Predatory pricing is the illegal business practice of setting the prices of a good or service far below its actual cost for the purpose of gaining a dominant share of the market by making it too unprofitable for more ethical firms to compete, with the ultimate goal of driving the competition out of the market. Once they achieve such an effective monopoly, unethical firms that engage in this strategy will then turn around and hike their prices while also degrading the quality of their products or services as they exploit their dominant position to extract as much money as they can from the consumers who depend upon their product.

But why should a firm that engages in such an unethical strategy wait to hike its prices and degrade the quality of its services to boost its bottom line? Especially when the market has high barriers to entry for new competitors?

Earlier this year, we analyzed the situation of Health Net, a California-based insurer that established the lowest cost plans available on Arizona's federal-government run Affordable Care Act (ACA) exchanges - setting the prices for their Obamacare health insurance plans so low that they set the level of subsidies available for Arizona consumers far below the levels that are typical in other states.

Health Net's prices for the plans it offered in Arizona for the October 2013-March 2014 enrollment period was approved by both the U.S. government and the Arizona Department of Insurance, which was required in order to be available for sale on the state's federal government-run health insurance marketplace. After being approved, no other competition would be allowed to enter the market, and no changes in pricing or plans approved for access to the state's Obamacare exchange would be allowed until the next national health insurance enrollment period begins in October 2014.

Now having that very high barrier in place, Health Net's predatory pricing scheme gave the firm a two-fold advantage against its competition. First it offered the lowest cost plans available for consumers by a wide margin. Second, because the cost of its plans were so much lower than those of its competition, the company succeeded in denying consumers the level of government subsidies that could otherwise have put the higher quality health insurance plans offered by Health Net's competitors within their affordable reach. Consequently, the firm was able to funnel a very large share of the state's health insurance consumers into its lower quality plans.

And with the market closed to real-time competition until October 2014, Health Net was free to degrade the quality of its plans and service to boost the firm's profits, as Arizona's Call 12 for Action reports:

Some key excerpts from the report:

As of April 18, the insurance department has 22 closed complaints against Health Net of Arizona HMO, plus 17 against Health Net Life Insurance Company PPO.

The three issues that come up the most: long wait times on the phone, disconnected calls and an inaccurate provider directory.

"It's as if you're tricked into thinking there are doctors and there aren't," said Debra Mulligan, a Rio Verde woman who says she chose Health Net of Arizona as her health-insurance provider based on the list of doctors she saw on the company's website. Once she signed up, she said the doctors listed on her plan wouldn't see her.

Ken Alltucker, health reporter for The Arizona Republic, has heard similar complaints from others who, like Mulligan, signed up for the Health Net of Arizona plan as well.

"They've gone to the website of Health Net," Alltucker said. "They see their doctor listed in the directory, but when they try to make an appointment with the doctor, they learn that he's not in network or she's not in network."

According to the report, Health Net has racked up more consumer grievances than all other health insurers in the state. Health Net Arizona currently has a one-star rating on Yelp, where consumers almost uniformly complain about the lack of customer service they obtain as well as the bizarrely long delays they encounter when simply calling the company.

Many might observe that you get what you pay for, however Health Net doesn't appear to be anywhere close to providing even the minimal level of coverage and service it indicated it would on Arizona's Obamacare exchange, as the company instead appears set on following its predatory pricing playbook.

After falling in February 2014 for the first time since June 2012, the initial median new home sale price in the U.S. reported for March 2014 increased by the largest percentage ever recorded since the U.S. Census Bureau began tracking this data back in January 1963. To put numbers to that achievement, the median new home sales price increased by 11.2% from February 2014's revised figure of $260,900 to March 2014's initial figure of $290,000.

At the same time, the preliminary estimate of 384,000 new home sales for March 2014 was significantly lower than the 449,000 recorded in February 2014.

Our chart below puts the trailing twelve month average of median new home sale prices into context with respect to median household income in the U.S., which allows us to account for annual seasonality in the housing data while also smoothing out the volatility of the median income data.

So why did the month-over-month median sale prices of new homes rise so much while the number of new home sales fell by so much?

The answer has a lot to do with the distortionary effects of the second U.S. housing bubble. One of the defining characteristics of a housing bubble is the effect that it has on the sales mix of new homes being sold. Here, as a housing bubble matures, builders come to pursue a strategy of trying to maximize their profits by producing an increasing share of new homes at higher and higher sale prices. Our chart below shows how distorted the mix of new homes being produced and sold has become:

But that strategy risks throwing the market into extreme volatility as the supply of more affordable homes becomes depleted. In this case, that portion of the available supply was effectively depleted in February 2014, leaving behind a large pool of much higher priced homes that were still on the market in March. Homes that were priced well above the affordable reach of typical U.S. home buyers, which is why the number of sales fell so dramatically from the previous month and also why their median sale price increased so dramatically from the previous month for the sales that did occur.

It is then the mismatch between the sales mix of the new homes available for sale and the household income of the potential pool of home buyers is what caused the number of new home sales to plummet in March 2014 as their median sale price skyrocketed. Just the same as what happened during the deflation phase of the first U.S. housing bubble as it picked up speed in the months following the sales volume peak recorded in January 2006.

Consequently, what we're seeing the in data today is consistent with the second U.S. housing bubble peaking as it enters its own deflation phase.

