Friday, November 22, 2019

How Does Trump Compare to Previous Presidents - Update 1

I published my first evaluation of Trump's performance on 9/6/2018, using Federal Budget and Financial Market data. This previous analysis used only one year of actuals for Trump and 6 years of forecasted results from the Office of Management and Budget.  This update has 3 years of actual data and only one forecasted year to make up his first term.  My experience has been the next year forecast is very good as most policy spending is already set.

As a refresher on my approach, I have covered the years from 1961 (Kennedy/Johnson) to the present.  For these years,  I downloaded the entire budget detail from the "Office of Management and Budget".  These data were analyzed using statistical techniques to establish the Annual Compound Growth Rate (CAGR) for each presidential term.  There has been one four year term for each political party (Carter, Bush1) and I have calculated Trump's CAGR using the 2020 Federal Budget publication but this time using only the years 2107 to 2020 to represent Trump's first  4 year term.

To compare each of the 9 Presidential Terms, I have focused on GDP, Budget Receipts (3 categories), Budget Outlays, Deficit, Supplemental Spending, and National Debt.  I have also added the growth of the Dow Jones Industrial Average as an additional  economic indicator which Trump uses frequently.  Since the United States is growing and spending is likewise growing exponentially, the use of Compounded Annual Growth Rates makes for equitable comparisons between Presidents.  A summary of these findings can be seen in the table below:

Looking at the individual categories above, Trump is NOT the best in any category!  When evaluating the economy, GDP is usually at the top of the list and Trump is below the Republican and Democratic averages on GDP growth and below the Republican average on Real GDP.  Trump's tax plan shows up in Corporate Income Taxes, shrinking at -3.9% compounded annually, resulting in Receipt growth at only 3.2%, the lowest of all Presidents. Spending growth is twice that of Receipts at 6.4% which is mid range among all 9 Presidents. To summarize, Trump is on the "bad" side of the Republican average on 7 of 11 categories.  He is on the "bad" side of the Democratic average on 11 of 11 categories.

I also launched an analysis to confirm (or disprove) the many comments from the Trump Administration concerning Trump's superior performance relative to previous Presidents. The scoring is based on assigning 2 points for best performance in a category and 1 point for second best.  Also, -2 points for worst performance in a category and -1 point for second worst.  Good performance is considered high growth in Receipts, GDP and Stock Market; poor performance is high growth in Spending and Deficit/Debt (traditional Republican principles).  Here are some top line findings: combining Presidential performance on the growth rates across all financial results: Trump is now alone at SECOND TO LAST place among all 9 Presidents. Bettering Trump are Nixon/Ford, Reagan, Bush 2, Obama, Carter, Kennedy/Johnson and Clinton.  Bush 1 has the lowest score of all Presidents and Clinton had the highest.

One of the sub-categories of "Outlays" or spending is Total Net Interest on the Federal Debt which is shown below:

The green, white and red sections around the data are statistical limits which are helpful in determining if all of the data fall within a "normal" range which helps identify "outliers".  If there are no outliers, the annual compound growth rate is determined.  It can be found in the data box, just above the blue highlighted number.

In this case the Trump's growth of the Interest on the Debt is 22.1% compounded annually.  This is 3 times higher than the other 8 President's combined average of 7.3%!  As you can see the slope of line is quite a bit steeper, reflecting the higher debt growth and higher interest rates that are likely to increase with such high national debt.  This has not been much discussed in the press but is a natural outcome of Trump's tax plan.  One more item in the news is the Trade War and its affect on the our economy.  Although it is already reflected in the GDP and Receipts above, I took a look at the Trade Deficit and Trump is running at a Compound Annual Growth Rate of 9.4% as compared to Obama at 1.7%!  Enough Said!!

Sunday, January 6, 2019

Is Border Security Really a National Security Threat?

On April 9, 2018, I published "Will Trump's Troops on the Border Really Help?" that evaluated the effects of having the military at the SW border.  As part of this post, I looked at Apprehensions at the Southwest Border and determined that military presence at the border had little effect on reducing this number.  While looking at 20 years of history on Apprehensions, I also concluded that NAFTA might have made a contribution to 75% reduction in Apprehensions since 2002.

Now that the Government is in a partial shutdown over "border security" with negotiations underway to solve this "problem",  I thought it would be instructive to update this Apprehension data and look at additional data to determine if it supports the claim that there is a National Security Threat.  All of this data was retrieved from US Customs and Border Patrol web site.

