This Song Would Totally Be a Hit Today

If only Blake Shelton performed it on "The Voice":

Except that only CeeLo Green would have the guts to do it. Still, that would be interesting, and likely better than many of the battle rounds....

As David Tufte described it:

Odd. A whole song video, sung by Italians, of nonsense words chosen to sound like English.

Made in 1972 by Adriano Celantano, it's a parody of Italian rockers who sang in English even though they didn't speak the language.

The scary thing is that it's not bad at all (if you go in for early 70's bubblegum funk). And you’ve got to love the "harp-syncing".

And who *doesn't* go for "harp-synching" or early '70's bubblegum funk? It's got platinum written all over it!

The Odds of Going to the Hospital

What are the odds that you will need serious medical care?

By "serious medical care", most people will automatically think of a situation where they might need to be admitted to a hospital to receive care for an unforeseen condition, so that's the standard we'll use to answer that question.

Beyond that, we'll break the information down by age and sex, simply because we can see these being major factors that might affect how likely a person will need hospital care.

It turns out to be a really difficult question to answer, because in the U.S., which is where we first sought to get hospital utilization data, tracks hospital discharges - not admissions. The problem with that is that the number of admissions won't necessarily track with the number of discharges, as patients die or perhaps otherwise leave the hospital before being officially discharged.

So we turned elsewhere to answer the question, and specifically to the island nation of Singapore, whose Ministry of Health makes the data not only easy to find, but presents it in a way that helps us answer our specific questions. Our first chart below illustrates the 2011 hospital admission rates by age group and sex per each 1,000 members of Singapore's resident population:

One interesting aspect of the data is that we see such high numbers for the 0-4 age group, which drops off dramatically for the 5-9 age group, which really didn't make a whole lot of sense to us at first. Why would a 4-year old have such a dramatically higher probability of being admitted to a hospital over a 5-year old?

We started thinking about it, and realized that the MOH's statisticians gave us a valuable clue - the number of hospital admissions for each 1,000 members of Singapore's resident population doesn't include hospitalizations associated with either normal deliveries for pregnancy or legalized abortions.

While both of these categories would count as foreseeable conditions, we suspect that the reason in the case of normal deliveries was in part to avoid double-counting. Here, where normal deliveries are concerned, we suspect that infants born in Singapore's hospitals are subsequently "admitted" to the hospital after being born, which is how the hospital admissions associated with normal deliveries are tracked.

Beyond that, we can see that the rate of hospital admissions for women of child-bearing age is over twice that of men of the same age, which likely corresponds to pregnancies that involved complicating factors requiring more intensive care, which would not count as a foreseeable condition.

Having worked out why that apparent anomaly exists, we used that knowledge to determine the probability of being admitted to a hospital for both men and women by age, reverse engineering Singapore's age-group based data to approximate the odds by single year of age from Age 0 through Age 84:

Note how nearly 100% of those 0-year olds are admitted to the hospital! Next, let's look at the same data for women from Age 0 to Age 84:

In looking at the differences in the data between men and women, we see that boys are more likely to be admitted to a hospital before Age 4, after which we see that both boys and girls have similar odds up until child-bearing becomes a factor. At that point, women are much more likely to require hospital admission than men (likely for the reasons we noted earlier), up until their mid-forties, after which, men become much more likely to require hospital admission.

The longer lifespan of women with respect to men likely explains that discrepancy, although we were surprised to see how wide that gap was by Age 84, with women having a 50% probability of being admitted to a hospital and men having almost a 90% probability.

References

Singapore Ministry of Health. Hospital Admission Rates* by Age and Sex 2011. [Online Report]. 10 November 2012. Accessed 8 October 2013.

Estimates of Nominal and Real GDP in the U.S. for 2013-Q3

Oh no! The government isn't reporting any economic data!

That's something that might stymie a lesser economist, but we're not going to let a lame government shut down stop us!

That's why today, we're going to do the job that the furloughed employees of the Bureau of Economic Analysis won't be doing this month, unless the partial government shutdown ends really soon and they crank out a rush job. We're going to estimate what the United States' Gross Domestic Product will be for the just completed third quarter of 2013.

After all, we've previously found that it takes maybe as many as 2.5 economists in the private sector to do the same job that it takes 16 government economists to do, so just how hard could it be?

Technically, we're going to forecast it, but then, since it takes the BEA three attempts before they finally get close to a good number, forecast values for GDP are probably just as good as an official government estimated one.

Let's do this visually, so you can get a sense of where we came up with our estimate of GDP for 2013-Q3. Our first chart is one based on math that we have been developing to quantify and visualize the impact of changes in government spending, taxes and the Fed's quantitative easing programs upon the U.S. economy, but which we'll now use to project what nominal GDP will be reported to be for the third quarter of 2013:

Using 2012-Q3's GDP as our base point, our forecasting method has come within 0.02% of the actual figure for nominal GDP that was reported in 2012-Q4, 2013-Q1 and 2013-Q2, or rather, the three quarters preceding the third quarter of 2013. We are projecting a nominal GDP of $16,764.5 billion for the U.S. in 2013-Q3, with the following assumptions that apply since the end of 2012-Q3, which marks our base reference point:

• Net Change in total assets held by Federal Reserve (QE): $927.8 billion


• Net Change in government taxes: $168.9 billion


• Net Change in government spending since 2012-Q3: -$21.0 billion

The first two quantities are pretty locked in at this point and won't likely be subject to future adjustment. The wild card in our forecast is the amount of government spending in the U.S., which consists of spending at the federal government level, as well as at the state and local level, for which we won't likely have a good estimate until late December 2013. Assuming that the BEA's data jocks get back on the job before then.