Elsewhere on the Interwebs

Barry Ritholtz answers the question of Where Are All the Homebuyers? Be sure to follow the links at the bottom of Barry's article that pick up on other aspects affecting the U.S. housing market.

The WSJ's Nick Timiraos reports on Why Home Price Gains Aren't Lifting the Economy.

Data Sources

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 23 April 2014.

U.S. Census Bureau. New Residential Sales Historical Data. Houses Sold by Sales Price: U.S. Total (2002-present). [PDF Document]. Accessed 28 April 2014.

Sentier Research. Household Income Trends: March 2014. [PDF Document]. Accessed 28 April 2014. [Note: We've converted all data to be in terms of current (nominal) U.S. dollars.]

Not much of interest happened with the S&P 500 during the trading week ending Friday, 25 April 2014. The market, which had been buoyed up by positive noise from earnings being reported during the week, fell back on Friday, but fairly consistently with what we expect.

We can see that in our alternative futures chart, where stock prices have most closely paralleled the trajectory associated with a forward-looking focus fixed upon 2014-Q3 in setting today's stock prices.

Here, stock prices were consistently within 1.5% of the midpoint of our target range for 2014-Q3. As such, we think the expectations associated with that quarter are still the driving factor for today's stock prices - even though positive noise related to better than expected earnings reports released during the week would appear to shifted a good portion of that attention toward 2014-Q4:

What we're not seeing however are any major changes in those expectations, which is why we are so far attributing the relative changes in stock prices since 15 April 2014 to noise, rather than to a clear-cut shift in investor focus.

In other words, despite all the noise, nothing much to see here.

Then again, if we wait long enough, something interesting might happen!

Analyst Notes

We've entered the one-year anniversary of the shift in investor focus from 2013-Q2 to 2014-Q1 back in April 2013, which preceded a period of considerable volatility in the stock market. We'll be paying quite a lot of attention to the echo effect over the next six-to-eight weeks as we evaluate how well our filtering technique is working.

In theory, one of the ways in which the Internet is supposed better than traditional broadcasting for media businesses is that it provides better opportunities for content advertising campaigns, where advertisers can have their ads automatically placed with complementary content.

Ideally, that means that an article about shoes, for example, would get matched with an ad for a company like Zappos, while online videos featuring cats would get paired with ads for cat-related products, rather than vice-versa. Today's technology makes it possible for advertisers to use content-matching algorithms that are designed to pick up on certain words or phrases within Internet-based content to automatically pair the article with an ad for a related product without ever being reviewed by human beings.

That can be a problem, because sometimes, the ads that get paired with Internet-based content in this way are things that the advertiser would really rather avoid because the association that results may not produce the desired positive outcome.

Keep that in mind as you look at the following screenshot of an article that appeared at PJ Media on Friday, 18 April 2014. This is what we like to call a juxtaposition fail:

There's more to the article than what is shown in our screen capture - the full story is available here.

But back to the juxtaposition fail, thanks to the efficiency and effectiveness of the automated content-matching algorithms used by today's Internet advertisers, we can now place the face of Wendy R. Davis, a politician who has attracted national attention and is currently seeking higher office in the state of Texas, with a news article about how the FBI is currently pursuing a corruption investigation into her past business dealings.

In a sense, that means that Wendy R. Davis' campaign is paying to expose Wendy Davis as a corrupt politician to potential voters in time for the next elections.

At the very least, if you see any ads for Wendy Davis with this article, you should be sure to click on them. As long as they're paying for them, we'd like them to get their money's worth!

On Tax Day 2014, the U.S. federal government owed its lenders over $17.577 trillion. Our chart below reveals who Uncle Sam's biggest creditors are:

The biggest surprise in this edition of our chart (compared to the previous edition) is the appearance of Belgium on the list, which jumped ahead of several other nations by more than doubling the amount that is being lent to the U.S. government from the small European nation over the last six months. Since Belgium is a major international banking center, what this really represents is the accumulation of U.S. debt by other foreign entities through Belgium's banks in much the same way as London's banks have historically served this role for countries such as China.

Here though, it appears that Russia-based interests may be behind the apparent surge in the nation's holdings of U.S. government-issued debt, with the driving factor being the desire to avoid losing access to the holdings from economic sanctions. Much of the increase in holdings through Belgium took place in the several months preceding Russia's 23 February 2014 actions to seize control of the Crimea peninsula from Ukraine, which indicates the very premeditated nature of the action.

Meanwhile, the U.S. Federal Reserve continues to accumulate the share of the U.S. government's debt, having gone from accounting for 1 out of every 8 dollars lent to the U.S. government to now account for nearly 1 out of every 7 dollars.

Data Sources

Federal Reserve Statistical Release. H.4.1. Factors Affecting Reserve Balances. Release Date: 17 April 2014. [Online Document]. Accessed 23 April 2014. [Data through 16 April 2014].

U.S. Treasury. Major Foreign Holders of Treasury Securities. Accessed 23 April 2014. [Data through February 2014].

U.S. Treasury. Monthly Treasury Statement of Receipts and Outlays of the United States Government for Fiscal Year 2014 Through March 30, 2014. [PDF Document]. [Data through March 2014].

Why won't wind energy power the future?

In our original analysis, we considered why wind energy producers are unlikely to ever become independent of government subsidies that currently sustain them and stand on their own as a reliable source of power for ordinary consumers.

But today, we're going beyond that, because we're going to directly address the single most important issue that will physically prevent wind energy producers from ever being more than a niche producer of energy consumed across the globe.