First, it will be important to understand two organizational components of Customs and Border Protection (CBP).  The Office of Field Operations (OFO) is the largest organization in CPB and is primarily responsible for security at Ports of Entry.  US Border Patrol has the responsibility for security along the border BETWEEN Ports of Entry.  This is the subject that is so much in the news concerning a "wall".  Part of the problem is that "border security" would include Ports of Entry AND the border between them.  The "wall" concentrates on the border between Ports of Entry.  So, if building a "wall" is a National Security imperative, it would be important to see if CPB data supports this claim.

I'll start once again with Apprehensions by Border Patrol, first by fiscal year.

There is a rapid decline from 2002 to 2011 when the Apprehensions fell from 1,600,000 per year to 400,000 per year.  If the number of illegal crossing constitutes a National Security concern, this crisis should have been declared in 1980's and 1990's!  Obviously, this 75% reduction in illegal crossings was  achieved without a complete wall.  

Breaking this annual data down into monthly data can give us plenty of data to look at Apprehensions since Trump took office.  First, I wanted to compare Obama's Administration to that of Trumps's first 2 years.

Most notable here is the lower left corner, highlighted in blue, which shows that Trump's average apprehensions ARE statistically lower that Obama's average.  Again it does not seem that the lowest average illegal crossings, in the last 35 years, are evidence of a National Crisis.

This graph highlights the first two years of Trump's administration to show that, although the average is statistically lower, it is in a steady climb of 89% compounded annually.  Might this again be related to the "undoing" of NAFTA by Trump and, therefore, gives a suggestion of a possible solution to illegal crossings through trade negotiations with Mexico.

Trump often talks about gang members, MS 13 in particular, crossing the border in large numbers as well as a "flood" of drugs.  So I also found CPB data on these areas as well.  First of all, gang members captured in FY 2018 represent only 0.18% of all apprehensions and MS 13 only 0.009%.  This does not sound like a National Security threat to me.  Finally, only 13% of drugs seized were seized by Border Patrol with the remaining seized by the Office of Field Operations (Ports of Entry).  The only exception to this is Marijuana, the amount is twice that seized at Ports of Entry.  However, the amount of marijuana seized between Ports of Entry has been reduced by 80% since 2012 without a complete wall.

In closing, it appears to me that there is absolutely no evidence from CPB to support building any additional wall components, nor yielding evidence of a National Security claim to access wall money by Executive Order.

PS- Just heard Mulvaney on Meet the Press say that there have been 60,000 apprehensions at the border over the last three years!  Not True.  10,000 of this number are called "Inadmissible" which are those people at the Ports of Entry rejected by Office of Field Operations and, therefore, not an illegal crossing.

Thursday, September 6, 2018

How Does Trump Compare to Previous Presidents?

I read this morning an article in my local newspaper: U.S. Trade Deficit Widens to $50.1B",  It stated that the Trade Deficit has been increasing the last two months "despite efforts by President Donald Trump to bring it down by renegotiating trade agreements and imposing taxes on imports".  Even though this is only two data points, it did get me thinking about my previous evaluations of Presidential performance on budget items and other financial measures.  For those who have read these previous posts, I will use the same categories of receipts and outlays based on Trump's first budget and forecast, which includes one year of actual spending.  Although Trump's budget forecast only goes through his 2023 (7 years), it should reflect his priorities which have been clearly stated and actions already taken.  To note, his forecasts likely do not include the impact of his trade policy decisions which are reflected in the Trade Deficit article referenced above.

As before, I downloaded the entire budget detail from the "Office of Management and Budget".  These data were analyzed using statistical techniques to establish the Annual Compound Growth Rate (CAGR) for each presidential term.  There has been one four year term for each political party (Carter, Bush1) and I have calculated Trumps CAGR using all 7 years included in the 2018 Federal Budget (through 2023).

I also launched this analysis as a way of trying to confirm (or disprove) the many comments from the Trump Administration concerning Trump's superior performance relative to previous Presidents.  Here are some top line findings.  Combining Presidential performance on the growth rates of all financial results, Trump is in a 3 way tie with Nixon/Ford and Bush 2 for SECOND TO LAST place among all Presidents. Bettering Trump are Reagan, Obama, Carter, Kennedy/Johnson and Clinton.  Bush 1 has the lowest score of all Presidents.  The scoring is based on assigning 2 points for best performance in a category and 1 point for second best.  Also, -2 points for worst performance in a category and -1 point for second worst.  (Good is considered high growth in Receipts and GDP; Bad is high growth in Spending and Deficit/Debt).