To get around that limitation, we went over data recorded from 1960 through 2012 to determine that average change in spending for both Federal and State & Local governments from the second quarter of each year to the third quarter to determine our estimate for this year. And you want to know the crazy thing about that? Even though the BEA shut down the computer system that reports historic data as part of their effort to completely flummox lesser economists, we didn't need to use their stinking site to get the historic GDP data on government spending at all.

Speaking of which, that value isn't something that would be impacted at all by the partial U.S. federal government shut down, which didn't begin until 1 October 2013, which is part of the fourth quarter of 2013.

Another factor we need to consider from better, private sector sources of information about the relative health of the U.S. economy is the possible return of organic economic growth, following the year-long microrecession experienced by the private sector of the U.S. economy from July 2012 through July 2013, which may have added a positive contribution to the GDP number. Since those conditions would appear to have resumed somewhat in September 2013 however, we think that contribution will be small, with the actual value likely to be reported to be very close to our forecast nominal GDP number.

As for real GDP, our inertial forecasting methods aren't quite as precise as they would seem to be for nominal GDP. Here, outside of periods where the U.S. economy has turned the corner from expansion to contraction, or vice versa, historical back-testing puts us within 2% of the value the BEA reports about 95% of the time, and within 1% of it almost 75% of the time.

Our second chart shows our projected value for real GDP in 2013-Q3:

Here we anticipate that real, inflation-adjusted GDP in the U.S. will most likely fall in a range between $15,590.7 and $15,910.4 billion in terms of constant 2009 U.S. dollars, with a 95% probability of falling in a range between $15,430.9 and $16,070.2 billion.

By definition, it has a 50% probability of being above the midpoint of our forecast range, $15,709 billion. We think that given the relative increase in government spending from 2013-Q2 to 2013-Q3, combined with the positive contribution of organic economic growth, that real GDP in the third quarter of 2013 will indeed be reported to be above that level.

And there you have it - a simple blog just replaced the topline work of the Bureau of Economic Analysis for the third quarter of 2013 using just a handful of data points. We'd actually rather they be able to doing the job themselves, since the full extent of the data collection and reporting that they do is something that does have real world value, but we can't help but think that there ought to be a private sector alternative available to fully pick up the slack during times like these.

A New View of Future Expectations for the S&P 500

Now that Eugene Fama, Lars Peter Hansen and Robert Shiller have collectively been awarded the Economics Nobel prize for their insights into how asset prices work, insights that we both routinely apply and have extended in our own work, we'll take this opportunity to open up a new window for how all that applies to the S&P 500.

We'll do that by remaking our favorite chart - the one that shows how changes in the year-over-year growth rate of today's stock prices keep pace with changes in the year-over-year growth rates of the dividends per share that are expected at specific points of time in the future - replacing the dividend futures data we obtain from IndexArb with dividend futures data from the Chicago Board of Exchange, which are really different from one another. The chart below shows all that data for each future quarter's dividends going all the way from 3 January 2013 through 10 October 2013:

Each of the data series that apply for a future quarter's dividends per share represent the expectations that investors have for the amount of dividends they will earn in that quarter. In the absence of large sources of noise, or variance, changes in the growth rate of stock prices will closely track with the trajectories associated with a specific future quarter where investors collectively focus their forward-looking attention.

In the chart above, we see that's the case at the very beginning of 2013, where investors focused their attention on the expected future defined by the second quarter of 2013 in setting stock prices. The focus of investors remained on that quarter, which ended in June 2013, well into April 2013.

At that point, investors began shifting their forward-looking attention to the more distant future defined by the expectations for dividends associated with the first quarter of 2014. We observe this shift in focus in the transition of daily stock prices (the dotted blue line) from the data series for 2013-Q2 to 2014-Q1.

That attention stayed there until 19 July 2013, when stock prices suddenly deviated from where investors were focused in response to what we've called the Bernanke Noise Event. Here, investors reacted to the new information that Fed Chairman Ben Bernanke communicated at a press conference that the Fed was seriously considering tapering off its purchases of government-issued securities once certain economic targets were hit by sending stock prices considerably lower than they would otherwise have been set if only the expectations of future dividends to be paid in 2014-Q1 were driving them.

That reaction was more than the Fed was ready to handle at that time. It took a month of effort, but the Federal Reserve finally succeeded in restoring the expectation that investors previously had that there would be no tapering of its QE programs until 2014, which we observe in stock prices resuming to closely track the expectations for 2014-Q1's dividends. But then, positive economic data combined with statements by lesser Fed officials led investors to believe that the Fed could begin tapering its QE program before the end of the third quarter of 2013.

That set off a larger negative reaction in stock prices. Only here, investors shifted their focus away from the more distant future quarter of 2014-Q1 in setting stock prices to instead fully focus on the critical quarter of 2013-Q3. We observe that shift taking place from the end of the Bernanke Noise Event through the end of August 2013, which marked the high point for the expectation of investors that the Fed would being tapering its QE programs in September 2013.

And then, the real-time economic outlook for the U.S. economy began to take a turn back to the worse, leading investors to increasingly bet that the Fed would not act to cut back its QE programs at the end of 2013-Q3, which led to rising stock prices as investors refocused their attention toward 2014-Q1. The Fed then surprised many, including us, that it would not act in 2013-Q3 to trim its QE bond-buying spree, but in retrospect, the evidence from stock prices and the expectations for future dividends supports that interpretation of events.

