Political Calculations
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January 31, 2013
Political Calculations One-Quarter and Two-Quarter GDP Growth Rate Temperature Gauges, 2012-Q4 First Estimate

Previously, we took the under in forecasting where the United States' GDP would be recorded in the fourth quarter of 2012, forecasting that the nation's real GDP would be recorded below our mid-range projection of $13,726.5 billion in terms of constant 2005 U.S. dollars.

Taking the under turned out to have been the right call for us to make, as the first estimate for inflation-adjusted GDP came in at $13,647.6 billion in terms of the BEA's chained 2005 U.S. dollars, a difference of roughly 0.6% from the value we have projected will be recorded when the BEA finalizes its estimate of GDP for 2012Q4 at the end of March 2013.

We had given 68.2% odds that 2012-Q4's real GDP would fall between $13,583.8 billion and $13,869.2 billion, as the U.S. economy would appear to be continuing to skirt the edge of what we would describe as a microrecession. That condition becomes more apparent as we consider our two-quarter GDP growth rate temperature gauge, where the growth rate for 2012-Q4 falls just into the "cold" purple zone.

Since we base our GDP forecasts on the two-quarter growth rate of GDP, our forecast was largely immune to the large swings in the U.S. federal government's spending for defense that took place in the second half of 2012, where planned spending had been pulled ahead into the third quarter of 2012 to offset potential cuts in this spending as part of the so-called "fiscal cliff" at the end of 2012 and also to provide a boost to the U.S. economy ahead of the national elections on 6 November 2012. Defense-related spending was then sharply reduced in the fourth quarter of 2012, accounting for much of the lackluster GDP growth rate reported in the quarter.

The other major economic event of the quarter, Hurricane Sandy, would appear to have had a negative, but very small effect upon GDP in the fourth quarter of 2012.

Looking forward, using the first estimate of GDP for 2012-Q4, our "modified limo" forecasting technique anticipates that real GDP in the first quarter of 2013 will come in around $13,697.6 billion in terms of constant 2005 U.S. dollars. A positive move, so that's the upside of the under.

Real GDP vs Climbing Limo Forecast vs Modified Limo Forecast, 2004 - 2012-Q4 First Estimate, with Projections to 2013-Q1 and 2013-Q3

We will update our projections as the BEA adjusts its estimates of GDP for the fourth quarter of 2012. At present, we would expect the BEA's estimate of real GDP for 2012-Q4 to be revised slightly upward by the time of their third revision at the end of March 2013.

Elsewhere on the Web

Jim Hamilton offers his analysis of the fourth quarter's GDP figures and points to other viewpoints.

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January 30, 2013

We didn't know this until yesterday, but apparently, our "What's Your Income Percentile?" tool is the second most highly ranked result on Google if you search for "household wealth percentile". Which we found out only because someone who works for the Federal Reserve Board came to our site after performing that exact search on Monday, 28 January 2012!

Well, that's not good enough, is it? We want to own the #1 result for that particular Google search and we're going to get it by building a tool that you can use to see how your household's net worth ranks among all U.S. households!

But first, we'll need to you to determine your household's net worth, for which we'll point you to Bankrate.com's Net Worth Calculator.

Once you have it, enter your household net worth into our tool below, and we'll estimate your percentile ranking among all Americans (as recorded by the U.S. Census in 2010!) [If you're among those Americans who owe far more on your loans than you have assets or who are still underwater on your mortgage and have a negative net worth as a result, enter your net worth as a negative value - just like the default value!]

Household Net Worth Data
Input Data Values
Your Household Net Worth

Your Household's Net Worth Percentile Ranking
Calculated Results Values
Your Household Net Worth Percentile

And now you know just what percentage of U.S. households have a net worth that is equal to or lower than yours! Our chart below shows our model for the distribution of net worth in the United States and how it compares to the data recorded by the U.S. Census.

U.S. Distribution of Net Worth, 2010

That dot in the upper right hand corner? That's the highest net worth we could find for an American, which according to Bloomberg, turns out to be Bill Gates, who had a net worth of over $64.4 billion on Monday, 28 January 2013.

Data Source

U.S. Census Bureau. Net Worth and Asset Ownership of Households: 2010. [Excel Spreadsheet]. Accessed 28 January 2013.

Update 9 March 2013: Retitled from "The Distribution of Net Worth in the United States".

Update 11 November 2013: If you enter a value of 0 for the net income, the tool above will return a percentile ranking of 100%. This is an artifact of the math, where we calculate the natural logarithm of the net worth you enter. Unfortunately for us, the logarithm of zero is undefined, which is why this result occurs (it's similar to the situation that exists when you attempt divide a value by zero.)

To work around that issue, you can borrow a technique from the field of numerical analysis - enter values that are close to, but not equal to zero, such as 1 and -1, then take the average of these results to represent the percentile for zero household net worth.

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January 29, 2013

Building on our previous data visualization exercise, we've now gone the extra mile and built a tool you can use to estimate what your percentile income ranking is for your age group!

U.S. Distribution of Income by Age Group, 2012

Just enter your data in our tool below, and we'll do the math, which is based on the age-based distribution of income in the United States for 2012 as reported by the U.S. Census Bureau.

Age and Income Data
Input Data Values
Select Your Age Group
Enter Your Total Money Income

Where You Rank Among Your Age Group
Calculated Results Values
Your Income Percentile Ranking Within Your Age Group

Some quick notes - the data from which we built this tool doesn't provide a lot of detail at either the lowest end of the income spectrum or at the highest end. As a result, if your entered income places you below the 5th percentile or above the 95th percentile for your age group, we can only tell you that you fall into that percentile range as our tool's accuracy appears to break down below and above those levels.

We're also experimenting with how to incorporate the code behind our tool directly in this post. If you find the tool doesn't work when you first try to access it on our site, please check back later - we'll have it up and running as soon as our time allows.


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January 28, 2013

Today, we're going to summarize the major trends of the last 22 years in the U.S. stock market as represented by the S&P 500 in a single chart as we introduce some of our analytical methods to our new readers.