Looking at the individual categories, Trump is NOT best in any category!  Lately, we have heard much discussion of GDP, of which he has the 3rd LOWEST growth rate.  This happens to be below the Republican average growth.  He is at the Republican average for Real GDP Growth.  Below you will find the complete table of results.

Trump's growth rates for all categories are in the middle of the pack in most cases.  However, he has the worst (highest) growth rate in Supplemental Spending (off-budget).  With the recently passed tax plan, there are still 3 Presidents with slower growth in Individual Taxes (Bush 2, Bush 1 and Reagan) and 2 Presidents with slower growth in Corporate Taxes (Bush 1 and Nixon).  Notice that compared to Obama, Trump has reduced Tax Receipt growth by 1/3, while at the same time quadrupling the growth in Outlays (spending).

Here are a couple of examples of how Compound Annual Growth Rates are determined.  First is the graph of Trump's GDP that we have mentioned above:

The green, white and red sections around the data are statistical limits which are helpful in determining if all of the data fall within a "normal" range which helps identify "outliers".  If there are no outliers, the growth rate is determined.  It can be found in the data box, just above the blue highlighted number.

One of the sub-categories of "Outlays" or spending is Total Net Interest on the Federal Debt which is shown below:

In this case the Trump's growth of the Interest on the Debt is 15.8% compounded annually.  As you can see the slope of line is quite a bit steeper, reflecting the higher debt growth and higher interest rates that are likely to increase with such high national debt.  This has not been much discussed in the press but is a good summary of Trump's tax plan.

Keep in mind that 6 of the 7 Trump years analyzed are FORECASTED numbers. Based on this and the likely hood that forecasted numbers are based on optimistic assumptions, it will be critical to reassess these conclusions as actual spending is posted in the years to come.

My belief is that success in government should be evaluated not by orders signed or regulations reduced, but by the financial health of the country and its citizens.  There is not evidence that a "best ever" claim is yet deserved.

Monday, April 9, 2018

Will Trump's Troops on the Border Really Help?

Trump has announced and obtained DOD approval to put 4,000 National Guard Troops at the Mexican Border to reduce the number of illegal immigrants entering the US.  Not that he has ever used data or logic to make such decisions, so I thought I would try to put his decision up against some actual data!

First, I downloaded aprehensions for the Southwest Region from 2000 to 2018 FY to date ,by month,  from US Customs and Border Protection as well as annual data from 1960 to 2017.

For context, take a look at the annual data in simple graph form below:

The first thing to notice is that aprehensions had been steadily increasing from 1960 - 2000 after which a rapid decline began.  For context, in 1979, Reagan campaigned on creating a North American Trade Agreement and through the 1980's negotiations began.  Clinton finally signed the agreement in 1993 and it was put into action in 1994.  The Agreement stated most tariffs were to be eliminated within 10 years. The NAFTA implementation might have been a contributor to the decline beginning 2001, which, by the way, was the first year of the Bush Presidency.

To get a better handle on the compound annual growth rate of apprehensions and the stability, the graphs below analyze the periods prior and post 2000:

From 1974 to 2000, the growth was quite steady at 3.7%, compounded annually, with 1986 showing up as a uniquely different year being above the Upper Control Limit (middle of negotiations?).  From 2001 to 2017 the decline was -8.8% at an undisturbed rate.  It was during these years that both Bush and Obama, sent troops to the border to help with apprehensions, which were already in steady decline.

Using monthly apprehension data beginning in 2000, lets now look at previous troop deployments to assess their impact, remembering the decline of -8.8% indicated a steady, stable decline.

Bush sent 6,000 troops to the border in 2006, which lasted two years, at a cost of $1,200 Mil.  Apprehensions connected with this deployment were only 176,000 of the 2,030,000  two year total or 9%. Clearly there were no INCREASES in monthly apprehensions during this deployment as seen in the graph above.  (The annual seasonal pattern spikes in March and bottoms in December)

The first graph above compares the two years prior to Bush's deployment to the two years of the deployment.  The conclusion would be that apprehensions dropped by 38% due to the deployment.  In the second graph, in the two years after the deployment, apprehensions dropped another 21.5%.  These last 3 graphs would cause me conclude that there was no impact in apprehensions from Bush's deployment. The $1,200Mil spent did NOT produce any "net extra apprehensions"

Below, you will see a similar analysis of the troop deployment done by Obama in 2010 which lasted only one year at a cost of $110 Mil for 1,200 troops.