Unfortunately, before they could make it back to the level that would be fully consistent with the expectations associated with 2014-Q1, a new negative noise event centered around the potential for a government shut down and partial default on the nation's debt reared its ugly head, causing stock prices to once again deviate away from the level they would otherwise be. And that brings us nearly up to the present.

If all this makes the stock market sound like a chaotic place, that's because it frequently is - but that doesn't mean there isn't a predictable order underlying it all. That's what lies beyond the work of newly-minted Nobel-prize winning economists Fama, Larsen and Shiller, whose work has made what we do possible.

Speaking of which, if you want to find out more about our work, it all begins here. You only have to review several years of worth of what we've worked out live, in real time, without the benefit of any sort of safety net to catch up to us!...

Notes: we've modified the chart in this post from previous versions by eliminating an additional scale factor of 12 that we were applying to both the changes in the growth rates of dividends and the change in the growth rate of stock prices, which was an artifact our annualizing the monthly data we were using when we first discovered the relationship between the two. Since this additional scale factor is applied to both dividends and stock prices, it effectively cancels out of our math describing how changes in the growth rates between the two are related, so we're taking this opportunity to dispense with it altogether.

Beyond that, we've also changed our amplification scale factor, which is the scale factor that matters in our math. This change was driven by our change in data sources, where there can be considerable differences between the dividend futures data reported by IndexArb and that reported by the CBOE. Using IndexArb's data, we had settled on a typical amplification scale factor of 9.0, while the factor we're opting to use for the present with the CBOE's data is 5.0.

The Differences Between the Expected Futures for Dividends

We've previously discussed our sources for where we obtain the dividend futures data we use to track what investors expect at different points in time of the future, but we haven't shown how they compare with respect to one another, much less to how actual dividends per share play out!

We going to do that today using data for the just-ended third quarter of 2013. Our chart below shows how the data for 2013-Q3's expected cash dividends per share tracked from 3 January 2013 through the end of the calendar quarter on 30 September 2013:

As we noted before, the main difference between our primary sources of dividend futures data is how they determine how much the cash dividends per share will be at the end of the quarter they track. The Chicago Board of Exchange (CBOE) dividend futures contract uses a "top-down" approach, where the price of the contract is set by futures trading activity (if you access their data, the reported value is ten times the expected cash dividends per share for the quarter, so be prepared to shift the decimal point accordingly).

Meanwhile, IndexArb uses a "bottom-up" approach, which takes expected dividend per share data from each of the S&P 500's component companies and weights them according to their market capitalization within the index to create its expected cash dividend per share value. IndexArb also complicates its reporting for future quarters as the information it provides really indicates the total amount of estimated dividends per share for the index that will be paid out between the present (today) and the end of the dividends futures contracts upon which they're based.

That means that to find the expected amount of dividends per share that will be paid out in a given quarter, you have to take the total amount of dividends per share that will be paid out by the end of that quarter and subtract the total amount of dividends per share that will be paid out by the end of the preceding quarter. So, if we want to do find the value for 2013-Q3, we have to subtract the dividends per share that would be paid out by 2013-Q2 from it!

That creates some problems, which you can see in the chart above. Here, the data for 2013-Q3 from IndexArb effectively flatlines at the expiration of the dividend futures contract for 2013-Q2 on the third Friday of June 2013 (21 June 2013), because the futures data for the preceding quarter is no longer available for us to do that subtraction operation.

We can also see differences in how the values start and change over time. Here, the CBOE's dividend futures data starts and a higher value than IndexArb's, but is subject to greater volatility, which you would expect given how its value is set.

The IndexArb data is less volatile, and although it begins at a lower value, we can see that it converges toward the values that the CBOE projects, at least through the end of the preceding quarter's data. Based on the trend we observe in the data before that time, we think that the two would converge very close to each other by the actual expiration of the dividend futures contracts on 20 September 2013.

Meanwhile, both of the expected dividend values for both sources fell short of the actual level of cash dividends per share of $8.909 that S&P reported for 2013-Q3 after the end of the calendar quarter on 30 September 2013.

We think the primary source of the discrepancy between the dividend futures and the actual value for cash dividends per share can be traced to the estimate of each S&P 500 component company's weighting within the index. S&P is the final arbiter of those values, while estimates used by others are just that - estimates. We should also note that there is also a bit of mismatch between the terms of the dividend futures contracts and the dividends that are paid out by the ends of the calendar quarters that S&P reports, which may also account for a good portion of the discrepancy between the futures and the actual data once it is reported.

Given our experience in tracking the data, what we find to be really remarkable that the dividend futures data is typically within a 3% margin of S&P's officially recorded value (that's true even of the three-month earlier cutoff for IndexArb in the absence of a real market-shaking event), and often, is within a much closer margin of error than that.

Speaking of which, since the CBOE data stays "live" longer than the IndexArb data, our next update of our favorite chart will be based solely on the CBOE's data, which we're going to unveil tomorrow. We were going to wait to do that development until our annual end of year hiatus, but it turned out to be a snap to do, and there's some really interesting insights that come out of it!

Image Credit: Schweitz Finance.

Data Sources

EODData. Implied Forward Dividends September (DVST). [Online Database]. Accessed 7 October 2013.

IndexArb. Dividend Analysis. [Online Data Report]. Accessed daily from 3 January 2013 through 21 June 2013.

