Political Calculations
Unexpectedly Intriguing!
July 31, 2013

Now that we have demonstrated that there is an extremely linear relationship between what people pay for the houses they own and their incomes, we're going to look at how the mix of house sales affects the reported sale prices.

Our first chart looks at the number of new homes sold in the previous twelve months for each month from January 2003 through June 2013, which spans all of the data reported by the U.S. Census Bureau for this measure:

Thousands of New Homes Sold in U.S. Each Month by Sales Prices, Trailing Twelve Month Moving Average, January 2003 through June 2013

In this chart, we're identifying the peak volume for the trailing twelve month average of U.S. new home sales as January 2006, which directly corresponds to the peak volume of sales for new homes in the $200,000 to $299,000 range and also the $300,000 to $399,000 range.

Our second chart takes the same data, but stacks the data so we can see the overall volume of new home sales recorded in the U.S. during that period:

Stacked: Thousands of New Homes Sold in U.S. Each Month by Sales Prices, Trailing Twelve Month Moving Average, January 2003 through June 2013

In these two charts, you can see the volume of lower priced homes decline during much of the inflation phase of the first U.S. housing bubble, as these lower priced homes were displaced by higher priced homes in the number of sales each month.

In the deflation phase for the volume of new home sales that took hold after January 2006 (the first U.S. housing bubble itself continued to inflate as new home sale prices continued to rise into early 2007), we observe that although the volumes of all new home sales by sale prices declined in this period, there is a relatively greater decline in the volume for higher priced new home sales (say for homes in the $300,000-$399,999 range) than for lower-priced new home sales (such as those in the under $150,000 range).

It's not until July 2012, with the beginning of the inflation phase of the second U.S. housing bubble, that we see the same pattern we observed during the inflation phase of the first housing bubble re-establish itself.

Our next chart looks at the relative share of sales for each range of sale prices reported by the U.S. Census Bureau, which confirms that the relative share of each level of pricing for new homes sold in the U.S. has largely returned to the levels last seen during the inflation phase of the first U.S. housing bubble:

Share of New Homes Sold in U.S. Each Month by Sales Prices, Trailing Twelve Month Moving Average, January 2003 through June 2013

This is where the extremely linear relationship that we've previously demonstrated between what people pay to live in the homes they own and their household incomes gives us a lot of insight. Unless the distribution of income within the U.S. has changed to support the price mix of new home sales, and it has not, that means that other, non-sustainable factors are driving them.

And as recognized experts on the distribution of income in the United States, we can confirm that there has been no meaningful change in that distribution in the last eleven and a half years covered by the Census Bureau's new home sale price mix data that can explain the large variation that we observe in the overall mix of new home sale prices.

The rapidly changing mix of new home sale prices then is an indication of distortionary forces at work in the U.S. housing market, where factors other than the fundamental driver of home prices, household income, are holding sway. Otherwise, we would not be seeing median new home sale prices skyrocket with respect to median household income over time. Something else is discouraging home builders from building affordable homes to satisfy the demand for housing at the lower end of the market.

That's why we describe the period since July 2012 as being the inflation phase of the second U.S. housing bubble. But what could be the consequences of having so many lower priced new homes effectively driven out of the market as a result of the second housing bubble's economic distortion effects?

Joel Kotkin of the New Geography observes how the skewing of the produced mix of new homes toward the higher end of the price scale during the current housing bubble will have very real consequences:

Generally speaking, as prices rise, single-family homes become scarcer and rents also rise. The people at the bottom, of course, suffer the most, since the lack of new construction, and the inflated prices for houses, also impacts the rental market. Since 1980, the average house price as reported by the National Association of Realtors has moved in near-lockstep with rents, as reported in the Consumer Price Index, except for the worst years of the housing bubble.

Kotkin also describes the impact of having such a skewed mix of new home production:

America's emerging housing crisis is creating widespread hardship. This can be seen in the rise of families doubling up. Moving to flee high costs has emerged as a major trend, particularly among working-class families. For those who remain behind, it's also a return to the kind of overcrowding we associate with early 20th century tenement living.

As was the case then, overcrowded conditions create poor outcomes for neighborhoods and, most particularly, for children. Overcrowding has been associated with negative consequences in multiple studies, including greater health problems. The lack of safe outside play areas is one contributing factor. Academic achievement was found to suffer in overcrowded conditions in studies by American and French researchers. Another study found a higher rate of psychological problems among children living in overcrowded housing.

This is occurring as a generation of middle-class people — weighed down by a poor economy, inflated housing prices and often high student debt — are being pushed to the margins of the ownership market. There will be some 8 million people entering their 30s in the next decade. Those struggling to move up face rising rents and dismal job prospects. It's not surprising that a growing number of Americans now believe life will be worse for their children.