Again, Obama claimed 18,000 troop based apprehensions during 2010 of the total 447,731 or 4%.  During 2010, average apprehensions dropped by 22.5% as compared to the 2009 and in 2011 apprehensions remained the same as 2010.  So again, troops at the border did not create any additional apprehensions.

So now Trump is sending 4,000 troops to the border as a "hair on fire" reaction to a lack of his wall being funded, but does the data support his reaction?

 Average apprehensions during Trump's administration are 34.7% lower than the average of the Obama years.  You can see that March 2018 is a large rise, but not outside the the Upper Control Limit.

So, troops at the border probably will not make any difference in apprehensions at the border.  Maybe we should just treat this deployment as Trump's Military Parade!  One final thought: Could the rise in apprehensions during Trump's administration be caused by Trump declaring the end of NAFTA, mirroring the rise prior to the implementation of NAFTA we see in the annual data??  

Monday, June 26, 2017

The Trouble with Quarter Earnings Releases in Business Reporting

Cause and effect is a very misused concept since we desparately want to explain everything that happens to us, both the good and the bad.  Cancer, "accidents", mental health, birth defects, happy marriages, successful people, wealth, intelligence all seek to find the silver bullet, so something can be cured or maximized.  But alas, randomness and chance are with us everyday, clouding our understanding of everyday events.  Blame, rather than causation, are more easily diagnosed with our belief systems rather than with data and understanding.

Although there are many examples of misunderstanding causation, I want to use business performance as represented by financial results and the related press releases which follow in this blog post.  First, I would like to review some key concepts I have used before:
  1. Variation.  It exists all around us all the time: Temperature, mood, blood pressure, drive time to work, rate of return.  As Edwards Deming said, "measure it once and you know; measure it twice and you don't know".
  2. All the ups and downs in results or performance are caused by only two things.  The first is Common Causes (Systemic) which are present all the time.  They are made up of all kinds of simple things which interact in random ways to influence a result or performance in predictable and measurable ways.  Take your drive time to work each day and think about all the things that influence the total drive time.  A partial list might include what time you leave, how anxious you are, stop light patterns, weather, other drivers, your car's performance, when you last fueled, stop signs, commercial truck traffic, school bus activity, pedestrians, how fast you are diving, and on and on.  The other influence is called a Special Cause (Assignable Cause) which generally is singular and rare.  These events will create a result beyond what is expected from the common or normal causes alone.  These are sometimes called Breakthroughs (when helpful) or Breakdowns (when hurtful).
  3. Understanding these two sources of variation are critical to making progress and sustaining any benefits in results.  Having a flat tire on your way to work is likely a special cause in the resulting drive time.  However, a "run flat" designed tire was created with the knowledge that flats do happen and the effect, which would be a special cause, can be minimized.
  4. Most people want to either place blame for a negative result or take credit for a positive one, when in fact it was caused by the Common Causes only (complex interaction of many causes). This is how cause and effect relationships are erroneously concluded.
  5. There is a simple way to establish the boundaries of variation when only Common Causes are present.  This uses only two calculated numbers: the average and the standard deviation.  Over a period of time, say you record the actual drive time to work each day.  Calculate the average and standard deviation and place two boarders around the average of plus/minus 3*SD.  These are called control limits and represents the spread of the  normal variation in drive times to work.  One day, you decide to leave for work 5 minutes earlier and arrive at work 8 minutes early.  If this is NOT outside the Lower Control Limit of drive times, you should not conclude leaving 5 minutes earlier will  shorten the drive time average.  Another example is a thermostat.  If you are in a large room with many people and everyone has been told to adjust the thermostat to their liking, you will find that the average room temperature will be the same over time, but the variation will increase significantly, making everyone unhappy with the room temperature.  This is considered "tampering" which makes the variation higher without changing the average.  
  6. This last point happens everyday when companies (and governments for that matter) report financial results.  There is a tendency to find blame when the results are down or a successful project when the results are up.  In the future, they will try to prevent the actions that were blamed or fund more similar projects that were successful.  HOWEVER, if these originally were NOT special causes, they are now tampering, making variation higher without any change in overall performance.  Business leaders do benefit from this higher variation since it will increase the probability of hitting a higher goal in the future without making any positive changes.  The stock market also thrives on this variation as the buy low, sell high creates higher gains (in the short term) which gives rise to high frequency trading.