To get up to speed with the information we're presenting, you should be aware that we've demonstrated over the last several years that the stock market typically operates in one of two states, which we've characterized in our most ground-breaking analysis as being either in a state of order or in a state of chaos.

During periods of order, both stock prices and their underlying dividends per share are closely coupled with each other, so much so that the variation in stock prices about a major trend defined by the same kind of simple power law that shows up all over nature, and which we've found can be described by the math of normal statistical distributions. During periods of chaos however, stock prices and dividends per share become decoupled from one another as a different kind of order takes hold as stock prices explode into Lévy flight, for which we've developed a different kind of math to describe and anticipate.

With that background now in place, here's our chart showing how the S&P 500 has swung from order into chaos and back again since December 1991:

S&P 500 Average Monthly Index Value vs Trailing Year Dividends per Share, December 1991 to January 2013 (as of 25 January 2013)

What makes this chart different from the one we last presented in September 2012 is that we've gone into greater detail in identifying the major influences that have dominated the U.S. stock market since the last major period of order ended in December 2007.

Here's our quick guide to each of the major periods of either order or chaos in the U.S. stock market since December 1991:

Order: December 1991 to April 1997 (Post Gulf-War Peace)

Following the disruptive event of the Gulf War, stock prices were closely coupled with dividends per share in the period through much of the 1990s, ending in April 1997.

Chaos: April 1997 to June 2003 (The "Dot Com" Stock Market Bubble)

Stock prices became decoupled from their underlying dividends per share when the U.S. government suddenly opened up the gap in the tax rates that applied to dividends and capital gains at the end of April 1997. With the tax rate on capital gains suddenly so much lower than it had been, an imbalance favoring non-dividend paying stocks exploded in what became known as the "Dot Com" stock market bubble, after the early Internet-related companies whose stocks benefited from the change in the nation's tax laws.

The inflation phase of the bubble continued until the bubble peaked and popped in August 2000, sending the nation's economy into recession as stock prices plummeted. The deflation phase of the bubble then continued until June 2003.

Order: June 2003 to December 2007 (The Bush Tax Reform)

On 28 May 2003, President George W. Bush signed the Jobs and Growth Tax Relief Reconciliation Act of 2003 into law, setting the same single tax rate for both dividends and capital gains and ending the imbalance between the two. Order quickly resumed as stock prices and dividends per share once again became closely coupled with one another.

Chaos: December 2007 to March 2009 (The 2008 Crash)

Order in the stock market came crashing to an end as stock prices began plummeting in January 2008 given a high level of distress in the U.S. banking and financial industries, which erupted into an extremely deep crash as the U.S. automotive industry saw the failure of both General Motors and Chrysler after August 2008 thanks to a very large spike in oil and gas prices that killed demand for these companies' gas-guzzling product lines. Stock prices ultimately bottomed on 6 March 2009 as China outlined how it would implement a massive economic stimulus program that would boost the entire world economy.

Chaos: March 2009 to April 2010 (Post Crash Recovery and QE 1.0)

With the bottom now in place, U.S. stock prices began to respond positively to a change of outlook for U.S. companies as the rate of descent for their expected future dividends began to slow and reverse.

The Federal Reserve also implemented its first quantitative easing program (QE 1.0) in March 2009, however it didn't have much impact in affecting stock prices until after February 2010, as it generated a rapidly inflating bubble in stock prices as trailing year dividends per share finally bottomed after the crash.

Chaos: April 2010 to August 2010 (The QE 1.0 Bubble Deflates)

As sharply as stock prices inflated with respect to dividends per share in their rapid rise after February 2010, they deflated just as quickly after QE 1.0 came to an end at the end of March 2010, with stock prices falling back to their February 2010 level by June 2010, just as order finally returned to the stock market as stock prices and dividends per share began to re-couple together.

Order: August 2010 to August 2011 (The QE 2.0 Bubble)

Although order technically returned to the stock prices after June 2010, the Federal Reserve's announcement that it would implement a new phase of quantitative easing (QE 2.0) near the end of August 2010 soon boosted stock prices with respect to where they had just stabilized with respect their dividends per share. The resulting bubble in stock prices continued for a full month after QE 2.0 ended on 30 June 2011, with stock prices finally falling back to where the equilibrium established in the new period of order would place them in the absence of an effective ongoing quantitative easing program by the Fed.

Order: August 2011 to Present (The Current Period, at least through January 2013)

Since August 2011, the relationship between stock prices and their underlying dividends per share has largely been stable, except for a brief period from December 2011 to May 2012 which was characterized by speculation with respect to the stock of Apple (NASDAQ: AAPL).

Here, a dramatic run-up in the stock began after it bottomed in mid-December 2011 on the speculation that Apple would initiate a new dividend. The stock then rose some 67% before peaking on 9 April 2012, just three weeks after Apple made its official dividend announcement. The company's stock price then quickly fell back by the end of May 2012 to where it then would follow a much less speculation-driven trajectory.

The company stock price has had an outsize effect on the valuation of the U.S. stock market during this period, as it has competed with ExxonMobil (NYSE: XOM) for being the largest company in the S&P 500 by market capitalization for much of the last year.

That brings us up to today, as the stock market is continuing its rally since mid-November 2012, where some of the rise in stock prices might be perceived to be due to the "magical" phenomenon of mean reversion. However, we've found that there are much more fundamental factors at work behind the rally using our chaos-based stock market analysis.

So there you have it - 22 years of the stock market explained in one chart. We'll close by observing that the Federal Reserve has once again initiated a new round of quantitative easing in December 2012, similar to what it did with QE 1.0 and QE 2.0, which we'll call QE 4.0, as the previously announced QE 3.0 was different in that the Fed focused solely on buying up mortgage backed securities instead of buying up U.S. Treasuries as well. At this point, it is still too early to tell if the Fed's newest round of quantitative easing will have the same impact on stock prices with respect to their dividends per share as the previous rounds appear to have had.

