Political Calculations
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October 27, 2016

Yesterday, the U.S. Census Bureau released its latest data on the average and median sale prices of new homes in the United States, with the newest data being reported for September 2016.

Much less noticed, the Census Bureau also revised each of the new home sale prices it previously reported over the preceding three months, affecting the data reported for June 2016, July 2016 and August 2016. Depending upon your media source, you may only have been aware of as many as two of those revisions of previous data.

Those revisions are a regular practice of the U.S. Census Bureau, which provides an initial estimate for the sale prices of new homes for each month it reports before revising it three more times over the next three months, where the fourth estimate represents the final estimate it publishes.

We became curious to see how much the estimates changed from first through fourth estimate, so we began tracking them beginning with the initial estimate published for December 2014. The results of that project are visually presented in the following chart, which shows a pretty remarkable pattern for the Census Bureau's reported median new home sale prices from their first through fourth and final estimate that receives almost no attention in the media.

Change in Median New Home Sale Price Estimates from First through Fourth Estimate

Four the 19 months for which we have four estimates of new home sale prices, spanning December 2014 through June 2016, we see that the second revision is the only one where the prices are more likely to be revised downward than upward, with 52% (10 of 19) being changed that way. After the second revision however, the upward revisions dominate, with 79% (15 of 19) of third revisions being adjusted above the second revision, and 84% (16 of 19) of fourth revisions being adjusted to be larger than the third revision.

Cumulatively, those adjustments combine to produce the result where 89% (17 of 19) of the fourth and final estimate is reported to be higher than the initial estimate. Over the period of time for our sample, the final estimate is on average some 3.3% higher than the initial estimate, although that ranges from a low of -1.5% to a high of 8.1%.

As the Census Bureau reports and revises its data, it reflects the increasing amount of information it has on the number of new home sales and their sale prices. Often, its initial estimates omit data for homes that have sold for higher prices, which tend to take longer to be reported, which would explain why the later estimates tend to be revised upward over time.

But perhaps the real question is why is that second estimate adjusted downward so much more often in comparison to later estimates?

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October 26, 2016

Periodically in the course of the various projects we're developing, we come across data that's interesting in and of itself. Today, that data is about the business of business jets, in which we're looking at the number of new business jets manufactured in the United States in the years from 2002 through the present.

Number of Business Jets Manufactured in the U.S., 2002-2015, with 2016 Projected

When new, business jets can carry price tags of anywhere between $3 million and $65 million, where at the typical sales price of $20 million for a midsize business jet, a change of just 50 sales in a single year can represent a billion dollar swing in the economy.

That makes the 55% decline in the industry that occurred in 2009 and 2010 an especially dramatic event. Lagging behind the official starting and ending dates of the Great Recession, the U.S. business jet industry effectively shrank its annual production by somewhere in the ballpark of $10 billion.

Something similar happened on a considerably smaller scale between 2012 and 2013, where the total number of business jets made in the USA fell by 10%. That microrecession directly led to Hawker Beechcraft's bankruptcy, where the company discontinued making business jets altogether as part of its subsequent reorganization. The company today is owned by Textron (NYSE: TXT), the parent company of Cessna, which manufactures a line of small to mid-size business jets.

Cessna's production was also hammered during the Great Recession, like all manufacturers, and uniquely between 2012 and 2013.

Sales of business jets were expected to improve in 2013 after being hit last year by fears of a "fiscal cliff". However, mandatory U.S. government spending cuts have made small business owners - Cessna's main customers - cautious about big purchases.

"There's rumored money sitting on the sidelines, waiting for clarity in the economy," said Jens Hennig, vice-president of operations at General Aviation Manufacturers Association (GAMA).

Global shipments of business jets fell 4 percent to 283 aircraft in the first half of 2013, according to GAMA, which represents more than 50 fixed-wing aviation aircraft makers, including Cessna.

Part of that negative business climate was directly generated by President Obama, who specifically targeted the buyers of business jets for criticism during his first term and also during the 2012 presidential debates. President Obama also proposed the budget sequester that produced the cuts in federal government spending cited by small business leaders as a leading reason for why they put off acquiring business jets during this time.

The only U.S. business jet manufacture to gain market share during this time was Gulfstream, a wholly owned subsidiary of General Dynamics (NYSE: GD), thanks largely to the introduction of two new models in late 2012, the G280 and the G650, the latter of which opened up a new niche in the business jet market: large-cabin executive jets. These new planes would fall in between the mid-size cabin aircraft manufactured by Cessna and Boeing's converted commercial transport aircraft, and proved especially popular with global customers, particularly in the Middle East.

