Political Calculations
Unexpectedly Intriguing!
January 18, 2019

There is a remarkably linear relationship between median and average new home sales prices in the United States. The following chart reveals that pattern for annual data reported by the U.S. Census Bureau for new home sales from 1963 through 2017 on a logarithmic scale.

U.S. Average Versus Median New Home Sale Prices, 1963-2017 (Log-Log Scale)

The amazing thing about this relationship is that it has held very consistently even as home prices in the U.S. have experienced both rising and falling trends through these years, where median and average home sale prices have generally increased and decreased in sync with each other. So much so that if we only had the median sale price data for a given period, we could reasonably estimate the average sale price for the same period within 2.7 percent of its recorded value about 68 percent of the time, and within 8.2 percent of its recorded value about 99% of the time.

While the relationship behind this math was developed using new home sales price data, it appears to also hold for existing home sales data with a similar margin of error.

Try it for yourself! Just enter the median new home sales prices for your period of interest in the following tool, and we'll take care of the rest! [If you're reading this article on a site that republishes our RSS news feed, please click here to access a working version of the tool on our site.]

Median U.S. Home Sale Price Data
Input Data Values
Median Sale Price

Average U.S. Home Sale Price
Calculated Results Values
Estimated Average Sale Price

For the default data, for a median home sale price of $220,000, we would expect the average home sale price in the U.S. in the same period of time to fall within several percent of $267,100, the value our tool finds after rounding to the nearest $100 increment.

Altogether, the relationship we've now established between median and average home sale prices in the United States enables a particular line of analysis that we've been seeking to do for some time, which hasn't been possible because the relative lack of availability of data for average home sale prices. Which is a strange thing to say because usually when we're looking for data that many reporting agencies don't realize may involve lognormal distributions, it's a lot easier to find averages than it is to get medians. It's a real credit to the outfits that do recognize this pattern in real estate prices that they properly report median sale price data as being representative of the prices that most home buyers are paying, where we hope they come to recognize that mean sale prices provide additional valuable information about these markets that should also be tracked and reported.

References

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in United States. [PDF Document]. 23 April 2018. Accessed 12 January 2019.


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January 17, 2019

John Bogle, the man who made passive, low-cost index investing a real world thing and who, as a result, built Vanguard into one of the world's largest investment management firms, passed away on 16 January 2019 at Age 89.

The idea of index investing that Jack Bogle championed proved to be very a big deal, which is why the index fund made Tim Harford's list of 50 Inventions That Made the Modern Economy (the UK edition is 50 Things That Made the Modern Economy), where we can strongly recommend the 10-minute podcast episode of the related BBC radio series if you want to learn more about its history.

If your available time is shorter than that, Jack Bogle once claimed that he could teach the essentials about investings in just a few minutes. In 2010, the Bogleheads' Ricardo Guerra put him to the challenge, where he distilled a lifetime of learning about successful investing into 3 minutes and 42 seconds....

Back in October 2006, we participated in a chapter-by-chapter review of the original edition of The Bogleheads' Guide to Investing (now in its second edition), where we had the honor of reviewing the final chapter of a book that sought to capture Jack Bogle's wisdom....

That was a lucky break for us, because the final chapter summarized all the lessons presented throughout the book, which gave us the opportunity to further condense Jack Bogle's thoughts on investing into just six lines, although with quite a few links to follow for deeper insights gleaned by the other participants in the project:

Today, millions of people are considerably richer than they might otherwise have been because of what Jack Bogle wrought. That's one hell of a legacy in the financial world!

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January 16, 2019

Back in 2009, we wrote about Hauser's Law, which at the time, we described as "one of the stranger phenomenons in economic data". The law itself was proposed by W. Kurt Hauser in 1993, who observed:

No matter what the tax rates have been, in postwar America tax revenues have remained at about 19.5% of GDP.

In 2009, we found total tax collections the U.S. government averaged 17.8% of GDP in the years from 1946 through 2008, with a standard deviation of 1.2% of GDP. Hauser's Law had held up to scrutiny in principal, although the average was less than what Hauser originally documented in 1993 due to the nation's historic GDP having been revised higher during the intervening years.

We're revisiting the question now because some members of the new Democrat party-led majority in the House of Representatives has proposed increasing the nation's top marginal income tax rate up to 70%, nearly doubling today's 37% top federal income tax rate levied upon individuals. Since their stated purpose of increasing income tax rates to higher levels is to provide additional revenue to the U.S. Treasury to fund their "Green New Deal", if Hauser's Law continues to hold, they can expect to have their dreams of dramatically higher tax revenues to fund their political initiatives crushed on the rocks of reality.