If it does, we'll know shortly, as the current period of order in the stock market gives us the means to determine what impact that might be with the analytical methods we've invented during the last several years.

This is a big part of what we do here at Political Calculations. Welcome to the cutting edge....

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January 24, 2013

Since 23 September 2012, the weekly data for seasonally-adjusted new jobless claims has been especially volatile.

The data reported last week, which applies for the week ending 12 January 2013, would appear to be more of the same. At least, that's what you might first think when you see where the data falls with respect to our statistical equilibrium chart of the trends in new jobless claims:

Residual Distribution for Seasonally-Adjusted Initial Unemployment Insurance Claims, 19 November 2011 - 12 January 2013

It looks just like an outlier, right? And truth be told, it definitely is. However, this outlier is not like the others, where we were able to easily identify the cause of the discrepancy with respect to the trend.

Instead, we think something positive might be at work. If it's what we think it is, the low number of initial unemployment insurance claim filings will be with us for another week, which we'll find out later this morning. The bad news is that it won't continue to be with us for much longer than that.

That positive something else is gasoline prices hitting their lows for 2012 some two to three weeks earlier, between 22 December 2012 and 29 December 2012. Here, the national average for retail motor gasoline prices dropped below $3.25 per gallon but more significantly, it dropped near and below $3.00 per gallon in large sections of the United States.

After having been elevated well above that level for the past two years, that threshold might very well mark the point where consumers believe gasoline prices are low, which in turn, might spark extra spending on their part thanks to the related boost in their discretionary income. That in turn would lead employers to retain higher levels of their employees, which would result in a lower level for new jobless claims!

This is very much the flip side to our hypothesis that there is a "high" level for gas prices in the U.S., which we've observed to kick in around a national average price at the pump of $3.50 per gallon. At this level, employers react to consumers having less of their income to spend on other things and the resulting loss to their business revenue by laying off larger numbers of their employees.

We've long noted that there is a 2 to 3 week lag between events like this occurring to when it shows up in the new jobless claims data. That's because most employers are "locked in" to their current payroll cycle - any employee retention decisions they make will take effect with their next payroll cycle. In the United States, with most employers issuing paychecks on an either weekly or biweekly basis, it then takes 2 to 3 weeks for the impact of any layoff decisions to fully show up in the data.

We say that this effect will be short lived, because the extra economic activity that might be associated with this positive factor will disappear after people begin receiving their 2013 paychecks, in which they will see a 2% reduction in their take-home thanks to the expiration of President Obama's Social Security payroll tax cut from 2011.

For a typical American household, that additional money now going to the U.S. government would be the rough equivalent of a sudden $1.40 per gallon increase in the price of motor gasoline in the United States.

The impact of that change will be progressively felt as employers change the amount of their tax withholding on behalf of the U.S. government in 2013. All paychecks should reflect the higher payroll tax by 15 February 2013 and most should see it for paychecks issued in mid-January.

Then again, the sudden dip in new jobless claims could be another data reporting problem, much like California's episode of incompetence back on 6 October 2012. Either way, we'll know what was behind the dip in new jobless claims within the next several weeks.

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January 23, 2013

We received a pretty unusual e-mail earlier this week from an individual at OnlineDegrees.net. Here is the text, which we'll present in snippets with our responses in between:

G'day,

G'day! How ya goin mate?

Not long ago, Google began reviewing websites for their past linking practices. They are looking for "over-optimized" back-links. What this means is that they are looking for links from one site to another that use the term that most users search for to find particular pieces of information. OnlineDegrees.net is one of these sites under review for bad practices.

Do tell! You've been very bad, haven't you?

While I appreciate your efforts to share our content and give credit where credit is due, I must respectfully request that you remove all links to OnlineDegrees.net from your site: politicalcalculations.blogspot.com

Let's see.... OnlineDegrees.net, OnlineDegrees.net, OnlineDegrees.net.... Doesn't ring any bells - are you sure that we've ever linked to OnlineDegrees.net?

This includes the links found on: politicalcalculations.blogspot.com/2010/04/cavalcade-of-risk-102.html

Oh, that one! Where we posted a link specifically submitted by OnlineDegrees.net to the edition of the Cavalcade of Risk blog carnival that we hosted back in April 2010.

That would be the very well-received edition of the Cavalcade of Risk where we shared your content and gave credit where credit was due by assigning OnlineDegrees.net's submission our second-lowest blog carnival contribution rating of Cc3, which is a rating that warns readers against clicking through to the contribution by describing the information at the link submitted by OnlineDegrees.net as being "Way off topic, might possibly make you stupider and also potentially painful".

We're pretty sure then that Google doesn't have a problem with how we've linked to OnlineDegrees.net. But why pursue this now, after more than two years?

We are updating our site to improve content and design, so I hope that you will return to see the information our site provides once this issue is resolved. Please send me an email, letting me know if and when you have removed our links from your site, or if you have any questions or concerns. I very much appreciate your help.

No, we can't say as that we have any questions or concerns. Your request for us to remove the link submitted by OnlineDegrees.net to the 102nd edition of the Cavalcade of Risk blog carnival that we hosted in April 2010 is denied.

And just so that the original post that earned our Cc3 blog carnival rating isn't lost as part of the update to OnlineDegrees.net's content and design, here is the Internet Wayback Machine's archived file of the content OnlineDegrees.net submitted to be included with that edition of the Cavalcade of Risk we hosted.

Thank you,

[NAME AND E-MAIL ADDRESS REDACTED]

P.S. I apologize if you received a request from us more than once. We are being assertive in our efforts to fix this.

We hope our public response works in place of the e-mail response you requested, as we've likewise chosen to be assertive in our efforts to deny your request as we stand by our editorial content.

We wish you the best of luck with your updates to OnlineDegrees.net's content and design. Although we've only ever linked to your site on just two occasions, should we ever disregard our own advice and click through the links we've posted to OnlineDegrees.net, we would certainly welcome improved content and design.