Curiously, a return to tenement-style housing would seem to be the solution advocated by Paul Krugman in a recent blog post in which he cited the work of Raj Chetty, Nathaniel Hendren, Patrick Kline, and Emmanuel Saez, who would seem to blame sprawl in part for the apparent lack of economic mobility in a number of otherwise fast-growing cities where low-income earning communities find themselves geographically separated from available economic opportunities.

The distortionary effects of housing bubbles that in part result from "smart growth" or outright anti-growth policies that seek to herd lower income earning households either toward the outskirts of cities where affordable single family homes in their price range actually exist or into the high-density housing projects designated for them by their communities' organizers would not appear to be among any of the factors considered in their analysis.

Data Source

U.S. Census Bureau. New Residential Sales Historical Data. Houses Sold by Sales Price: U.S. Total (2002-present). [PDF Document]. Accessed 26 July 2013.

Previously on Political Calculations

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July 30, 2013

The average rate at which median new home sale prices in the United States has been escalating is over 17% faster than the average rate at which median new home sale prices rose during the initial inflation phase of the first U.S. housing bubble.

The initial inflation phase of the first U.S. housing bubble ran from November 2001 through September 2005, when the Federal Reserve ended its extremely low-interest rate policy following the end of the 2001 recession, as it finally all-but-closed the gap between its Federal Funds Rate and the level at which it would have set that rate if they had been factoring in actual economic conditions in accordance with the Taylor Rule. During this portion of the inflation phase of the first U.S. housing bubble, median U.S. new home prices were rising by $21 for every $1 that median household incomes were increasing.

Taking into account the latest revisions to U.S. housing data, since July 2012, which we count as Month 0 for measuring the inflation of the second U.S. housing bubble, we find that median new home prices in the U.S. are now increasing by $24.71 for each $1 that median household incomes have increased during the period. Our chart below shows the steeper rate at which nominal median new home sale prices in the U.S. are inflating with respect to non-inflation adjusted median household incomes:

U.S. Median New Home Sale Prices vs Median Household Income, 1999-2013 - June 2013

Our second chart provides more historical context for considering the rate at which median new home sale prices are increasing, showing how they have increased with respect to median household income since the income data began to be reported in 1967:

U.S. Median New Home Sale Prices vs Median Household Income, 1967-2013 - June 2013

Our final chart shows all the median new home sale price data we have available, indicating the trailing twelve-month average of these prices going all the way back to December 1963:

Trailing Twelve Month Moving Average of U.S. Median New Home Sale Prices, December 1963 to June 2013

We show the twelve month moving average for the median new home sale prices to account for seasonality in the data.

Some housing market observers, such as Calculated Risk's Bill McBride, will be quick to point out that median new home sale prices are very sensitive with respect to the price mix of new homes that are sold, with a shift by home builders to sell either very high or very low end homes greatly affecting the median values.

However, the changing mix of the sale prices of houses sold each month is something that is affected by the distorted market conditions that are part and parcel with the presence of a bubble in the U.S. housing market. We'll consider the impact of that bubble-driven changing price mix for Americans in the very near future, when this link will connect through to that analysis....

Data Sources

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 24 July 2013.

Sentier Research. Table 1. Household Income Trends: January 2000 to January 2013 (in January 2013 $$). [Excel Spreadsheet with Nominal Median Household Incomes courtesy of Doug Short]. Accessed 13 March 2013.

Sentier Research. Household Income Trends: July 2013. [PDF Document]. Accessed 29 June 2013. - We update Doug Short's converted nominal median household income data with the nominal median household income data that Sentier Research reports each month. This is the most recent report, which provides this data through June 2013.

Previously on Political Calculations

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July 29, 2013

Last week, we declared the end of the Bernanke Noise Event - that brief eruption of uncertainty that sent stock prices falling after some poorly chosen comments on the part of Fed Chairman Ben Bernanke regarding the timing of when the Fed would begin tapering off its direct injection of money into the U.S. economy. The Fed had spent the next several weeks doing damage control and had finally set things close to right (see chart below).

But then somebody at the White House, perhaps upset at seeing the impact that Bernanke and various members of the Fed had upon the markets with just their words, decided that they needed have their own negative noise event too. Which they would appear to have launched by floating a trial balloon proposing that Larry Summers, the former Obama economic adviser previously best known for sleeping through White House meetings, who is perhaps now becoming better known for apparently neither understanding nor believing in the kind of successful monetary policy that has been keeping the U.S. economy out of a full-fledged recession since September 2012, was President Obama's leading choice to replace Ben Bernanke after his term as Fed Chair ends in January 2014.