Meanwhile, the U.S. Bureau of Economic Analysis completed a comprehensive revision to historic GDP figures in 2013, which significantly altered (increased) past estimates of the size of the nation's Gross Domestic Product.

The following chart shows what we found when we updated our analysis of Hauser's Law in action for the years from 1946 through 2018, where we're using preliminary estimates for the just-completed year's tax collections and GDP to make it as current as possible.

Hauser's Law in Action, 1946 - 2018

From 1946 through 2018, the top marginal income tax rate has ranged from a high of 92% (1952-1953) to a low of 28% (1988-1990), where in 2018, it has recently decreased from 39.6% to 37% because of the passage of the Tax Cuts and Jobs Act of 2017.

Despite all those changes, we find that the U.S. government's total tax collections have averaged 16.8% of GDP, with a standard deviation of 1.2% of GDP. Applying long-established techniques from the field of statistical process control, that gives us an expected range of 13.2% to 20.5% of GDP for where we should expect to see 99.7% of all the observations for tax collections as a percent share of GDP.

And that's exactly what we do see. The next chart zooms in on the total tax collections as a percent share of GDP data from the first chart, and adds the data for individual income tax collections as a percent share of GDP below it.

Total and Individual Income Tax Collections as Percent of GDP, 1946 - 2018

What we find is that the federal government's tax collections from both personal income taxes and all sources of tax revenue are remarkably stable over time as a percentage share of annual GDP, regardless of the level to which marginal personal income tax rates have been set. The biggest deviations we see from the mean trend to be associated with severe recessions, when tax collections have tended to decline somewhat more than the nation's GDP during periods of economic distress.

We also confirm that the variation in total and personal income tax receipts over time is well described by a normal distribution. We calculate that personal income tax collections as a percentage share of GDP from 1946 through 2018 has a mean of 7.6%, with a standard deviation of 0.8%.

For both levels of tax collections, if Hauser's Law holds, we would then expect any given year's tax collections as a percent of GDP to fall within one standard deviation of the mean 68% of the time, within two standard deviations 95% of the time, and within three standard deviations 99.7% of the time. And that is pretty close to what we observe with the reported data from 1946 through 2018.

As for high tax revenue aspirations, we can find only three periods where tax collections rose more than one standard deviation above the mean level.

  1. In 1968, the Democratic U.S. Congress and President Lyndon Johnson passed a 10% income surtax that took effect in mid-year, which suddenly raised the top tax rate from 70% to 77% (which increased the amount collected from top income tax earners by 10%.) Coupled with a spike in inflation, for which personal income taxes were not adjusted to compensate, this tax hike led to outsize income tax collections in that year.
  2. The sustained high inflation of 1978 (7.62%), 1979 (11.22%), 1980 (13.58%) and 1981 (10.35%) led to higher tax collections through bracket creep, as income tax brackets in the U.S. were not adjusted for inflation until 1985 as part of President Ronald Reagan's first term Economic Recovery Tax Act.
  3. Beginning in April 1997, the Dot Com Stock Market Bubble minted a large number of new millionaires as investors swarmed to participate in Internet and "tech" company initial public offerings or private capital ventures, which in turn, inflated personal income tax collections. Unfortunately, like the vaporware produced by many of the companies that sprang up to exploit the investor buying frenzy, the illusion of prosperity could not be sustained and tax collections crashed with the incomes of the Internet titans in the bursting of the bubble, leading to the recession that followed.

Now, what about those other taxes? Zubin Jelveh looked at the data back in 2008 and found that as corporate income taxes have declined over time, social insurance taxes (the payroll taxes collected to support Social Security and Medicare) have increased to sustain the margin between personal income tax receipts and total tax receipts. This makes sense given the matching taxes paid by employers to these programs, as these taxes have largely offset a good portion of corporate income taxes as a source of tax revenue from U.S. businesses. We also note that federal excise taxes have risen from 1946 through the present, which also has contributed to filling the gap and keeping the overall level of tax receipts as a percentage share of GDP stable over time.

Looking at the preliminary data for 2018, which saw both personal and corporate income tax rates decline with the passage of the Tax Cuts and Jobs Act of 2017, we see that total tax receipts as a percent of GDP dipped below the mean, but still falls within one standard deviation of it, just as in over two-thirds of previous years. Tax receipts from individual income taxes however rose slightly, despite the income tax cuts that took effect in 2018, staying above the mean but still falling within one standard deviation of it.