You're welcome,

Ironman at Political Calculations

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January 22, 2013

We have a project we're working on behind the scenes here at Political Calculations, where we keep having to work backward in time to figure out when an average American man or woman who has reached Age 65 in a given year was born, and then forward in time to project the year to which they can reasonably expect to live if they have the same average remaining life expectancy of a man or woman who reached Age 65 in the year that they did!

So rather than keeping doing the math, we've constructed a couple of visual aids to make it quicker to get our answers. First, we've tapped the U.S. Centers for Disease Control's data for remaining life expectancy for people who reached Age 65 in each year from 1950 through 2009:

Remaining Life Expectancy at At 65, 1950 - 2009

And then, using that data, for the birth years that correspond to the year in which the American men or women turned 65, we worked out the year to which these individuals can reasonably expect to live given the CDC's remaining life expectancy estimates, which we've presented in our second chart below.

Well, not so fast. Since that data, while useful for our purposes, would make for a pretty uninteresting chart to share with all of you, we've added some extra information to it. We've identified the range of birth years that would correspond to the legal minimum (17) and maximum (45) ages of enlistment for military service in World War 2, along with a special range that corresponds to those who would have been 26 years old during the war - the average age of U.S. servicemen in the Second World War.

Year to Which an Average U.S. Man or Woman Can Expect to Live, Provided They Have Reached Age 65 and Have Average Remaining Life Expectancy

If you look closely, those aren't straight lines in the chart above - they actually curve upward ever so slightly!

Some Cool Facts

The oldest living Congressional Medal of Honor winner from World War 2, Nicholas Oresko, just turned 96 years old on 18 January 2013, which puts his birth year of 1917 right in the middle of our highlighted "Age 26 during World War 2" range.

We note that the youngest legally-enlisted servicemen, those born in 1928 who would have been Age 17 in 1945, could reasonably have expected to live to 2008, given the average life expectancy for people born in that year who later turned Age 65 in 1993. By that standard, every veteran of WW2 alive today is someone who has lived longer than the average American born in the same year they were.

Here's hoping that all the remaining veterans of WWII continue to exceed the average American's lifespan expectations!

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January 21, 2013

Craig Newmark points to some interesting analysis that suggests that the recent run-up in U.S. stock prices can be attributed to the newest rounds of quantitative easing:

What is clear is that the recent market rally is once again being driven by the Federal Reserve's QE programs. Money is flowing out of bonds, and the dollar, and into equities. The weekly chart below shows the decline in the market this past September and October as excess reserve balances with the Fed were drawn down. The subsequent rally has been fueled by the Fed as it has pumped reserve balances sharply higher.

But here's the thing. The rally started a month too early for the Fed's QE efforts to be responsible for it. Here, the Fed's latest QE efforts (let's call it QE 4.0) really only began properly on 12 December 2012. The rally, on the other hand, began after stock prices bottomed on 15 November 2012 - a month before the Fed announced it would expand its balance sheet and long after the previous generation QE 3.0 was initiated in August 2012.

So the Fed's quantitative easing isn't behind the stock market rally. Instead, we can demonstrate that investor expectations for future dividends is behind it.

Following the 6 November 2012 national elections in the U.S., influential investors began racing the clock to beat the expiration of low tax rates for dividends after the end of the year, which were now guaranteed thanks to the outcome of the elections.

Beginning after the market's close of business on 15 November 2012, large numbers of U.S. companies began announcing that they would pay out extra or special dividends before the end of the year.

That activity focused investors on the fourth quarter of 2012 for setting stock prices, which began rising along with investor expectations for the dividends that would be paid out before the end of the year.

That activity continued up through 20 December 2012, which marked the end of the dividend futures contracts for the fourth quarter of 2012.

After that point, investors shifted their attention to a more distant point in the future - to the second quarter of 2013. Stock prices have continued to rise in the rally because they started the month at a level below where the expected change in dividends per share for 2012-Q2 would place them. Today, investors remain focuses on 2013-Q2 in setting stock prices, which we observe as the change in the growth rate of stock prices converging with the expected change in the growth rate of dividends per share for that future quarter.

Our animated chart below shows this transition in the period from 20 December 2012 through the futures for 21 January 2013, along with the shift in focus of investors from 2012-Q4 to 2013-Q2, which you can see as the sudden 5-month leftward shift of the green/red trailing year future dividends per share acceleration data.

Animated Accelerations of S&P 500 Average Monthly Index Value and Trailing Year Dividends per Share, for Futures Through 20 December 2012 through 20 January 2013

And that's why the rally that began back on 15 November 2012 has continued to run. Investors had better hope that the Fed's latest QE efforts start affecting asset prices soon, because the alternative future points in time for where investors might next choose to focus their attention in setting stock prices aren't as pretty.


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January 18, 2013

Where do you fit in the 2012 ranking of total money income by age group in the United States?

While we've previously built a tool where you can find out your percentile ranking among all individuals, men, women, families and households in the U.S., we thought it might be fun to break the data for individuals down a little differently - by age group!

Our chart below reveals what that distribution looked like for 2012, as indicated by the curves showing the major income percentiles from the 10th through the 90th percentile for each indicated age group on the horizontal axis.

U.S. Total Money Income Distribution by Age, 2012

The data in the chart represents the income distribution for the estimated 194,271,175 Americans from Age 15 through Age 74. As such, the space between each of the percentile curves on the chart then covers the total money income of some 19.4 million individual Americans.

What stands out most in the chart are the changes in the vertical spread between the 10th, 50th and 90th percentiles by age group, which might be taken as a measure of the relative income inequality for each age group. For example, we see the Age 15-24 group seems to have the greatest income equality, with the least amount of vertical separation between each of the income percentile thresholds.

We said "seems" for the Age 15-24 group, because believe it or not, this group has the highest income inequality of any age group as measured by the Gini index. The reason why has to do with the high concentration of very low income-earning individuals within this age range (for example, about 50% of all minimum wage earners are found in this age group!), against which a relative handful of very talented young people, including entertainers and star athletes, go straight from their school years to multi-million dollar incomes, often before many of these individuals see their careers flameout before they even make it into the next age group. The same phenomenon isn't true for the older age groups, who all tend to gain in income as they gain greater experience, as their Gini index values do follow the pattern we observe in the chart above.