Our chart below tracks how investors have reacted to the news:

Change in Growth Rates of Expected Future Trailing Year Dividends per Share with Daily and 20-Day Moving Average of S&P 500 Stock Prices through 26 July 2013

Right now, given the fundamentals of how stock prices work, stock prices should be rising as the change in the growth rate of stock prices should be keeping pace with the level indicated by the currently expected change in the growth rate of their underlying dividends per share for 2014-Q1, which is where the Fed succeeded in restoring the forward-looking focus of investors by the end of the Bernanke Noise Event.

Instead, stock prices are tracking mostly sideways in response to the uncertainty provided by the White House's new negative noise event, which we see in the form of a negative impulse for the daily track of the acceleration of stock prices, as investors are reacting negatively to the prospect.

Just hope that the trial balloon pops. The alternative futures available for investors to focus upon aren't anywhere near as good as that described by the acceleration of dividends expected for 2014-Q1.

Previously on Political Calculations

If you're just discovering our brand of analysis now, here's a good part of the electronic trail for how we got to this point! First up, the basic theory we've developed and where we get our data:

Next, that electronic trail of analysis we've provided throughout the event:

  • The World Investors and the Fed Live In Now - Our snapshot of the market right before the event, in which we note that investor concern about the future of QE was growing and remark that there will be a market reaction in response to the outcome of the Fed's two-day meeting later that week.
  • The Bernanke Noise Event - as the Summer of 2013 shall ever be known to investors....
  • Now Is It Time to Sell? - according to statistics, a quaint branch of mathematics that only works to describe how stock prices vary with respect to their trend when order is present in the market. The problem with it is that the market goes in and out of order, so it's periodically pretty useless....
  • The Fed's Real QE Mistake: Timing - We explain how Bernanke really screwed up.
  • Now What Will You Do? - the statistical line is crossed! We look at everything that we see screaming "sell", without actually saying it's time to sell.
  • The Fed Attempts to Walk It Back - we anticipate how the Fed will respond to Bernanke's error, and we determine if it will work.
  • The GDP Multiplier for QE - Not about investing, at all! Instead, we explain why sustaining QE at current levels is so important to the U.S. economy at present.
  • "Never Bet Against the Fed" - we visually illustrate that the Fed's response to repairing the damage from Chairman Bernanke's blunder is working and recap why fears of stock market doom, despite signals to the contrary, were really overblown.
  • Bernanke Closes the Gap - we mark the end of the Bernanke Noise Event.
  • The Noise of Summers - this article, as it appears on our own site, with that chart that the various sites that simply republish our RSS news feed may not have included!

We tossed the last link in because we're well aware that the vast majority of our readers encounter our articles elsewhere on the web! Come and visit us, if for no other reason than it's the one place on the web where our work appears, and in the case of the tools we develop, works, just about exactly as we intended!

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July 26, 2013

This edition of our Inventions in Everything series is very different, because for the first time, the inventor isn't human....

Frog with Leaf Umbrella

And so, we add frogs to the growing list of animals that make tools to suit their own purposes. Core77's hipstomp and Rain Noe have some questions:

The amazing photos here, captured by Indonesia-based photographer Penkdix Palme, make you wonder: Was the umbrella's invention biomimetic in the sense that we saw an animal doing this and then emulated them? Or is it simply common sense that early man, caught in the rain, seeks to block it by holding a deflective object above their head?

Whichever you believe, there's no question that Palme's photos are stunning. Your initial reaction may be to assume that they're faked, but Palme's work is being shown by National Geographic, and I'd like to think they would've sniffed out any hijinks.

Previously on Political Calculations

Other Stuff We Can't Believe Really Exists

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July 25, 2013

How does the total compensation of the average U.S. federal government employee compare to that of the average U.S. individual income earner who works full-time, year-round?

To find out, we've taken the average cash incomes earned by each and added the average benefits that each receives through their employer as reported by the Congressional Budget Office in 2012. They found that:

On average for workers at all education levels, benefits for federal employees cost about $20 per hour worked, whereas benefits for private-sector employees cost $14, CBO estimates. Thus, benefits for federal workers cost 48 percent more per hour worked, on average, than benefits for private sector workers with similar attributes. Benefits also constituted a larger share of compensation for federal workers, accounting for 39 percent of the cost of total compensation, compared with 30 percent in the private sector.

We next visualized those numbers, in which we reveal the average total compensation of U.S. federal government employees and individual Americans who work in full time jobs all year long:

Average Total Compensation of Private Sector and Federal Government Employees in U.S., 2011

We find that while the average U.S. federal government employee makes $14,632 more in direct cash income than their private sector counterpart, at $74,436 versus $59,804, the extremely generous benefits with which they are also compensated boosts their real income margin by $26,632 over the average private sector income earner, putting their total compensation at $114,436 versus $87,804.