Hauser's Law appears to have held up surprisingly well over time.

Will it continue? Only time will tell, but given what we've observed, it would take more than simple changes in marginal income tax rates to boost the U.S. government's tax revenues above the historical range that characterizes the strange phenomenon that is Hauser's law.

References

Bradford Tax Institute. History of Federal Income Tax Rates: 1913-2019. [Online Text]. Accessed 13 January 2019.

Tax Foundation. Federal Individual Income Tax Rates History. [PDF Document]. 17 October 2013.

U.S. Department of the Treasury. September 2018 Monthly Treasury Statement. [PDF Document]. 17 October 2018.

U.S. Bureau of Economic Analysis. National income and Product Accounts Tables. Table 1.1.5. Gross Domestic Product. [Online Database]. Last Revised: 21 December 2018. Accessed: 14 January 2019.

U.S. White House Office of Management and Budget. Budget of the United States Government. Historical Tables. Table 1.1. Summary of Receipts, Outlays, and Surpluses or Deficits (-): 1789-2023. Table 2.1. Receipts by Source: 1934-2023. [PDF Document]. 12 February 2018.

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January 15, 2019

One of the most important and perhaps least well known metrics for the U.S. stock market is the growth rate of dividends for the S&P 500, which is why we started a new series to feature it last year.

The following chart visualizes the year over year growth rate of the S&P 500's trailing year dividends per share for each month of the 21st Century, starting from the beginning of the last year of the 20th Century and continuing through December 2018, with a bonus projection of the currently expected future for S&P 500 dividend growth through March 2020.

Year Over Year Growth Rate of S&P 500 Dividends Per Share in the 21st Century, 2000-Q1 through 2018-Q4, with Projected Future Through 2020-Q1

We've also indicated the National Bureau of Economic Research's official periods of recession in the 21st Century (so far!) on the chart.

As for how to best use this data, you really want to pay close attention to how fast the growth rate of dividends per share is changing, where negative accelerations for dividends generally coincide with falling stock prices, and positive accelerations tend to coincide with rising stock prices. Also, if you compare the projected future for 2018 with what actually happened for the S&P 500's dividend growth rate, 2018 was a year that mostly lived up to early expectations.

That's not always the case, where we've seen dramatic changes in those expectations in this century, particularly when the U.S. economy fell into recession. If there's one observation that you want to take away from the chart however, it is perhaps Tadas Viskanta's observation that "recessions are a dividend killer"!

Previously on Political Calculations

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January 14, 2019

2019 is off to a rollicking start for the S&P 500 (Index: SPX), which appears to have launched into its first Lévy flight event in 2019.

If that's not a term you're readily familiar with, here's what that means. A Lévy flight is similar to a random walk for stock prices, but instead of the relatively small changes in stock prices that characterize a true random walk, it is characterized by the sudden emergence of comparatively large changes - more so than would be predicted by a normal distribution.

From our perspective, Lévy flight events can occur whenever investors shift how far forward in time they are looking into the future as they go about setting current day stock prices, where the differences in expectatations for the sustainable portion of future earnings associated with these different points of time drive these outsized changes in stock prices. For the first Lévy flight event of 2019, that shift appears to be from the distant future quarter of 2019-Q4 back to the current quarter of 2019-Q1.

Alternative Futures - S&P 500 - 2019Q1 - Standard Model with Annotated Redzone Forecast - Snapshot on 11 Jan 2019

It was even sort of predictable, where we described what would happen if investors acted to shift their forward-looking attention just as they appear to have, well before the market even opened last week.

  • If investors remain focused on the distant future quarters of 2019-Q3/2019-Q4, the S&P 500 can be expected to generally follow a downward trajectory throughout 2019-Q1, falling into a true bear market for the index.
  • If investors shift their attention toward 2019-Q1, the effect would be to boost stock prices higher, where they would largely move sideways during the quarter with respect to their current level.
  • Should investors shift their forward-looking focus to 2019-Q2, the market would see a significant rally above its current level.

Investors chose Door #2 in this real-life Monty Hall problem!

Meanwhile, because we've now entered the period of time where it will be relevant, we've redrawn our redzone forecast to correspond with this selection, anchoring its starting point with where the S&P 500 closed on Friday, 11 January 2019. If you want to know more about our assumptions in generating the forecast, we've incorporated them in the annotations on the chart.