Speaking of which, one thing that's pretty clear in the chart is that incomes at each major percentile threshold increase across the board as individuals accumulate work experience up through the Age 40-44 group. Above that point, that's would seem to only be true for above-median income-earning individuals.

Going back to the overall patterns we observe in this income distribution visualization, we see that the greatest vertical spread between the 10th and 90th percentiles occurs for the Age 50-54 group, which corresponds to the peak earning years for Americans.

But that vertical spread indicating income inequality diminishes rapidly for older age groups, which is consistent with the transition from earning wages and salaries to only having retirement income. It's especially interesting to see that the peak the retirement-associated decline occurs earlier for the 90th percentile income-earners, while it occurs around Age 55-59 for the lower income-earning percentiles.

The vertical spread between the 10th and 50th percentiles are interesting as well. Here, see see that after rising rapidly for the young, the 50th percentile income level begins to plateau for those around Age 35-39, then holds fairly level through Age 55-59, after which it declines as older individuals increasingly leave wage and salary-earning jobs they've had for years for retirement.

We'll revisit this chart in an upcoming post, where we'll conduct something of a thought experiment....

Notes

We took the age-based total money income data presented by the U.S. Census to construct cumulative income distributions for each included age group, then used ZunZun's curve-fitting tools to develop mathematical models for each to calculate the income that goes with a particular income percentile. The indicated incomes in the chart above are typically within a few hundred dollars of the IRS' published data.

As another hint to what's coming soon here at Political Calculations, those mathematical models just might show up in the future as a new tool that you can use to see exactly what your income percentile ranking is within your own age group!

Reference

U.S. Census Bureau. Current Population Survey. 2012 Annual Social and Economic Supplement. Table PINC-01. Selected Characteristics of People 15 Years Old and Over by Total Money Income in 2011, Work Experience in 2011, Race, Hispanic Origin, and Sex. [Excel Spreadsheet]. 12 September 2012.

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January 17, 2013

Picking up from where we left off, we find that the exchange rate-adjusted growth rate of trade between the U.S. and China showed some improvement in October and November 2012:

Year over Year Growth Rate of U.S.-China Trade, January 1986 through November 2012

China saw an uptick in the year over year growth rate of its U.S. imports to 9.6% in October 2012, which fell back in November 2012 to 4.6% - a level that we have found to be consistent with near-recessionary levels of economic growth in that nation.

Meanwhile, the U.S. imported a increasing amount of goods from China in both October and November 2012, with a year over year growth rate of 4.8% in October and 5.6% in November. While an increasing year-over-year growth rate would indicate a growing economy, we should note that the trade figures tend lag the economy by anywhere from one to three months, so this result may be consistent with the solid growth the U.S. economy recorded in 2012-Q3.

The overall value of trade between the two nations hit an all-time record in October 2012, with the U.S. exporting $10,823.3 billion in goods and services to China and importing $40,289.5 billion in goods and services from China. These peak values were partly due to the falling value of the U.S. dollar with respect to the Chinese yuan.

Data Sources

U.S. Census Bureau. Trade in Goods with China. Accessed 13 January 2013.

Board of Governors of the Federal Reserve System. China / U.S. Foreign Exchange Rate. G.5 Foreign Exchange Rates. Accessed 13 January 2013.

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January 16, 2013

As we expected, economic growth in the third quarter of 2012 was revised upward twice before being finalized at the end of December 2012, rising from the originally reported annualized growth rate of 2.0% to 3.1% in the BEA's third (and final for now) estimate for that quarter.

We had forecast that real GDP would be recorded at $13,602.8 billion in terms of constant 2005 U.S. dollars, and the BEA's third estimate came in at $13,652.6 billion - a difference of $49.8 billion, or within 0.04% of the BEA's last recorded figure.

We've updated our forecast for where GDP in the fourth quarter of 2012 with that finalized data:

Real GDP vs Climbing Limo Forecast vs Modified Limo Forecast, 2004 - 2012Q3

Our inertia-based forecast is overly optimistic and we anticipate that real GDP in 2012-Q4 will be recorded at a level below the $13,726.5 billion in terms of inflation-adjusted, chained 2005 U.S. dollars shown in the chart above, thanks to the combination of our expected major slowdown in economic growth for the quarter and the negative impact of Hurricane Sandy.

We'll close by repeating our comments from 29 October 2012:

In considering the overall strength of economic growth in the United States, our one and two quarter temperature gauges both indicate the economy is currently performing in the "cool" zone, indicating sluggish economic growth. Our less volatile two-quarter GDP growth rate temperature gauge indicates that the U.S. economy is actually trudging along at near-recessionary levels.

We anticipate that this condition will continue through the fourth quarter of 2012 and will worsen going into 2013.

You can't say you weren't warned months ago!

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January 15, 2013

Today, we're taking a preliminary look at just who owns all the debt issued by the U.S. federal government through 30 September 2012 - the end of the U.S. government's fiscal year. Our chart below visualizes what we found:

Preliminary Fiscal Year 2012: To Whom Does the U.S. Government Owe Money?

The information presented in our chart above is preliminary, as the U.S. Treasury typically revises its foreign entity debt ownership data in March of each year.

Overall, U.S. entities own just 65.8% of all debt issued by the U.S. federal government. Ranking the major U.S. entities from low to high, we find that:

  • The U.S. government's military retirement fund owns 2.4% of the national debt.
  • The U.S. government's civilian employee retirement fund accounts for another 5.6% of the nation's debt.
  • The U.S. Federal Reserve, thanks to its quantitative easing programs of recent years, has racked up holdings equal to 10.8% of the total U.S. national debt.
  • The U.S. Social Security Trust Fund claims 16.7%.
  • U.S. individuals and institutions, which includes regular Americans, banks, insurance companies and other government entities, own 30.4% of the nation's debt.