Keeping in mind that the average income of Americans in the private sector is considerably elevated by some very highly paid individuals such as CEOs, very specialized medical professionals, sports stars and entertainment moguls, the total compensation of U.S. federal government employees puts them all in a league of their own. And that's not even including their extreme job security.

Is it any wonder then that U.S. federal government employees are almost more likely to die than leave their jobs?

References

Asbury Park Press. Federal Employees, 2011. [Online Database]. Accessed 28 June 2013

Congressional Budget Office. Comparing the Compensation of Federal and Private-Sector Employees. [PDF Document]. January 2012

Previously on Political Calculations

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July 24, 2013

Yesterday, as part of our look at the distribution of income for U.S. federal government employees in 2011, we compared them with the distribution of incomes earned by all individual American income earners. But is that really a good comparison?

If we're talking about major contributors to the level of income inequality in the United States, the answer is clearly yes. But then, that includes everyone from widows drawing Social Security survivors benefits and people who only work part time during the course of the year. One thing we reported in our previous analysis is that roughly 95% of the 2,221,780 civilian, non-postal service members of the U.S. federal government workforce work full-time, all year-round.

So, if we want to get a better sense of how the distribution of income for U.S. federal government employees compares to U.S. individual income earners, we should compare them with the portion of the U.S. population who is employed in full-time jobs, all year round.

And that's exactly what we've done in the following chart!:

Income Distribution of Full-Time, Year-Round U.S. Individual Income Earners and U.S. Federal Government Employees, 2011

In our chart, we find that the median income earned by a U.S. individual in 2011 who works full-time, all year-round is $44,934, some $22,040 less than the median income earned by U.S. federal government employees.

Meanwhile, the average income earned by a U.S. individual in 2011 was $59,804, which is $14,632 less than the average income of $74,436 earned by U.S. federal government employees.

So, once again, we find that the pay of U.S. federal government employees are strongly skewed to the upper end of the income spectrum of the United States.

But then, that only considers the cash portion of their compensation. In the next part of our analysis, we'll factor in the value of the benefits that each receive!

References

Asbury Park Press. Federal Employees, 2011. [Online Database]. Accessed 28 June 2013

U.S. Census Bureau. Current Population Survey. Annual Social and Economic (ASEC) Supplement. Table PINC-01. Selected Characteristics of People 15 Years and Over, by Total Money Income in 2011, Work Experience in 2011. Race, Hispanic Origin, and Sex: Worked Full-Time, Year-Round, Both Sexes, All Races. [Excel Spreadsheet]. Accessed 28 June 2013

Previously on Political Calculations

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July 23, 2013

How has the distribution of the income for U.S. federal government employees changed since 2008?

We ask that question today, because we revisited the Smiths of Washington D.C. to see how much cash income that each person with "Smith" in their surname took home from their federal government job in 2011 [1].

Let's get right to it, shall we? Our chart below shows the cumulative distribution of cash income [2] for all non-postal U.S. federal government employees named "Smith" for 2011:

Cumulative Distribution of Total Cash Income of Federal Government Employees Named Smith, 2011

Now let's do some quick comparisons with 2008. The data for federal government employees excludes military and postal employees:

Data20082011ChangePercent Increase
Number of "Smiths" Employed by U.S. Federal Government8,7539,4376847.8%
Number of U.S. Federal Government Employees2,040,0662,221,780181,7148.9%
Median Income of U.S. Individuals$26,513 $26,588 $750.3%
Median Income of U.S. Federal Government Employees$60,310 $66,974 $6,66411.0%
Average Income of U.S. Individuals$38,376 $39,660 $1,2843.3%
Average Income of U.S. Federal Government Employees$68,294 $74,436 $6,1429.0%
Highest Paid "Smith" Employed by the U.S. Federal Government [3]$275,000 $362,448 $87,44831.8%

The following chart illustrates the percent increase in the incomes of the median and average U.S. civilian, non-postal federal government employee and U.S. individuals from 2008 to 2011:

Percent Increase of Median and Average Incomes of U.S. Federal Government Employees and U.S. Individuals from 2008 to 2011

The pay of U.S. federal government employees has been frozen since 2010. As you can see from our table above comparing the median and average incomes of regular Americans with U.S. federal government employees, they did extremely well during the deep recession years by comparison.

Next, we've built a quick tool where you can find the percentile ranking of your income among the U.S. federal government's employees. 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 at our site!

Income Data
Input Data Values
Your Income

Your Federal Government Employee Income Percentile (2011)
Calculated Results Values
Your Percentile Ranking Among All U.S. Individual Income Earners
Your Percentile Ranking Among U.S. Federal Government Employees

In the tool above, the results indicate the percentage of either U.S. individuals or U.S. federal government employees who earn either as much cash income as you do, or less. As a heads up, our model of the distribution of income for U.S. federal government employees is least accurate at the very lowest end of the income spectrum, where it may overstate the income percentile by as much as 2.5%. However, once the entered income reaches the tenth percentile, it is typically within 1% or less of the actual values over the rest of the income spectrum.