With the Fed's future actions now fading into the background noise after dominating much of the market-related news headlines last week, we can perhaps look forward to investors sustaining their focus on 2019-Q1 as earnings season gets under way in the week ahead. That should mean the end of the first Lévy flight event of 2019, with smaller stock price movements from day to day, but this is also when a number of companies will change investor expectations for the future, which can change stock prices as investors rapidly absorb all new information.

Speaking of new information, here are the major market-moving headlines from the past week....

Monday, 7 January 2019
Tuesday, 8 January 2019
Wednesday, 9 January 2019
Thursday, 10 January 2019
Friday, 11 January 2019

Barry Ritholtz listed the week's positives and negatives in his weekly succinct summary of the major economics and market-related news, and deployed the word "stalement"! What does that mean? It's defined in the Urban Dictionary!...

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January 11, 2019

If you're a fan of the theory of dynamic plate tectonics (and really, who isn't?), you can spend a lot of time checking what that has meant for where you live by playing with Dinosaur Pictures' Ancient Earth Globe app, where you can plug in your address and see how the Earth where you're at has changed over tens and hundreds of millions of years!

We did that, where we plugged in a famous address in Washington D.C., which centered the globe in today's world on the Western Hemisphere. We then moved backwards in time, until we got to a point where the spot where Washington D.C. would eventually be located moved into the opposite hemisphere. The following animated image shows 300 million years worth of that continental drift in reverse....

Animation: Washington D.C. from Today Back to 300 Million Years Ago

We set up the animation so that each of the frames would be displayed for eight seconds, which should allow enough time to read some of the additional information that the app presents.

Do check it out - although we stopped at 300 million years, the app goes back some 750 million years.

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January 10, 2019

The Bureau of Labor Statistics has been tracking the average pay and benefits earned by American workers in all occupations and working in all industries since at least the first quarter of 2004 [1], where we now have nearly 15 years worth of data that indicates how much the average civilian employee in the U.S. has been compensated for their hours worked.

We've visualized the nominal data reported by the BLS in the following chart, where we've presented the average wage or salary and the total benefits earned per hour worked with the combined total compensation earned by civilian workers in the U.S. from 2004-Q1 through 2018-Q3. The data for 2018-Q4 won't be available until 19 March 2019.

Average Compensation per Hour for All Civilian Workers, All Occupations in All Industries, 2004-Q1 through 2018-Q3 title=

From 2004-Q1 to 2018-Q3, the cost to civilian employers in the U.S. of compensating their employees rose from $24.95 per hour to $36.63 per hour, an increase of 47%. Breaking that figure down into its components, hourly wages and salaries rose by 41% from $17.71 to $25.03 over that period, while the value of benefits paid to civilian employees as part of their total compensation rose by 60% from $7.23 to $11.60 per hour.

In our next chart, we're presenting the same quarterly information, but now adjusted for inflation to be in terms of constant 2018-Q3 U.S. dollars.

Inflation-Adjusted Compensation per Hour for All Civilian Workers, All Occupations in All Industries, 2004-Q1 through 2018-Q3 title=

After taking inflation into account, we find that hourly wages and salaries have risen by 5% from 2004-Q1 to 2018-Q3 and that their benefits have increased by 19%. Together, the inflation-adjsuted total compensation of civilian employees in the U.S. has increased by 9% from 2004-Q1 through 2018-Q3.

Both employers and employees have incentives to favor benefits over wages and salaries in considering how employees will be compensated for their labor, where in particular, the portion of employee compensation that goes toward paying the employer-provided benefit of health insurance is exempt from federal, state and local income taxes.

Notes

[1] On a quarterly basis, following the North American Industry Classification System (NAICS) for tracking costs across various industries. The BLS also has annual employee compensation data going back to 1986 that followed the older Standard Industry Classification (SIC) code system.

References

U.S. Bureau of Labor Statistics. Employment Cost Trends: Employer Cost for Employee Compensation. [Online Database]. Accessed 4 January 2018.

Organization for Economic Co-operation and Development. Main Economic Indicators: Consumer Price Index: Total All Items for the United States (Quarterly, Seasonally Adjusted). [Online Database]. Accessed 4 January 2018.

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January 9, 2019

The future for the dividends of the S&P 500 (Index: SPX) in 2019 looks to be one in which there will be year over year gains, where their rate of growth will peak in 2019-Q2 and then decelerate into 2020.