That single issue is the relative energy return on investment for wind energy with respect to the technologies that are needed to make operating wind farms a viable business proposition and a genuinely reliable source of energy for consumers.

Right now, wind energy producers have the problem that they can only generate power when the wind is blowing. That would be great for them if the wind would reliably blow the most at the times that consumers demand the most power, but unfortunately for wind producers, there is often a considerable mismatch between when their facilities produce the most power and when people actually need it.

That is evident from the image above, which shows the times that show when and how much power could have been produced by wind (blue) and solar (gold) energy on each day during a single month (April 2010) compared with when and how much power consumers actually demanded (red) on each of those days. In this chart, in which all the data is normalized to show its percentage of maximum energy production or demand, we observe that the normalized amount of wind energy produced is often well out of sync with the normalized power demands of consumers.

In fact, there are times when wind energy producers actually have to shut down their operations rather than to dump the power they produce onto the power grid at times when there is not enough demand for it. Here, if the wind power generating facilities are not shut down in these situations, they could negatively impact other, more reliable methods of energy production that cannot be arbitrarily shut down to compensate for the unnecessary surge of power, risking considerable disruption and damage to the power grid.

But if the power produced by wind energy could be stored however, that operational issue would go away. And that's where the matter of energy return on investment now comes into play.

To generate electricity using wind power, it doesn't take much of an energy investment to produce the equipment and things needed to generate quite a lot of power from wind. For every unit of energy that goes into the production of wind power, today's established technology generates, or returns, about 18 times that amount. Along with the large government subsidies made available to wind energy producers, which they require to be profitable, the relatively large energy output for energy input to create wind energy producing facilities is what has allowed the rapid growth of wind's share of U.S. energy generation over the last two decades.

But the energy return on investment for the technologies that might be used to cleanly store the energy produced by wind power is far lower, which makes them undesirable to use with wind energy production. For for most of those options, it would actually make more sense, both environmentally and economically, to shut down production from wind energy rather than use these power storage technologies, like batteries, to store the energy produced from wind power.

Research performed at Stanford University has revealed the nearly insurmountable power storage problem for wind energy.

As more and more renewables come online, large batteries have become more and more attractive as an energy storage option. But as with most developing technologies, they're often expensive, and thus Stanford's research focus.

The Stanford scientists examined the energy return on energy investment (EROI) ratios of using several technologies to store solar and wind energy. The EROI calculation is relatively simple – the amount of energy produced by a technology divided by the amount of energy required to build and maintain a storage system.

"Batteries with high energetic costs consume more fossil fuels and therefore release more carbon dioxide over their lifetime," said lead author Charles Barnhart. "If the battery's energetic cost is too high, its overall contribution to global warming could negate the environmental benefits of the wind or solar farm."

Based on this formula, many battery technologies may not provide a positive EROI when used for wind energy. "Both wind turbines and photovoltaics deliver more energy than it takes to build or maintain," said co-author Michael Dale. "The overall energetic cost of wind turbines is much lower than conventional solar panel."

Stanford’s EROI found the energy demands of solar power installations comparable to the energy demands of the five leading battery technologies. But wind farms, since they require less energy to build and maintain, significantly reduce EROI from 20-50% depending on the energy storage technology.

That's a problem for wind power, because curtailment – shutting off the turbines when they’re generating too much power – only reduces EROI by 10%. "For wind farms, the energetic cost of curtailment is much lower than it is for batteries," said Dale. "It would actually be more energetically efficient to shut down a wind turbine than to store the surplus electricity it generates."

As for what technology might work to make storing energy produced by wind turbines both environmentally and economically desirable, Stanford's researchers identify one technology that exists today:

Pumped-hydro energy storage performs best of all the available options, providing an EROI 10 times better than conventional batteries, but with limited deployment options.

Basically, pumped-hydro energy storage would involve using surplus power produced by wind turbines to pump water uphill into to an elevated reservoir, where it could then be released back down through a water turbine to produce energy at the time its actually needed.

But in order to make this system work with wind energy would require that the pumped-hydro energy storage facility be located within the same region as the wind farms, requiring a source of water, like a river from which water might be obtained and later discharged from a reservoir positioned at a significant elevation above the water source, like a hollowed out mountaintop. To pull off that combination of features with viable wind energy production requires a lot of fortunately located geography, which is what really rules out this option for many wind farms, which are often located offshore at near sea level or on the relatively flat plains that coincide with relatively predictable winds over land.

The problem for wind energy producers then turns out to be somewhat of a paradox. Because it is too easy and environmentally clean to generate energy from the wind, almost every method that might be used to store that energy to make wind a more reliable source of power for utility consumers is too relatively wasteful to consider.

Curiously, that problem doesn't exist for the considerably more energy intensive option of producing power from solar power generating technologies. Because the technologies that might be employed to store power produced from solar use a similar level of energy as what it does to generate solar power, it is much more technologically and economically feasible to use these methods to store surplus solar power to be used when consumers actually demand it.

But for wind energy, those options just don't make much technological, environmental or economic sense. In the end, it's not politics that will prevent wind energy from ever becoming a reliable source of power for utility consumers. It's physics.

References

Murphy, D. J. and Hall, C. A. S. (2010), Year in review—EROI or energy return on (energy) invested. Annals of the New York Academy of Sciences, 1185: 102–118. doi: 10.1111/j.1749-6632.2009.05282.x [Ungated version].

