Political Calculations
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July 18, 2019

Komal Sri-Kumar is the president and founder of Sri-Kumar Global Strategies who just had a very interesting bit of analysis published by Bloomberg: The Bond Market Is Now a Giffen Good. In this piece, he makes the argument that sovereign debt, such as U.S. Treasuries, may be considered to be a Giffen good, which he explains in his opening paragraphs:

With some $13 trillion of bonds worldwide yielding less than zero percent, it would be easy to characterize fixed-income assets as nothing more than a giant bubble waiting to burst. Those who agree probably haven’t heard of the concept of a “Giffen good.”

Simply put, a Giffen good is a paradox of economics where rising prices lead to higher demand, which is in contrast to the negatively sloped demand curve that students learn in Economics 101. Named after 19th century Scottish economist Sir Robert Giffen, a Giffen good is typically an essential item that, because of its higher price, leaves less resources to purchase other items. (To be sure, many economists debate whether a Giffen good actually exists.)

In terms of the bond market, it’s important to understand that the rapid plunge in yields, especially for sovereign debt, reflects increased concern about the state of the global economy. Those concerns, in turn, only fuel demand for the safest assets even at negative yields, which pushes prices higher and yields even lower.

He goes on to identify three factors (which we've excerpted below) for why the interest rate yields of sovereign bonds and Treasuries are falling, which in the strange world of bond investing, means their prices are going up:

First, inflation rates have been low or declining in the U.S., euro zone and Japan, encouraging investors to allocate more resources to fixed-income assets despite falling yields. High rates of inflation reduce the purchasing power of bond holders, but low rates of inflation do the opposite....

Second, expectations for central bank monetary policy have been kind to bond investors. Ten-year yields have fallen below policy rates in the U.S., Germany and Japan, providing a reason – and pressure - for monetary authorities to reduce rates....

Third, the steep decline in U.S. and German risk-free yields have increased the attractiveness of lower-rated sovereign credits.

How long sovereign bonds and Treasuries might act like Giffen goods remains to be seen, but we should recognize that the conditions that bring Giffen goods into existence are typically transitory. Either those conditions will not endure, or should they persist, at some point, the rising prices that might have initially motivated investors to buy increased quantities of sovereign bonds may grow too high, with demand for sovereign debt sharply dropping off after that point as the Law of Demand reasserts itself.

No one really knows how high that price is. Nobody should want to find out the hard way.

More Reading

Frank Steindl introduced the concept of Money and Bonds as Giffen Goods back in December 1973, which is the earliest reference to the concept that we can find. It is also the only reference we can find before we began exploring the concept of Debt as a Giffen Good back in May 2009.

Since then, a few analysts have weighed in on the topic, including StatsGuy's Money as the Ultimate Giffen Good at The Baseline Scenario in December 2009, Eric Falkenstein's Treasuries a New Kind of Giffen Good at Falkenblog in August 2011, Kevin Erdmann's discussion of Bonds and Real Estate as Giffen Goods in May 2014, and our own followup More Evidence That Debt Is A Giffen Good in January 2017.

While not considering the role of either money or debt as a Giffen good, Timothy Taylor wrote about recent, strong evidence of Giffen Goods in Real Life at Conversable Economist in January 2012. Since the reputation of Giffen goods is that they are elusive, it's fascinating to see them documented whenever they appear.

And speaking of sovereign debt, we would be remiss if we didn't include Visual Capitalist's United Nations of Debt infographic showing data from 2017:

Visual Capitalist: United Nations of Debt

Nearly every nations' debt is bigger now. What could possibly go wrong?

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July 17, 2019

We came across a news story in the Los Angeles Times about San Francisco's 2019 Point-In-Time count of its homeless population that caught our attention because it indicated that the total number of homeless counted in San Francisco in January 2019 wasn't 8,011 as previously reported, but 9,784 after more accurately accounting for the "hidden homeless". Here's an excerpt:

Over the last several months, cities and counties across California have been releasing homeless counts. The results have been grim.

San Francisco was no exception. In May, the city released data that showed homelessness had jumped 17%. That was bad enough. Last week, a more complete accounting, known as a point-in-time count, showed the problem was even worse.

The count revealed that homelessness in a city that’s become a caricature of wealth inequality in the U.S. had actually increased by about 30% from 2017, when the last count took place.