Standard and Poor. S&P 500 Index Earnings and Estimates. [Excel Spreadsheet]. Accessed 7 October 2013.

Penguin Slapping

First, a right-thinking penguin describes their motive for slapping others:

Hippies, of course, being the among the groups of people who who are just a little too pleased with themselves. Speaking of which, penguins putting the slapdown on others would appear to be something that actually happens in nature:

Cultural evolution in action!

How Much Would a Federal Default Affect the U.S. Economy?

Since the single topic of the press conference that President Obama staged with his party's media collaborators on Tuesday, 8 October 2013 revolved around the topic of what could happen if the U.S. government chooses to default on its debt obligations, or as will more likely be the case, doesn't default on those obligations and instead doesn't spend as much as U.S. politicians would like it to spend, we thought we would go straight to the bottom line and find out how much the U.S. economy would be affected.

But first, we'll need some numbers, which CNBC tracked down for us:

Treasury Secretary Jack Lew is about to face the very same choices confronted by any financially struggling American household: Which bills to pay and when to pay them.

If Congress fails to raise the debt ceiling by around Oct. 17, Lew, who has been in the job less than a year, will have to sit at his desk and figure out how to make due on roughly one-third less in the way of government funds for the bills he has to pay. Because he can no longer borrow, according to the Bipartisan Policy Center, government spending will fall by about 32 percent, or $108 billion in the first month.

On a side note, to put that situation in context, this is no different from what could very well happen just 20 years from now when Social Security's trust fund has been fully depleted, as expected. At that time, the federal government will reduce all payments to Social Security beneficiaries by roughly 26%, unless it significantly increases the amount it borrows. And that's if everything goes as U.S. politicians have promised without any spending reform - this is one reason why the political fight over the debt ceiling and government spending levels is taking place now, because waiting will make needed reforms so much more painful. Not to mention, more necessary.

Back now to the question at hand: how much would a government spending cut of that magnitude affect GDP?

The good news is that we can answer that question with just back-of-the-envelope math! And we can do it on a "daily" basis.

That $108 billion reduction in federal government spending works out to be $3.6 billion per day. We know that the GDP multiplier for all government spending in the U.S. is 0.6, which we know from research published by the U.S. Federal Reserve applies when the nation's official unemployment rate is over 7.5%. Which is the case at present, thanks to the furloughing of federal government employees! If it were under 7.5%, we would need to use a GDP multiplier of 0.5 to account for the shock of a sudden change in government spending, as government spending is considered to deliver even less of an impact to GDP when the economy is in a healthier state.

Taking our potential government spending reduction of $3.6 billion per day, and multiplying it by our GDP multiplier for government spending of 0.6, we find that the U.S. economy will lose out the equivalent of $2.16 billion worth of GDP per each day that Uncle Sam doesn't have his credit limit reset to a higher level.

Now, to measure the impact upon GDP, just multiply that number by the number of days the U.S. federal government operates in that situation!

If played out through the remaining 78 days of 2013, assuming we stick with President Obama's planned schedule for putting the U.S. federal government into default, that would reduce the nation's GDP for the fourth quarter of 2013 by $168.48 billion.

To put that number into perspective, the fiscal drag produced by the $56.3 billion by which U.S. federal taxes will be higher in the fourth quarter of 2013 than they were in the fourth quarter of 2012 thanks to President Obama's tax hikes that took effect back in January 2013, GDP in the U.S. will be nearly $168.92 billion smaller in 2013-Q4 than it would otherwise have been given the GDP multiplier for taxes.

Why, that's almost exactly the same amount! Perhaps that explains why President Obama has been so intent on doubling down on his "no negotiation with the duly elected representatives of American citizens" strategy - he'll produce twice the negative fiscal drag on the U.S. economy in 2013-Q4 if only he and his supporters can stick with it!

And yes, numbers like those mean a recession, as the Federal Reserve's quantitative easing programs won't produce enough juice for the economy to offset that kind of fiscal drag, offsetting only somewhere between $250 billion and $290 billion of the hit if the debt ceiling isn't increased by 31 December 2013.

Of course, if the debt ceiling situation is resolved sooner than than, it is very much possible that the U.S. will have positive economic growth in 2013-Q4 - only seeing slower growth than it would have had instead. Which is pretty much the story for every quarter during President Obama's entire tenure in office.

The Sebelius Solution

On Monday, 7 October 2013, U.S. Secretary of Health and Human Services and Obama administration cabinet member endorsed the idea of Americans skipping out on buying health insurance in 2014 in favor of paying the "penalty" tax instead in an interview with the nation's most-trusted news anchor, Jon Stewart:

Real Clear Politics describes the interview:

Secretary of Health and Human Services Kathleen Sebelius defended Obamacare in a very contentious interview with Daily Show host Jon Stewart on Monday night.

Stewart pressed Sebelius on why businesses get a one-year delay on Obamacare but individuals do not. After several attempts for an answer, Sebelius eventually said individuals could delay Obamacare for a year -- by paying the penalty.

JON STEWART: So this is what some would consider the first mall that's been created [for purchasing health care insurance].

KATHLEEN SEBELIUS: You bet. The first -- new rules for companies.

STEWART: So why is it that individuals, though, couldn't say that they didn't want to do it just for a year, like business?

SEBELIUS: Well, they can.

STEWART: Oh, they --

SEBELIUS: They'd pay a fine. They'd pay a fine at the end of the year, but they don't have to -- I mean, they can say I didn't want to do it. The theory is they can't pick and choose if they're going to get hit by a bus or diagnosed with a illness. For a lot of young folks, there is one fall on the basketball court, one auto accident from a lifetime of hospital bills they can't pay.