Now, take a look at a few examples. I will start with AIG.  The revenue has been in steady decline (only common causes), since June of 2011.  Said another way, they have NOT had a significant change in revenue in the last 21 quarters.

However, from the quarterly earnings release for June of 2016 (the last quarter in this graph) I quote:

“AIG’s second quarter results show strong improvement towards all the goals the Board and I announced in January,"

The word Improvement, to me, indicates there has been a change in the performance for which there is no evidence in this case unless the goal is to reduce revenue!  Also interesting to note that the quarterly earnings release only deals with Net Income in their discussions, not revenue.

Campbell Soup gives us another good example with very stable revenue.

From the July, 2016 Earnings Release comes this quote: 

"Sales of $1.687 billion were comparable to prior year as the benefit from the acquisition ofGarden Fresh Gourmet was offset by the decline in organic sales and the adverse impact of currency translation. Organic sales decreased 1 percent primarily driven by Campbell Fresh,reflecting declines in carrots and carrot ingredients, as well as the impact from the voluntary recall announced on June 22 of Bolthouse Farms Protein PLUS drinks. The estimated negative impact on net sales in the fourth quarter related to the recall and related production outages was approximately one percentage point."  

Looking at the graph, all the items mentioned above are singled out common causes which do not explain the July result.  What explains the July result is the complete set of numerous and complex common causes.

As for the Campbell Soup Earnings per Basic Share graph, you will see that the most recent July, 2016 quarter is clearly a special cause and needs an explanation.

This is their response: 

"As reported EBIT was a loss of $37 million, reflecting the non-cash impairment charge, pension and post-retirement mark-to-market losses and charges associated with cost savings initiatives as previously mentioned. Excluding items impacting comparability, adjusted EBIT decreased 2 percent to $253 million reflecting higher advertising and consumer promotion expenses and a lower adjusted gross margin percentage, partly offset by lower administrative expenses".  

The first part of the first sentence is pretty logical as a special cause, but all the remaining words sound very much like list just a few of the common causes.

Using the SOME common causes to explain a special cause will contaminate the institutional memory as these couple of common causes might be used again to create a needed breakthrough in the future, which will NOT materialize.  This would then begin a hunt for the "guilty" for why this project did not work.

Coca Cola is another example of trying to explain something that does not exist.  Both the Revenue and EPS graphs are shown below.

Notice that both graph are stable with only common causes present for the last 5.5 years.  Here is what they are saying in their earnings release for September 2016: 

"I am pleased to report that we delivered results in line with our expectations,"; "While our year-to-date reported net revenues declined 5%, our core business organic revenues* have grown 4% despite continued global economic and political volatility."; and "Full Year Organic Revenue and Comparable EPS Outlook (Both Non-GAAP) Remain Unchanged".

So declining sales and EPS are your expectations!!  Also, look over here at our business unit that is doing well because of these two common causes!?  Finally, saying your outlook remains unchanged means that you do not have any breakthroughs in your business strategy that would turn around your declining results.  Speaking of "outlook", remember if your results have been stable for many years, forecasting future results is a statistical piece of cake.  And these forecasts are what the stock analysts use to establish stock price recommendations.  If you miss your forecast, your stock price takes a hit.  Having stable business results, and therefore, good forecasts, is the best way to promote higher stock prices.  Knowing what causes real breakthrough in results is what can drive reliably raising future forecasts.

Delta Airlines revenue is an interesting case.  Notice that the 7 years, ending September 2016, were show a  stable trend of 3.3% growth.  

But look at what they talked about in their release on September 2016:

"Delta’s operating revenue for the September quarter decreased 5.6 percent, or $624 million, of which $100 million was due to the [computer] outage and $70 million was from prior year Yen hedge gains." 

Having a computer outage that reduced $100 million in revenue IS NOT A SPECIAL CAUSE like they think it is; nor is the Yen hedge.  Both are just among the normal things that affect their quarterly results, within the bounds of the control limits (blue and yellow lines above).  The more the business leaders use isolated common causes to explain their results, the more they will be "tampering" which makes the quarterly variation higher without changing the average result!  

You can see that I am only on the "D" companies in my list that I regularly track.  I am sure you can imagine there are many more examples of of explaining results of a stable business with one or two common causes or totally missing a special cause that needs explaining.  THE ROOT CAUSE OF ALL THESE ERRORS IS USING "INDEX VERSUS YEAR AGO" WHEN REPORTING AND ANALYZING FINANCIAL RESULTS.  In most cases, a few points percentage change, up or down, is due only to the complex set of common causes and needs understanding but not explanation.

