Political Calculations
Unexpectedly Intriguing!
December 15, 2017
Drink Containers - Source: http://www.sde.ct.gov/sde/cwp/view.asp?a=2626&q=322418

President Donald Trump drinks a lot of Diet Coke, where according to the New York Times, his daily consumption consists of as many as twelve 12-ounce cans of the artificially-sweetened, zero-calorie carbonated beverage.

That report has sent CNN into a frenzy, where the cable news channel prioritized that story over the story of the attempted terrorist pipe bomb attack in New York City's subway in its televised broadcasts on the same day.

But since that story raised questions about President Trump's health, where the effects of that apparently high level of Diet Coke consumption were called into question. The Washington Post was sucked into the story, providing a general overview of what the medical profession knows about the potential health-related risks that might arise from drinking that many cans of diet soda a day, and came away with not much insight.

It's a lot of soda to consume in one day, and — were it regular soda — most research suggests the potential consequences would be alarming. A 12-ounce can of regular Coke has 140 calories and 39 grams of sugar. By instead drinking Diet Coke, which has no calories or sugar, Trump has avoided consuming 1,680 calories and 468 grams of sugar daily.

But the effects of drinking diet soda have been long debated by experts, with some studies raising concerns about long-term health consequences. Experimental research on artificial sweeteners, like the ones found in diet soda, is inconclusive. The Canadian Medical Association Journal found in July that there are very few randomly controlled studies on artificial sweeteners — just seven trials involving only about 1,000 people — that looked at what happened when people consumed artificial sweeteners for more than six months.

Overall, most medical risks associated with high levels of diet soda consumption would appear to be very low, with the potential exception of two of its ingredients, caffeine and aspartame, where the Food and Drug Administration (FDA) and the European Food Safety Authority (EFSA) have set levels for Acceptable Daily Intake (ADI), which "is defined as the maximum amount of a chemical that can be ingested daily over a lifetime with no appreciable health risk, and is based on the highest intake that does not give rise to observable adverse effects".

We did some digging and found that the FDA sets the ADI for caffeine at 6 milligrams per kilogram of body weight per day (the EFSA sets the limit for children at half that level). Meanwhile, the FDA sets the ADI limit for aspartame, which is branded as "NutraSweet", at 50 milligrams per kilogram of body weight per day, where the EFSA sets it at 40 mg/kg/day.

That gives us enough information to be able to estimate how many cans of Diet Coke that President Trump, or for that matter, anybody, can safely drink per day to keep a low risk of adverse health effects.

So we have! In the following tool, we've used Diet Coke specific data to estimate the number of 12-ounce cans of that beverage that you might get away with drinking each day, but you are welcome to change the data to consider whatever beverage containing caffeine or aspartame you might consider drinking to work out how many units per day that you can consume within the FDA's acceptable daily intake levels. If you're accessing 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.

Diet Beverage Data
Input Data Values
Caffeine (per Unit of Consumption)
Aspartame (per Unit of Consumption)
Your Body Weight [pounds]

Number of Units That Can Be Consumed Before Exceeding the FDA's Acceptable Daily Intake Limits for...
Calculated Results Values
... Caffeine
... Aspartame

Using the tool, with the default data body weight set to be equal to what President Trump was reported to weigh at this writing in December 2017, we find that while President Trump could drink nearly 30 cans of Diet Coke and stay under the FDA's ADI guidelines for aspartame, his real daily limit is to drink the equivalent of no more than 13.8 12-ounce cans of Diet Coke per day, which would keep him within the FDA's ADI limits for "safe" caffeine consumption. At the reported dozen cans of diet soda drunk per day, President Trump is falling within those limits for his body weight.

Playing with the tool, we find that if President Trump were to lose more than 31 pounds, he would need to reduce his daily diet soda consumption to stay within the FDA's safe limits for daily caffeine intake.

As they say, it is the dose that makes the poison for any ingestible substance. Things like the concentration of ingredients within the substance being consumed and the size of the person doing the ingesting are just two of the factors that can affect the determination of what is an okay amount of consumption of any substance for an individual.