Now, unlike the nation's politically-connected businesses, who won't have to pay the penalty tax they otherwise would have to pay thanks to President Obama's arbitrary choice to disregard the legal provisions of the Patient Protection and Affordable Care Act for one year on their behalf, the Obama administration wants individual Americans to choose between paying hundreds, if not thousands for health insurance, or lose the subsidy tax credit for buying health insurance when they file their income taxes, which would mean a slightly higher income tax bill.

But, maybe that's something that's worth doing. It all depends on how much extra taxes you would have to pay if you chose to delay your personal implementation of the Obamacare law compared to how much you would have to pay for health insurance coverage. Fortunately for you, we have an app to help you decide if you should pursue the Sebelius solution!

You'll need to go to the government's health insurance marketplace portal to track down the relevant data that you'll need to enter in the tool below, which is needed to either determine how much your health insurance subsidy tax credit would be or your tax (good luck with that!), or you can take advantage of the plan premium data for 34 states that Hugh Chou extracted from that site while it actually worked during a brief portion of its existence.

Your Household Data
Input Data	Values
Your Total Household Income, or Modified Adjusted Gross Income (If Known)
Number of Household Members
Number of Children in Household
Your State's Health Insurance Exchange Data
Select Your State (Select "United States" If Your Territory Isn't Listed)	United States Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming District of Columbia
Monthly Premium for the Second Lowest-Cost "Silver" Plan Available To You
Monthly Premium for the Lowest-Cost "Bronze" Plan Available To You
Monthly Premium for the Health Insurance Plan You're Considering Purchasing

Your Annual Health Insurance Results
Calculated Results	Values
Annual Premium (Full Price) of the Health Insurance Plan You're Considering Purchasing
Annual Subsidy Tax Credit You'll Receive For Buying This Health Insurance
Your Annual Out-of-Pocket Costs
For Health Insurance (Premium Only, No Co-Pays or Deductibles)
For the Alternative Tax If You Don't Purchase Health Insurance (And Not Provided by Your Employer)
Potential Savings or Costs If You Choose to Pay the Tax Instead of the Premium
Your Potential Savings (or Costs, if Negative)
The Bottom Line

The default data in our tool above is designed to consider the case of a single mother who is a part-time Trader Joe's employee in California, and who is being forced out of their equivalent "Gold"-level employer-provided plan into a more "affordable", but lower quality "Silver"-level plan through Obamacare.

Oh, and while we're at it, the table below shows the odds of either a man or woman of the indicated ages requiring the kind of hospital care that Kathleen Sebelius described in her interview with Stewart:

Chance of Going to Hospital
Age Group	Female	Male
Less than 1	1 in 3	1 in 2
1 - 10	1 in 10	1 in 8
10 - 20	1 in 9	1 in 10
20 - 30	1 in 4	1 in 8
30 - 40	1 in 3	1 in 6
40 - 50	1 in 4	1 in 4
50 - 60	1 in 3	1 in 3
60 - 70	1 in 2	1 in 2
70 and Older	4 in 5 (1 in 1.25)	4 in 5 (1 in 1.25)

In case you're wondering why the odds of a woman being admitted to a hospital is double that for a man between the ages of 20 and 40, it largely has to do with a medical condition called "pregnancy", which is something that most people can very easily plan around. Speaking of which, if one plans their due date properly, they could hold out until the next enrollment period to get covered, paying the tax instead, if much cheaper, until their new coverage kicks in to cover the medical expenses associated with having a child. Then perhaps dropping it again after their and their child's odds of needing medical care drops to much lower levels.

Let's call that the family plan version of the Sebelius Solution!

But then, what if getting low income people to accept their income tax increase is the whole point of Obamacare? In that light, since it would cost the federal government more in subsidies to actually support people buying health insurance through its exchanges, and since it stands to gain higher tax revenue if it can get them to choose not to, or as it is working out, because they can't because the exchanges are dysfunctional (perhaps because they were never intended to work), it would make sense for the tax hungry members of the Obama administration to push this very reasonable alternative....

The Noisy Irritant Strikes Again!

Take a look at the following chart, a snapshot of the trading activity on 8 October 2013 through 2:02 PM EDT:

Now, looking at that chart, we can identify 10:46 AM EDT as the approximate point in time, give or take a minute, at which the investors suddenly reacted negatively to some event. Since it typically takes investors just two to four minutes to react to an event they weren't expecting, that actually market the end of the period of time in which we would need to look for a market moving event. Want to guess what major market moving news hit the wires within that window of time?

We won't keep you in suspense. The noisy irritant in the White House is behaving as we expected. USA Today's David Jackson reports:

President Obama called House Speaker John Boehner on Tuesday, again telling the Ohio Republican he will not negotiate on budget items until the GOP-run House ends the shutdown and raises the debt ceiling.

Obama also scheduled a White House statement on the budget shutdown for 2 p.m.; he will also take questions from reporters.

"The president is willing to negotiate with Republicans -- after the threat of government shutdown and default have been removed -- over policies that Republicans think would strengthen the country," said a White House readout of the 10:45 a.m. phone call to the House speaker.

The readout noted that Obama "repeated what he told (Boehner) when they met at the White House last week."

Boehner spokesman Brendan Buck confirmed the conversation, saying that "the president called the speaker again today to reiterate that he won't negotiate on a government funding bill or debt limit increase."