Barnhart, Charles J., Dale, Michael, Brandt, Adam R. and Benson, Sally M. The Energetic Implications of Curtailing Versus Storing Solar- and Wind-Generated Electricity. [PDF Document]. Energy Environ. Sci., 2013, 6, 2804. 14 August 2013.

National Weather Service Forecast Office. High Winds Impact West Texas and Southeast New Mexico. [Online Article]. 8 December 2009.

Following our analysis that median new home sale prices in the U.S. have begun to contract, we decided to dig deeper to find out more. We'll begin with the Wall Street Journal's description of the general climate in the U.S. real estate industry throughout the first quarter of 2014:

Reports from local real-estate agent groups in some of the markets that were the first to rebound, including Las Vegas, Phoenix and San Diego, show year-over-year declines in March home sales. February data for pending home sales nationally—a barometer of early-spring activity—show a decline of 11% from a year ago.

And in markets around the country, fewer people are showing up at open houses. An index of home-buyer traffic in 40 U.S. markets compiled by Credit Suisse was down a little more than a third from March of last year. In some parts of the country, cold weather has put a damper on traffic.

New construction of single family homes is also increasing slowly, according to new data released Wednesday. New building permits for single-family homes in March fell 1.2% below the year-earlier level, the Commerce Department said Wednesday. New single-family home starts rose 1.9% from a year earlier.

"Overall, even after adjusting for weather, it has been worse than what most people expected," said Tom Lawler, an independent housing economist in Leesburg, Va.

The WSJ goes on to confirm one of our earlier observations that the sudden increase in mortgage rates is a major factor behind the deceleration that appears to be taking hold:

The sluggish start to the spring home-buying season—a crucial period for sales because families typically want to lock into a school district by the end of summer—comes as investors cut back on purchases of homes that can be rented or flipped for a quick profit. Meanwhile, potential buyers are still adjusting to a sharp rise in both home prices and borrowing costs over the past year. With prices and mortgage rates up, the nation's median monthly home payment—including principal and interest—has risen 20% in the past year to about $900, according to John Burns Real Estate Consulting.

The WSJ then went on to identify the recent cost trends for a number of local real estate markets that were seeing rapid price increases in 2013:

Here, we see that the increase in home prices is decelerating for a number of markets, and that they have actually begun to fall in the Phoenix metropolitan area. Based on that, we decided to drill down into local news coverage to see the factors at work in that market. Here, we found a good description of the trends in Phoenix' home sales since the beginning of 2014:

A drop in home sales and an increase in listings helped pull down metro Phoenix home prices in February.

The Valley's median home-sales price fell to $195,000 in February, the lowest since August, according to Arizona State University's W.P. Carey School of Business.

The median also fell in January, to $196,500. The median sales price was $205,000 in December. That means median prices have dropped almost 5 percent since the start of 2014.

The number of sales in February also was a concern for the real-estate analyst who prepares the report.

"Home-sales activity was a startling 26 percent below February 2013," said Mike Orr, director of the Center for Real Estate Theory and Practice at W. P. Carey School of Business. "Despite the large price gains since last year, this is the weakest February in four years."

He said metro Phoenix home sales typically climb in spring, but the market is still on track to see little or no appreciation this year.

What makes what's happening in Phoenix' local real estate market particularly interesting is that the region was completely unaffected by the winter weather that would appear to have negatively impacted other regional real estate markets in the United States.

Phoenix was also one of the markets most negatively affected by the deflation of the first U.S. housing bubble, which subsequently benefited from the influence of investors who bought up large quantities of distressed and foreclosed properties from July 2012 through July 2013 - the primary inflation phase of the second U.S. housing bubble.

Having drained the supply of inexpensive properties, the same investors that drove the recovery of home prices in the Phoenix metropolitan area have begun to exit the market:

The house-flipping frenzy is over in metro Phoenix, though a few investors are still able to make it work if they can find the right house.

The dramatic drop in foreclosures across the Valley means there are few houses to be bought cheaply, fixed up and resold quickly for a profit.

"There was the point where we had 11,000 foreclosures in one month," said Marty Boardman, a real-estate business owner who began investing in Valley houses in 2002. "From what I understand, today the average is around 500 or 600."

[...]

"Last year I just decided that enough is enough," said Boardman. "The profit margin was just too thin in Phoenix, and there were too many investors in the market."

Now, let's zoom out and see how the #1, #2 and #3 national investment firms in residential real estate are now playing the markets:

Blackstone’s acquisition pace has declined 70 percent from its peak last year, when the private equity firm was spending more than $100 million a week on properties, said Jonathan Gray, global head of real estate for the New York-based firm.

American Homes 4 Rent and Colony American Homes, the second- and third-largest single-family landlords, also have been scaling back as bargains dry up. Home prices have risen 24 percent since a post-bubble low in March 2012, which was about when corporate buyers started their buying spree, according to the S&P/Case-Shiller index.

Note that Blackstone, the largest player, really didn't get started buying up available residential real estate until July 2012, marking the beginning of the inflation phase for the second U.S. housing bubble.

With investors having run up home prices enough to effectively price themselves out of the market, the inventory of homes for sale in Phoenix and other markets has begun to rise. But because mortgage rates also rose sharply in the second half of 2013, the remaining consumers in the market, who are primarily people who are seeking to buy homes to live in themselves, are at a financial disadvantage. The typical prices of homes available for sale in the market, when translated into the monthly payments of a mortgage, are simply too far above what these ordinary home buyers can support on their household incomes.