Speaking of which, the biggest factor that we haven't considered with this tool is whether diet soda is your only source for your daily caffeine and aspartame intake. The extent to which you may be ingesting additional caffeine or aspartame through other foods, beverages, medicines, etc. would reduce the amount that you would need to consume in the form of diet soda to stay within the FDA's or EFSA's guidelines.

If you don't know that extent, we would argue that it would be prudent to significantly dial back on your diet soda consumption to ensure that you don't accidentally run into the situation where you experience any of the adverse health effects that are the reason for why the ADI guidelines exist in the first place.

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December 14, 2017

The Federal Reserve did the completely expected yesterday and announced that it would increase the Federal Funds Rate, the interest rate that U.S. banks charge when loaning money to other banks overnight, by a quarter percent, raising its target range for the Federal Funds Rate to now be between 1.25% to 1.50%.

Using the FOMC's announcement to take a snapshot in time of the probability of recession in the United States, we find that through 13 December 2017, it has ticked slightly up from our last report to 0.40%.

Recession Probability Track - 2 January 2014 through 13 December 2017

With the Federal Funds Rate still effectively set at 1.16% (the midpoint of the FOMC's previous target range between 1.00% and 1.25%) and the slightly declining spread in the yields between the 10-year and 3-month constant maturity U.S. Treasuries, the probability of a recession occurring within the next 12 months dropped just a fraction of a percentage point to 0.40% from the 0.37% where we last estimated it.

As such, there is currently very little chance that the National Bureau of Economic Research will someday declare that a national recession began in the U.S. between now and 13 December 2018 according to Jonathan Wright's recession forecasting methods.

That doesn't mean however that all parts of the U.S. will be recession free. As we've seen in recent years, parts of the U.S. may indeed experience what we've described as a microrecession, where some degree of economic contraction has occurred, but which lacks the combination of scale, scope and duration needed for the NBER to recognize a recession at the national level.

Previously on Political Calculations


When it comes to the health of his state's economy, California Governor Jerry Brown has been walking on eggshells this year.

Twice each year, once in January and again in May, Gov. Jerry Brown warns Californians that the economic prosperity their state has enjoyed in recent years won't last forever.

Brown attaches his admonishments to the budgets he proposes to the Legislature – the initial one in January and a revised version four months later.

Brown's latest, issued last May, cited uncertainty about turmoil in the national government, urged legislators to "plan for and save for tougher budget times ahead," and added:

"By the time the budget is enacted in June, the economy will have finished its eighth year of expansion – only two years shorter than the longest recovery since World War II. A recession at some point is inevitable."

It's certain that Brown will renew his warning next month. Implicitly, he may hope that the inevitable recession he envisions will occur once his final term as governor ends in January, 2019, because it would, his own financial advisers believe, have a devastating effect on the state budget.

Unfortunately for Governor Brown, the recession he fears may already have arrived in California.

The following chart showing the trailing twelve month averages of California's civilian labor force and number of employed is one that we've adapted from a different project to show that data in the context of the state's higher-than-federal minimum wage increases and periods of negative GDP growth for the national economy. It shows that in 2017, the size of the state's labor force has peaked and begun to decline in 2017, while the number of employed shows very slow to stagnant growth during the year.

California (Age 16+) Labor Force and Total Employed, Trailing Twelve Month Averages, January 2004 - October 2017

The data for this chart is taken from the summary tables for the state's monthly reports on the California Demographic Labor Force, which are produced by California's Employment Development Department. These are therefore the same numbers that Governor Brown sees, and they have been signaling throughout 2017 that the state's economy is going through a period of stagnation after having generally grown since bottoming in mid-2011 following the Great Recession.

The labor force and employment numbers aren't telling the full story however, which becomes evident when we factor in the state's growing population. The following chart shows the labor force and employment to population ratios for the state's civilian work force.

California Trailing 12 Month Averages of Labor Force and Total Employed as Percentage of Noninstitutional Civilian Population, June 2004  - October 2017

In this chart, we find that California's employment to population ratio peaked at 59.2% in December 2016, having slowly declined to 59.0% through October 2017. Meanwhile, California's labor force to population ratio last peaked at 62.6% in October 2016, which has since dropped to 62.1% a year later.

