Political Calculations
Unexpectedly Intriguing!
June 30, 2016
The Pengagon - Source: https://www.hirono.senate.gov/tours

Not long ago, we built a tool to estimate the economic impact of new jobs, where we focused on what the economic footprint that particular industries might have if they were to start doing business in a community. Shortly after that, we uncovered just how much of the GDP of the United States has come about in recent years from contractors supporting U.S. military operations and civilian government activities overseas.

That got us wondering about the economic contribution of the U.S. military within the United States to the communities where it maintains bases, so we wondered if we could rework our original economic impact tool to do that math.

So we did! We estimated the number of jobs that are generated within communities that have a significant military presence, coming up with a figure between 4.0 and 4.6 per active duty personnel.

That's high compared to what we saw for the private sector oil and aerospace industries, but that also reflects the unique nature of the military's activities, which require higher levels of support for its labor and logistics-intensive operations that often involves highly specialized equipment and ordnance.

That high figure also accounts for why local and state elected officials vigorously compete to put military bases within their districts and states, and also why they just as vigorously fight military base closures so fiercely.

The rest of the economic impact math is pretty similar to what we did previously with our new jobs economic impact tool, so we've simply dropped some military specific values for a small community as our tool's default values. If you have a specific scenario you would like to consider, just swap out our default numbers with ones that apply for your situation. In case you're reading this article on a site that republishes our RSS news feed, please click through to our site to access a working version of the tool below.

New and Existing Job Data
Input Data Values
Number of Active Duty Personnel Being Added to the Community
Average Annual Income for New Jobs Being Directly Added by the Military
Average Annual Income of Other Jobs in the Community
Number of Other Local Jobs That Will Be Generated for Every Active Duty Service Member
Military's Projected Economic Output for Work Done in Community

Economic Impact of New Jobs in Community
Calculated Results Values
Total Annual Income from Jobs Directly Provided by the Military
Estimated Number of Additional Other Jobs Created in Community
Total Annual Income from Additional Jobs Generated in Community
Combined Annual Income from All Jobs Added to Community
Total Annual Economic Contribution of the Military to the Community

As with our private sector economic impact tool, our military economic impact tool will also consider the cost to a community for a base closure or reduction in active duty personnel stationed within the community.

But for the communities that score new military facilities, there's big reason for excessively elaborate ribbon-cutting ceremonies!

Dignitaries join Oregon Army National Guard Maj. Gen. Raymond F. Rees, The Adjutant General, Oregon (center), for the official ribbon cutting ceremony during the open house at the MSG Gunnar Larson Armory in St. Helens, Ore., Oct. 22. Source: https://www.oregon.gov/OMD/pages/pressrelease/2010/10-22-10press.aspx


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June 29, 2016

Although the data for recent months is still preliminary, it appears that the rapid inflation phase of the second bubble for new home prices in the U.S. ended in September 2015.

The second bubble for new home prices in the U.S. had gone through two primary phases. The initial inflationary phase of the second U.S. housing bubble saw the trailing year average of median new home sale prices escalate by $25.37 for every $1.00 that U.S. median household income rose in the period from July 2012 through July 2013. After a brief transition period, the second U.S. housing bubble entered into a second inflationary phase, where median new home sale prices rose by $11.17 for every $1.00 that U.S. median household income rose in the period from January 2014 through September 2015.

But since September 2015, it appears that the rate at which median new home prices are rising with respect to median household income is consistent with the rates that we've observed for the U.S. housing market outside periods of housing bubbles.

U.S. Median New Home Sale Prices vs Median Household Income, Monthly: December 2000 through May 2016, Annual: 1999 through 2015

Since September 2015, the trailing year average of median U.S. new home sale prices has been rising at a rate of $3.26 for every $1.00 that median household income has increased. This current average rate of increase with respect to median household income compares to the following non-bubble growth rates for median new home sale prices that we've observed in the historic data:

  • December 2010 to July 2012: An increase of $3.34 for every $1.00 that U.S. median household income increased.
  • 1987-1999: An increase of $3.60 for every $1.00 that U.S. median household income increased.
  • 1967-1986: An increase of $4.07 for every $1.00 that U.S. median household income increased.

The following chart shows all the available median new home sale price and median household income data we have going back to 1967.

U.S. Median New Home Sale Prices vs Median Household Income, Monthly: December 2000 through May 2016, Annual: 1967 through 2015

In terms of affordability, a median new home costs over $103,500 more in 2016 than what the median new home built in the pre-U.S. housing bubble years from 1987 through 1999 would have cost if not for the inflationary impact of the U.S.' two inflationary housing bubbles in the years from 2000 through 2015, most of which would seem attributable to the U.S.' most restrictive local housing markets.

Data Sources

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [Excel Spreadsheet]. Accessed 27 June 2016.

Sentier Research. Household Income Trends: May 2016. [PDF Document]. 23 June 2016. [Note: We have converted all the older inflation-adjusted values presented in this source to be in terms of their original, nominal values (a.k.a. "current U.S. dollars") for use in our charts, which means that we have a true apples-to-apples basis for pairing this data with the median new home sale price data reported by the U.S. Census Bureau.]

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June 28, 2016

The U.S. Federal Reserve released its latest Flow of Funds report for the U.S. economy back on 9 June 2016, which we're finally getting around to today to give us a better idea of how the U.S. economy performed in the first quarter of 2016.

Based on what we see, the U.S. economy is continuing to show signs of moving toward positive acceleration after the year over year change in the compounded rate of growth of private debt in the U.S. bottomed in mid-2015.

Acceleration of Private Sector Debt in the United States, January 2006 through March 2016

It is likely that positive impulse carried into 2016-Q2, which means that the performance of the U.S. economy likely improved over 2016-Q1, although it would still be mired in slow growth. That the acceleration of private debt in the U.S. has been continuously negative since mid-2014 through the first quarter of 2016 marks the longest period of time that situation has existed since the Great Recession.

With the BEA poised to issue its annual revision in its GDP figures near the end of the next month, we may need to revise this analysis to reflect that updated data. The Fed will release its next update of its flow of funds data on 16 September 2016.

Previously on Political Calculations

Data Sources

U.S. Federal Reserve. Data Download Program. Z.1 Statistical Release (Total Liabilities for All Sectors, Rest of the World, State and Local Governments Excluding Employee Retirement Funds, Federal Government). 1951Q4 - 2015Q4. [Online Database]. 9 June 2016. Accessed 27 June 2016.

U.S. Bureau of Economic Analysis. Table 1.1.1. Percent Change from Preceding Period in Real Gross Domestic Product. 1947Q1 through 2015Q4 (second estimate). [Online Database]. Accessed 27 June 2016.

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June 27, 2016
Market Chaos! Run!

