S&P 500 from 13 months earlier, 12 months earlier and one month earlier in projecting a particular day's most likely stock prices. The chart below shows the trajectories for each that apply in 2015 (the heavy black line represents current day stock prices).

S&P 500 Index Value (Historic Data Base Reference Points) Used in Standard Model Forecast Projections, 2015

If you pay close attention to our chart, you'll find that the current day S&P 500 is almost perfectly following the trajectory that stock prices did exactly one month earlier, when investors were weighing the potential negative impact of falling oil prices on the growth prospects upon the U.S. stock market in the future. That dynamic is what our model has picked up upon.

The fact that it would appear to be repeating is a phenomenon that's largely driven by the U.S. bond market. Our thinking is that the investment decisions that were made in December 2014 are being repeated again in January 2014 with the maturation of one-month U.S. Treasuries. It's kind of like an aftershock after an earthquake, or in this case, a noise event in the U.S. stock market, where a past event is actually driving stock prices in the current day, to the extent that such an event can.

The degree to which events in the past might drive today's aftershocks or to more often dissipate as yesterday's echoes would really appear to depend greatly upon what investors expect for the future as the maturity and option expiration dates associated with their previous investment choices come to pass and provide the means for executing new decisions. If the future doesn't change in the interim, why should the investment decisions of investors change?

So it's actually luck that is behind that our model's ability to have accurately projected the trajectory that stock prices followed last week. It's just fun to see that it's possible to build a particular kind of luck into a mathematical model!

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19 January 2015

Purple and orange!

And the winner is.... Purple and orange!

The survey we conducted last week as to what color scheme we should use on our chart showing the most complex set of data we track drew a sufficient number of responses to declare the colorblind, laptop screen, print and black-and-white photocopy-friendly choice of purple and orange the winner!

The funny thing is that we also correctly predicted the trajectory of stock prices for the week of 12 January 2015 through 16 January 2015, but we'll discuss why we were successful and what that means later this week.

In the meantime, lets have a flashback to 2011, when the color combination of purple and orange represented "fashion's coolest clash" and as recently as 2013, was considered by room designers to be "dramatically bold and seriously chic"!

But best of all, following the purple and orange path led us to Welder:

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16 January 2015

Is your home complete today?

Your Home Is Not Complete Without a Sanitary Unit

HT: Core77, who celebrated the artistic achievements of the Works Progress Administration from 1934.


15 January 2015

Via e-mail, one of our readers asked some very good questions, which frame the seemingly fortunate economic situation in the U.S. pretty well:

With the falling price of oil, there is a chance to see if “trickle up” economics work as opposed to "trickle down" economics … What is the overall economic impact of lower fuel prices?

It seems the lower price of oil may be with us long enough to test the “trickle up” theory. I use the term "trickle up" because this is not the result of government Keynesian policies that narrowly focus the economic shift. Everyone, rich and poor, is being given a choice on how to reallocate their money now that fuel costs are a lower percentage of their expenses. [ assuming the government doesn’t find a way to take the extra $ back with new taxes ]

Many assume that if Wall Street is taking a hit due to the impact of low oil prices, the country is taking a hit … perhaps the stock market is only a short term indicator of national economic health at the top of the economic chain. If this is the case, stock prices only provide a short term “trickle down” view of the state of the US economy. What if “trickle up” is a longer term economic phenomenon that works outside the cycle time of the market? What indicators show the impact of extra money in every individuals pocket? Are there any short term “trickle up” indicators?

Here is the response we provided back on 5 January 2015, which we've modified since by either expanding our comments to quote things we had only linked before, or [making some correction in grammar or spelling], or adding links to news articles that hadn't yet been written:

[We] think the key to determining if there is such a trickle-up effect is to recognize that there are different cycles at work, which aren't necessarily synchronized with each other. For instance, if they were, then Lance Roberts' take on the economic impact of falling oil prices would be correct:

In the financial markets and economics it is a common occurrence that the media and commentators will latch on to a statement that supports a cognitive bias and then repeat that statement until it is a universally accepted truth.

When such a statement becomes universally accepted and unquestioned, well, that is when I begin to question it.

One of those statements has been in regards to plunging oil prices. The majority of analysts and economists have been ratcheting up expectations for the economy and the markets on the back of lower energy costs. The argument is that lower oil prices lead to lower gasoline prices that give consumers more money to spend. The argument seems to be entirely logical since we know that roughly 80% of households in America effectively live paycheck-to-paycheck meaning they will spend, rather than save, any extra disposable income.