Our default data in the tool above is the median income earned by all U.S. individuals in 2011. 50% of Americans with income earn more than this amount, and 50% earn less.

As you can see however, our tool estimates that about 5% of all U.S. federal government employees earn this amount or less, which means that at least 95% of all U.S. federal government employees earn more than this annual pay. That means that the U.S. federal government's non-postal, civilian employees are major contributors to the overall level of income inequality in the United States.

In upcoming posts on this topic, we'll compare the U.S. federal government's non-postal, civilian workers to U.S. individuals who work full-time, all-year round.

Notes

[1] Why 2011? We plan to compare the income distribution of federal government employees with those of regular Americans, for which the most recent year that the U.S. Census Bureau makes the data available is 2011. The Census Bureau won't release the data for 2012 until sometime in September 2013.

[2] We combined each Smith's base pay with any additional "award" they were paid in 2011 to come up with their total cash income for the year.

[3] Joseph K. Smith, a Medical Officer employed with the Veterans Health Administration in Birmingham, Alabama took home a cash income of $362,448 in 2011 (salary only). Interestingly, the largest bonus paid to a "Smith" employed by the U.S. federal government in 2011 was paid to another Medical Officer working out of the same station, Phillip D. Smith, who pocketed an extra $19,425 on top of his regular annual pay of $258,267 in 2011.

References

Asbury Park Press. Federal Employees, 2011. [Online Database]. Accessed 28 June 2013

U.S. Census Bureau. Federal Government Civilian Employment by Function: March 2008. [PDF Document]. Accessed 28 June 2013

U.S. Census Bureau. Federal Government Civilian Employment by Function: March 2011. [PDF Document]. Accessed 28 June 2013



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July 22, 2013

The stock market noise event that began with an unfortunately statement made by Federal Reserve Chairman Ben Bernanke back on Wednesday, 19 June 2013 at 2:42 PM Eastern Daylight Time is essentially over.

We've chronicled the event from the beginning, as the S&P 500 first first lost some 4.8% of its closing value on 18 June 2013 in just four trading days, before taking another eleven trading days to recover to just over that level, to finally get to the effective conclusion of the noise event another seven trading days later!

What marked the end of the event was the conclusion of Chairman Bernanke's previously scheduled two days of testimony before the U.S. Congress, in which the Chairman was very careful to keep on the Fed's damage control message that the beginning of the end of its latest programs of quantitative easing was not imminent, and would be very unlikely before the end of 2013. Investors reacted by more completely shifting their forward-looking focus to the first quarter of 2014 in setting stock prices, which we can observe in our chart below:

Change in the Growth Rates of Expected Future Trailing Year Dividends per Share with the Daily and 20-Day Moving Average of S&P 500 Stock Prices

In our chart, we see that the change in the growth rate of daily stock prices (indicated by the dotted blue line) rapidly closed the gap with the level indicated by the year-over-year change in the expected growth rate of trailing year dividends per share for the first quarter of 2014 (indicated by the solid green line). With that level representing where investors are now focused, it is now well within the typical range of variation that we observe when the stock market is characterized by relatively low levels of noise.

What this means is that the Fed has been successful in re-shifting the forward-looking focus of investors back to the level of expectations associated with the future quarter of 2014-Q1.

In the absence of a new noise event, we would anticipate that the acceleration for stock prices will converge with and bounce around this level. The good news is that will mean generally rising stock prices.

The bad news is that noise is always present in the stock market - only its source and volume ever changes!

On a closing note, we'll observe that if nothing else, Ben Bernanke's second term in charge of the Fed is ending as it began, with a noise event that only arose as a direct result of his status as the Chairman of the Federal Reserve. Let's face it - he certainly wouldn't have anywhere near the same impact on markets if he were just a tenured professor at the second best university in New Jersey.

There's some symmetry there to appreciate, but if we're being honest, we're hoping that the next Fed Chair won't be so damned noisy in their comings and goings.