But don't just take our word for it. Others have noticed that effect as well:

"People are coming out and shopping [for new homes], but they're not buying," said Brad Hunter, chief economist for home-construction analysis and consulting firm Metrostudy, a division of Hanley Wood LLC. "My analysis is that a lot of this has to do with sticker shock."

Mr. Hunter and other housing-market observers theorize that sales volumes won't pick up markedly until builders rein in their price increases and first-time buyers and less-affluent buyers are ushered back into the market by better job and wage growth and a slight loosening of mortgage-qualification standards.

That state of affairs is not a sustainable situation, so something has to change so more transactions can take place. That something is the price of homes for sale, which are now responding to the increase in supply and the decrease in demand by either decelerating their rate of increase or by falling outright, depending upon the local real estate market in question.

That dynamic, played out in varying degrees in all the real estate markets across the country, but especially in the markets that had seen the most volatility in prices during the years of the first housing bubble and the most investor activity in the second, is what is now causing the second U.S. housing bubble to enter into its deflation phase.

And that's how the U.S. real estate market entered into such a state of malaise in early 2014, with housing prices stalling out or falling in enough local markets to show up as an outright decline in the trailing twelve month average of median new home sale prices in the preliminary data for February 2014.

Perhaps because it was so uneventful, the trading week ending 17 April 2014 was a positive one for stock prices.

The relative lack of fireworks allowed investors to focus on the earnings news being reported during the week, much of which was positive. That, in turn, positively affected stock prices - so much so that it's somewhat of a tossup at this point whether what we observe is the result of simple noise or if the positive earnings reports led investors to shift their forward-looking attention to the more positive-looking quarter of 2014-Q4 in setting today's stock prices.

That latter possibility is hinted at in our chart showing the changes in the year-over-year growth rates of stock prices with respect to the trailing year dividends per share for the S&P 500.

Here's how that played out in our alternative futures chart, where stock prices would appear to be falling between the futures defined by the expectations associated with 2014-Q3 and 2014-Q4:

We'll find out soon if there's more to the uptick in stock prices than positive noise.

Analyst Notes

If you're looking closely at our chart showing the accelerations of stock prices with respect to the expected trailing year dividends per share in future quarters, you'll see that the acceleration of daily stock prices would appear to have reached the level of 2014-Q4. But if you look at the alternative futures chart, which is in part based on that data, the level of stock prices is below the level that would match what we project for 2014-Q4.

The difference has to do with how we project the alternative futures trajectories. Throughout the period shown on this chart, we assume a "typical" basic size for the echo effect associated with the fiscal cliff deal rally from early 2013, because we cannot precisely project the actual size of the combined echo and current day noise that will be measured on any given future date.

Meanwhile, our accelerations chart shows the actual recorded combined value for both echo and noise. If we were to substitute those values with the ones we use in our projections, we would see a considerably better match between the two.

But since we work in the future, there's not much point in doing that because predicting the past is only useful when you don't remember it.

Maybe not as good as the alternate ending for Gravity, but not bad either....

Have a great weekend!

What happens when the long-term unemployed are suddenly cut off from being able to cash in on the federal government's extended unemployment benefits program?

That's the case for millions of Americans who have been unemployed for 27 weeks or longer, for whom the federal government's extended unemployment benefits program expired after 28 December 2013.

Now without that financial assistance for several months, and therefore being highly motivated to find work to replace their lost income from unemployment benefits, we wondered how successful those individuals have been.

Early reports indicate that very little has changed for the employment prospects of the long-term unemployed, at least through the first month of their no longer having unemployment benefits, but what has changed would seem to have changed for the better. Here's an example from Illinois, where 74,000 people lost extended unemployment benefits after the program expired on 28 December 2013:

One month later, 64,000 or 86 percent, still were without work, according to an Illinois Department of Employment Security analysis released today.

With 14% of the long-term unemployed in Illinois having found jobs in just one month according to the state's official statistics, Illinois saw a rate of improvement that's notably better than the 10% to 11% rate of new hiring success that studies indicate is typical for those who have been unemployed for 27 weeks or longer in recent years. That's also remarkable in that January 2014 saw extremely cold winter weather disrupt much of Illinois' economy, costing it billions of dollars.

However, that's only after one month after their extended unemployment benefits expired. The average dedicated job search ranges between three and six months in duration, so we wouldn't necessarily expect much of a change in new-hire statistics for the long-term unemployed after that short a period of time.

We'll have to watch how that continues to play out.

According to preliminary data published by the U.S. Census Bureau, the trailing twelve month average of median sale prices for new homes fell in February 2014 after peaking a month earlier.

The preliminary new home sale price for February 2014 was $261,800, which was up from January's revised $260,800. However, the trailing twelve month average for median new home sale prices, which smooths out seasonal variations in the data, fell to $265,100 in February 2014 from January's 265,375 - the first contraction we've observed in the data for some time.

The Census Bureau's monthly data is typically revised upward for several months after it is first reported, as it takes time for larger sales occurring in a given month to be recorded.

Our chart below shows how the trailing year average of median new home sale prices have evolved with respect to median household income in the U.S. over the last 15 years. Note that the falling housing prices came as median household income saw its biggest increase since August 2012.