If you want to know where stock prices are going to go next, you need to know three things:

  1. What stock prices are today.
  2. What the expectations are for the amount of dividends that will be paid out in future quarters today.
  3. How far into the future investors are focusing when they make their investment decisions today.

If you know those three things, you have a decent shot at being able to predict the future trajectory of stock prices, assuming that no unusual amounts of speculative noise are at work in the stock market.

The first two are not hard to figure out. You can easily look up stock prices and also the values of the dividend futures contracts that will give you an indication of what dividends that investors reasonably expect will be paid out in future quarters. You can even uses contemporary news reports to identify how far forward in time investors are focusing their attention.

But the holy grail of being able to tell exactly where stock prices are going to go in advance of their getting there is being able to tell in advance when investors are going to suddenly shift their forward-looking focus from one point of time in the future to another. The occurrence of those kinds of events are quintessentially random in nature, and when they happen, they are often associated with sudden and very large movements in stock prices. Instead of just pacing along a garden variety random walk, they suddenly erupt into a full Lévy flight, or as we've come to understand them, a quantum random walk.

When they happen, they are a sight to behold. Last Friday's Brexit event provided an excellent case study for such an event, where investors appear to have shifted their attention from the distant time horizon of somewhere between 2017-Q1 and 2017-Q2 to the much nearer term future of 2016-Q4, with U.S. stock prices following along accordingly.

Alternative Futures - S&P 500 - 2016Q2 - Standard Model - Animation: 7 April 2016 through 24 June 2016

In the animated image above, we're showing the trajectory of the S&P 500 in the period from 7 April 2016 through 24 June 2016, with respect to the alternate levels it might be based upon the historic value of stock prices and the expectations for dividends in future quarters. [If you're reading this article on a site that republishes our RSS news feed and the animation doesn't play, you may want to click through to our site to see the original animation. For it to play, you will need to use a modern web browser with JavaScript enabled].

Every time you see the lines move in this animation, you're seeing the effect of the changing expectations for the future. When you see a sudden shift in the value of stock prices, you're seeing the effects of investors changing their time horizon in making their current day investment decisions in response to the random onset of market moving news events.

The Brexit event isn't the only dramatic example of this factor that directly drives the volatility of stock prices at work that we can present. It was also clearly apparent 10 months earlier, during China's August 2015 stock market meltdown - here's our animation of that event.

Alternative Futures - S&P 500 - 2015Q3 - Rebaselined Model - Animation: 28 July 2015 through 28 August 2015

Not uncoincidentally, the Brexit event represents the most the U.S. stock market has declined in a single day since the China event 10 months earlier. And in truth, the reason it wasn't bigger is because there is less of a difference in the expectations for future dividends between the respective future quarters that investors shifted their attention from and the future quarters they shifted their focus toward.

Update 27 June 2016, 6:00 PM EDT: And now, investors are looking more intently at the defacto current quarter of 2016-Q3....

Alternative Futures - S&P 500 - 2015Q3 - Standard Model - Snapshot 2016-06-27

Having already mentioned market moving news events, here are the headlines that caught our attention in Week 4 of June 2016 - the week when the Brexit vote caused investors to reel in their forward-looking attention to a less distant point of time in the future.

Monday, 20 June 2016
Tuesday, 21 June 2016
Wednesday, 22 June 2016
Thursday, 23 June 2016
Friday, 24 June 2016

Events like last Friday's are why we make a point of keeping track of certain contemporary news stories.

Previously on Political Calculations

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June 24, 2016

Most people don't realize this, but the entire science of economics is really about cows.

Really! Just consider the following list of economic systems that have been proposed, which we've grafted together from a several different sources, and which nearly all begin with a single scenario, where you have two cows....

Anarchism

  • You have two cows.
  • Either you sell the milk at a fair price or your neighbors try to take the cows and kill you.

Bureaucracy

  • You have two cows.
  • Under the new farm program the government pays you to shoot one, milk the other, and then pours the milk down the drain.

Capitalism

  • You have two cows.
  • You sell one and buy a bull.
  • Your herd multiplies, and the economy grows.
  • You sell them and retire on the income.

Communism

  • You have two cows.
  • The government seizes both and provides you with milk.
  • You wait in line for hours to get it.
  • It is expensive and sour.

Fascism

  • You have two cows.
  • The government takes both of them and hires you to take care of them, and sells you the milk.

Socialism

  • You have two cows.
  • The government takes one and gives it to your neighbor.
  • You form a cooperative to tell him how to manage his cow.

Totalitarianism

  • You have two cows.
  • The government takes them and denies they ever existed.
  • Milk is banned.

So what is it about cows that make them so useful for demonstrating different concepts like these different systems of allocating resources in economics?

The short answer is once you've grasped the concept of having two cows, you suddenly have a stake in understanding the concepts of supply and demand that drive real world events wherever resources are scarce and must be allocated by some means, and ideally, the most effective means that make the most people happy.

And as you're about to see, that can be a real challenge. Just consider the following news story from July 2012, where the effect of an especially severe period of drought in U.S. farm states created similarly severe shortages of feed grains for the nation's beef cattle, which created a very painful situation in those states where cattle ranching represents a big part of their agricultural economy.

But the impact of the drought that forced farmers to either sell off more of their cattle herds for slaughter than they really wanted to or else go bankrupt didn't end when the rains returned.

And in fact, the negative impact has endured for years. The accelerated slaughter of beef cattle in 2012 and 2013 caused the supply of cows to fall to reach a 63-year low in 2014, which in turn, caused their price to increase because the demand for beef did not fall enough with respect to the available supply to keep from rising. This is the reason why Americans have seen such high prices for beef in the supermarket during the last few years.

So when the rains returned, easing the shortage of feed grain and thereby allowing cattle farmers to regrow their herds, some people with highly deficient thinking might think that situation would be almost immediately remedied. Such people would be wrong, as other facts of nature would ensure a prolonged depression in beef production, which would begin with an even greater negative impact in the near term, as income would be deferred today as the price of investment for being able to realize more income through greater growth in the future.

The number of young, female cattle held back for breeding probably rose 3.1 percent to 5.53 million head, according to the Bloomberg survey. Beef supplies will keep falling because those heifers aren’t going to the feedlot, said John Nalivka, president of Sterling Marketing Inc., an agricultural economic research and advisory company in Vale, Oregon.

“It’s a real ironic situation that most people wouldn’t think about,” Nalivka said. “At the initiation of herd expansion, you actually reduce your production. That means we’re going to have tight beef supplies for the next two to three years.”