The problem is that the economy is a ZERO-SUM game and gasoline prices are an excellent example of the mainstream fallacy of lower oil prices.


The obvious ramification of the plunge in oil prices is that eventually the loss of revenue will lead to cuts in production, declines in capital expenditure plans (which comprises almost 1/4th of all capex expenditures in the S&P 500), freezes and/or reductions in employment, and declines in revenue and profitability.

The majority of the jobs "created" since the financial crisis have been lower wage paying jobs in retail, healthcare and other service sectors of the economy. Conversely, the jobs created within the energy space are some of the highest wage paying opportunities available in engineering, technology, accounting, legal, etc. In fact, each job created in energy related areas has had a "ripple effect" of creating 2.8 jobs elsewhere in the economy from piping to coatings, trucking and transportation, restaurants and retail.

Simply put, lower oil and gasoline prices may have a bigger detraction on the economy that the "savings" provided to consumers.

Newton's third law of motion states:

"For every action there is an equal and opposite reaction."

In any economy, nothing works in isolation. For every dollar increase that occurs in one part of the economy, there is a dollars' worth of reduction somewhere else."

But the thing is that there is extra money coming into the economy because significant income (jobs) has/is not yet being lost in the oil industry. That "extra" money has provided a small, stimulative burst where increased economic activity in other sectors [of the economy] (such as restaurants, to name one industry that immediately benefited from the oil price decline in 2014), produce more income (growth) through a "trickle-up" effect, which is a big reason why the U.S. economy did so well in 2014-Q3 and Q4.

Perhaps the biggest question going into 2015 is how long that dynamic can play out. We would anticipate that the stock market will be especially rocky as oil industry-related companies begin to cull their dividends in greater numbers, which will be offset to the degree that firms in other industries might boost theirs. There are other dynamics that play into that, but from the core fundamentals that drive stock prices, that's the main aspect to which we're paying close attention at this time.

Water Trickling from Faucet - Source: ready.gov

Today, we're finding out that dynamic is just about played out, which we're seeing investors recognize through falling stock prices, falling yields for long term U.S. Treasuries, and falling commodity prices.

Worse, the fourth quarter of 2014 is turning out to not have been anywhere near as good as expected. Retail sales plunged in December, while the falling oil prices promise to dent economic activity in the states that have led the U.S. economic recovery following the December 2007-June 2009 recession.

That trickle up effect was sure nice while it lasted!

So far, there haven't been any major dividend cuts outside of just a few oil industry-related companies, so U.S. stock prices have instead been tracking along with investors' expectations for the timing of the Federal Reserve's planned hiking of short term interest rates.

Which is to say that they've risen whenever the news indicates that things are going well enough for the Fed to hike those rates by the end of the second quarter of 2014, and have fallen whenever the news is such that it becomes more likely that the Fed will delay its rate hikes to later quarters in 2015. At present, stock prices, as represented by the S&P 500, are consistent with investors betting on the Fed delaying its plan to hike rates until the fourth quarter of 2015.

Those temporal shifts in investor expectations account for the S&P 500's rocky ride so far in 2015 - at this point, there has been very little change in the amount of dividends expected to be paid out in each quarter of the current year. The only thing that would be worse would be for U.S. companies to respond to the increasing revenue distress they are facing by cutting their dividends, because that would fundamentally change the likely trajectories that stock prices will follow to the downside.

And then, it could be 2008 all over again as everyone waits on pins and needles for the next bad news to drop.

But unless and until that situation actually develops, investors will most likely focus on the world's central banks for their responses to the growing risks of global recession, which means that the market's rocky ride will continue. For now, anyway.


14 January 2015

For the third month in a row, our alternative measure of the relative health of China indicates that nation's economy is contracting.

Going by the international trade data collected by the U.S. Census Bureau, it would appear that the currency value-adjusted growth rate of the total value of goods that China imported from the U.S. in November 2014 shrank from the levels recorded in September and October 2014, suggesting that China's economic contraction worsened in November 2014.

Year Over Year Growth Rate of Value of US-China Trade, January 1986 through November 2014

The Census Bureau's trade data confirms earlier reports that indicated that China's economic situation deteriorated in November 2014.

By contrast, the year over year growth rate in the value of goods exported from China to the U.S. suggests that the U.S. economy continued to expand in November 2014, but at a slower pace than in the preceding two months.