Meanwhile, foreign entities own 34.2% of all U.S. government-issued debt, with the following nations' individuals and institutions representing the five biggest holders of that debt, again ranked from low to high:

  • United Kingdom: 0.9%
  • Brazil: 1.6%
  • "Oil Exporters", which includes Ecuador, Venezuela, Indonesia, Bahrain, Iran, Iraq, Kuwait,Oman, Qatar, Saudi Arabia, Algeria, Gabon, Libya, Nigeria and the United Arab Emirates: 1.7%
  • Japan: 7.0%
  • China (including Hong Kong): 8.1%

All other nations hold approximately 15% of the U.S. outstanding national debt.

The Role of Quantitative Easing in Offsetting Foreign Ownership of the U.S. National Debt

The Federal Reserve's various quantitative easing programs of recent years, where the U.S. government-chartered central bank has purchased large quantities of U.S. government-issued debt in its attempts to keep the U.S. government's spending elevated and the U.S. economy stimulated by lowering long-term interest rates, are especially interesting in the degree to which they've succeeded in offsetting the share of the U.S. national debt owned by foreign interests.

Here, the Fed boosted its holdings of U.S. Treasury securities from a low of $474 billion on 18 March 2009 when it launched QE 1.0 to a peak of $1.684 trillion on 21 December 2011, which fell back to $1.676 trillion by 26 September 2012 - just before the end of the U.S. government's 2012 fiscal year.

The Fed also boosted its holdings of other federal agency debt securities from $48 billion on 18 March 2009 to a peak value of $169 billion on 10 March 2010, which has slowly declined to $83 billion as of 26 September 2012. All told, the Federal Reserve held an additional $1.21 trillion of the U.S. national debt compared to what it did before it began its quantitative easing programs.

As a result, the U.S. Federal Reserve has gone from holding 4.7% of all U.S. government-issued debt as of 18 March 2009 to holding 10.8% of it as of the end of the U.S. government's Fiscal Year 2012. During the peak of the program, the Federal Reserve crowded out almost every other purchaser of U.S. government-issued debt.

Assuming that other U.S. entities would have been unable to accumulate more of the U.S. national debt than they did during this period and that the U.S. government would have spent as much money as it did, if not for the Federal Reserve's quantitative easing programs, the share of the U.S. national debt held by foreign entities would have increased to 41.7%, with the bulk of the foreign acquisitions going to China.

As it stands, a little over 1 out of every 3 dollars borrowed by the U.S. federal government is now owned by foreign interests.

Data Sources

U.S. Federal Reserve. U.S. Treasury securities held by the Federal Reserve: All Maturities. Accessed 14 January 2013.

U.S. Federal Reserve. Federal agency debt securities held by the Federal Reserve: All Maturities. Accessed 14 January 2013.

U.S. Treasury. Major Foreign Holders of Treasury Securities. Accessed 14 January 2013.

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January 14, 2013

With their hope for building a Death Star to stimulate the U.S. economy now dashed because of "budget constraints", the only hope left for the people who signed onto the White House petition in support of the project turned out not to be Obi-Wan Kenobi, but rather a radical plan to create change - specifically a plan to mint a one-trillion dollar coin that might perhaps be used to pay for the Emperor's evil endeavors.

Their new hope was to make a special American Eagle Platinum Bullion Coin and simply stamp "One Trillion Dollars" on it, which to us seems really lame. After all, this represented a real opportunity to go onto what we'll call the "platinum standard", so it seemed to us that the coin should be made out of $1,000,000,000,000 worth of platinum. Because that would be extra special!

Using the spot price for platinum of $1,629 per ounce at the close of business on 11 January 2013, we estimate that it would take just over 613,873,542 ounces of platinum to make the coin, which works out to be about 38,367,096.4 pounds, or a bit over 19,183.5 tons.

That seems like a lot, but physically, that much platinum would only occupy almost 21,427 cubic feet of space, just enough to fit inside this modest home design of "rare beauty".

Now, here's where it gets interesting, because all the platinum that has ever been mined on Earth would fit in a room that's just 25 cubic feet in volume. That would leave the U.S. Mint about 21,402 cubic feet of platinum short of what would be needed to do the job properly.

So we find that the trillion dollar coin fanatics plan was never feasible and instead recommend that they should return to their original Death Star ambition. At least that plan stands a better chance of achieving success - especially now that the U.S. Treasury has officially killed their hopes for the trillion dollar platinum coin.

Until then, these stormtroopers of progress will have to go back to their day jobs of repressing the portion of the population that still has free will.

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January 11, 2013

We think we finally have enough non-outlier event data to map out the current trend for new jobless claims in the U.S. through the week ending 5 January 2013:

Closeup of Residual Distribution of U.S. Seasonally-Adjusted Weekly Initial Unemployment Insurance Claims, 19 November 2011 through 5 January 2013

The last time the U.S. had a flat trend for new jobless claims was right before the onset of the so-called "Great Recession" at the end of 2007. The only problem is that it's gone flat at a level some 48,000 layoffs per week higher than was typical during the low-unemployment years of the Bush administration.

As for what brought on the new trend, we believe it was falling gasoline prices in the U.S. beginning in early September 2012, where prices plummetted after spiking at the end of summer in most states other than California, whose refinery problems with their boutique blends caused gas prices there to continue skyrocketing into October 2012.


We have a crazy idea. You know how some people make their own candles at home? What if we put together some kits with the components and equipment needed for people to make their own incandescent light bulbs, similar to the kinds whose manufacture is currently in the process of being progressively phased out, and tapped into the market being defined by those people who are hoarding 100-watt light bulbs? Shark Tank, here we come!


It seems that after eight years of blogging anonymously, we may finally have been outted, complete with a very handsome photo. Or perhaps it's all a horrible error and our Seeking Alpha profile still offers the only real glimpse of our true nature. Either way, it explains a lot!