The following chart shows the future for the S&P 500's quarterly dividends per share for 2018 and 2019, as given by the CME Group's quarterly dividend futures. The initial dividend futures indicated in the chart represents a snapshot of the data that was taken some 12 months before the projected end of the indicated quarter, while the final figure represents the last recorded estimate just prior to the end of the indicated dividend futures contract period, reflecting the final measure of how the dividend futures changed during the preceding year.

The Future for S&P 500 Quarterly Dividends per Share, 2018-Q1 through 2018-Q4, with Futures through 2019-Q4

We've also provided Standard & Poor's reported quarterly cash dividends for the S&P 500 for the completed quarters of 2018 to provide a frame of reference for the dividend futures data. Readers should note what we call the "term mismatch" issue with comparing these data sources, which arises because dividend futures contracts run from the end of the third Friday of the month preceding a calendar quarter through the third Friday of the month ending a calendar quarter (for example, 2019-Q1 will reflect dividends to be paid out from 22 December 2018 through 15 March 2019).

These dividend futures contract periods conflict with the dividend data that Standard & Poor reports as being paid during each calendar quarter (for example, 2019-Q1's figure will cover all dividends paid from 1 January 2019 through 31 March 2019). While this issue exists for all quarters, we've observed that this term mismatch issue often leads to big differences between the figures that each source reports for Q4 and the next year's Q1 figures, where the dividend futures data considers the surge of dividends paid out right before the end of each calendar year as belonging to Q1. This difference accounts for why the futures data for Q1 appears to overestimate the final figures reported by S&P and why the futures data underestimates the final figures for Q4 each year.

In looking at the projected future for S&P 500 dividends in 2019, the year over year rate of dividend growth for the CME Group's dividend futures in 2019 is set to peak at 12% for 2019-Q2, after which, the dividend futures data indicates a slowing rate of year over year growth through 2019-Q4, which currently shows just 4.3% of year over year growth. Here are the CME Group's initial and final projections for each quarter's dividends per share for 2018 and 2019:

  • 2018-Q1: $13.08 (increased to $13.20)
  • 2018-Q2: $12.95 (remained at $12.95)
  • 2018-Q3: $13.00 (increased to $13.75)
  • 2018-Q4: $13.75 (increased to $13.95)
  • 2019-Q1: $13.95 (+5.7% y/o/y from $13.20)
  • 2019-Q2: $14.50 (+12.0% y/o/y from $12.95)
  • 2019-Q3: $14.00 (+1.8% y/o/y from $13.75)
  • 2019-Q4: $14.55 (+4.3% y/o/y from $13.95)

As a bonus, If you review the CME Group's S&P 500 quarterly dividend futures, you'll find that they've also indicated that 2020-Q1 will have a dividend payout of $14.25 per share. If that figures holds, the year-over-year rate of dividend growth for the S&P 500 will increase by just 2.2%, year over year (y/o/y), in that quarter.

But will it? There are a lot of things that could happen between now and the end of the first quarter of 2020 that could change that projected outcome. After all, that big positive jump in the projected dividends futures for 2018-Q3 from its initial value to its final value was affected by the passage of the Jobs and Tax Cuts Act in December 2017.

In 2019, a trade deal with China could provide a similar boost. Or a poorly considered tax hike could shrink it. There are a lot of ways that the expectations for the future of S&P 500 dividends could change before 2020 arrives!

References

CME Group. S&P 500 Quarterly Dividend Index Futures Quotes. [Online Database]. Accessed 8 January 2019.

Standard and Poor. S&P 500 Index Earnings and Estimates. [Excel Spreadsheet]. Accessed 8 January 2019.

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January 8, 2019
Stock Market Chaos!

Bear markets have notorious reputations for stock price volatility, where big daily changes in stock prices are a characteristic that distinguishes bear markets from bull markets.

These periods include bear market rallies, which often see outsized upward movements in stock prices that punctuate periods of corrections or bear markets and often extend into the early phases of recoveries from them.

That's relevant today because we've just seen two such rallies in the last two weeks, one on Wednesday, 26 December 2018 and Friday, 4 January 2018, where the S&P 500 (Index: SPX) rallied by an outsized amount with respect to its typical level of volatility.

What is an outsized amount for the stock market to go up in a single day? Building on our statistical analysis to quantify daily market volatility for the S&P 500 since 3 January 1950, we can put the threshold for identifying an outsized upward movement in its level at a 2.92% increase above its previous day's closing value, which is three standard deviations above the mean daily change of 0.034% for the index, where the variation in the percentage change is well-described by a normal distribution.