Previously on Political Calculations

If you're just discovering our brand of analysis now, here's a good part of the electronic trail for how we got to this point! First up, the basic theory we've developed and where we get our data:

Next, that electronic trail of analysis we've provided throughout the event:

  • The World Investors and the Fed Live In Now - Our snapshot of the market right before the event, in which we note that investor concern about the future of QE was growing and remark that there will be a market reaction in response to the outcome of the Fed's two-day meeting later that week.
  • The Bernanke Noise Event - as the Summer of 2013 shall ever be known to investors....
  • Now Is It Time to Sell? - according to statistics, a quaint branch of mathematics that only works to describe how stock prices vary with respect to their trend when order is present in the market. The problem with it is that the market goes in and out of order, so it's periodically pretty useless....
  • The Fed's Real QE Mistake: Timing - We explain how Bernanke really screwed up.
  • Now What Will You Do? - the statistical line is crossed! We look at everything that we see screaming "sell", without actually saying it's time to sell.
  • The Fed Attempts to Walk It Back - we anticipate how the Fed will respond to Bernanke's error, and we determine if it will work.
  • The GDP Multiplier for QE - Not about investing, at all! Instead, we explain why sustaining QE at current levels is so important to the U.S. economy at present.
  • "Never Bet Against the Fed" - we visually illustrate that the Fed's response to repairing the damage from Chairman Bernanke's blunder is working and recap why fears of stock market doom, despite signals to the contrary, were really overblown.
  • Bernanke Closes the Gap - the article you're reading right now, as it appears on our own site, just as we intended it!

We tossed the last link in because we're well aware that the vast majority of our readers encounter our articles elsewhere on the web! Come and visit us, if for no other reason than it's the one place on the web where our work appears, and in the case of the tools we develop, works, just about exactly as we intended!

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July 19, 2013

Did you ever wonder what might be on the inside of a Lego® figure? Or any number of fantastical cartoon-like creatures?

Jason Freeny did, and has since filled up his art gallery with his anatomical cut-away sculptures revealing the results (HT: Core77)!

Jason Freeny: Anatomical Lego Men

We thought you might enjoy Freeny's art in case you've already seen the trailer for The Lego® Movie in theaters his summer. And if not....

The movie will be released in 2014. No word on whether it features any graphic autopsy scenes....

Other Stuff We Can't Believe Really Exists

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July 18, 2013

For a given amount of income, how much should owning a house cost?

That's really the issue that a housing affordability index needs to address. And as Barry Ritholtz recently noted, it's an issue that the National Association of Realtors®' Housing Affordability Index completely fails to achieve (typos repaired):

In the past, we have discussed how worthless the NAR's Housing Affordability Index is. This weekend saw an odd column in Barron's that was suckered in by the silliness of that index.

This suggests to me it is time to take another pass showing exactly why this index has so little value to anyone tracking housing values and affordability. Let’s begin by going back to our 2008 analysis:

"The index as presently constructed is utterly worthless. It provides little or no insight into how affordable US Housing actually is. Further, what is omitted from the index is especially relevant to the problems occurring in the housing market today. The Index fails to account for — or even recognize — any of the out of the ordinary circumstances that are currently bedeviling the Housing market."

That's not the worst of it — during the huge run up from 2001-2007, there was but one month — ONLY ONE MONTH! — where the NAR said homes were not affordable!

Barry then proceeds to take apart some of the sillier aspects of a recent analysis that said that despite recent interest rate hikes, "single-family houses are still quite attainable", before getting to the real question that matters: "Can American families afford homes?"

Now, we're regularly addressing that question as it applies to the median sale prices of new homes with respect to the median American household income, but what about other U.S. households? What's the baseline reference for them?

As it happens, we just slogged through all the Consumer Expenditure Reports' data since 1984 on how much of a household's income goes to paying the principal, interest, taxes, insurance, maintenance, repairs, and other expenses directly related to owning a home. And from that data, we can work out how much the average American household with a given amount of household income pays out each year to own their home.

Annual Expenditure for Owned Dwellings vs Annual Income Before Taxes for Various Income Ranges Reported in the Consumer Expenditure Survey, 1984-2011 [Current Year U.S. Dollars]

Our tool below then captures the average total amount that an American household with the income you enter would pay to own their own home over the course of a year. What's more, we'll tell you how what what you might pay in a year to own your own home compares with that average:

(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!)

Annual Household Income Data
Input Data Values
What's your annual household income before taxes?
How much do you pay to own your home in a year?

Housing Affordability
Calculated Results Values
Average Annual Amount that Americans with Your Income Pay to Own Their Homes
Ratio of Your Annual Cost with the Average for Your Income
Average Monthly Amount that Americans with Your Income Pay to Own Their Home

In the tool above, a housing affordability index value greater than 100% tells you that you what you are paying to live where you do is greater than the average amount paid by Americans with the same household income before taxes. Meanwhile, a housing affordability index value below 100% tells you that what you pay is less than what the average American household with your income pays for its dwelling.

We've also calculated the monthly amount that an American household with your income would pays on average, so you can compare it with your current or prospective mortgage payment. The thing to remember here is that to stay affordable, the payment on the home you might be considering buying needs fall below the average, because things like maintenance, repairs and anything else that isn't covered by your mortgage payment can easily push your housing expenditures above the average affordability line.