Flashing forward to 2016 however, reports indicate that the market for Gulfstream's large-cabin business jets has begun slipping compared to previous years, while Canada's Bombardier, which manufactures Learjets and its Challenger 300/350 model in the United States, has seen sales drop by nearly one third. At the same time, Cessna's sales are projected to rise during the year, thanks in part to new models it has begun producing.

And then, there's Boeing, whose business jet business represents a small fraction of its overall sales, which are pretty stable from year to year at a very low number.


General Aviation Manufacturers Association (GAMA). General Aviation 2000 Statistical Databook. Table 1.4a. Worldwide Business Jet Shipments by Manufacturer (2002-2015). [PDF Document]. 29 March 2016.

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October 25, 2016

Once upon a time, and for a very long time, Americans could buy a single can of Campbell's Condensed Tomato Soup for the price of just one dime.

Unit Price per Can of Campbell's Condensed Tomato Soup at Discounted Sale Pricing, January 1898 through October 2016

And for much of the time when Americans could buy a can of condensed tomato soup for a dime, U.S. dimes were made of silver. Or more specifically, they were made of "junk silver", which means that they were made of 90% silver and 10% copper by weight.

Since nearly all of their value was derived from their silver content, for all practical purposes, Americans paid for their soup with silver. We wondered how many ounces of silver it would take to buy a single Number 1 can of Campbell's Condensed Tomato Soup in any month throughout its entire history, even after U.S dimes stopped being made from silver in 1965. Seeing as we have all those monthly prices for silver going back to 1880, we were able to generate the following chart showing how many fine ounces of silver bullion it would take to buy a can of Campbell's Tomato Soup in each month since January 1898, which is as far back as we have that price data.

Cost of a Single Can* of Campbell's Condensed Tomato Soup in Ounces of Fine Silver Bullion, January 1898 - October 2016

In terms of its equivalent value in silver, Campbell's Tomato Soup has become more affordable, where since U.S. price controls over silver were ended after 1967, the relative price of soup has dropped from a typical range of 0.10-0.20 ounces per can to a range of 0.02 to 0.12 ounces per can.

By contrast, the average price of a can of Campbell's Condensed Tomato Soup in U.S. dollars has risen from $0.10 in 1967 to $0.80 as of October 2016, a factor of 8X. Over the same time, the price of one fine ounce of silver has risen by 15X in terms of U.S. dollars. Meanwhile, since 1967, the price of gold is up over 35X.

Since we're coming up on Halloween, which do you suppose would be the more useful form of currency after the zombie apocalypse?

Source: CDC - http://blogs.cdc.gov/publichealthmatters/files/2011/05/blogbanner_zombieprep_560x140.jpg

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October 24, 2016

In the third full week of October 2016, the S&P 500 ended higher than it closed in Week 2 of October 2016.

And yet, the week had something of a downcast to it, as can be seen in our alternative futures chart.

Alternative Futures - S&P 500 - 2016Q4 - Standard Model with Connected Dots Overlay - Snapshot on 2016-10-21

As expected, our futures-based model's projections of the alternate paths the S&P 500 would be likely to take based on how far forward in time investors are looking was off target, which is a result of our standard model's use of historic stock prices as the base reference points from which it projects future stock prices. In this case, the indicated trajectories for the period from 18 October 2016 to 21 November 2016 represents an echo of the noisy volatility that the S&P 500 experienced a year ago.

However, our "connect-the-dots" method of compensating for the echo effect to improve the accuracy of our forecast trajectory appears to be working - at least through the first several days in which we would need it to!

But it will need to continue working over the next four weeks for it to be really worthwhile. Until then, we suspect that how we visualized the connected dots trajectory in the chart above is what really gives the week its downcast feel.

Speaking of which, here are the headlines that caught our attention during Week 3 of October 2016.

Monday, 17 October 2016
Tuesday, 18 October 2016
Wednesday, 19 October 2016
Thursday, 20 October 2016
Friday, 21 October 2016

Barry Ritholtz succinctly summarizes the positives and negatives of the week's market and economic news.

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October 21, 2016

When junk science goes unchallenged, it can have real world consequences.

In today's example of junk science, we have a case where the real world consequences involve taxes being selectively imposed on a single class of products that is commonly purchased by millions of consumers, soda pop, because of the perceived harm to people's health that is believed to result from the excessive consumption of a single one of its ingredients, sugar.

What makes this an example of junk science is the combination of ideological and cultural goals of the proponents of the city's soda tax and the inconsistencies associated with their proposed solution to deal with it, in which they are ignoring thousands of other foods and beverage products that also contain similar levels of sugar in its various forms (sucrose, fructose, et cetera), which will not also be subjected to the tax aimed at solving a perceived public health issue. The table below lists the specific items from our checklist for how to detect junk science that apply to today's example.