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January 10, 2013

Over the holidays, we updated and corrected our original analysis of the rate of assaults in both the United States and Canada. It turns out that one of our original charts had only shown the number of Level 2 and 3 assaults for Canada rather than all nonfatal, nonsexual assaults and our calculation of the total assault rate for Canada was also off by about 30 assaults per 100,000 Canadians.

Today, we're going to revisit that analysis and then take things one step further and do a more direct comparison of the rate of assaults between the populations of the two nations by extracting the assault rate data for the portion of the U.S. population that is most demographically similar to the entire population of Canada.

First, let's take a look at the total number of nonfatal, nonsexual assaults for the entire populations of both nations in 2006 in the following chart:

Nonfatal, Nonsexual Assaults for Canada and the United States, 2006

Here, we see that Canadians experienced some 253,704 assaults in 2006, while Americans recorded 1,598,706 nonfatal, nonsexual assaults in the same year.

Next, because the size of the two nations' populations is so different, let's compare the rate of assaults for each 100,000 people in both nations in our next chart. Note that the U.S. data is based upon the entire population, include the nation's very large black and Hispanic sub-populations, which are nearly absent in Canada (Canadian blacks make up about 2% of that nation's population, while the percentage share of Hispanics in Canada make up less than 1% of Canada's population.):

Nonfatal, Nonsexual Assaults per 100,000 People for Canada and the United States, 2006

We find that Canada's total assault rate per 100,000 inhabitants is 802.23, while the U.S. total assault rate for each 100,000 Americans is 535.80, as Canadians are considerably more likely to become victims of assault than are Americans.

Originally, that was as far as we took our analysis, because of a quirk with the U.S. data - we weren't directly able to compare the rate of assault between Canada and the portion of the U.S. population most demographically similar to Canada's population because a very large fraction of the data from the U.S. WISQARS database doesn't directly identify the U.S. demographic group into which assault victims fall. The table below illustrates what we found for 2006:

U.S. EthnicityAssaults (2006)Population (2006)Assault Rate (2006)
White, Non-Hispanic534,789199,200,396268.47
Black, Non-Hispanic431,35839,857,1071,082.26
Hispanic189,18142,468,693445.46
Other, Non-Hispanic70,38016,853,716417.59
Not Stated372,997N/AN/A
Total1,598,705298,379,912535.80

Those 372,997 assaults where the race or ethnicity of the victims was not stated represents over 23% of all nonfatal, nonsexual assaults in the United States and is the reason why we didn't break the data down for our international comparison previously. But, it has occurred to us that we can allocate those assaults into the other demographic categories reported in the WISQARS database by the frequency of assaults for those categories.

For example, the number of known white, non-Hispanic assault victims represent 43.6% of the total number of assault victims where the race or ethnicity of the victims has been recorded, so it might be reasonable to allocated 43.6% of the number of assault victims whose demographic details are not stated into that category. And we can do similar math for the remaining categories - our next table reveals the results of that process.

U.S. EthnicityAssaults (2006)Population (2006)Assault Rate (2006)
White, Non-Hispanic697,531199,200,396350.17
Black, Non-Hispanic562,62539,857,1071,411.61
Hispanic246,75142,468,693581.02
Other, Non-Hispanic91,79716,853,716544.67
Total1,598,705298,379,912535.80
White + Other, Non-Hispanic789,329216,054,112365.34

In this table, we've combined the totals for the "White, non-Hispanic" and "Other, non-Hispanic" portions of the U.S. population, which represents the portion of the U.S. population that is the most demographically similar to the entire population of Canada. In doing that, we find that this portion of the U.S. population experiences less than half the rate of assault per 100,000 members of the population as do Canadians, with 365.34 nonfatal, nonsexual assaults per 100,000 Americans as compared to 802.23 per 100,000 Canadians. That difference is visualized in our final chart:

Nonfatal, Nonsexual Assaults per 100,000 People for Canada and the Portion of the United States Population Most Demographically Similar to the Canadian Population, 2006

Put another way, Canadians are victimized by assault a little over twice as often as the Americans most demographically similar to them are, with 337 more nonfatal, nonsexual assaults per 100,000 inhabitants occurring in Canada.

By contrast, we already found that this same population experiences just one less homicide per 100,000 than do their demographic peers in the U.S., which might be attributed to Canada's more restrictive gun control laws.

So the question for gun control advocates in the U.S. comes down to this - would you trade that one less homicide per 100,000 for an additional 337 assaults per 100,000 (if we limit ourselves to only considering crimes that involve the risk of direct physical injury or death for the victims)?

Because that would appear to be the trade off that Canadians have made for their more restrictive gun control laws. All on top of having more brutal murders that increasingly involve other kinds of deadly weapons.

Data Sources

Juristat. Canadian Centre for Justice Statistics. Statistics Canada - Catalogue No. 85-002, Vol. 28, No. 7. Crime Statistics in Canada, 2007. Table 2. Selected Criminal Code Incidents, by most serious offence, Canada, 2006 and 2007. Accessed 1 January 2013.

U.S. Centers for Disease Control. WISQARS Nonfatal Injury Reports. Accessed 1 January 2013.

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January 9, 2013

According to the December 2012 employment situation report, job growth stalled out in the final three months of 2012, as the number of employed Americans (143,305,000) was nearly unchanged from the levels recorded in the previous two months.

That outcome is consistent with our earlier observation that the fourth quarter of 2012 would likely see a significant deceleration in economic activity following the comparatively robust pace of growth recorded in the third quarter.

Change in Number of Employed Americans by Age Group, Since Total Employment Peak in November 2007, through December 2012

Breaking down the employment situation by age groups, we find that the number of employed teens (Age 16-19) fell by 66,000 from November 2012 to December 2012 to 4,402,000 as the number of young adults (Age 20-24) declined by just 25,000 over the same time to 13,570,000. Meanwhile, the number of employed individuals Age 25 and older increased by 119,000 from the previous month to reach 125,333,000.