Unless upcoming revisions to the preliminary data change this result, February 2014 would mark the first time since June 2012 that the trailing year average of median new home sale prices declined from the previous month. July 2012 marks Month 0 of the period that coincides with the inflation of a new bubble in the United States according to the data we track.

The 19 month long period of month-over-month price increases in the twelve-month average from July 2012 through January 2014 would be the longest recorded since the 32 months of steady month-over-month increases recorded between January 2004 and September 2006, which coincides with the peaking of the first U.S. housing bubble.

As noted in other analysis, the ISM Non-manufacturing Report on Business for March 2014 indicates that the real estate, rental and leasing industry contracted in March 2014. If so, we may now be witnessing a peak in the second U.S. housing bubble.

Previously on Political Calculations

We were among the first to declare that a second housing bubble was forming in the U.S. economy, and we were the first to back it up with an objective framework of analysis and data. Our ongoing analysis is chronicled below....

• The U.S. Housing Bubble Is Back - we apply our groundbreaking analytical methods to determine that a new housing bubble has begun to inflate in the U.S. economy.
• Fuel, Oxidizer and a Spark - Part 1 - we revisit the origins of the first U.S. housing bubble and identify the factors that ignited it.
• Fuel, Oxidizer and a Spark - Part 2 - we explain why housing prices rose so much more in just four states than they did elsewhere, and point our finger at the Fed's below-market interest rate policy as the primary source of fuel for the bubble.
• Fuel, Oxidizer and a Spark - Part 3 - we examine the factors that kept the first U.S. housing bubble going, even after the Fed finally acted to stop throwing so much fuel on the fire.
• Confirming the Second U.S. Housing Bubble - using revised data, we confirm that there is no apparent new-year slowdown in the inflation phase of the new U.S. housing bubble.
• As the Housing Bubble Inflates: Month 9 - we use hard data to refute the housing bubble deniers!
• As the Housing Bubble Inflates: Month 10 - we note the fourth consecutive record for median new home sale prices and discuss the spark that set off the second U.S. housing bubble.
• Setting the Baseline for a Better Housing Affordability Index - how affordable is your home when compared with every other American homeowner? We create a new index to answer that question for any household income level.
• As the Second U.S. Housing Bubble Inflates: Rapidly Escalating Prices - each revision of median new home sale prices indicates the second U.S. housing bubble is growing even faster than the first!
• The Sales Mix of the New Housing Bubble - we find that just like in the first U.S. housing bubble, the sales mix of new homes in the second U.S. housing bubble is being distorted in a very similar way.
• The First Anniversary of the Second U.S. Housing Bubble - we mark the first birthday of the second U.S. housing bubble.
• Is the Second U.S. Housing Bubble Beginning to Peak? - We note a deceleration in the upward trajectory of median new home sale prices and identify the primary cause. Along the way, we find that bubbles can only exist if the Fed wants them to exist!
• U.S. New Home Sale Prices Stalling Out - We confirm that the rise of new home sale prices was beginning to sputter in the third quarter of 2013.
• Breathing New Life Into the Second U.S. Housing Bubble - After stalling out through September 2013, we find that U.S. housing prices began to rise again with lower mortgage rates following the Fed's decision to delay tapering its purchases of U.S. Treasuries and Mortgage-Backed Securities in September 2013.
• Slowing Inflation for the Second U.S. Housing Bubble - looking at the data through December 2013, we find that while the second housing bubble has resumed inflating, it would also seem to be inflating at a decelerating rate.
• U.S. New Home Sale Prices at the Mercy of Mortgage Rates - we observe that the growth of new home sale prices would appear to be decelerating as mortgage rates rise and accelerating when they fall.
• Revisualizing the Second U.S. Housing Bubble - we map out the inflation-adjusted trajectory of median new home sale prices with respect to median household incomes.
• Real Estate Prices Begin to Contract - the data is preliminary, but if it holds, we may be seeing the first month-over-month decline in median new home sale prices since the second U.S. housing bubble began to inflate in July 2012.

Data Sources

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 24 March 2014. [Note: All this data is reported in terms of current (nominal) U.S. dollars.]

Sentier Research. Household Income Trends: February 2014. [PDF Document]. Accessed 11 April 2014. [Note: We've converted all data to be in terms of current (nominal) U.S. dollars.]

Suppose you're one of the millions of Americans who do not have health insurance through your employer for whom it makes much more financial sense to pay the Obamacare tax than it does to buy health insurance. To avoid getting hit with a larger tax bill than you might otherwise expect when you file your taxes for 2014, how much extra should you have withheld from each of your paychecks today?

Our latest tool will help you answer this critical question, because the IRS' withholding tables for 2014 do not take the Affordable Care Act's income tax increase for 2014 into account.

Just enter the indicated data in our tool, and we'll do the math that will apply for you for the 2014 tax year (it will not apply for 2015 or any year afterward).

In the tool above, we assume that you haven't had any extra amount withheld from your paycheck to pay for the Obamacare income tax for 2014, and will need to do so over your remaining paychecks for the year. We also assume that you will be filing as a Single individual for the year, have no dependents to claim on your income taxes and that you are not eligible for Medicaid.

Depending upon how expensive health insurance is in your region, you may be exempt from the tax if the annual cost of the premiums for a "Bronze"-level plan exceeded 8% of your annual household income, so you'll want to confirm if that's the case for you.