The new numbers use a broader definition of what’s considered to be homeless that goes beyond what’s mandated by the U.S. Department of Housing and Urban Development. They include homeless people in jails, hospitals and residential treatment facilities.

Partly what stands out in this story is its bad reporting, because the figure behind the 17% increase in San Francisco's homeless count that was reported in May 2019 and the figure behind the 30% increase reported last week were both the result of the city's 2019 Point-In-Time Count of its homeless population. The difference between the two figures is who they include in their totals, where the claim that the later reported figure was the result of "a more complete accounting, known as a point-in-time count" is highly misleading.

The count of 8,011 homeless is based on a standardized definition of who should be counted as homeless that is set by the U.S. Department of Housing and Urban Development, which may be compared with data reported in other regions and for the same region in previous years, which makes the data valid for tracking trends across space and time. The higher count of 9,784 reflects the results of what we believe is a reasonable expanded definition of who should be counted as being homeless that is useful for better quantifying the true size of the city's homeless population, which is specifically useful for directing how public officials and private relief organizations might use their limited resources to address problems related to the region's full homeless population.

We can show how both these aspects matter by getting into the city's actual report, rather of relying upon the LA Times account of it, where we started with the question: how many of San Francisco's residents are homeless and how many are not?

The answers to these questions are shown in the following chart, which also confirms that 1.1% of San Francisco's estimated population of 883,305 (as of July 2018) was counted as being homeless in January 2019:

The expanded definition of San Francisco's homeless population includes 472 who were in jail during the period of the January 2019 Point-In-Time count, so we decided to focus on this subset of the city's homeless population, where we wondered what percent of the city's imprisoned population they made up.

While San Francisco's four jails have a total capacity of 1,531 inmates, they hold an average of 1,330 inmates on any given day. Using that latter figure, the homeless would account for about 35% of the city's average daily inmate population:

At this point, it would be nice to know if there is a changing trend with respect to the number of homeless San Franciscans being incarcerated in the city's jails. The city's report indicates that some 299 homeless people were incarcerated in the city's jails back in January 2017, however the 2019 report also indicates that the homeless count survey's methodology significantly changed between 2017 and 2019. As such, rather than comparing apples-to-apples, the 2017 and 2019 data for the city's jailed homeless represent more of an apples-to-oranges comparison, where the two figures cannot be used to establish if any trend exists. Standard definitions matter for this reason.

One thing stands out to us in this data is the apparent rate of incarceration for San Francisco's homeless population. While 4.8% (about 1 in 20) of the city's homeless were residing in the city's jails in late January 2019, that's a relatively huge fraction of the base population compared to the incarcerated share of 0.1% for the city's non-homeless population.

The following chart expresses these percentages as the number of inmates per 100,000 of each group's base population, where we confirm that San Francisco's homeless were 49 times more likely to be in jail than the city's non-homeless population at the time of the city's 2019 Point-In-Time count of its homeless population.

That's fascinating because the city has been seeking to close one of its jails and has been implementing progressive reforms to its criminal justice system to make that possible through reduced arrests and prosecutions. In the absence of more effective law enforcement, property crimes and low-level offenses have spiked in San Francisco, making it all-but-impossible for the city officials to follow through their jail-closing ambition.

But perhaps it could if it more effectively addressed the problems posed by its homeless population and the problems that made them homeless in the first place. As it is, San Francisco's leaders seem to have made the very expensive choice to effectively dedicate a large portion of its available jail space to house about 5% of its homeless population without doing anything to reduce any of the city's crime. With the expanded numbers better describing the city's homeless population, they can develop better solutions than they have done to date to deal with all these problems.

What do you suppose the numbers would look like for Los Angeles if that city performed its own expanded count of its very large homeless population?

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July 16, 2019

We're a little over the halfway point between the Federal Open Market Committee's scheduled meetings, where the Federal Reserve's interest rate-setting body will announce a quarter point rate cut in the Federal Funds Rate at the conclusion of its next two-day meeting on 31 July 2019, its first reduction since December 2008 when it dropped to near-zero.

According to the probabilities indicated by the CME Group's FedWatch Tool, that reduction will be the first of three rate cuts in 2019, which if all are implemented as currently expected, will lower the target range for the interest rate the Fed charges banks to borrow money overnight from today's level of 2.25-2.50% to 1.50-1.75% by the end of 2019.