S&P 500 Daily Volatility (Percent Change Between Closing Value and 
Previous Trading Day's Closing Value), 3 January 1950 - 4 January 2019

For the 17,364 daily observations we have covering the 69 years from 3 January 1950 through 4 January 2019, we count a total of 115 days where stock prices closed more than 2.92% above their previous days close, accounting for 0.66%, or roughly 1 in 151, of the total observations.

These outsized rallies are not evenly distributed throughout the period however. Going year by year, here's are the main periods where they are concentrated, which cover 100 of the 115 outsized single day rallies:

  • 1955: 2 between 6 June 1955 and 6 July 1955.
  • 1962: 3 between 29 May 1962 and 24 October 1962.
  • 1974-1975: 8 between 12 July 1974 and 27 January 1975.
  • 1982: 5 between 17 August 1982 and 30 November 1982.
  • 1987: 3 between 20 October 1987 and 29 October 1987.
  • 1990-1991: 3 between 27 August 1990 and 21 August 1991.
  • 1997: 2 between 2 September 1997 and 28 October 1997.
  • 1998: 5 between 1 September 1998 and 15 October 1998.
  • 2000-2003: 25 between 16 March 2000 and 17 March 2003.
  • 2008-2009: 29 between 11 March 2008 and 15 July 2009.
  • 2010: 5 between 10 May 2010 and 1 September 2010.
  • 2011: 8 between 9 August 2011 and 20 December 2011.
  • 2018-2019: 2 between 26 December 2018 and 4 January 2019 (at this writing).

Aside from 1955, all of these periods where the S&P 500 experienced single day price gains of 2.92% or more have coincided with or closely followed negative corrections or bear markets for the S&P 500.

References

Yahoo! Finance. S&P 500 (^GSPC) Historical Prices, 3 January 1950 through 4 January 2019. [Online Database]. Accessed 4 January 2018.

Yardeni Research. Stock Market Briefing: S&P 500 Bull & Bear Market Tables. [PDF Document]. 13 February 2018.

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January 7, 2019

A bear market is "a condition in which securities prices fall 20 percent or more from recent highs amid widespread pessimsism and negative investor sentiment." By that definition, the S&P 500 (Index: SPX) has verged onto the edge of a bear market during the last two weeks, having fallen by 19.8% from its previous record closing value of 2,930.75 on 20 September 2018 to 2,351.10 on 24 December 2018.

Since that Christmas Eve, the S&P 500 has experienced what might be best described as a bear market rally, which has been characterized by two remarkably strong closes: a 5.0% surge on Boxing Day and a 3.4% gain on Friday, 4 January 2018.

We wish we could say that we had seen the last of the bear, but the math behind how stock prices work is signaling something very different. The S&P 500 completed its fifth Lévy flight event of 2018, where investors have fully shifted their forward-looking focus toward the distant future quarters of either 2019-Q3 or 2019-Q4, where long held expectations of a deceleration in dividend growth at these times has brought stock prices down from their formerly lofty height. The following chart shows the trajectory of the S&P 500 against the backdrop of where our dividend futures-based model would set them according to how far forward into the future investors are looking.

Alternative Futures - S&P 500 - 2018Q4 - Standard Model - Snapshot on 4 Jan 2018

At this time, there isn't much difference in the expectations for year-over-year dividend growth between 2019-Q3 and 2019-Q4, where we don't see much point in distinguishing between the outlook for these quarters until that situation might change. With that in mind, here is what the dividend futures model is projecting for the future of the S&P 500 through the end of the first quarter of 2019.

Alternative Futures - S&P 500 - 2019Q1 - Standard Model - Snapshot on 4 Jan 2018

The new quarter is presenting a considerable forecasting challenge in that our model's use of historic stock prices as the base reference points from which it projects the potential alternate futures for the S&P 500 is being impacted by the echo of volatility in stock prices from a year ago. To account for that echo effect on our model's projections, we've added a red-zone forecast to our alternate futures chart, where we have assumed that investors will continue to focus on 2019-Q3 or 2019-Q4 in the period from 11 January 2019 through 22 April 2019. We also anticipate that the market's recently high volatility will continue, where we've drawn the redzone forecast to be slightly wider than the typical plus-or-minus 3% error range that we would expect if investors were closely focused on one particular future point of time.