These are important considerations because even though the IRS has not been given explicit directions to punish taxpayers who might underwithhold their income taxes by the amount of their Obamacare tax, you will still owe the money. The IRS is busy proving that it will come after you, or your children, to collect it, decades after the agency decides that they "loaned" you the amount you may have underwithheld. No matter how small it is, with interest and penalties.

Have a happy tax day!

By now, most of our readers will know that we anticipated last week's stock market "correction" and that we communicated it weeks ago. Our updated alternate futures chart below confirms how closely the real world followed our forecast:

That's why we were fascinated to read Barry Ritholtz's take on the event, which he later reposted on his blog:

Whenever we see any sort of disruption in markets an explanation usually follows. The headlines will explain that “Markets are going up/down because of this good/bad thing.” News anchors will solemnly intone why the volatility is significant and what it means for one thing or another.

None of these casual explanations can withstand close examination. They are often things that have existed for months or years, and so can’t account for what happened yesterday.

Stocks are fully valued, and have been for a while, so why is it that valuations suddenly matter after not mattering at all? The market for initial public offerings is too hot? Wait, the Federal Reserve is going to end quantitative easing, something it has been warning us about for two years? Now it suddenly matters?

Of course, all of these narratives serve a singular purpose: They give the appearance of meaning and rationality to actions that are meaningless and irrational. The daily action in the markets is a form of noisy, random, Brownian motion. If you are looking for a clear reason as to why stocks did what they did, then you are in the wrong line of business.

Normally, we would be in full agreement with Barry's assessment. But because we're in such a unique position of having seen what happened in the market all last week coming well in advance of its arrival, we probably can provide more insight into the nature of the event than the ordinary market observer.

We would describe it as being much like an aftershock to an earthquake. Except in this case, the aftershock was more pronounced than the original shocks, thanks to a confluence of factors from both a year ago and from a month ago.

To understand why takes getting into the math behind how stock prices work, which we'll let you do on your own.

In this case, we're fortunate in that the volume of noise in the stock market is relatively low while investors went into the event strongly focused on the future quarter of 2014-Q3 in setting today's stock prices, which ends just under five months from now.

The basic explanation for the event can be found in the financial news reports that coincide with the various factors that would be entered into our math, for which we're confident that you can successfully use a search engine like Google to identify. If it helps, because the calendar is involved, so is the bond market. You will specifically be looking for events where capital flows would have moved money between the stock and bond markets, where you'll find synchronized changes in stock prices and bond yields, where both suddenly rose or fell together in response to the specific real world events that drove the markets at those times.

We say the event is an aftershock because the investment decisions that were made at these times tied up the money associated with them, where maturity and option expiration dates had to be reached before new actions could be taken based on newer information.

And that is pretty much the how, when and why of what happened in the markets last week, which to us, are the more interesting aspects of the event.

The good news, if you can call it that, is that the market fell by less than our model forecast on Friday, 11 April 2014. While still well within our expected range (indicated by the green-shaded vertical error bars for investors focused on 2014-Q3 in our chart above), the positive noise here will contribute to dampening future aftershocks. From our perspective, it would appear that the event is largely over.

That's not to say that stock prices couldn't still move downward in the near term, as could happen with the arrival of a new and negative noise event or if investors were to shift their focus away from 2014-Q3 to either the nearer term 2014-Q2 or the more distant future of 2015-Q1. And speaking of 2015-Q1, now that we have the finalized value for dividends paid in 2014-Q1, we've made our quarterly adjustment to the expected change in the growth rate of dividends per share for that future quarter.

As a final note, we'll observe that this most certainly isn't the first that time we've successfully charted the future course of the stock market or correctly called turns in it, which even Barry Ritholtz would have to admit is quite the parlor trick for something so seemingly impossible.

But our really long time readers know that the truth of how we do what we do is far more unsettling....

Previously on Political Calculations

• Extending the Alternate Futures
• The Evolving Future of the S&P 500
• The Math Behind How Stock Prices Work
• Inside an Impossible Prediction for the S&P 500

In less than a week, the deadline for filing for 2013's federal income taxes will be upon us. That makes this a very good time to find out how many pages it takes to explain the U.S. federal tax code!

Our source for this data is the Wolters Kluwer CCH Standard Tax Reporter, which has updated their data through the 2013 tax year:

We find that for those filing their personal income taxes on 15 April 2014, they must comply with the terms of a tax code that takes 73,954 pages to explain. To tax professionals.

Just for fun, we thought it would be interesting to find out how fast the U.S. tax code has been growing during President Obama's tenure in office. Here, we turned to an older version of the graphic above to find out that through 2008, the year before President Obama was sworn into office, the U.S. tax code was just 67,506 pages long.

In President Obama's first two years in office, when his political party also controlled both the U.S. House of Representatives and the U.S. Senate and used its control to impose massive new taxes on the American people like the Patient Protection and Affordable Care Act, the U.S. tax code grew to be 71,684 pages long, which works out to be an average exponential rate of 3.0% per year.

If it had been allowed to continue growing at that rate, the U.S. tax code would effectively double in length every 24 years.

After 2010 however, the Democratic Party lost control of the U.S. House of Representatives, with one of the outcomes of that loss being that the U.S. federal tax code has grown much more slowly in all the years since.