Going by these measures, it would appear that recession has arrived in California, which is partially borne out by state level GDP data from the U.S. Bureau of Economic Analysis:

Last year was a very good one for the state’s economy. The 3.3 percent gain in economic output in 2016 was more than double that of the nation as a whole and one of the highest of any state.

However, California stumbled during the first half of 2017. California’s increase was an anemic six tenths of one percent in the first quarter compared to the same period of 2016, and 2.1 percent in the second quarter, well below the national rate and ranking 35th in the nation.

The report revealed that almost every one of California’s major sectors fell behind national trends in the second quarter, with the most conspicuous laggard being manufacturing.

On a final note, the charts we've featured above were adapted from our project tracking the impact of California's minimum wage hikes on its teen labor force, where we've been that labor force and employment data since July 2003 (which hopefully helps explain why the trailing 12 month labor force and employment to population ratio chart starts showing data beginning in June 2004). As bad as the charts above are for California's labor force, the employment situation for California's teens is much worse, having itself peaked in October 2016.

California Teen (Age 16-19) Labor Force and Total Employed, Trailing Twelve Month Averages, January 2004 - October 2017

California's teens are best thought of as being the proverbial canaries in the coal mine.


December 13, 2017

How well are typical American households faring through the third quarter of 2017?

To answer that question, we're going to turn to a unique measure of the well-being of a nation's people called the national dividend. The national dividend is an alternative way to measure of the economic well being of a nation's people that is primarily based upon the value of the things that they choose to consume in their households, which makes it very different and by some accounts, a more effective measure than the more common measures that focus upon income or expenditures throughout the entire economy, like GDP, which have proven to not be well suited for the task of assessing the economic welfare of the people themselves.

To get around that problem, we've developed the national dividend concept that was originally conceived by Irving Fisher back in 1906, but which fell by the wayside in the years that followed because the government proved to not be capable of collecting the kind of consumption data needed to make it a reality for decades. And then, it wasn't until we got involved in 2015 that anybody thought to try it, where we've been able to make the national dividend measure of economic well-being into a reality.

With that introduction now out of the way, let's update the U.S.' national dividend through the end of September 2017 following our previous snapshot which was taken for data available through April 2017.

Monthly National Dividend, January 2000 through September 2017

We find that the third quarter of 2017 has seen some of the most robust increases in the national dividend in 2017, which itself has been an improvement over what happened to it in 2016, where the national dividend actually declined in the latter half of that year.


This is the first update that we've had since June 2017, which is a direct consequence of Sentier Research's termination of its monthly household income estimates data series after May 2017. We had suspended our presentation of our national dividend estimates until we developed a viable substitute for this original data source, which we've been test driving for this application behind the scenes.

What we've found so far is that our estimates for the national dividend are conservative in the period from 2015 onward, in that we believe that they are understating the amount of consumption by U.S. households, which we believe is a consequence of a change in methodology by the U.S. Census Bureau for how it collects the source data we use in our calculations. We do not as yet have enough data to establish the extent to which our estimates of national income may be understated, which we're continuing to collect and review behind the scenes. We do believe however that our measure is capturing the overall picture for the direction of the national dividend, which perhaps is a more useful indication of the relative well-being of typical American households that can be determined by this kind of analysis.

Previously on Political Calculations

The following posts will take you through our work in developing Irving Fisher's national dividend concept into an alternative method for assessing the relative economic well being of American households.


Chand, Smriti. National Income: Definition, Concepts and Methods of Measuring National Income. [Online Article]. Accessed 14 March 2015.

Kennedy, M. Maria John. Macroeconomic Theory. [Online Text]. 2011. Accessed 15 March 2015.

Political Calculations. Modeling U.S. Households Since 1900. 8 February 2013.

U.S. Bureau of Labor Statistics. Consumer Expenditure Survey. Total Average Annual Expenditures. 1984-2015. [Online Database]. Accessed 7 February 2017.