Using a model developed by Jonathan Wright back in 2006, at today's levels, the Federal Funds Rate combined with the ongoing inversion of the 10-Year and 3-Month U.S. Treasuries indicate a nearly 1-in-10 chance that the National Bureau of Economic Research will someday determine that a national recession began in the United States sometime between 12 July 2019 and 12 July 2020. The Recession Probability Track shows those odds as a 10% probability, which has occurred because of the sustained inversion of the U.S. Treasury yield curve since 23 May 2019.

U.S. Recession Probability Track Starting 2 January 2014, Ending 12 July 2019

The Recession Probability Track is based on Jonathan Wright's 2006 paper describing a recession forecasting method using the level of the effective Federal Funds Rate and the spread between the yields of the 10-Year and 3-Month Constant Maturity U.S. Treasuries.

Because Wright's model was developed using historic data prior to when the Fed adopted its unconventional monetary policy of quantitative easing as the Federal Funds Rate was held at near-zero levels, it doesn't take into account the effects of the reverse of that policy, quantitative tightening, which has been ongoing since May 2014, and which the Fed plans to continue into September 2019.

Measured as the "shadow Federal Funds Rate", several analysts have indicated they believe quantitative tightening would add at least three full percentage points to the nominal Federal Funds Rate if it were incorporated in that interest rate, raising it to an adjusted level of about 5.4%.

When we subsitute that adjusted Federal Funds Rate into our recession odds reckoning tool, which like our Recession Probability Track chart is based on Jonathan Wright's paper, we find the adjusted probability of recession starting between 12 July 2019 and 12 July 2020 is 40%, or rather, a chance of 1-in-2.5.

If you have a particular recession risk scenario you would like to consider, please take advantage of our recession odds reckoning tool. It's really easy, and if it helps, the average yields of the 10-Year and 3-Month Treasuries over the last 90 calendar days ending on 12 July 2019 are 2.28% and 2.32% respectively, while the average effective Federal Funds Rate over the same period is 2.40%.

If you would like to catch up on any of the analysis we've previously presented, here are all the links going back to when we restarted this series back in June 2017.

Previously on Political Calculations


July 15, 2019

At 3,013.77, the S&P 500 (Index: SPX) closed at the highest level in its history on Friday, 12 July 2019, having spent the entire day trading above 3,000 for the first time ever.

Then again, the index has achieved new record high closing values 11 times in the last four weeks. What is more notable is that investors have continued to set their forward-looking focus on 2020-Q1 in setting stock prices...

Alternative Futures - S&P 500 - 2019Q3 - Standard Model, with Redzone Forecast Between 21 June 2019 and 15 July 2019 Assuming Investor Focus on 2020-Q1 - Snapshot on 12 Jul 2019

Even though investors are now expecting the Fed to cut short term interest rates in the U.S. three times in upcoming months, with quarter point reductions expected after the Federal Open Market Committee concludes upcoming meetings on 31 July 2019, on 18 September 2019 and on 11 December 2019.

CME Group FedWatch Tool Probabilities of Federal Funds Rate Changing at Future FOMC Meeting Dates, Snapshot on 12 July 2019

Investor expectations of a fourth quarter point rate cut being announced in 2020-Q1 has been oscillating about the 50% probability mark in recent weeks, with the CME Group's FedWatch Tool indicating the probability of that event being around 35% as of the end of trading on 12 July 2019.

That's where most of the action has been for investors looking forward in time in making their current day investing decisions ahead of the earnings season for 2019-Q3 officially getting underway in the next week, as Fed officials have been 'flooding the zone' in attempting to set future expectations. Here are the market-moving headlines we extracted from the week's news, where you can see the unusually large representation of statements made by the Fed's minions among the regular flow of news on Wednesday and Thursday....

Monday, 8 July 2019
Tuesday, 9 July 2019
Wednesday, 10 July 2019
Thursday, 11 July 2019
Friday, 12 July 2019

Elsewhere, Barry Ritholtz listed 6 positives and 6 negatives he found among the week's major market and economy-related news. Barry also celebrated the fifth anniversary of his Bloomberg Radio Masters In Business - if you've been looking for a podcast focused on business and finance topics to tune in during your daily commute, do check it out!

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July 12, 2019

From 3Blue1Brown, who generated "12 oddly satisfying minutes" of animations using pure Fourier series animations:

But what is a Fourier series? That takes twice as long to explain, but if you follow the link, you'll see some of the math behind the animations featured in the video above.


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