Official trade data reported by China, which given its historical unreliability, which even the nation's leaders believe should only be used to get a sense of the overall direction of the China's economy, suggests that things improved somewhat in December 2014, but with other nations' economies outpacing its own, which appears to be trudging along a mildly negative-to-zero growth trajectory at present.


Board of Governors of the Federal Reserve System. China / U.S. Foreign Exchange Rate. G.5 Foreign Exchange Rates. Accessed 13 January 2015.

U.S. Census Bureau. Trade in Goods with China. Accessed 13 January 2015.

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13 January 2015

This is the last time that we're going to feature an updated version of the following chart, showing the change in the number of employed Americans by age group since the level of total employment peaked in the U.S. just ahead of the so-called Great Recession.

Change in the Number of Employed Americans by Age Group, Since Total Employment Peak in November 2007, Through December 2014

Here's what we've learned after seven years of tracking this data, where we've focused upon teens (Age 16-19), young adults (Age 20-24) and adults (Age 25 and older):

  • As bad as the "Great Recession" was for many Americans, it was harder on young adults and the hardest upon teens.

  • The federal minimum wage increases of 2007, 2008 and 2009, combined with a number of state minimum wage increases, and without any meaningful economic growth to offset their combined negative impact, effectively removed 1.4 million teens from the ranks of the employed, a situation that only recently improved in just the past three months.

  • That improvement came only after oil and gasoline prices began to fall dramatically in late June 2014, which provided the only significant stimulus to the U.S. economy in the past seven years. Americans responded by increasing their demand for things like fast food, which responded to the increased demand by hiring new employees at or near the minimum wage.

  • The situation is slightly better for young adults, whose employment numbers have only just returned to their pre-Great Recession levels in recent months.

  • Combined, U.S. teens and young adults account for approximately half of all Americans who earn wages at or near the minimum wage level.

  • By contrast, Americans over the Age of 25 effectively recovered from the Great Recession as measured by their numbers among the employed over a year ago.

Looking at the present employment situation for teens and young adults, we find that there hasn't been any meaningful improvement in their employment prospects since October 2014. Meanwhile, U.S. adults have continued to gain jobs. The number of employed teens has held at a level that is 1.15 million below their November 2007 level, while the number of employed young adults has just dropped back underwater after having briefly risen above it.

That situation seems somewhat out of whack, especially as oil and gasoline prices in the U.S. have continued to fall, however we should note that 21 states in the U.S. were set to increase their minimum wages in January 2015. Nine of these states had relatively small minimum wage hikes, as they only adjusted their minimum wage to account for the rate of inflation. The other thirteen states increased their minimum wages by a larger percentage.

Meanwhile, the state of California imposed a very large hike in its minimum wage in July 2014. Unlike nearly all other states, teens in California have seen no improvement in their employment figures as a result of the entire U.S. economy being stimulated from falling oil prices.

We think those state level minimum wage hikes are limiting the gains that teens and young adults would otherwise be seeing as a result of Americans being able to benefit from not having to pay so much for oil and gasoline. That situation should ease somewhat as inflation helps wash out the effect of the state-level minimum wage hikes, but will ultimately be limited because of the negative impact of the next round of state level minimum wage increases that will be on tap for 2016.

It shouldn't take an economic detective to point out the obvious, but apparently, it does, because some people still haven't learned anything over all these years.


12 January 2015

What's a good color scheme for showing complex data?

That's an issue we often face since we frequently feature charts produced using Microsoft Excel incorporating multiple series of data, where visually telling one data series from another can present quite a challenge. A challenge that can become even greater if the charts that use Microsoft's default color palette are viewed on an LCD screen, or if the viewer has some degree of colorblindness, or if the charts are printed out and then potentially again if the printed charts are photocopied.

Not long ago, one of our readers alerted us to ColorBrewer2, an online application for selecting color palettes that might be used for producing maps on the web, which identifies the palettes that are most viewer friendly.

We're still playing around with the application, but we think we've narrowed down a couple of color palettes upon which we might standardize our presentation of complex data, which complement the color palette we use on our site. We'd like your opinion, so we'll test drive both of them today with an updated version of one of our most complex charts.

The first chart presents our "Purple and Orange" color scheme, which promises to be visually distinguishable for colorblind readers, even on an LCD screen, and also when printed out and subsequently photocopied:


The second chart shows the same data, but using a "Purple and Green" color scheme, which is supposed to have all the advantages of the "Purple and Orange" scheme, but which is not photocopy friendly.