Expanding the U.S. herd is a slow process. Calves have nine-month gestation periods and take 20 months to 22 months to reach slaughter weight, according to Ron Plain of the University of Missouri in Columbia. Animals typically are fattened on corn until they weigh about 1,200 pounds (544 kilograms), when they are sold to meatpackers. The calf crop probably declined to 33.57 million head, down 2.1 percent from a year earlier, the Bloomberg survey showed.

As a result of those considerations, at a minimum, the shortage of beef cattle that was caused by a shortage of feed grain that itself was caused by an especially severe multi-year drought would not begin to recover for a nearly three year long period of time.

Coincidentally, that is exactly what we see now beginning to happen in the USDA's data for U.S. beef production. The following chart spans a little over 10 years of time, from January 2005 through April 2016, which allows us to consider the impact of a couple of major shocks to the economy.

U.S. Beef Production, January 2005 - April 2016

Amazingly, where U.S. beef production is concerned, the negative impact of the most severe period of drought from 2011 through mid-2014 was nearly three times greater than the negative impact of the so-called Great Recession from January 2008 through June 2009 upon the nation's cattle farms.

It has already lasted much longer. For now, it appears to have reached the point where it has started to turn the corner and begin growing again. It will however still be several years before a full recovery can be said to have achieved. Assuming no new climate change shocks or national recessions whack the market environment for cows again in the meantime.

Update 17 July 2016: The negative real economic shock of drought also appears when we drill down into the available data for individual states with a substantial beef cattle industry. Here, because the USDA doesn't break out beef production by state, we need to substitute the inventory of cattle on feedlot, which is the final stage of live cattle production where beef cattle are finished before being processed into beef products. The chart below applies for the state of Kansas, which was at the epicenter of severe-to-extreme drought in the U.S. during the period from 2010-Q4 through 2014-Q2.

Kansas Cattle on Feedlot (Capacity: 1,000+ Head), January 2005 - May 2016

The data confirms that Kansas' inventory of cattle was decimated as a direct outcome of the prolonged period of drought that it experienced. For Kansas' agricultural industry, that impact is especially significant because the state's beef cattle industry is responsible for generating anywhere from one-half to two-thirds of the entire agriculture industry's total cash receipts in any given year.

It's rather amazing to see the desperate lengths to which some have gone in attempting to pin the full blame of Kansas' poor economic performance in recent years on the state's fiscal policies(!?!), rather than even consider that a substantial portion of that performance resulted from the contribution of other factors. Like an extreme, prolonged period of drought....

Kansas Statewide Average Palmer Drought Severity Index and Real GDP (Agriculture, Forestry, Fishing & Hunting), 2005-Q1 through 2015-Q4

Believe it or not, there are those who have used methods indistinguishable from junk science to dismiss the large and prolonged negative impact that the especially severe drought of 2012-2013 has had upon the economy of the states whose economies were most affected by it, who claim that the very real climate change event of drought had no significant or sustained real effect upon their economies.

As you might imagine, such people are little more than modern day Lysenkoists - the kind of super creepy people so committed to a bizarre political agenda that they don't notice how disconnected they have become from reality, much less how they have fully beclowned themselves in becoming real life climate change deniers.

We're not sure yet how to fit such people into a two cow framework, but we do know how to have fun at the expense of their many mistakes. Which we will do at our leisurely convenience, unless they should miraculously demonstrate that they have the ethical integrity to own up to them first.

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June 23, 2016
Market Chaos! Run!

If we go by media reports, there is a very fine line between ho-hum and major fear in the U.S. stock market as it considers the potential outcome of the United Kingdom's popular referendum today on "Brexit", in which the British people will state their preference to either remain part of the European Union or will declare that they no longer wish to remain part of Europe's dominant economic and monetary union.

Here is a case in point from yesterday's headlines, courtesy of Reuters:

Wall Street flat, all eyes on Brexit vote

From that headline, you would expect that Wall Street isn't very emotional at all on the topic of Brexit. If you looked at how U.S. stock prices traded on that day, you would find that they fell by 3.45 points, or 0.165%, on the day before the U.K.'s historic vote.

If you want to use an adjective to describe that level of change from the previous day's close in the market, flat is a pretty good one to choose.

Now, compare that headline with the following one that Reuters produced just over a week ago:

Wall Street falls as Brexit vote becomes major fear

From that headline, you would reasonably expect there to have been major market carnage on Wall Street that day, wouldn't you?

There certainly was, if your threshold for major market carnage in the U.S. stock market involves the S&P 500 plunging downward by 3.74 points, or by 0.180%, from its previous day's closing value.

Clearly, where the the most mainstream of media is concerned, there is a very fine line between ho-hum flatness and outright fear in the markets. It just happens to fall somewhere within the 0.29 point gap between a market index that falls by 0.165% on a day defined by what might be described as mildly watchful apprehension and one that falls by 0.180% from the previous day on a day filled with "major fear"!

Update 24 June 2016, 9:24 AM EDT:

Are you ready for blood running in the streets panic - at least, if we go by Reuters' measure of fear? Via Barry Ritholtz, here are the pre-market futures following the actual Brexit vote:

Pre-24 June 2016 Market Futures, via Barry Ritholtz - Source: http://ritholtz.com/2016/06/brexit-meltdown/

Barry writes:

We haven’t seen numbers like this since the financial crisis — although to be fair, these numbers bring us in the USA back to where we were on Monday, prior to the rally this past week; Europe seems to be getting punished to a much greater degree.

As a heads up for what's going to happen in today's stock market action, we're about to get a case study on what happens to U.S. stock prices when investors suddenly shift their forward looking focus from one point of time in the future to another. In this case, from the distant future to the much nearer term. This will be evident today as a direct result of the Brexit vote outcome.

Where the U.S. stock market is concerned, nothing has changed with respect to the expectations for the amount of dividends that will be paid out in the future - at least, as yet, and thus, nothing has changed with respect to the alternative trajectories that U.S. stock prices might take, except just how far forward into the futures are looking. If you want to know where stock prices are going to go, figure out how far into the future investors are looking (use the following chart as your guide, in which we've sketched in how the stock price futures for the S&P 500 stand before the market opens.)

Alternative Futures - S&P 500 - 2016Q2 - Standard Model - Snapshot 24 June 2016, pre-open

We've been through this kind of rodeo with our model's performance before, back when China had its meltdown in August 2015. There will also be a wild card speculative element (noise) in today's trading, but the main shift in the trajectory of stock prices should become pretty apparent over the next several trading days, if not sooner.

As for what to expect, assuming no new unexpected events impact the market, should investors remain focused on either the near term future defined by 2016-Q3 or 2016-Q4, the S&P 500 is likely within 1-2% of where it will end the day. It is certainly possible that an outburst of speculative noise might erupt in the market, which could take it down by an additional 4% from where it looks set to open, but the immediate impact of the Brexit event itself will likely fade during the day, leading stock prices to stabilize.