U.S. Bureau of Labor Statistics. Consumer Price Index - All Urban Consumers (CPI-U), All Items, All Cities, Non-Seasonally Adjusted. CPI Detailed Report Tables. Table 24. [Online Database]. Accessed 15 November 2017.

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December 12, 2017

Since the end of the first quarter of 2016, the S&P 500 has experienced a relatively stable period of order, where the variation of stock prices with respect to the mean trend curve established from the relationship between stock prices and their trailing year dividends per share has generally followed a standard normal distribution.

When we last reported on the status of the current period of order several months ago, the level of the S&P 500 had dropped to the point where stock prices were within one standard deviation of falling below a level that would indicate that the period of order was at very high risk of breaking down. Today, we can confirm that the S&P 500 has instead reverted back to the mean trend curve that defines its current period of order.

S&P 500 Index Value vs Trailing Year Dividends per Share, 30 September 2015 through 8 December 2017, with period of order since 31 March 2016

So in case you've ever wondered what "reverting to the mean" really means where stock prices are concerned, what has happened with the S&P 500 from 21 August 2017 to 8 December 2017 can be considered to be a textbook example of mean reversion.

And in case you're wondering what it means when stock prices move outside the outer limits described by this kind of analysis, where order really does break down (as opposed to simply being the result of statistical outliers in a continuing trend), the ultimate textbook example involves the ultimate sell signal.

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December 11, 2017

The S&P 500 behaved more as we expected that it would during the first full week of December 2017, with stock prices dipping as investors shifted their forward looking focus to 2018-Q1 in setting current day stock prices.

Alternative Futures - S&P 500 - 2017Q4 - Standard Model - Snapshot on 08 December 2017

But ended up on Friday, 8 December 2017 at a level that would at first appear to be more consistent with their being focused on 2018-Q2. The reason for that has a lot to do with the positive jobs report that came out on Friday, 8 December 2017, which had the official unemployment rate hold steady from the previous month at 4.1%, but which is down a half percent from November 2016. The report was stronger than expected, which appeared to clear the way for the Fed to not just announce that they will hike U.S. short term interest rates this Wednesday, 13 December 2017, but up to three more times in 2018.

The CME Group's FedWatch tool is reflecting that assessment, where after a 100% probability that the Fed will hike rates on this Wednesday (with a 90.2% chance they'll hike them to a target range of 1.25%-1.50%, and a 9.8% chance they'll hike them even higher to the 1.50%-1.75% range), the Fed Funds Rate futures suggest additional hikes in at least the first quarter of 2018 (2018-Q1) and again in the third quarter of 2018 (2018-Q3).

Probabilities for Target Federal Funds Rate at Selected Upcoming Fed Meeting Dates (CME FedWatch on 8 December 2017)
FOMC Meeting Date Current
100-125 bps 125-150 bps 150-175 bps 175-200 bps 200-225 bps 225-250 bps
13-Dec-2017 (2017-Q4) 0.0% 90.2% 9.8% 0.0% 0.0% 0.0%
12-Mar-2018 (2018-Q1) 0.0% 38.6% 54.8% 6.5% 0.1% 0.0%
13-Jun-2018 (2018-Q2) 0.0% 17.9% 44.7% 31.8% 5.3% 0.3%
26-Sep-2018 (2018-Q3) 0.0% 10.3% 32.8% 36.5% 16.9% 3.2%

Since no hike in the Federal Funds Rate would appear to be anticipated for 2018-Q2 at this time, investors have little reason to focus much of their forward-looking attention on this future quarter, which is why we think that they are now primarily focusing on 2018-Q1, where the level of the S&P 500 is still falling within the range that we would anticipate they would be in that situation.

In any case, this upcoming week will be a big one for markets as the Fed acts and also because we'll start getting our first look at what the future holds for dividends through the end of 2018. In the meantime, here are the market-moving headlines that caught our attention during Week 1 of December 2017.

Monday, 4 December 2017
Tuesday, 5 December 2017
Wednesday, 6 December 2017
Thursday, 7 December 2017
Friday, 8 December 2017

The invaluable Barry Ritholtz provides an overview of the positives and negatives for the U.S. economy and markets in the first full week of December 2017.

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