Finally, here's the survey:

Create your free online surveys with SurveyMonkey , the world's leading questionnaire tool.

We'll follow up with the results after we've collected enough responses.


09 January 2015

Bill Gates puts his mouth where his money is, or more specifically, where he has invested in a new technology that can recycle a stream of sewage into clean water and electricity. (HT: Core77).

Bet you thought this would just be an old Howard Hughes story!


08 January 2015

Today, President Barack Obama is expected to talk about the state of the nation's housing market recovery at a speech in metropolitan Phoenix, Arizona, one of the hardest hit regions for the real estate industry in the whole country. We thought we'd show you what that recovery really looks like in advance of the President's speech.

Our first chart shows the number of new houses being built in the United States in each month from January 1959 through October 2014:

Seasoanlly Adjusted Annual Rate for New Residential Construction, January 1959 through October 2014 (Chart Through December 2015) - Source: U.S. Census Bureau

In this chart, we see that years after the first U.S. housing bubble peaked in 2006, the new housing market in the U.S. has finally recovered to a level that is consistent with the volume of production that occurred during previous major recessions.

Meanwhile, the median sales price of new housing has skyrocketed since the first housing bubbble bottomed and stabilized, with the typical home now being sold in the U.S. now far out of the affordable reach of the typical American household:

U.S. Median New Home Sale Prices vs Median Household Income, December 2000 through November 2014

This was largely due to the onset of what we've described as the second U.S. housing bubble, where major investment firms bought up mass quantities of distressed properties, creating an artificial shortage that has continued into the present day. The primary inflation phase of that investor-driven activity took place between July 2012 and July 2013.

Since then, the rate of growth of median sale prices for new homes has slowed, but is still well above historic rates of growth consistent with a health new home market. Since January 2014, the median sale price of a new home in the U.S. has been rising at $9.77 for each $1 that median household income has increased, which is anywhere from 2-3 times the typical pace that was seen in the period from 1967 through 1999, or in the initial post-housing bubble crash recovery period from January 2011 through June 2012.

Our next chart below shows the longer term picture for the escalation of median new home sale prices in the U.S. since 1967.

U.S. Median New Home Sale Prices vs Median Household Income, 1967 through November 2014

One of the big reasons that new home prices have escalated during the second U.S. housing bubble is because U.S. home builders deliberately neglected producing affordable homes as investment firms bought up low priced homes in the existing real estate market, focusing instead on building larger percentages of premium homes that they attempt to sell for premium prices.

Share of New Homes Sold Each Month in U.S. by Sales Price, Trailing Twelve Month Moving Average, January 2003 - October 2014

As with the first U.S. housing bubble, we see that the sales mix of the current housing market has once again become considerably skewed toward the high end of the market. We see that new homes priced $300,000 or more now claim about 40% of all sales, up roughly 10% from the level recorded in July 2013.

That's quite a dramatic change in such a short period of time. In fact, this kind of change in the sales mix of new homes should be considered to be a characteristic of a bubble in the new home market. Speaking of which, we should also note that what determines if a housing bubble exists is the rate at which prices change with respect to household income - comparisons of the current price level or quantity of homes built with those recorded during previous peaks or troughs do not matter in that determination.

That's why the proposals to cut the cost of mortgage insurance in half and to relax mortgage lending standards to allow lower down payments that President Obama is expected to make in his speech in Arizona today are particularly out of touch - doing absolutely nothing to fix the problem of housing prices that are increasingly rising out of the affordable reach of the typical American household. Worse, they could potentially trick people who really can't afford the kinds of homes currently being sold in the U.S. to sign mortgages for homes they cannot afford, which proved to be a real problem, if not a big mistake, during the deflation phase of the first U.S. housing bubble.

Of course, this is the same President who gave a speech yesterday trumpeting the recovery of the U.S. automobile industry at an automobile production plant that has been shut down for the past week because of poor consumer demand for the kind of fuel efficient automobiles produced at it, so expecting the President to be in touch with economic reality might be expecting far too much.

It would seem then that the perspective of the U.S. economy that a President gets from spending so much time on the nation's golf courses probably isn't sufficient to keep in very good touch with the nation's economic realities. But at least he has something positive to show for all his time on the links, as media reports indicate his golf game is improving.