It is also possible that the world's central banks will take an action that will succeed in refocusing the attention of investors on the more distant future, which would be accompanied by a significant rally.

We'll have fun watching how it all plays out!

Update 24 June 2016, 9:38 AM EDT:

Via Eddy Elfenbein's Twitter feed:


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June 22, 2016

Updates! Scroll down....

How much will U.S. GDP most likely be revised when the U.S. Bureau of Economic Analysis publishes its annual revision to the nation's real GDP on 29 July 2016?

We started working on that question last Thursday, the day after the BEA released its revision of GDP data for the individual 50 states and the District of Columbia, when we identified the "maximum potential" size of the revision to be a -2.0% decline from its value that was recorded at the end of 2015.

We updated that post two days later to take into account the contribution to national GDP from the U.S. government's overseas military and civilian activities, which add to the GDP contributed by the 50 states and the nation's capital to be equal to what the BEA should report for the nation's entire GDP. (Although we did that work last Friday, we only just featured that contribution to national GDP in the period from 2005-Q1 through 2015-Q3 yesterday.)

We then used that information along with the BEA's just-revised data for the individual 50 states plus DC to determine the "maximum likely" size of the upcoming revision to the nation's real GDP. The chart below reveals what we found.

Previously Reported and Revised Real GDP, 2005-Q1 Through 2015-Q4, per BEA Regional Data released on 2016-06-14, Revised to Account for 'Overseas' GDP, with Date Correction - was 14 June 2015, now corrected to 14 June 2016 - previous chart here: https://2.bp.blogspot.com/-EzKqOVcLGC4/V2XJce71MhI/AAAAAAAANkk/uxCWYmwSK98c6baRUFRi1-NmNArdwz1qgCLcB/s1600/Political-Calculations-2016-GDP-Revision-Projection-spanning-2005Q1-to-2015Q4.png

But the "maximum likely" revision of -1.4% of previously reported GDP through 2015-Q4 is not the "most likely" size of the upcoming revision to the nation's GDP will be, because the BEA's plans for the revision of the national level GDP data will only cover the period from 2013-Q1 through 2016-Q1.

That means that it will miss the discrepancy that opens up in 2012-Q3 and 2012-Q4 between the just-revised state level GDP and previously indicated overseas federal GDP and its previously recorded national level GDP. That discrepancy is just over $55.1 billion in terms of constant 2009 U.S. dollars in 2012-Q4, which itself is over 24% of the full $225.7 billion discrepancy that our previous calculations indicates between the pre-revised national level real GDP and the post-revised state level GDP data through 2015-Q3.

Because the BEA won't be including that $55.1 billion portion of the discrepancy from 2012, the "most likely" size of the revision that it will report at the end of July 2016 is therefore -1.1%, which is 24% less than the "maximum likely" revision of -1.4% we previously calculated.

Our "most likely" estimate assumes however that the BEA's estimates of the contribution to national GDP from the U.S. government's overseas military and civilian activities will not greatly change from what it has previously indicated. Should the BEA revise its estimates of this component of nation real GDP, the actual size of the BEA's upcoming revision to the national GDP will entirely depend upon how that single factor might change.

In the case that it turns out that more GDP than previously indicated was generated through supporting the U.S. government's various overseas activities, the actual magnitude of the revision will be smaller than what we've now indicated the "most likely" size of the revision to be, and vice versa for the opposite scenario.

So if you want to place your bets on the over or under, all you need to do is to take your best guess as to just how much more or less of the nation's real GDP has been generated through supporting the U.S. government's activities overseas than what the BEA has previously indicated. To make it interesting, we've set up an online survey where you can put in your two cents and also find out what the consensus is for all those who have answered that single question!

Update 27 July 2016: This is so cool! We had an extended contact today with an analyst who works for the BEA, who wanted to know more about how we came up with our estimate of how real GDP would change using the BEA's recently revised regional account data.

That was fantastic timing, because we just happened to have our spreadsheet open because we were updating it with state level GDP data from 2016-Q1 that was just released today.

In going over that material, we discovered a problem that threw off our calculations, with the effect that the results we had obtained weren't matching what they were getting from 2014-Q3 onward in replicating our analysis. We were able to trace the problem back to the GDP deflator that we used to convert nominal GDP data to inflation-adjusted "real" data, where we were multiplying the nominal data by the GDP deflator data for the national level data (the data whose revision is set to be published on Friday, 29 July 2016) instead of the GDP deflator data that applies for the aggregate 50 states plus Washington DC, which just happened to be in the spreadsheet column next to it.

After we made the appropriate correction, all our results from 2014-Q3 onward snapped into place and all results matched, from the period from 2005-Q1 through 2014-Q2, where there was never any problem, and now from 2014-Q3 through 2015-Q4! The following chart shows the latest and greatest for what we expect from Friday's GDP revision based only on the state level GDP revision from June!

Previously Reported and Revised Real GDP 2005-Q1 Through 2015-Q4 (Updated 27 July 2016)

As for the outcome of the analysis, the error we made with using the incorrect GDP deflator overstated the amount by which real GDP is likely to be revised by 0.5% of GDP, so instead of the maximum likely change of -1.4% that we had previously calculated, the maximum amount by which national GDP might change as a result of the revisions the BEA has made to its GDP data for the 50 states plus Washington DC is -0.9%, with the maximum discrepancy now taking place in 2013-Q3. This data is indicated in the chart above by the dark-green line.

But since the BEA's national revision will cover the period from 2013-Q1 to the present, the revision of the national level GDP will not include the now-confirmed $55 billion discrepancy that opens up between the national GDP data and the national aggregate state level GDP in 2012. We are therefore now estimating that the most likely revision that will be made to the national GDP data on Friday, 29 July 2016 will be an adjustment of -0.6% in 2013-Q3. This data is indicated in the chart above by the bright red line (and the blue arrow at 2013-Q3).

We'd like to thank everyone who provided their useful assistance in getting to this point - in terms of collaborative effort, this has been one of the biggest projects we've had the pleasure of working on since launching Political Calculations. It's always exciting when we get to break brand new ground and do analysis that was never possible before, and we appreciate your shared enthusiasm!

On a final note, if you happened to have come across this post by way of Econbrowser, you might want to pass along information back to the author who pointed you in this direction that their observations have been described as "not relevant". We're pretty sure that particular author hears that a lot....

There's more that we'd like to be able to discuss on the topic of the upcoming national-level GDP revision, but that will have to wait until after that data is released. Until then, what you see above represents the most that anyone can reasonably glean about what the revision will look like based only on data that is already available to the public.

Update 29 July 2016: The verdict is in! The chart below shows the revisions in national level real GDP from 2013-Q1 through 2015-Q4....