Now, that's what we would describe as a presidential-class tantrum, especially because the President had to go out of his way to deliver it.

A Microrecession Dead Cat Bounce?

We may have been too optimistic last month in noting the end of a year-long period of microrecession in the U.S. economy.

Here, we've been tracking the number of public U.S. companies that have been announcing decreases in their dividends each month. August 2013 had seen the number of U.S. companies acting to cut their dividends drop below the key level of 10 per month, which we've previously observed marks the boundary between a growing U.S. economy and a U.S. economy that is experiencing recessionary conditions.

The data for September 2013 is now out, and the early suggestion is that the U.S. economy is not yet out of the woods.

As we ask in the chart, is this a proverbial dead cat bounce (a one-time event as the number of companies acting to cut their dividends bounces back into recessionary territory) or is the U.S. economy experiencing the same kind of recessionary conditions that characterized the entire year from July 2012 through July 2013?

There are two things of which we can be sure. Neither the impact of the partial U.S. government shutdown, which didn't even begin until 1 October 2013, nor the potential impact of a U.S. Treasury default on the U.S. national debt that President Obama has planned for 17 October 2013 are responsible for this outcome.

Instead, since the number of public U.S. companies announcing dividend cuts each month is perhaps the single best indicator of the real-time health of the private sector of the U.S. economy, what the data for September 2013 really suggests is that the U.S. economy is quite not as strong as the previous data indicated.

And that could be a more significant factor in driving today's stock prices than the increasing level of political noise emanating from Washington D.C.

Image Credit: InvestmentPaths.com.

Nice Market You Have There. Shame If Something Should Happen To It.

We're not going to update our favorite chart this week, as we're still busy modifying it to cover the activity we anticipate into 2014. So instead, we thought we'd analyze the biggest market action, or non-action as the case really was, from last week!

Our story all begins with President Obama's interview with CNBC at market close on Wednesday, 2 October 2013 (transcript available):

By the next morning, the market had reacted in such a way to the President's comments that CNBC was compelled to report how investors were interpreting them, which is reflected in our original headline for this post. CNBC's Finance Editor Jeff Cox writes in Wall Street wonders if Obama wants a selloff:

In an exclusive interview with CNBC, the president warned Wall Street that this shutdown could be different. Previous halts in nonessential government activities have caused little market reaction, with major averages actually rising most of the time in the month after the shutdowns are settled.

Obama's remarks indicated to some observers that he is trying to push investors out of the relative complacency they have shown so far. Futures were broadly lower Thursday, indicating markets may be taking heed.

"They feel that a severe market selloff would be helpful to break the logjam," said Greg Valliere, chief political strategist at Potomac Research Group in Washington. "It would be helpful in making the Republicans sue for peace. Obama and [Senate minority leader] Harry Reid believe that."

If President Obama was looking to trigger a selloff for Thursday, he succeeded. The chart below shows the trajectory of the S&P 500 from Monday, 30 September 2013 through Friday, 4 October 2013. Note the movement on Thursday, 3 October 2013:

In the first hour after opening, the S&P 500 index fell 10 points in the first hour before stabilizing, holding at a level of about 1678 until 11:26 AM EDT. That was the point in time at which the news broke that Christine Lagarde, the head of the International Monetary Fund, who shares political connections with President Obama in Chicago, was warning of the potential impact that a debt default by the Obama administration would have on the world economy (the linked article was originally posted at 11:26 AM EDT).

That news was sufficient to take the S&P to its low of 1671 for the day, hitting bottom just after noon had keeping near that level until 12:26 PM EDT.

What happened next was perhaps the most remarkable event of the day. At 12:19 PM EDT, he New York Times reported that the Speaker of the U.S. House of Representatives, John Boehner, had told colleagues that he was "determined to avoid a federal default and is willing to pass a measure through a combination of Republican and Democratic votes", which investors apparently took several minutes to absorb before reacting.

Their reaction was sufficient to wipe out the effect of IMF head Christine Lagarde's comments, and the market bounced back up to the 1680 level before trading in a narrow range between 1678 and 1682 for the rest of the day, closing at the low end of that range. By the end of trading on Friday, 4 October 2013, the market had wiped out the negative impact of President Obama's threatened default altogether, as it recovered to its pre-Obama threatening warning level.

What we find interesting in all this is that there was so little effect on the market from the noise contributed by each of these political actors. The current President of the United States of America, Barack Obama, in seeking to create a market selloff to exploit for his own political advantage, couldn't huff and puff enough to make the S&P 500 blow down by much more than 10 points. Meanwhile, the comments of the head of he International Monetary Fund, Christine Lagarde, who owes her position to President Obama's patronage, only succeeded in pushing it down another seven points.

By contrast, the Speaker of the House of Representatives John Boehner's comments reassured the markets enough to recover by anywhere from 7 to 12 points. Put another way, his calming influence cancelled out the negative influence of head of the IMF and, for good portion of that Thursday afternoon, periodically exceeded the negative influence of the President in terms of total point movement.

Perhaps things will change and President Obama's negative influence will grow as we get closer to the President's planned default date. For now though, it's pretty plain that the market isn't reacting the way that President Obama wants, as the market's action on Thursday, 3 October 2013 indicates that it largely views him as a noisy irritant. That's not something that the President can long afford to continue if he wants avoid an early lame duck status, so we think it's likely that he'll instead increase his level of apparent irrationality in refusing to compromise on implementing his increasingly-troubled "affordable" health insurance initiative and his desire to sustain excessive levels of government spending.