Monday, February 29, 2016

Democrats Make the Best Republicans, Economically Speaking

For many national election cycles, I have listened to the Republicans express their platform positions of: Smaller Government, Lower Taxes, Smaller Federal Debt, and Higher Economic Growth.   As I am now living off of my savings, these topics are ever more important to me; especially the last one!  So, as I listen to all of the current Presidential Primary debates, rhetoric and talking heads, it is difficult to distinguish how any of the candidates will help my current standard of living be maintained.  So back to the data and facts I go, to help me understand the actual execution against the 4 Republican Platform positions mentioned above.  As it turns out, my previous posts were a great place to start.

In this post, the Presidents since JFK have been evaluated on many Federal Budget Spending categories as was done in the earlier post.   They have been evaluated individually and collectively as Republicans and Democrats.  So, in addition to updating the data with one more year of data from the 2017 Federal Budget Package, I also added a new category of the Dow Jones Industrial Average at beginning of each year over this same timeframe.  This, with the Gross Domestic Product, gives a good overview of the macro economic picture.  In summary, the Democrats did better in delivering 3 of the 4 Republican Platform components listed above!  Surprised like me??  Read on.

As way of review for those of you who are new my blog here is a bit of background. Looking at the actual Federal Spending by year would clearly bias conclusions for the most recent Presidential terms since our economy and budgets are steadily growing. Therefore, all of my analysis is based on the growth rate of budget spending expressed as percent growth compounded annually for each Presidential term.  There are an equal number of terms for both Republicans and Democrats in my analysis with each party also having one 4 year term.  In addition, Kennedy/Johnson were combined into one 8 year term as was Nixon/Ford.  Since Obama has submitted the 2017 Budget, the 2016 budget is half over, the 2016 estimate should be fairly close and will round out his 8 year term.

Although there are several ways to establish compound growth rate for these Presidential terms, I am using a statistical tool called Control Charts.  They are graphs of the actual budget spending, by year. An average is calculated for each Presidential term, which in this case is the exponential growth average.  Around this average, are placed "Upper and Lower Control Limits" which are the plus/minus 3 sigma boundaries of annual spending. This allows for the determination of any statistical anomalies during a Presidential term, which in turn would unduly influence the compounded growth rate calculation.  For example, here is the growth of the Dow Jones Industrial Average (DJIA) during Obama's term:

The time frame on this is from 1961, JFK, through 2016, end of Obama's term.  At the end of this graph you will notice the colors are stronger, which means that all the statistical calculations were done over the 8 year term of Obama, 2009 - 2016.  In this 8 year section of the graph, you will notice 3 colors.  The green "zone" is the +- 1.5 sigma zone where most of any consistent results should fall.  Where it turns from white to red is the +- 3 sigma boundary or Upper Control Limit (UCL) and the Lower Control Limit (LCL) where 99.7% of any consistent results should fall.  For Obama, this would mean that there are not any "outlier" years in his term, and ,therefore, the calculated Annual Compound Growth Rate (CAGR) of 10.8% is accurate.  The CAGR can be found in right hand box under the graph just above the light blue highlighted number.  To note, double clicking on any graph or picture will allow you to see a larger version.

Staying with the DJIA, here is a graph for the term of Bush 2:

Over his 8 year term, the years all fall within the UCL and LCL and all but one in the "Green Zone" signifying his years are consistent (no outliers).  His CAGR for the Dow Jones is 4.0%.  This same analysis was done for 14 Federal Budget and economic categories for each Presidential term from JFK forward.  The good news is that the graphs for all Presidential terms did not show any statistical outlier years and, therefore, their spending growth rates are true.

Below you will see the summary table of the Presidential terms with all the budget categories evaluated for each term.  There are two key numbers for each term and budget category: the average annual spending which is presented for context (Federal Debt is at the end of Term) and the Compound Annual Growth Rate (CAGR) which is the key focus of this analysis.

As I have done in the past, to evaluate each Term relative to the others, I have defined "Best" as Receipts with the highest growth rates and Outlays, Deficits, Supplementals and Debt with the lowest growth rates.  In short anything that makes the Debt fall.  In the table above, magenta color reflects the "Best" performance in each budget category.  Likewise, the orange color represents the "Worst" performance.  Any underlined number was found to be statistically different from all other results.  At the bottom of the table is the average growth for all Democratic terms and the average growth for all the Republican terms.