Previously Reported and Revised Real GDP, 2005-Q1 through 2015-Q4 (29 July 2016)

Compared to our final pre-revision prediction from 27 July 2016, we were off by 0.1% of GDP through 2015-Q4, where we had previously projected no change.

More significantly however, national-level real GDP was increased by 0.2% of its previously reported figure in 2013-Q3, where the aggregate GDP data for the 50 states and the District of Columbia had instead indicated that a 0.6% of GDP decline for that quarter was most likely. That means that the amount of GDP that the U.S. generated in that quarter from Overseas Federal Military and Civilian Government Activities was revised to be significantly much higher than the BEA had previously indicated, in effect, adding an additional 0.8% of GDP on top of what the BEA now indicates was generated within the actual territory of the United States.

We'll dig deeper into the national-level GDP revision periodically over the next several weeks!

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June 21, 2016

Since January 2007, the GDP of the United States has been boosted by an unusual source: the wars it is fighting abroad.

We can see that from our pioneering analysis of the upcoming July 2016 revision of national GDP, which becomes clear when we pair that data with the national roll up of GDP data for the individual 50 states and the District of Columbia.

The difference between the two data series is entirely made up of the contribution to the nation's GDP from federal military and civilian activity located overseas, which because it falls outside of the territory covered by the U.S. Bureau of Economic Analysis' Gross Domestic Product measurements, cannot be attributed to a particular state.

And because it primarily represents the work of contractors to support the U.S. government's various military and foreign policy endeavors overseas, primarily in Iraq and Afghanistan, it represents the hidden contribution to the national Gross Domestic Product of the United States from its foreign wars.

We calculated the difference between the national level data and the aggregate data for the 50 states plus the District of Columbia in the period from the first quarter of 2005 through the third quarter of 2015 (using pre-14 June 2016 revision data for the aggregate data, which only extended through 2015-Q3). Our results are visualized in the following chart:

The GDP of War: Contribution to U.S. GDP by Contractors Supporting Overseas Federal Military and Civilian Activity, 2005-Q1 to 2015-Q3

What this chart reveals is just how much the unknown soldiers of Afghanistan and Iraq contributed to the economy of the United States, which may very well be the only quantifiable recognition they will get.

President Barack Obama, speaking at Arlington National Cemetery, used standard language of reflection declaring, “We honor the sacrifice of the thousands of American servicemembers — men and women — who gave their lives since 9/11, including more than 2,200 American patriots who made the ultimate sacrifice in Afghanistan.” This is factually accurate.

However, it overlooks the important sacrifices made by non-service members on behalf of military missions. Since 9/11, a total of 1,592 private contractors (approximately 32 percent of whom were Americans) working on Department of Defense contracts were also killed in Afghanistan. Last year, private contractors accounted for 64 percent of all U.S. deaths in Afghanistan (56 service members and 101 contractors died). But we cannot know exactly where last year’s deceased are from, because shockingly the U.S. Department of Labor “does not routinely track the nationality of workers injured or killed under any of the laws administered by the program.”

This common practice of omitting the contractors’ role in U.S. military operations is troubling for several reasons. It overlooks their service and sacrifice, it disperses the burden of war onto poorly paid or protected locals or third-country nationals, and it gives a false impression of a much smaller U.S. military footprint and national commitment. Whenever the White House and Pentagon announce how many troops will be deployed to Iraq or Afghanistan, they never mention how many contractors will be deployed alongside them. When journalists and analysts request information, officials and spokespersons seem to never have it on hand, and it’s difficult to later obtain accurate or updated estimates....

This relative disregard for contractors is especially puzzling given that their support for recent military missions spans almost all phases of operations: shaping the environment, deterrence, support to stabilization operations, and civil governance. Their tasks include training, intelligence, transportation, translation, and force protection. But “contractors” is a dirty word in some military and policy circles, one that many Americans may conflate with the notorious firm formerly known as Blackwater, which was responsible for the massacre of 17 Iraqis in September 2007. However, even at the height of the surge, Blackwater employees comprised only 1 or 2 percent of all contractors in Iraq.

At its peak in the first quarter of 2012, the contribution of U.S. contractors working to support Overseas Federal Military and Civilian Activities was $241.4 billion, which is about 1.5-1.6% of the entire GDP of the U.S. that was recorded for that quarter.

It likewise represents the billions of dollars that were wasted through what can only be considered to be the military and foreign policy failures of the Obama administration in both Iraq and Afghanistan.

Data Sources

U.S. Bureau of Economic Analysis. Table 1.1.6. Real Gross Domestic Product, Chained Dollars, billions of chained (2009) dollars, seasonally adjusted at annual rates. [National Income and Product Accounts (NIPA) Online Database]. Accessed 14 June 2016. [Note: Pre-29 July 2016 revision data.]

U.S. Bureau of Economic Analysis. Quarterly Real Gross Domestic Product by State, 2005-2014 (Prototype Statistics). [Excel Spreadsheet]. 2 September 2015. Accessed 19 November 2015. [Note: Pre-14 June 2016 revision data.]

U.S. Bureau of Economic Analysis. Current-Dollar Gross Domestic Product (GDP) by State, 2014:III-2015:III. [Excel Spreadsheet]. 2 March 2016. Accessed 2 March 2016. [Note: Pre-14 June 2016 revision data. Nominal data was converted to be in terms of chained 2009 U.S. dollars.]

References

Reuters. Timeline: Invasion, surge, withdrawal; U.S. forces in Iraq. [Online Article]. 18 December 2011. Accessed 20 June 2016.

Stanton, Zack. Summer 2014: Interactive Timeline: War in Afghanistan. Wilson Quarterly. [Online Application]. Accessed 20 June 2016.

Glenn, Cameron. Timeline: Rise and Spread of the Islamic State. Wilson Quarterly. [Online Article]. Accessed 20 June 2016.

Micallef, Joseph V. A Legacy of Failure: Obama's Mideast Foreign Policy. Huffington Post. [Online Article]. 18 October 2015. Accessed 20 June 2016.

Zenko, Micah. The New Unknown Soldiers of Afghanistan and Iraq. Foreign Policy. [Online Article]. 29 May 2015. Accessed 20 June 2016.

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June 20, 2016

How is the pace of dividend cuts in the U.S. stock market during 2016-Q2 coming along compared to the previous quarter? And how does that compare to the pace of dividend cuts that was recorded in the year ago quarter of 2015-Q2?

The last time we answered these questions was six weeks ago, so now that we're in the home stretch for 2016-Q2, let's find out how the pace of dividend cuts announced in the quarter has progressed. Our first chart below updates our chart comparing the pace of dividend cuts between 2016-Q1 and the current quarter of 2016-Q2.