The latest employment situation report revises all the employment data obtained in the seasonally-adjusted household survey portion of the report going back to January 2008 to account for updated seasonal factors, which is typically done with the December jobs repot each year. Our chart in this post reflects these revisions, which affect the period of time in which the U.S. economy first went into recession (it peaked in December 2007 and began declining in the months afterward) and its subsequent recovery.

Perhaps the most remarkable aspect in the chart above is that there has been no effective improvement in the employment situation for U.S. teens since the recession officially ended in June 2009. In fact, since October 2009, which marks the effective end of the decline in the number of employed teens, the number of working teens in the United States has held level at approximately 4,382,000, plus or minus 152,000 teens, in all the months since.

As such, the disappearance of jobs for U.S. teens represents a very large share of the jobs gap that has restrained the recovery of the U.S. economy.

On a final note, the January 2013 employment situation report, set to be released on 1 February 2013, will reflect more substantial revisions to both the establishment and household survey portions of the report, with the household survey portion being updated to account for the U.S. Census Bureau's annual update of the U.S. population. Data from December 2012 or earlier will not be likewise adjusted, which may make direct comparisons between data being released in 2013 and data from earlier years really problematic.

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January 8, 2013

Prompted by the desire to avoid higher taxes on dividends as part of President Obama's desired tax hikes on investment income in 2013, a record number of U.S. companies acted to pay out record levels of dividends in the final quarter of 2012 [Excel spreadsheet] .

Here is the basic rundown from Standard and Poor's Dividend Action Report [Excel spreadsheet]:

  • 4,002 U.S. companies made announcements regarding their dividend policies in December 2012, a new record. The previous record was 3,716 declarations which was set in December 2011.
  • 483 of these companies announced they would pay an extra, or special, dividend before the end of 2012, also a new record. The previous record of 233 extra dividends paid out in one month was set in December 2007, just as the U.S. economy was entering into recession.
  • 124 companies announced they would increase their regular dividends going forward.

And now for the kicker. In December 2012, 93 U.S. companies announced that they would be cutting their regular dividends going forward, also a new record. The previous record of 81 companies announcing dividend cuts in a single month was set in March 2009, as the U.S. stock market was hitting bottom during the "Great Recession".

Our chart below puts the number of dividend cuts being announced in December 2012 into perspective:

Number of Public U.S. Companies Posting Decreasing Dividends, 
January 2004 through December 2012

Much of this activity was prompted by the desire of influential investors to avoid higher taxes on dividends, which in the absence of a deal between the U.S. Congress and President Obama, would have meant a top tax rate on dividends of 43.6% in 2013, as opposed to a maximum tax rate of 15% on dividends in 2012. The fiscal cliff deal worked out in the U.S. Senate early in the morning of 1 January 2013 set the maximum tax rates for both dividends and capital gains at 20%, which is further increased by a separate tax increase on investment income of 3.8% as part of the tax hikes mandated by the Patient Protection and Affordable Care Act (aka "ObamaCare"), which then brings the top tax rate on dividends and capital gains up to 23.8%.

The all-time record number of dividend cuts announced in December 2012 represent the outcome of two main forces at work in the economy. First, a large number of U.S. companies have a worsening outlook for their businesses and are acting to preserve their cash flow by reducing their dividend payments to shareholders. Second, a large number of the companies that acted to pay out special dividends before the tax rates on dividends went up on 1 January 2013 have already made the determination that they will be unable to regenerate enough of the funds they were setting aside to pay out dividends at the levels they had originally promised for 2013 from their cash flow and have acted to reduce their dividend payments to shareholders in the future accordingly.

Both factors will put downward pressure on stock prices in 2013, particularly for small and mid-cap companies. Large cap companies like those that make up the S&P 500 will likely fare better, although these companies were not immune from the game of "beat the clock" that was going on in December 2012 for avoiding higher dividend taxes. Our next chart shows the quarterly cash dividends per share for the S&P 500 that have been paid out since the first quarter of 2009, along with the dividends currently expected to be paid out in each quarter in 2013, based upon dividend futures data:

S&P 500 Quarterly  Dividends per Share, 2009-Q1 Through 2012-Q4, with Expected Future Dividends per Share Through 2013-Q4

Based on Standard and Poor's estimate of the amount of dividends per share paid out by the companies of the S&P 500 in the fourth quarter of 2012, we now estimate that somewhere between 40 to 60 cents per share was pulled into 2012 from 2013.

Our next chart reveals the downward pressure this action will place upon stock prices in 2013:

Accelerations of S&P 500 Average Monthly Index Value and Trailing Year Dividends per Share (and Futures as of 7 January 2013)

It will take a substantial effort on the part of the Federal Reserve's quantitative easing programs to offset the effect of the negative acceleration of dividends upon stock prices in 2013. We don't believe they will be entirely successful.

Our final chart tracks the history of investor expectations for future S&P 500 trailing twelve month dividends per share (you'll have to bear with us for sentences like this one, as we work in the future, but live in the present for the tax advantages. We refer you to Note #1 for further insight into our grammatical choices):

Expected Future Trailing Year Dividends per Share for the S&P 500 as of 7 January 2013

In this chart, we can see the sudden small improvement in investor expectations for the future as a result of the fiscal cliff deal reached on 1 January 2013. We also see a considerable amount of "bunching" between the expected trailing year dividends per share for future quarters, which is an indication of a decelerating economy. A growing economy, by contrast, is indicated by a growing spread between the dividends expected in distant future quarters over time.

On a final note, you can also see that the trailing year dividends expected in 2013-Q4 are riding directly on top of those for 2013-Q3. This is a consequence of the record dividends that are being paid out in 2012-Q4, which add to the trailing year total for 2013-Q3 but not to the total for 2013-Q4.

If not for the tax avoidance behavior associated with the fiscal cliff situation, we would otherwise call that result a clear indication of a dead-on recession. The U.S. economic situation will be better than that appears, but we fear that 2013 will still be characterized by microrecessions, especially in the first and third quarters of the year.

Notes

[1] Yes, we know sentences like that are difficult for many to follow. But as those of us who navigate through the time vortex that is the stock market well know, "tenses are difficult, aren't they?"

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