Finally, if you have an adjustable rate mortgage, you *really* want to have your monthly payment fall far below the average amount listed above, because your future mortgage payments after your rates are adjusted will likely be quite a bit higher as compared to today's just off-the-bottom, all-time-record lows.

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July 17, 2013

Extremely linear. That's the term we would use to describe the basic relationship between what people pay to live in the homes they own and what they earn.

Here's the evidence. We constructed the chart below from data collected as part of the Consumer Expenditure Survey for each year from 1984 through 2011 (full year data for 2012 won't be available until late September 2013), which presents the average annual amount of money spent toward mortgage and interest payments, property taxes, insurance and other expenses associated with home ownership for a number of income ranges.

Annual Expenditure for Owned Dwellings vs Annual Income Before Taxes for Various Income Ranges Reported in the Consumer Expenditure Survey, 1984-2011 [Current Year U.S. Dollars]

In this chart, we've excluded the data for the lowest and highest income ranges presented in the data, since these cover unbounded conditions that makes them outliers with respect to all the other reported data.

The data points are then clustered at the average annual income before taxes that apply for the reported income ranges, which are the standard ranges reported in Table 2 of the Consumer Expenditure Survey, which covers expenditures for various income levels up to $70,000, and also Table 2301 (for 2003 and after), which provides additional detail of average annual expenditures for a number of income levels above $70,000.

Taking all the data together, what we find is that there is a very strong and direct straight-line relationship between the expenditures for home owners and their income before taxes.

That relationship continues to exist after we adjust for the effects of inflation over time. Our next chart shows the same data as the first, but in terms of constant 2011 U.S. dollars.

Annual Expenditure for Owned Dwellings vs Annual Income Before Taxes for Various Income Ranges Reported in the Consumer Expenditure Survey, 1984-2011 [Constant 2011 U.S. Dollars]

Just for fun, we next performed a linear regression for the data for three years, 1986, 2007 and 2011, which we've presented in our third chart (all data is presented in terms of non-inflation adjusted current year dollars.)

Annual Expenditure for Owned Dwellings vs Annual Income Before Taxes for Various Income Ranges Reported in the Consumer Expenditure Survey for 1986, 2007 and 2011 [Current Year U.S. Dollars]

We selected these years because they include a very long-ago pre-housing bubble year (1986), the peak housing bubble year (2007) and a post-bubble pop year (2011).

Here, we find that the lines for the relationship between housing expenditures and incomes for the non-housing bubble years of 1986 and 2011 are close to parallel to each other, but the slope for the peak housing bubble year of 2011 is considerably steeper, as housing expenditures spread considerably for a given level of income compared to non-bubble years.

That observation suggests that one of the characteristics of a housing bubble is that it will affect the slope of the relationship between housing expenditures and incomes, as expenditures first swell with the inflation phase of the bubble before collapsing after it pops and begins to deflate, in tune with the illusion of having more wealth than can be afforded on the incomes of homeowners.

We think that the actual mechanism by which this phenomenon works is pretty humdrum, largely amounting to homeowners tapping the apparently growing equity in their properties through refinanced mortgages and home equity loans during the inflation phase of the housing bubble, the payments for which are then added to the expenditures for housing. As a housing bubble grows, the slope steepens until it pops, after which the slope levels back out as homeowners struggle to get their housing expenditures back in line with their actual level of household income. (Or as the sentimental data jocks at the Bureau of Labor Statistics like to call them, "consumer units").

It's pretty amazing difference that such an apparently small change in the slope of the relationship between housing expenditures and income makes for all the difference between excessive exuberance and depression in the U.S. housing market.

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July 16, 2013

In June 2013, the number of people Age 16 or older in the United States who were counted as having jobs rose by 160,000 to 144,058,000. The biggest gains were claimed by Americans between the ages of 20 and 24, who saw their numbers in the workforce increase by 193,000 to 13,605,000, while American teenagers between the ages of 16 and 19 saw their seasonally-adjusted number in the workforce rise by just 24,000 to 4,469,000.

Unfortunately, the number of adult Americans (Age 25 and older) who were counted as having jobs fell by 57,000 to 125,984,000 in June 2013, which is why the net change in the number of employed Americans only rose by 160,000 from the previous month.

Our chart below shows the change in the number of employed Americans for each of these age groups since November 2007, which marked the most recent peak for the total number of employed Americans of 146,595,000:

Change in Number of Employed by Age Group Since Total Employment Peak Reached in November 2007 through June 2013

Compared to November 2007, there are 2,537,000 fewer Americans with jobs as of June 2013. Of these, teenagers make up the largest share, with 1,458,000 fewer employed teens making up 57% of the sustained job loss observed since that time. U.S. teens have gone from representing 4.04% of all American workers in November 2007 to just 3.10% in June 2013.