Cumulative Announced Dividend Cuts in U.S. by Day of Quarter in 2016, 2016-Q1 vs 2016-Q2, Snapshot on 2016-06-17

We find that the number of dividend cuts announced in 2016-Q2 through Friday, 17 June 2016 puts it in the borderline range that falls between recessionary conditions being present in the economy and outright contraction occurring within the economy. This marks an improvement over the past six weeks that suggests that the U.S. economy is relatively healthier now than it was just weeks ago.

But how does that compare to the year ago period? Our second chart reveals the differences between the current quarter of 2016-Q2 and the year ago quarter of 2015-Q2.

Cumulative Announced Dividend Cuts in U.S. by Day of Quarter, 2015-Q2 vs 2016-Q2, Snapshot on 2016-06-17

Going by the measure of the number of announced dividend cuts that we've been able to track through our two main sources, the U.S. economy in 2016-Q2 is unequivocally slightly worse than it was in 2015-Q2. We can confirm this in that the total number of dividend cuts with nearly two weeks remaining in the second quarter of 2016 is already higher that the level that our two sources recorded in the same quarter a year earlier.

At the same time, although they have generally followed a similar trajectory through this point in time, dividend cuts in 2016-Q2 have typically been announced sooner than they were in the year ago quarter of 2015-Q2.

Consequently, we would describe the economic trajectory of 2016-Q2 as very similar to 2015-Q2, although having come out of a worse first quarter of the year.

We don't anticipate many additional dividend cuts to be announced through the remainder of June 2016, so unless that significantly changes, we won't visit these charts again until after the end of the calendar quarter.

Next, let's update our chart showing the trajectory of the S&P 500 with respect to the alternate trajectories that our futures-based model of how stock prices work would project.

Alternative Futures - S&P 500 - 2016Q2 - Standard Model - Snapshot 2016-06-17

In Week 3 of June 2016, the S&P behaved largely as our model would predict if investors are focused on the distant future quarter of 2017-Q1 in setting today's stock prices.

As for why that might be, let's review the headlines we considered to be significant in explaining the behavior of stock prices in the trading week ending on Friday, 17 June 2016.

Monday, 13 June 2016:
Tuesday, 14 June 2016:
Wednesday, 15 June 2016:
Thursday, 16 June 2016:
Friday, 17 June 2016:

Data Source

Seeking Alpha Market Currents Dividend News. [Online Database]. Accessed 17 June 2016.

Wall Street Journal. Dividend Declarations. [Online Database]. Accessed 17 June 2016.

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June 17, 2016

Today we are pleased to present a guest contribution by CNBC Radio's This and That's Pat Kelly, who vividly remembers when he first knew he was a 'Thought Leader' and who gives a talk about 'Thought Leadership' that will inspire your thoughts.

Truly, a brilliant skewering of the pretentious crap that characterizes too many pretentious people in academia.

HT: Core77.

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June 16, 2016

Last year, humans on the planet Earth would appear to have set a new world record for fossil fuel consumption.

Each year in June two very important reports are released that provide a comprehensive view of the global energy markets. The highlight of the recently released Renewables 2016 Global Status Report was that the world’s renewable energy production has never been higher. But the biggest takeaway from this year’s BP Statistical Review, released Wednesday, may be that the world’s fossil fuel consumption has also never been higher.

While global coal consumption did decline by 1% in 2015, the world set new consumption records for petroleum and natural gas. The net impact was a total increase in the world’s fossil fuel consumption of about 0.6%. That may not seem like much, but the net increase in fossil fuel consumption — the equivalent of 127 million metric tons of petroleum — was 2.6 times the overall increase in the consumption of renewables (48 million metric tons of oil equivalent).

How much of that year-over-year increase in the equivalent amount of petroleum consumed, representing the planet's increase in total fossil fuel consumption by humans, do you suppose could have ended up in the Earth's atmosphere?

Doing the math, we know that for every 1 kilogram of petroleum that is burned, approximately 3.15 kilograms of carbon dioxide is generated. [We say "approximately" because this figure assumes 100% complete combustion.]

Therefore, if we assume that all 127 million additional equivalent metric tonnes of petroleum consumed in 2015 were fully combusted, it would generate a little over 400 million metric tonnes of carbon dioxide, which marks the maximum amount of additional CO2 that could have been emitted into the air above the level produced by all fossil fuel consumption through human activities in 2014.

That's 0.4 billion metric tonnes, which is the number we need to plug into our tool for calculating the atmospheric concentration of CO2 given the number of billions of metric tonnes of carbon dioxide emissions. 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.

Amount of Carbon Dioxide Emitted into Atmosphere
Input Data Values
Carbon Dioxide Emissions [Billions of Metric Tonnes]

Contribution to Atmospheric Carbon Dioxide
Calculated Results Values
Additional Carbon Dioxide in Atmosphere [Parts per Million]

Compared to 2014, the concentration of carbon dioxide in the Earth's atmosphere has been increased by a maximum of 0.051 parts per million, given the incremental increase in human fossil fuel consumption by people during 2015.

By comparison, the 2015 Indonesia wildfire had well over four times the impact, increasing atmospheric CO2 by at least 0.224 parts per million.

And if we consider the 1997 Indonesia wildfires, which increased the concentration of atmospheric carbon dioxided by approximately 0.54 parts per million in 1997 and 1998, that event had nearly 10 times the impact.

Please keep these values and dates in mind when considering the following chart, which shows the trailing 12 month average of the year-over-year change in the amount of atmospheric carbon dioxide in the Earth's atmosphere.

Trailing Twelve Month Average of Year-Over-Year Change in Parts per Million of Atmospheric Carbon Dioxide, January 1960-May 2015

Looking over the atmospheric CO2 data, we expect the current upswing in the rate at which the level of carbon dioxide in the Earth's atmosphere is changing to continue in the near term, as the data likely doesn't yet reflect the impact of the Fort McMurray wildfire.

Data Sources

National Oceanographic and Atmospheric Administration. Earth System Research Laboratory. Mauna Loa Observatory CO2 Data. [File Transfer Protocol Text File]. Updated 6 June 2016. Accessed 6 June 2016.

Oil Rigs on Bakken - Source: BLS - http://www.bls.gov/opub/btn/volume-2/pdf/employment-wages-bakken-shale-region.pdf


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June 15, 2016

Updates! Scroll down....

Yesterday, the U.S. Bureau of Economic Analysis released its estimates of state level Gross Domestic Product through 2015-Q4. As it did, the BEA revised its previous quarterly GDP estimates for each state going back to at least 2005-Q1.

In doing that, the BEA's data jocks may have provided an unexpected sneak peek of how its estimates of national GDP for the U.S. will be officially changed when the agency releases is annual revisions for that data during the last week of July 2016.