Data Sources

Sentier Research. Household Income Trends: July 2014. [PDF Document]. Accessed 23 December 2014. [Note: We have converted all the older inflation-adjusted values presented in this source to be in terms of their original, nominal values (a.k.a. "current U.S. dollars") for use in our charts, which means that we have a true apples-to-apples basis for pairing this data with the median new home sale price data reported by the U.S. Census Bureau.]

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 1 December 2014.

U.S. Census Bureau. New Residential Sales Historical Data. Houses Sold by Sales Price: U.S. Total (2002-present). [PDF Document]. Accessed 1 December 2014.


07 January 2015

In December 2014, the number of publicly-traded U.S. companies announcing that they would reduce their dividend payments jumped up to 25, a level that we believe is consistent with contractionary distress being present within the U.S. economy.

Monthly Number of Publicly-Traded U.S. Companies Announcing Dividend Cuts, January 2004 through December 2014

From our observations of the limited data available, having 10 or more companies announce that they are cutting their dividend payments in a single month is sufficient to indicate that there are recessionary conditions in the U.S. economy. When that figure rises above 20 per month, it tends to coincide with some degree of contraction within the U.S. economy, which can impair the nation's GDP.

That's not to say that level of contraction qualifies as a full-bore recession - from all indications, it's more a sign that there is an increased degree of distress within the U.S. economy that is, as yet, too limited in scale, scope or duration to qualify as an official period of recession as might be determined by the National Bureau of Economic Research, which we describe being in a state of microrecession.

While the number of U.S. companies acting to cut their cash dividend payments to investors has been above the recession line for some time, the type of company announcing dividend cuts has begun to expand in recent months. Prior to November 2014, most firms announcing dividend cuts were those that are especially sensitive to rising interest rates, such as real estate investment trusts, which have been on tap ever since the U.S. Federal Reserve confirmed that it would be terminating its most recent quantitative easing programs by the end of 2014.

While many of those types of firms are still announcing dividend cuts, we've observed an increasing number of oil industry-related firms that have begun taking similar actions in response to falling profits, which are being driven by plunging world oil prices and their effect upon business revenues.

At present, it would appear that the fallout is very limited in scope, with just a handful of very small and price-sensitive firms in oil-related industries taking the action of cutting their dividends as their revenue and profit prospects fade. The big questions going into 2015 are: how far will oil prices drop, how long might they stay depressed and will other sectors be able to benefit enough to offset the distress in the oil industry? The answers to these questions will determine the duration and severity of the recessionary forces at work within this sector of the U.S. economy and the stock market as a whole.

Data Source

Standard & Poor. Monthly Dividend Report. [Excel Spreadsheet]. Accessed 6 January 2015.

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05 January 2015

Just a couple of charts to help put the progress of the current trend in the U.S. stock market into better context. First, let's take a close up look showing the daily values of the current trend from 4 August 2011 through 5 January 2014:

S&P 500 Index Value vs Trailing Year Dividends per Share, 30 June 2011 through 05 January 2015

Next, let's zoom out a bit and look at the major trends that have held sway in the U.S. stock market since December 1991:

S&P 500 Average Monthly Index Value vs Trailing Year Dividends per Share, 30 June 2011 through 05 January 2015

From first impressions, it would initially appear that stock prices are reverting to the mean defined by the stable relationship that has existed with their underlying trailing year dividends per share in the currently established trend.

But falling oil prices have the potential to disrupt that trend, as we ominously described less than a month ago in how the current state of order might break down in the U.S. stock market. The market's action on Monday, 5 January 2015 in response to falling oil prices underscores that potential.

Curiously, the day's statements of a Fed official meant to reassure the market actually failed because they made the same mistake that Ben Bernanke did in June 2013: they focused investors on the wrong period of time in the future, one whose expectations of future cash dividends (the reasonably sustainable portion of earnings) would pull stock prices lower rather than help them recover to their previous level.

Fortunately, it was a minor Fed official who made the mistake and their error did little to worsen the damage that had already been done as a result of the news of falling oil prices and their negative impact on the expectations on companies whose businesses have greatly profited from higher oil prices, such as Exxon Mobil (NYSE: XOM) and Chevron (NYSE: CVX), and less obviously, Caterpillar (NYSE: CAT), which has made a lot of money selling earth moving equipment to oil extractors and Goldman Sachs (NYSE: GS), which has made a lot of money financing oil extractors.

That's the kind of thing that will have investors on pins and needles as they wait for bigger shoes to fall than have to date in the oil industry.

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