If it helps put the teen employment situation in context, June 2013's seasonally-adjusted increase of 24,000 teens with jobs would, according to the outplacement firm of Challenger, Gray & Christmas, represent the strongest start for teen summer employment in seven years.

To be fair, Challenger, Gray & Christmas' claim would appear to be based on the BLS' non-seasonally adjusted figures, which indicate that some 779,000 U.S. teens found jobs in June 2013. Overall, they claim that 994,000 teens have become employed since the "official" start of the summer jobs season with the Memorial Day holiday weekend in May.

The firm indicates that U.S. teens seeking work will have the best luck in finding summer employment in nontraditional jobs, such as at "trampoline centers, large bowling alleys with arcades, movie theaters offering full-service dining, and pools with water slides".

They also indicate that teens have been competing with older, displaced workers in the economic recovery. What they don't indicate is whether having raised the federal minimum wage by nearly 41% from June 2007 to July 2009 might have negatively affected whether U.S. employers could continue to afford to hire U.S. teens, who represent the least skilled, least educated and least experienced portion of the entire U.S. workforce, at the higher wage levels mandated by the U.S. government or in those states that have set even higher minimum wage levels.

Odd how the seasonally-adjusted total number of employed teenagers just hasn't budged much at all since the U.S. job market absorbed the impact of the last federal minimum wage hike in the months following its implementation, isn't it?

Data Reference

U.S. Bureau of Labor Statistics. June 2013 Employment Situation Report. [PDF Document]. 5 July 2013.

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July 15, 2013

Two weeks ago, we observed that the Fed's attempts to walk back the damage done by outgoing Fed Chairman Ben Bernanke's comments suggesting that the Fed was moving up the timetable for ending its quantitative easing programs had appeared successful in arresting the declines in U.S. markets, as investors were suddenly forced to shift their forward-looking focus to a much less positive nearer term future. Today, as promised, we'll review just how successful they've been.

Our chart below, which shows the change in the growth rate of U.S. stock prices, as represented by the S&P 500, has changed with respect to the expected changes in the growth rates of trailing year dividends per share of the index for the next four quarters ending in the future (mind the notes in the margin and the changes from previous versions):

Change in Growth Rates of Expected Trailing Year Dividends per Share with Daily and 20-Day Moving Average of S&P 500 Stock Prices, through 12 July 2013, with Dividend Futures through 15 July 2013

In this chart, we see that after a number of influential Fed officials succeeded in arresting the decline of U.S. stocks through their comments, stock prices held mostly level until the Fed released the minutes from its June 2013 meeting and Fed Chairman Bernanke spoke to the press again on 10 July 2013. This combination of new information for the market appears to have reassured investors that the Fed will not begin any significant tapering its quantitative easing policies in 2013, as the change in the growth rate of stock prices has once again begun to converge with the level that coincides with the expectations investors have for the first quarter of 2014.

We would expect that stock prices will continue to converge with this level in the absence of new, negative noise events. And for now, that means rising stock prices.

"Never Bet Against the Fed"

During what we can now accurately describe as the Bernanke Noise Event, we presented two investing-related posts where we asked "Now Is It Time to Sell?" and "Now What Will You Do?", where we indicated that stock prices were getting set to send, and then sending, a pretty clear "sell signal".

But we never came right out and said "sell"! That's because we recognized very early on that the Fed would have to respond to Chairman Bernanke's unfortunate comments in a way that would re-shift the forward-looking focus of major investors back to 2014-Q1, which would mean that the decline in stock prices would be arrested and stabilized (at least), and potentially recover to much higher levels depending upon how successful the Fed's efforts to walk back its mistake would be.

Why work to focus investors on the first quarter of 2014 in setting their future expectations? Right now, in the absence of good data quantifying the reasonable future expectations of investors beyond 2014-Q2, it was really the only option available to the Fed that doesn't come with a minimum market decline of 30%, which would coincide with a major decline in the economic confidence of Americans, which in turn, would have severely negative consequences for the entire U.S. economy. That's why it won't be until 2014-Q1 at the very earliest that we'll see any tapering in the Fed's quantitative easing programs, when investors will hopefully also have a much less negative alternative future to focus upon.

If there's one lesson that every investor should take to heart it's this: "Never bet against the Fed"! Especially when it needs to act to fix its self-inflicted wounds before its mistakes might cause both markets and the economy to implode.

Previously on Political Calculations

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We tossed the last link in because we're well aware that the vast majority of our readers encounter our articles elsewhere on the web! Come and visit us, if for no other reason than it's the one place on the web where our work appears, and in the case of the tools we develop, works, just about exactly as we intended!

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