Below are my highlights from the table related to Republican platform components mentioned at the beginning of this post:
  1. SMALLER GOVERNMENT:  Total Federal Outlay growth was 1% smaller for Democrats.  Obama had the lowest growth at 1.5%.  I also evaluated Government employee growth.  Unfortunately, this data only existed from 1981 to 2016.  In this case the Democrats grew Federal employees 1.6% slower than Republicans.  So, Democrats actually create SMALLER government than Republicans!
  2. LOWER TAXES:  Total Receipt or Tax growth was lower for Republicans by 3.6%.  The lowest Receipt growth was 3.2% for Bush 2.  And Republicans argue LOWER taxes yield HIGER economic growth (trickle down)???  Unfortunately this does not seem to be the case, since the Real GDP grew 1% slower for Republicans AND the Dow Jones grew 1.3% slower as well.  Another way to look at Receipts/Taxes was to ratio the average annual receipts divided by the average GDP for each Term.  In this case the Republican "Tax" rate is only 0.1% lower than Democrats.  So, Republicans do deliver on this platform element.  But...
  3. SMALLER FEDERAL DEBT:  Every President has grown the Federal Debt!  However, the Democrats grow the debt 5.1% slower than Republicans.  Debt growth was the smallest for Kennedy/Johnson at 2.9%.  So, the combination of higher taxes and smaller government by Democrats has caused lower growth in the Debt.  
  4. HIGHER ECONOMIC GROWTH:  Real GDP, which represents economic growth, was 1% higher for Democrats.  Kennedy/Johnson had the highest growth at 5.4%.  Using the Dow Jones Industrial Average as another Economic indicator shows growth 1.3% higher for Democrats.  Clinton had the highest growth at 20.4%.  So, again, the Democrats grow the economy faster than Republicans!
So, in the upcoming election, if you are Socially Conservative and Fiscally Conservative, put any money you have under your mattress.  However, if you are Socially Liberal and Fiscally Conservative, do I have a Political Party for you.

Tuesday, June 23, 2015

Social Security and Medicare Cost per Person - Update

My last post on Social Security and Medicare costs per person was published in 5/23/2011 and a great deal has happened since then, especially with the Affordable Care Act (ACA).  I am sure that this will become a hot topic during the Presidential campaign along with the Social Security Trust Fund.  So I thought it might be worth a look at the current status of both of these trust funds and also do some forecasting using the latest Federal Budget (2016) forecasts through 2020.

As before, I used The Federal Budget Package for 2016 published by The Office of Management and Budget as well as the Historical Tables.  All of this is easily found on The Government Publishing Office site.  When the 2016 budget was published, the 2015 fiscal years was nearly complete, so even though 2015 is shown as an estimate, I am treating it as a very good estimate which may not necessarily be the case from 2016 onward.  In addition to doing my own forecasting of the inflows, outflows and resulting Trust fund balances out to 2060, I also have converted the 2016 budget forecasted and historical Social Security and Medicare outflows to Outflow/Person using census forecasts for the population over 65.  This ratio is then forecasted out to 2060 but converted back to Total Outflow to determine the Trust Fund Balances out to 2060.  [Note:  The Social Security Trust fund I am forecasting includes the Disability Fund which is used by people under 65 but this fund is less than 10 of the Social Security Trust Fund.  Also, there are some people who do draw on Social Security before 65, which I will evaluate later in this post.  Likewise the Medicare Trust Fund is the combined total of the Hospital and Supplemental Funds.  Lastly, the ratios of money you paid in to what you will take out  for either SS or Medicare remains the same from the 5/23/2011 post].

Looking at Social Security first, remember that the payroll tax rates, which you see on your W-2, have not increased since 1992.  Prior to this date, the payroll tax rates had been increased about every two years.  Prior to 1992, the SS Trust Fund balance forecast was not in jeopardy but each year since 1992, the forecasts have become increasingly dismal.  Also remember that there is a cap on wages to which the SS tax rate is applied, which limits in the Trust Fund inflow.  Below is a graph of the OASDI Trust Fund 
Balance (Old Age and Survivors and Disability Insurance) out to 2060 under 4 different scenarios.