Consequently, we expect the political noise affecting the markets to continue and grow louder. We're pretty sure that the markets would really rather get back to real business and not have to continue paying attention to irrational and ineffective executive leadership in Washington D.C. But then, that's the kind of leadership that emanates from the nation's capitol these days.

How To Brush Your Teeth in 6 Seconds

Invention often involves solving problems that many people might not think are problems until they see what a free-market developed solution for it might be.

A great example of that is flavored toothpaste. In the old Soviet Union, with its centralized economic planning, there was only one flavor of toothpaste, as the communists who ran the country saw no need for the government's toothpaste factories to produce any more than one flavor of toothpaste, viewing the idea of having more than one flavor as being extremely wasteful. That view is shared by many of today's college campus Marxists and many of Washington D.C.'s bureaucrats and elected officials who believe "one size fits all":

In the workshop "The Meaning of Marxism," Socialist Worker journalist Eric Ruder explained basic Marxist theory to a filled classroom.

He addressed the conundrum that most people today seem relatively well-off under capitalism.

"We're so much more productive as a society, literally thousands of times more so, except we let huge proportions [of people] actually die of starvation and material want, for no particular reason," he said. "It's a social problem, not one of material wealth."

Towards the end of the lecture, Ruder used toothpaste as an example of capitalism's inefficiencies.

"If you no longer have one section competing against another, you start to eliminate all kinds of waste," he said, referencing toothpaste brands Colgate and Crest.

Ruder then described the "wastefulness" of toothpaste's price: "About 90% of the price you pay for toothpaste goes into packaging, advertising, and profit, and 10% is the actual contents of the toothpaste."

"If you look into our economy as a whole, there is waste of that sort everywhere that you look," he said.

That's exactly the kind of progressive thinking they had in the Soviet Union, which they put into real world action. The Soviet Union's central economic planners made sure that just one kind of toothpaste would be manufactured waste-free in their government-owned toothpaste factories, which would all be done without profit.

The results were about what anybody with any real common sense would think. There were massive and chronic shortages of toothpaste, because there was no incentive for the government's toothpaste makers to produce enough toothpaste to meet their captive peoples' needs for it. As a result, their teeth suffered mightily.

And then it got even worse, because when don't have to ever improve a product or develop a new one to try to win consumers to earn a profit and continue doing business in a competitive market, you don't develop new and better technologies to meet the needs of the people whose needs you claim to satisfy, but aren't satisfying because you view the kind of marketing research and development it takes to do that as wasteful activity. Here's what that meant in the one-party-fits-all communist dictatorship:

Toothpaste meant whatever was available. Toothbrushes had hard bristles that cut the gums, sometimes doing more harm than good. Dental technologies were years behind those of the West; the 17-year-old who was crowned Miss USSR in 1990 flew to Philadelphia the same year to have the gap in her teeth closed and a few cavities filled.

Now, imagine yourself in that environment. Suppose that when you had the one glorious socialist toothpaste, you didn't like how it tasted, as you ripped your gums while brushing. How much incentive would you have to continue brushing your teeth?

As a result, in striving to prevent "wasteful" activity, the "know-it-alls" of the Soviet Union created an even worse level of waste. One measured by wasted teeth and health and lives. If only the Soviet socialists really cared more about people, but then, their answer to that was that the people wouldn't have to pay to go to the dentist to fix their teeth. Guess what else was in very short supply in the old Soviet Union, where the incentive to provide good dental health care just wasn't there....

Like the Soviet Union's central planners, today's progressives miss the fundamental lesson about toothpaste - it only works to fight the worse waste of tooth decay and other oral diseases when it's used. Having more than one flavor to choose from many means it's more likely that you'll find a toothpaste you are willing to use often. And for the trivial cost associated with the packaging of toothpaste to differentiate it from others so consumers can identify it on store shelves, consumers can have as much of the kind of toothpaste they want to have thanks to the incentive of profit for its producers and the marketing and advertising they did to help you to find the toothpaste solution that worked best for you.

And that brings us to what we really wanted to share with you today. Imagine a new kind of toothbrush that's so individualized for you that you can brush your teeth with it in just six seconds. It's called the "Blizzadent" (HT: Core77, who also provides a neat visual history of the technology of toothbrushes):

You can read more about how it works here, but basically, they take a 3-D scan of your teeth from your dentist to custom build a unique toothbrush for you, which optimizes the toothbrushing process by brushing all your teeth, and your gums, at the same time, using the optimal techniques for doing so - providing far better oral hygiene than you might ever be able to achieve using a regular toothbrush. You put some liquid toothpaste (oh no, another kind!) on your tongue to coat your upper teeth, then put Blizzadent toothbrush it in your mouth, then bite and grind your teeth on it 10-15 times, rinse it out, and you're done, having perhaps done the best job in brushing your teeth that you ever hope to do (at least, until a new invention comes along), all in about six seconds. What's more, Blizzadent claims their toothbrush can last an entire year.

We'll let you be the judge if it's worth the asking price, which you'll have to balance against the cost of regular toothbrushes, dental floss and potential dentistry expenses that you might now be able to avoid because you're using a tool that does a better job in promoting your dental health.

It's exactly the sort of capitalist-invented device that today's progressives and Marxists would view as wasteful. But then, they've already proven they don't really care about you, much less the condition of your health, so why should you listen to them or do what they tell you to do?

Is the Second U.S. Housing Bubble Beginning to Peak?