We're also trying something new in generating the redzone forecast, where rather than simply drawing a red box on the chart, we've incorporated it into the code we use to generate the chart itself, where it may fluctuate in response to changes in stock prices and future expectations until they become relatively locked in. We're looking forward to finding out how well that might work.

Starting with where the S&P 500 closed on 4 January 2019, here's how to read the chart, in order of greater to lesser likelihood:

  • If investors remain focused on the distant future quarters of 2019-Q3/2019-Q4, the S&P 500 can be expected to generally follow a downward trajectory throughout 2019-Q1, falling into a true bear market for the index.
  • If investors shift their attention toward 2019-Q1, the effect would be to boost stock prices higher, where they would largely move sideways during the quarter with respect to their current level.
  • Should investors shift their forward-looking focus to 2019-Q2, the market would see a significant rally above its current level.

We've previously covered why investors have fixed their attention on 2019-Q3/2019-Q4 in setting current day stock prices, where we'll simply observe that nothing has yet changed that might prompt them to change that forward-looking focus. If anything, the last two weeks of news from the Federal Reserve has only fixed it at that point more tightly, where Fed officials have indicated that if and when they choose to resume hiking interest rates, it will be during these quarters. Combined with China's worsening economic outlook, which is contributing to the long-anticipated deceleration of U.S. dividend growth in 2019-Q3 and 2019-Q4, these factors account for what seems to be shaping up as a gloomy outlook for S&P 500 investors in the first quarter of 2019.

Monday, 24 December 2018
Wednesday, 26 December 2018
Thursday, 27 December 2018
Friday, 28 December 2018
Monday, 31 December 2018
Wednesday, 2 January 2019
Thursday, 3 January 2019
Friday, 4 January 2019

Over the holidays, Barry Ritholtz presented the positives and negatives for the last week of December 2018 and the first week of January 2019, counting a total of 11 pluses and 11 minuses as the old year ended and the new one began.

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January 4, 2019

Median household income in the United States rose to $63,554 in November 2018, a 0.5% increase over the Sentier Research's estimate of $63,220 for October 2018. The following chart shows the nominal (red) and inflation-adjusted (blue) trends for median household income in the United States from January 2000 through November 2018. The inflation-adjusted figures are presented in terms of constant November 2018 U.S. dollars.

Median Household Income in the 21st Century: Nominal and Real Estimates, January 2000 to November 2018

2018 has seen a remarkably strong growth trend in median household income in the United States. In both nominal and inflation-adjusted terms, the income earned by the typical American household at the middle of the nation's distribution of income has set new record highs in each of the last eleven months in both nominal and inflation-adjusted terms.

November 2018 saw the year-over-year growth rate of nominal median household income in the U.S. tick down from October 2018's record high value for the monthly data series, which extends back to January 2001.

Median Household Income in the 21st Century: Year Over Year Growth Rate, January 2001 to October 2018

Overall, with just December 2018's data left to be processed to close out the year, it appears that 2018 is set to become one of the best years ever for income gains for typical American households.

Analyst's Notes

Closing out 2018 may be delayed because of the partial government shutdown, should it persist well into January 2019, where the federal agencies that produce the data both Sentier Research analyses and that we use in crafting our alternate estimates are both considered to be non-essential.

Our alternate estimate for median household income in November 2018 is $63,041, which falls within 1% of Sentier Research's Current Population Survey-based estimate for the month. The methodology for the approach we've developed to generate the alternate median household income estimate is described here.

In generating inflation-adjusted portion of the Median Household Income in the 21st Century chart and the corresponding year-over-year growth rate chart above, we've used the Consumer Price Index for All Urban Consumers (CPI-U) to adjust the nominal median household income estimates for inflation, so that they are expressed in terms of the U.S. dollars for the month for which we're reporting the newest income data.

Data Sources

U.S. Bureau of Economic Analysis. Table 2.6. Personal Income and Its Disposition, Monthly, Personal Income and Outlays, Not Seasonally Adjusted, Monthly, Middle of Month. Population. [PDF Document, Online Database (via Federal Reserve Economic Data)]. Last Updated: 21 December 2018.

U.S. Bureau of Economic Analysis. Table 2.6. Personal Income and Its Disposition, Monthly, Personal Income and Outlays, Not Seasonally Adjusted, Monthly, Middle of Month. Compensation of Employees, Received: Wage and Salary Disbursements. [PDF Document, Online Database (via Federal Reserve Economic Data)]. Last Updated: 21 December 2018.