How to Distinguish "Good" Science from "Junk" or "Pseudo" Science
Aspect Science Pseudoscience Comments
Goals The primary goal of science is to achieve a more complete and more unified understanding of the physical world. Pseudosciences are more likely to be driven by ideological, cultural or commercial (money-making) goals. Some examples of pseudosciences include: astrology, UFOlogy, Creation Science and aspects of legitimate fields, such as climate science, nutrition, etc.
Inconsistencies Observations or data that are not consistent with current scientific understanding generate intense interest for additional study among scientists. Original observations and data are made accessible to all interested parties to support this effort. Observations of data that are not consistent with established beliefs tend to be ignored or actively suppressed. Original observations and data are often difficult to obtain from pseudoscience practitioners, and is often just anecdotal. Providing access to all available data allows others to independently reproduce and confirm findings. Failing to make all collected data and analysis available for independent review undermines the validity of any claimed finding. Here's a recent example of the misuse of statistics where contradictory data that would have avoided a pseudoscientific conclusion was improperly screened out, which was found after all the data was made available for independent review.

As part of the discussion related to today's example of junk science, you'll also see the phrase "Pigovian tax". These are named after British economist A.C. Pigou, who proposed that imposing taxes on things or activities that produce undesirable consequences would lead to less of the undesirable consequences, assuming that lawmakers set that kind of tax to the correct level to compensate for the cost of the negative consequences and impose it everywhere it needs to be imposed to achieve the intended result.

Otherwise, what you will get will closely resemble today's example of junk science, where one city's lawmakers are making a total hash out of nutrition science, public health, and tax policies.

Busybodies in the American public, never content to leave other people alone, always seem to need a common enemy to rally against. For years, it was McDonald's. Then it was Monsanto and Big Pharma. Now, it's Big Soda.

At first glance, a war on soda might appear to make sense. There is no nutritional benefit to soda. Given the large and growing segment of the U.S. populace that is obese or contracting type 2 diabetes, perhaps a Pigovian tax on soda (with the aim of reducing soda consumption) makes sense. After all, the science on sugar is pretty clear: Too much of it in your diet can lead to health problems.

But a closer look at food science reveals that a tax on sugary drinks (such as soda, sports drinks, and tea), a policy being pondered by voters in the San Francisco Bay area, is deeply misguided. We get sugar in our diets from many different sources, some of which we would consider "healthy" foods.

Taxed versus Untaxed Grams of Sugar in Selected Foods and Drinks

A 12-oz can of Coke has 39 grams of sugar. That's quite a bit. How does that compare to other foods? You might be surprised.

Starbucks vanilla latte (16 oz) = 35 grams

Starbucks cupcake = 34 grams

Yogurt, sweetened or with fruit (8 oz) = 47 grams

Homemade granola (1 cup) = 24.5 grams

Grape juice (8 oz) = 36 grams

Mango (1 fruit without refuse) = 45.9 grams

Raisins (A pathetic 1/4 cup) = 21 grams

If these food activists were consistent, they would also advocate for a tax on fruit juice, granola, and coffee. But considering that these very same activists are probably vegan, organic food-eating granola-munchers, they're not going to do that. The truth is, moderation is key to a healthy diet and preventing diseases like obesity and type 2 diabetes*. But that simple message is boring, and it doesn't excite nanny state activists.

Furthermore, if proponents of a soda tax were actually serious about reducing diseases related to poor nutrition, they would endorse a public health campaign aimed at raising awareness of the sugar content found in all foods. Or, they might endorse a Pigovian tax on all high-sugar foods. But, they won't do that, either, because it would be widely despised, as people strongly dislike paying large grocery bills. So instead, they demonize Big Soda, which is politically popular.

And that is the very definition of a feel-good policy based on junk science.

*It should also be pointed out that food choices are only one factor among many that determine whether a person becomes obese or develops type 2 diabetes. Genetics, weight, and physical inactivity also play roles.

Unfortunately, the field of nutrition science has often been the victim of pseudoscientific research and practices.

In today's example, the nutrition pseudoscience that argues that only sugary soda beverages should be taxed to deal with the negative consequences of excessive sugar consumption has intersected with the self-interest of politicians who strongly desire to boost both their tax revenues and their power over the communities they govern without much real concern about seriously addressing the public health issues that they are using to justify their policies.

The way you can tell if that's the case is what they do with the money from the taxes they collect. If any part of that money is diverted to other unrelated purposes, such as to pay public employee pensions for example, then it is a safe bet that they never believed the public health problems they said they would solve by imposing such taxes were anywhere near as great as they claimed.

And unfortunately, like the junk science on which such poor public policy is based, you often won't find out until long after the damage has been done.


Berezow, Alex. San Francisco Soda Tax: A Feel-Good Policy Based On Junk Science. [Online Article]. American Council on Science and Health. 29 September 2016. Republished with permission.


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