From 2010 to 2013, we find that the growth of the U.S. federal tax code has decelerated to grow at just a third of the rate that it did when the Democratic Party controlled the U.S. Congress and the White House. The tax code has grown at an exponential rate of just 1.0% per year since 2010, a pace that would have it double in size every 72 years.

Altogether, the U.S. federal tax code has grown at an average exponential rate of 1.8% per year since 2008.

If you wanted one word to describe the U.S. economy in the first quarter of 2014, the word 'tractionless' comes immediately to mind.

The latest real evidence for that assessment comes not from the latest jobs report, which many found disappointing but instead from the U.S. stock market, where once again, the number of publicly-traded U.S. companies who announced they would be cutting their dividends during the month of March remained at elevated levels. Levels that are consistent with recessionary forces at work in the U.S. economy:

Unlike the unemployment rate, which is usually a lagging indicator of the health of the economy, the number of companies announcing dividend cuts each month is a coincident indicator - something that tells us about the state of the economy today, in real time.

And what the elevated number of companies acting to cut their dividends in March 2014 tells us is that at least some parts of the U.S. economy are contracting rather than expanding.

Just for fun, we turned to the Institute of Supply Management's reports for March 2014 to see which sectors of the economy are producing the least traction. Here's the quick summary for both manufacturing and non-manufacturing industries. First, for manufacturing industries, where the reports were generally positive:

The four industries reporting contraction in March are: Apparel, Leather & Allied Products; Wood Products; Electrical Equipment, Appliances & Components; and Miscellaneous Manufacturing.

And now for non-manufacturing industries, which is where most of the drag on the U.S. economy would appear to be originating, and which one respondent's comments points the finger at a major reason why:

The five industries reporting contraction in March are: Mining; Educational Services; Health Care & Social Assistance; Real Estate, Rental & Leasing; and Other Services.

Let's run through the non-manufacturing industries where we have some insights briefly:

Mining: The sluggishness in the U.S. mining industry can likely be traced directly back to the Chinese government's decision last year to slow down the growth of the nation's economy. With that nation growing much more slowly, it requires far fewer resources produced through mining to sustain it.

Educational Services: There is a major slow down underway for education services, particularly for for-profit universities, which are reporting declining enrollment levels.

Health Care & Social Assistance: We cannot do any better than to quote what one respondent to the ISM's survey said about what's hurting that particular industry:

"Healthcare reform continues to adversely impact hospital projected/actual revenue." (Health Care & Social Assistance)

Real Estate, Renting & Leasing: The major story here is the decline of demand for real estate in the U.S., where the rapid rise in prices driven by large investment firms who were buying up large quantities of distressed residential properties from 2012 to 2013 ultimately led them to stop buying so much property as their potential returns on their investments declined. Combined with the Fed's decision to taper its quantitative easing programs, which made buying real estate more expensive because of the corresponding hike in mortgage interest rates, the amount of economic activity in the real estate sector has been falling as a result.

And there you have it. While likely not enough to pull the entire U.S. economy down into recession, we at least now have some idea of which parts of the economy are experiencing recessionary conditions at the present time.

Ben Casselman, the youthful chief economics writer of Nate Silver's FiveThirtyEight blog, describes the state of the jobs recovery:

After more than six years, the U.S. private sector has at last regained the jobs lost in the Great Recession.

The economy added 192,000 jobs in March, the 42nd consecutive month of growth, the Bureau of Labor Statistics reported Friday. All the gains were in the private sector, pushing nongovernment employment to 116 million, just above the prior record set in January 2008, when the recession was just beginning. The private sector lost 8.8 million jobs in the recession and has gained 8.9 million since.

But the wounds of the recession are far from fully healed. Total payrolls remain more than 400,000 below their prior peak due to deep cuts in the number of government workers, especially at the state and local level. And the adult population (16 years and older) has grown by 14 million since the recession began, meaning the U.S. job market is nowhere close to fully recovered on a per-capita basis. The long-term unemployment crisis drags on, the legacy of what is by some measures the slowest recovery since World War II.

Going by the age demographics of the U.S. civilian labor force, we observe that the jobs recovery for U.S. adults, Age 25 and older, as February 2014's data turned out to not be an outlier as we had previously suspected.

We also observe that the jobs data for young adults, Ages 20 through 24, is now just one good jobs report away from also fully recovering the jobs lost by this portion of the U.S. workforce in the aftermath of the December 2007-June 2009 recession.

But there is one demographic group for whom there has been no recovery at all....

Curiously, the youthful Casselman completely misses the one portion of the U.S. private sector labor force that has effectively experienced no recovery from its recession bottoms in his reporting: U.S. teens Age 16 through 19.

Instead, Casselman laments the reduction in the number of people working for the federal, state and local governments across the U.S., somehow missing that these same government employees experienced no significant job loss at all during the recession. Here, the combination of federal, state and local governments across the U.S. added 200,000 people to their payrolls from December 2007 through June 2009, the period in which the U.S. economy contracted during the recession.

The reduction in jobs for government workers since the end of the recession has largely come about as a result of the failure of the U.S. economy to recover strongly enough to continue sustaining the growth of government payrolls, especially at the state and local level.

Even with such a delayed impact, government workers have still experienced a far milder recession than the private sector did. And in fact, many of the job losses that have occurred in the public sector could have been avoided if government employees were willing to modestly trim their retirement benefits to levels consistent with those available in the private sector.

But they had other priorities. It's just a shame that they're not the same as those of regular Americans.