In the chart below, we show the potential magnitude of the pending revision to real GDP in the U.S. The green line is how the nation's real GDP level is currently being reported by the BEA in the period from 2005-Q1 through 2015-Q4, while the black line shows how the BEA's regional data for the real GDP of the entire United States, spanning all industries, has just been reported.

Previously Reported and Revised Real GDP, 2005-Q1 Through 2015-Q4, per BEA Regional Data released on 2016-06-14

There appears to be very little difference from previously reported real GDP figures from 2005-Q1 through 2006-Q3, but after that quarter, a widening gap opens up all the way through the end of 2015-Q4, at which point, the U.S.' inflation-adjusted GDP is revised downward by $324 billion (in terms of inflation-adjusted constant 2009 U.S. dollars).

Stated differently, real GDP in the U.S. is 2.0% smaller than what the BEA previously reported it to be. In terms of the percentage change of the magnitude of the revision in U.S. real GDP, the BEA's downward revision in 2016 looks to be more than double the size of 2014's and 2015's downward annual revisions.

About half of the total downward revision is concentrated during the period of 2007 through 2008, during the period leading up to and going into the first year of the Great Recession, with a second downward surge mostly taking place during 2012 and 2013, when the U.S. economy skirted the edge of an official recession in what we've previously described as a microrecession.

It will be interesting to find out if the BEA did indeed provide an unintended advance sneak peek of its upcoming annual GDP revision exercise for 2016.

Update 8:56 AM EDT: A potential, but partial explanation:

Annual Revision of Gross Domestic Product by State

In conjunction with today's release of fourth quarter 2015 gross domestic product (GDP) by state statistics, BEA is making available on its Web site revised statistics for 2008–2014 and annual statistics for 2015. The annual revision of GDP by state incorporates newly available and revised state source data, most notably the 2012 Economic Census for industries (except for manufacturing, which was previously incorporated).

Additional information on this revision will be available in an article in the July 2016 issue of the Survey of Current Business.

So yes, there is a substantial revision coming down the pike for national GDP, where the regional accounts data is indeed giving us an early sneak peek of the revisions that will be made.

Meanwhile, there is a difference between the reported national level GDP (the green line in the chart above) and the just reported regional GDP rollup for the United States (the black line in the chart above):

GDP by state for the U.S. differs from the GDP in the national income and product accounts (NIPAs) and thus from the Industry Economic Accounts' GDP by industry, because GDP by state for the U.S. excludes federal military and civilian activity located overseas, which cannot be attributed to a particular state.

That doesn't fully explain what we see in the data, because the contribution of federal military and civilian economic activity overseas to U.S. GDP is not something that just started happening beginning with 2006-Q4 - otherwise, we would see much larger differences between the reported national level real GDP and the regional rollup of state level real GDP in the period from 2005-Q1 up to that quarter.

A potential explanation for why that might be more of a factor after 2006 is the Iraq War surge, which became U.S. policy in January 2007. To the extent that U.S. military contractors added to the national level GDP, but not state level GDP during that heightened period of activity would potentially explain a portion of the difference in the period preceding 2008.

But again, military contractors were reaping the benefits of their contracts for work overseas before the surge as well. We should be seeing a much greater difference between national and regional rollup data for GDP in the period from 2005-Q1 to 2006-Q3 than what we are for that factor to fully explain what we see in the data.

On the other hand, when the national level data goes through its annual revision in late July 2016, we'll have a way to quantify how much that kind of economic activity is boosting U.S. GDP.

Update 16 June 2016: We were contacted by one of our readers who pays close attention to the BEA's revisions of GDP. Apparently, the BEA's plans for the revision of the national level GDP data will only cover the period from 2013-Q1 through 2016-Q1.

That's really weird. It's a lot harder for the BEA to disentangle the state level contributions by industry from their national level source data, but once it's done, it means that they've also updated and revised the national level data per all the most recently available information. It just doesn't make sense to sit on that much revised data and not update the national level figures to reflect the entire scope of all the revision work that has been done.

What that means is that there will very likely be an ongoing discrepancy between the state-level GDP and its rollup to the national level, and the BEA's reported national level data. The two datasets should largely match, except for that contribution by U.S. contractors who support U.S. military operations overseas, which falls outside the economic activity that occurs within the 50 states and the District of Columbia as noted by the BEA, and which should only represent a very small fractional contribution to the national GDP figures above the aggregate rollup of state level GDP for the 50 states and Washington DC.

Update 18 June 2016, 6:20 PM EDT: We've been working behind the scenes with other competent econobloggers to sort out just how big the BEA's upcoming national level GDP revision will be when it is finally posted in the last week of July 2016. In doing that, we've estimated just how big the contribution to national GDP is for federal military and civilian activity located overseas, based on the available pre-revision data we have to estimate that figure through 2015-Q3. The chart below shows that contribution and updates our findings:

Previously Reported and Revised Real GDP, 2005-Q1 Through 2015-Q4, per BEA Regional Data released on 2016-06-14, Revised to Account for 'Overseas' GDP, with Date Correction - was 14 June 2015, now corrected to 14 June 2016 - previous chart here: https://2.bp.blogspot.com/-EzKqOVcLGC4/V2XJce71MhI/AAAAAAAANkk/uxCWYmwSK98c6baRUFRi1-NmNArdwz1qgCLcB/s1600/Political-Calculations-2016-GDP-Revision-Projection-spanning-2005Q1-to-2015Q4.png

We project that the maximum "likely" size of the upcoming revision for national GDP is -1.4%. We expect it will actually be less than that figure because the upcoming national GDP revision will only cover the period from 2013-Q1 through 2016-Q1, which will therefore not fully address the discrepancy that begins appearing after 2012-Q2.

It is also possible that the federal military and civilian activity located overseas will turn out to be significantly larger than what the BEA's data has previously indicated, which would also narrow the gap between how national GDP is currently being reported and what the just-revised aggregate state GDP suggests it will turn out to be.

This is really pretty cool because this is the first time that this kind of predictive exercise has even been possible thanks to the BEA's more timely reporting of its regional GDP data series. As our long time readers know, we're very happy whenever we're both on the cutting edge of doing new analysis and can share our work in progress in developing a brand new kind of analysis to get to the real story behind the numbers in the economy.

Update 27 July 2016: This is so cool! We had an extended contact today with an analyst who works for the BEA, who wanted to know more about how we came up with our estimate of how real GDP would change using the BEA's recently revised regional account data.

That was fantastic timing, because we just happened to have our spreadsheet open because we were updating it with state level GDP data from 2016-Q1 that was just released today.