  1. The blue line is the result of taking the 2016 budget forecast growth rates on Inflow (taxes mostly) and Outflow (benefits paid), then calculating the resulting balance of the fund.  You see that it goes negative in 2032.
  2. The purple line represents what would happen if the cap on wages taxed was immediately removed in 2015, with all other assumptions the same as in #1.  This extends the life of the fund to 2052 assuming that benefits paid do NOT change.
  3. The red line is the result of taking the CAPPED wages from #2 but applying a payroll tax rate that would exist in 2015 if payroll taxes had continued to be raised every two years at their historical rate.  To note, this tax rate would save OASDI Trust fund even with CAPPED wages.
  4. The green line has the same assumption as #3, except that wages had never been capped and the tax rate had gone up every two years from 1992,  in line with the history prior to 1992.
As you can see, the solution to the OASDI Fund is to increase the payroll tax or significantly reduce benefits.  It seems removing the cap is really not a TAX INCREASE but would cause the wealthy to pay more of the load.  This would buy some time to figure more acceptable solutions…tax rate hike or benefit reductions.

I also tried to look at the OASDI Fund using the most favorable growth rates in Inflow and Outflow, to determine if "rose colored glasses" might tell us anything different.  The highest growth in Inflow (taxes) was from 1995 to 2014 at 4.1% compounded annually. The lowest growth in Outflow (benefits) was from 2009 to 2014 at 4.1% compounded annually.  Using these two growth rates the Fund goes negative in 2043!  The bad news is that the 2016 Budget Forecast for these growth rates is 3.5% for Inflow and 4.8% for Outflow which results in the Fund going negative 2032 (the blue line in the graph above). Finally, converting the Outflow to Outflow/Person and finding the lowest growth rate for this number, the lowest is from 2009 to 2014 at 1.5% compounded annually.  If this forecast were used along with over 65 population growth the OASDI Trust Fund would never go negative!  By the way, the average per person benefit in this scenario is $1,563 per month in 2015.

Thinking about all of this Inflow and Outflow made me think about my own decision: When do I start to take my SS benefits???  So, out with the excel spreadsheet. Using the benefit estimates from by Social Security Annual Statement for age 62, 66 and 70, I created a simple model.  I assumed my  benefits would increase at 2% per year starting whatever year I began taking them.  Here is what I found to be my total benefits paid to me:
                                     Start at 62                    Start at 66                   Start at 70

Live to 80                     $495,356                      $495,353                    $459,997

Live to 90                     $837,912                      $964,469                 $1,031,902

If taking these benefits early allowed me to not to draw this amount from any IRA's, there is an additional benefit of growth in the IRA which amounts to (at 5% growth) about another $40,000 in the 4 years from 62 to 66, which buys a few more years!  Therefore, I started taking by benefits at 62 since I don't have long life genes in my family and I wanted to get in while the Fund is still solvent.

Now on to Medicare.  Again, I did some forecasting using Inflow (taxes mostly) and Outflow (benefits) using different growth rates on these numbers.  In addition, I also converted Outflow to Outflow/Person and studied this growth rate in different periods of time.  Using these different forecasts, I determined the resulting Medicare Trust Fund balance which is graphed below.

  1. The dark blue line uses the growth rates calculated over the 20 years from 1995 to 2014 for both Inflow and Outflow/Person.  This goes slightly negative for 14 years and then recovers.
  2. The green line uses the growth rates calculated over the 6 years from 2009 to 2014 for both Inflow and Outflow/Person.  This scenario never yields a negative Fund balance.
  3. The light blue line uses the growth rates calculated from 2015 to 2020 in the Budget Forecast.  Here the Fund Balance never goes negative.
  4. The red line uses the 20 year growth rates from 1995 to 2014 on Inflow and Total Outflow.  This goes negative in 2032.
  5. The purple line uses the 6 year growth rates from 2009 to 2014 on Inflow and Total Outflow.  This goes negative in 2028.
  6. The orange line represents the 6 year Budget Forecast growth from 2015 to 2020 for Inflow and Outflow.  This forecast does not go negative.  
What is the big difference in the growth rates from 2015 to 2020 being forecasted by the government.  Might this be the impact on Medicare of the ACA that has been often discussed?  Lets look at growth in for Total Medicare Outflow in an exponential control chart.

As you can see, the growth rate in Medicare Outflow (and Outflow per Person) since 2012 is down to 1.7% (the number in the table just above the blue shaded number).  This includes 3 years of actuals and is a statistically significant change.  For reference, the growth from 1995 to 2011 was 7.3%.  I am sure the Government is glad to see the low numbers for 2012-2015 and is happy to forecast this into the future as a way of claiming success on ACA which was signed into law in March of 2010.  The first insurance sign ups began in October of 2013.  If these numbers hold up, it could be that the Trust Fund might live on after all.