Has the inflation phase of the second U.S. housing bubble begun to peak?

The latest data from the U.S. Census Bureau for median new home sale prices (Excel spreadsheet) is suggesting that may indeed be the case. Here, we observe a deceleration in the rate at which median new home sale prices have been escalating, which appears to have begun after May 2013:

The chart above spans the period of time covering the inflation phase of the second U.S. housing bubble, which began after July 2012 and continues through the present. In the chart, we observe that the trailing twelve month average of median new home sale prices, which we calculate to minimize the effect of seasonality in the U.S. real estate market, was growing at a linear rate in the months from July 2012 through May 2013. After that month however, the growth rate of median housing prices has begun to decelerate, which we observe in the increasing deviation of newer median home sale prices from their previous trend.

What could have caused such a change in trajectory after May 2013?

Keeping in mind that it takes three factors to ignite a housing bubble: fuel, oxidizer and a spark (these links will take you to our three part series on the origin of the first U.S. housing bubble), we find that what changed after May 2013 is the bubble's fuel supply - interest rates!

Here, talk of the Fed's potential tapering of its current quantitative easing programs prompted a surge in the 10-Year U.S. Treasury, which given the well-established connection between the two, has prompted a surge in U.S. mortgage rates. Using data from the Fed, the first chart (on the left) below shows how they've changed during the period of the second housing bubble (July 2012 through August 2013), while the second chart (on the right) shows how they've changed since the so-called "Great Recession" ended in June 2009:

The relatively sudden escalation of U.S. interest rates is having the effect of starving a fire of fuel - it is putting the brakes on what had been the rapid rise of U.S. home prices, as it appears that the second U.S. housing bubble is now beginning to peak.

What that outcome indicates is that the Fed's policy with respect to interest rates can indeed affect whether or not the U.S. housing market can experience the conditions of an economic bubble. Far from being the result of factors far beyond its control, we find that a sustained housing bubble can only exist if the Fed desires one to exist, as it clearly has the ability to influence the pace at which it might inflate through its ability to influence U.S. interest rates.

That's not to say that the Federal Reserve can arbitrarily create such a bubble, as there are other factors that will determine if one can form in the first place, but the Fed most certainly has the ability to affect how long a bubble that has begun to inflate might be sustained through policies that push interest rates below their "natural" levels.

Let's next update our chart showing how median new home sale prices in the U.S. have changed since December 2000 with respect to median household incomes in the U.S.:

Pay close attention to the inflation phase of the first U.S. housing bubble in the chart above. It didn't begin to decelerate until September 2005, which is when the Fed finally had increased interest rates to approximately where they would be set by a Taylor Rule according to contemporary information available to the Fed, which might be considered to represent their natural, market-based level. That was the point at which the Fed began to effectively reduce the amount of fuel that it was feeding that particular fire.

The same phenomenon would appear to be happening again today. Only now, instead of exercising direct control over interest rates, the Federal Reserve is exercising a more indirect influence through its quantitative easing programs, through its purchases of $45 billion per month in U.S. Treasuries and a little more directly through the QE program where it has been buying an average of $40 billion of agency-issued Mortgage Backed Securities (MBS), which it has been operating since September 2012.

That would be the point in time at which the Fed acted to push the interest rates that directly impact mortgages below the level that the market might otherwise have set them, succeeding in doing so through May 2013. We can see that influence in the U-shaped trajectory that U.S. mortgage rates followed after September 2012 up through May 2013. In the absence of the Fed's quantitative easing program, the trajectory of mortgage rates would have more closely followed a V-shaped pattern, corresponding to actual market conditions where real estate prices were rapidly escalating during this period of time.

In June 2013, the markets reacted to the unexpected news that the Fed might begin cutting back on its QE programs sooner than previously expected by putting both Treasury yields and mortgage rates much closer to where they would otherwise set them, as if the Fed already had taken that action. This is why U.S. mortgage rates shot upward so quickly.

Though not quite as the Fed might have planned, the impact of that sharp increase in mortgage rates upon the trajectory of median new home sale prices in the U.S. demonstrates that the Fed would have the ability to control the duration of an economic bubble if it chose to do so. We conclude then that like the first U.S. housing bubble, the second U.S. housing bubble is a desired outcome for the Fed in setting its monetary policies.

Given how things are playing out so far, it would seem then that economic history has a way of repeating itself, only faster and less impressively where the second U.S. housing bubble is concerned.

Elsewhere on the Interwebs

Yale's Robert Shiller, who is to modern financial theory today as Tycho Brahe was to the science of astronomy in the 1500s, is just now becoming concerned that the U.S. housing market may be entering into an economic bubble.

Meanwhile, Jason Zweig picks up on a similar behavioral finance-related "animal spirits" vibe in trying to explain that what we'll call "herd instincts" are responsible for why economic bubbles form.

Sigh. Such are the leading intellectual lights of this age. Stone knives and bearskins, indeed.

References

Federal Reserve Bank of St. Louis. Economic Data. 30-Year Conventional Mortgage Rate (MORTG). [Online Database]. Accessed 30 September 2013.

Sentier Research. Household Income Trends: July 2013. [PDF Document]. Accessed 26 September 2013. [Readers should note that we have converted all older inflation-adjusted values presented in this source to be in terms of their original, nominal values (a.k.a. "current U.S. dollars") for use in our charts, which means that we have a true apples-to-apples basis for pairing this data with the median new home sale price data reported by the U.S. Census Bureau.]

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 26 September 2013.

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!