In going over that material, we discovered a problem that threw off our calculations, with the effect that the results we had obtained weren't matching what they were getting from 2014-Q3 onward in replicating our analysis. We were able to trace the problem back to the GDP deflator that we used to convert nominal GDP data to inflation-adjusted "real" data, where we were multiplying the nominal data by the GDP deflator data for the national level data (the data whose revision is set to be published on Friday, 29 July 2016) instead of the GDP deflator data that applies for the aggregate 50 states plus Washington DC, which just happened to be in the spreadsheet column next to it.

After we made the appropriate correction, all our results from 2014-Q3 onward snapped into place and all results matched, from the period from 2005-Q1 through 2014-Q2, where there was never any problem, and now from 2014-Q3 through 2015-Q4! The following chart shows the latest and greatest for what we expect from Friday's GDP revision based only on the state level GDP revision from June!

Previously Reported and Revised Real GDP 2005-Q1 Through 2015-Q4 (Updated 27 July 2016)

As for the outcome of the analysis, the error we made with using the incorrect GDP deflator overstated the amount by which real GDP is likely to be revised by 0.5% of GDP, so instead of the maximum likely change of -1.4% that we had previously calculated, the maximum amount by which national GDP might change as a result of the revisions the BEA has made to its GDP data for the 50 states plus Washington DC is -0.9%, with the maximum discrepancy now taking place in 2013-Q3. This data is indicated in the chart above by the dark-green line.

But since the BEA's national revision will cover the period from 2013-Q1 to the present, the revision of the national level GDP will not include the now-confirmed $55 billion discrepancy that opens up between the national GDP data and the national aggregate state level GDP in 2012. We are therefore now estimating that the most likely revision that will be made to the national GDP data on Friday, 29 July 2016 will be an adjustment of -0.6% in 2013-Q3. This data is indicated in the chart above by the bright red line (and the blue arrow at 2013-Q3).

We'd like to thank everyone who provided their useful assistance in getting to this point - in terms of collaborative effort, this has been one of the biggest projects we've had the pleasure of working on since launching Political Calculations. It's always exciting when we get to break brand new ground and do analysis that was never possible before, and we appreciate your shared enthusiasm!

On a final note, if you happened to have come across this post by way of Econbrowser, you might want to pass along information back to the author who pointed you in this direction that their observations have been described as "not relevant". We're pretty sure that particular author hears that a lot....

There's more that we'd like to be able to discuss on the topic of the upcoming national-level GDP revision, but that will have to wait until after that data is released. Until then, what you see above represents the most that anyone can reasonably glean about what the revision will look like based only on data that is already available to the public.

Update 29 July 2016: The verdict is in! The chart below shows the revisions in national level real GDP from 2013-Q1 through 2015-Q4....

Previously Reported and Revised Real GDP, 2005-Q1 through 2015-Q4 (29 July 2016)

Compared to our final pre-revision prediction from 27 July 2016, we were off by 0.1% of GDP through 2015-Q4, where we had previously projected no change.

More significantly however, national-level real GDP was increased by 0.2% of its previously reported figure in 2013-Q3, where the aggregate GDP data for the 50 states and the District of Columbia had instead indicated that a 0.6% of GDP decline for that quarter was most likely. That means that the amount of GDP that the U.S. generated in that quarter from Overseas Federal Military and Civilian Government Activities was revised to be significantly much higher than the BEA had previously indicated, in effect, adding an additional 0.8% of GDP on top of what the BEA now indicates was generated within the actual territory of the United States.

We'll dig deeper into the national-level GDP revision periodically over the next several weeks!

Update 2 August 2016: Added boldface type to selected text above. Somehow, one particular critic is so committed to a non-relevant narrative that they chose to completely ignore the now emphasized text where we were happy to describe the actual error we made, just so they could continue their pursuit of their preferred narrative.

Given their history, that is perhaps not so surprising. In fact, in their obsessive pursuit, they have even managed to check off two new categories from the "How to Detect Junk Science" checklist.

How to Distinguish "Good" Science from "Junk" or "Pseudo" Science
Aspect Science Pseudoscience Comments
Progress Most scientific fields are the subjects of intense research which result in the continual expansion of knowledge in the discipline. Pseudoscientific fields generally evolve very little after being first established. What small amount of research and experimentation that is carried out is generally done more to justify the belief than to extend it. The search for new knowledge is the driving force behind the evolution of any scientific field. Nearly every new finding raises new questions that demand exploration. There is little evidence of this drive in the pseudosciences.
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.

If you can't tell from our discussion above, we were quite happy to both challenge our assumptions and to share our data and calculations with others where they could be reviewed, which was a key part of what led to our making real progress in understanding what the BEA's 2016 GDP data revisions are really communicating. More on that in a new post, soon!

Final Update! (10 August 2016) One of our readers asked via e-mail for more elaboration on why the problems of the subcomponents of chain-weighted "real" GDP not being additive would not be relevant in this case.

It certainly would if we were trying to create more than a first-pass approximation of the contribution of Overseas Federal Military and Civilian Government Activities, which would be the difference between total GDP and domestic (within just the 50 states + DC) GDP. In this case however, those problems are not relevant because we're only concerned with how much the reported figures change with respect to the figures that the BEA had previously reported. Our hypothesis was that the change in domestic GDP when it was revised in mid-June 2016 would be mirrored in the total GDP revision that came out at the end of July 2016. If that hypothesis held, the change in total level GDP would have been directly proportionate to the change in domestic GDP.

As we later learned however, after the July 2016 revision to total GDP was published, the change in domestic GDP that was recorded in June 2016 was really signaling that the BEA had previously misattributed GDP earned overseas through the federal government's activities to having happened within the 50 states and District of Columbia. Our hypothesis proved to be wrong, which we were happy to report!

Our "critic" however is really fixated on the additive real GDP issue however, and thus far, has refused to even acknowledge that something else, an error in using the incorrect GDP deflator for converting nominal GDP from 2014-Q3 onward into "real" GDP terms, was responsible for our having projected that total real GDP might be revised lower through the end of 2015. That was the problem we found and fixed on 27 June 2016, two days before the revision was made public.

In fact, their refusal to move on from their misdiagnosis that the additive real GDP issue was somehow relevant in this case, even after we reported it, is why we've flagged them with the "Progress" category from our junk science checklist. And also the "Inconsistencies" category, because they clearly ignored our explanation of what really caused the error.

It's not like we're immune from errors ourselves. We even generated a post where the problems with subcomponents of real GDP not being additive (or subtractive) would be relevant! Then waited for them to notice and to correct us. We even thanked them in an update to that post.

We're disappointed to report however that they don't seem very appreciative of our acknowledgment of their relevant contributions. Then again, we're not responsible for any aspect of their happiness, or lack thereof. We would simply observe that normal people would spend far less than 10 hours a day making multiple visits to this one single post on our site for weeks on end.

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