U.S. Department of Labor Bureau of Labor Statistics. Consumer Price Index, All Urban Consumers - (CPI-U), U.S. City Average, All Items, 1982-84=100. [Online Database (via Federal Reserve Economic Data)]. Last Updated: 12 December 2018.

References

Sentier Research. Household Income Trends: January 2000 through May 2017, March 2018 through November 2018. [Excel Spreadsheet with Nominal Median Household Incomes for January 2000 through January 2013 courtesy of Doug Short]. [PDF Document]. Accessed 28 December 2018. [Note: We've converted all data to be in terms of current (nominal) U.S. dollars to develop the analysis presented in this series.]

U.S. Census Bureau. Historical Income Statistics. Table H-5.  Race and Hispanic Origin of Householder--Households by Median and Mean Income:  1967 to 2017. [Excel Spreadsheet]. Accessed 5 December 2018.

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January 3, 2019

2018 has gone out with a bang for dividend-paying stocks in the U.S. stock market. Here's the dividend metadata for December 2018:

  • In December 2018, 5,934 U.S. firms declared dividends, an increase of 2,210 over the 3,724 recorded in November 2018. That figure is also an increase of 1,428 over the number recorded in December 2017 and the largest number ever recorded for a data series that extends back to January 2004.
  • 179 U.S. firms announced they would pay an extra, or special, dividend to their shareholders in December 2018, an increase of 87 over the number recorded in November 2018. That figure is also an increase of 35 over the total recorded in December 2017.
  • 138 U.S. firms hiked their dividend payments to shareholders in December 2018, a decrease of 27 from the number recorded in November 2018, which is an increase of 12 over the total recorded in December 2017.
  • A total of 40 publicly traded companies cut their dividends in December 2018, an increase of 20 over the number recorded in November 2018 and a decrease of 14 from the 54 recorded in December 2017.
  • Just 1 U.S. firm omitted paying their dividends in December 2018, the same as the number recorded in November 2018. That figure is also a decrease of 6 from the number of firms that omitted paying dividends back in December 2017.

The following chart illustrates the number of dividend increases and decreases recorded in each month from January 2004 through December 2018:

Number of Public U.S. Firms Increasing or Decreasing Their Dividends Each Month, January 2004 through December 2018

In addition to going out with a bang, dividend paying companies also exited 2018 on a cautionary note, with the number of dividend cutting firms rising above the threshold indicating recessionary conditions developing for the U.S. economy for the month of December 2018.

Looking back at the final quarter of 2018 however, we find positive improvements across the board for all but one of the U.S. stock market's basic dividend metrics.

  • 2018-Q4 had 13,312 firms issue dividend declarations, compared with 11,102 in 2017-Q4.
  • 369 firms announced they would pay an extra dividend to their shareholders in 2018-Q4, up from the 294 that acted to pay special dividends back in 2017-Q4.
  • The number of dividend rises announced in 2018-Q4 was 475, which was disappointing when compared to 2017-Q4's total of 495.
  • 2018-Q4 saw 73 firms announce dividend reductions, which was down from 2017-Q4's count of 95.
  • Just 4 firms omitted paying dividends in the fourth quarter of 2018, significantly lower than the 19 that suspended paying their dividends in the final quarter of 2017.

We do have more information on the dividend cutting firms for 2018-Q4, where our near real-time sample captured 46 of the quarter's 73 reductions. In the following summary, companies listed more than once cut their dividends more than once.

The following chart tallies the number of dividend cuts in our sample by industrial sector:

Sampled Dividend Cuts in U.S. by Industrial Sector, 2018-Q4

By far and away, the oil and gas industry saw the greatest amount of distress during the fourth quarter of 2018, accounting for 63% of our sample and coinciding with a significant decline in oil prices during the quarter as global demand diminished. The financial sector, including Real Estate Investment Trusts (REITs), came in second with 17.4% of the dividend cuts in our sample, where the Fed's rate hikes negatively impacted eight of these interest rate-sensitive firms. Food producer and the manufacturing sector each recorded 2 dividend cutting firms each (manufacturing included the highly distressed GE), while the technology, mining, consumer goods and utilily industries rounded out our sample with just one dividend cut recorded in each.

References

Standard and Poor. S&P Market Attributes Web File. [Excel Spreadsheet]. Accessed 2 January 2019.

Seeking Alpha Market Currents. Filtered for Dividends. [Online Database]. Accessed 2 January 2019.

Wall Street Journal. Dividend Declarations. [Online Database]. Accessed 2 January 2019.

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