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David Stanowski
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National Economic Indicators
by David Stanowski

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Total Federal Receipts
Consumer Sentiment
Vehicle Miles Traveled
Electric Power Generation
Employment Metrics
Case-Schiller Residential Real Estate Indexes

The Decline of America Shown in One Chart:

The Era of BIG GOVERNMENT began in 1913 with the passage of the Federal Reserve Act (December 23,1913), allowing unlimited credit creation; the ratification of the 16th Amendment (February 03,1913), authorizing the collection of "income tax"; and the ratification of the 17th Amendment (April 08, 1913), ending the appointment of Senators by the state legislatures, undermining state independence and power which transferred more control to the federal government.

"From that time forward, the United States ceased being a free, "isolationist", prosperous country with a stable currency and became a nation of taxation, inflation, regulation, debt and foreign wars; activities that reward the political class." EWT July 2018

The Gilded Age (1870-1900) witnessed the greatest economic and Productivity growth in the nation's history. "In 1860, the nation's total wealth was $16 billion. By 1900, it was $88 billion. (Editor's note: this is an increase of 450%, from 1860 to 1900, or approximately 11.25% per year!) This translated into a per capita increase from $500 to $1,100. Driving this growth was an explosion in American manufacturing—in 1869, the manufacturing sector of the economy generated $3 billion, a figure which rose to $13 billion by 1900."

"For starters, there was an unprecedented explosion of new industrial and agricultural technology. The United States patent office issued 440,000 patents between 1860 and 1900—12 times more than during the preceding 70 years. On the farms, steam tractors and mechanical reapers, harvesters, and combines all greatly increased agricultural productivity. By 1900, it required only 15 man-hours per acre to raise wheat, while a century earlier, it had taken 56 man-hours per acre." The Economy of the Gilded Age  

"During the 1870s and 1880s, the U.S. economy rose at the fastest rate in its history, with real wages, wealth, GDP, and capital formation all increasing rapidly. For example, between 1865 and 1898, the output of wheat increased by 256%, corn by 222%, coal by 800% and miles of railway track by 567%. Thick national networks for transportation and communication were created. The corporation became the dominant form of business organization, and a scientific management revolution transformed business operations.

By the beginning of the 20th century, gross domestic product and industrial production in the United States led the world. Kennedy reports that "U.S. national income, in absolute figures in per capita, was so far above everybody else's by 1914." Per capita income in the United States was $377 in 1914 compared to Britain in second place at $244, Germany at $184, France at $153, and Italy at $108, while Russia and Japan trailed far behind at $41 and $36." Gilded Age

Why hasn't the American economy been able to match the growth rates of the Gilded Age during the 20th Century's further industrialization and the 20th and 21st Centurys' Information Age?

BIG GOVERNMENT and its high taxes, debasement of the currency and regulations. BIG GOVERNMENT = War and Welfare!

The following chart clearly shows that before 1913 Americans paid 1-5% of the GDP to the federal government in taxes; after 1913, it took about 30 years to establish the new range of taxes paid between 15-20%, but they have never returned to their previous level.

Federal Receipts as a % of GDP 1790-2018

Monthly Total Federal Receipts:
 Latest Update: 11 August 2018

What is the best way to accurately measure the strength of the economy?

The "official" method is to use the Gross Domestic Product (GDP), but there are obvious inaccuracies and distortions with this metric. GDP is a very complicated calculation requiring many assumptions and estimates, so there are numerous potential problems with how it is computed. 

"The actual number for GDP is therefore the product of a vast patchwork of statistics and a complicated set of processes carried out on the raw data to fit them to the conceptual framework." Coyle, Diane (2014). GDP: A Brief but Affectionate History.

One of three common ways to calculate GDP is: 
GDP = Y = C + I + G + (X − M)

Where C = consumption, I = investment, G = government spending and (X – M) = net exports
There are many reasons to doubt that this formula is the best method to measure economic strength. For example, it is difficult to see how and why government spending is given the same weight as private-sector activity, because the private-sector had to produce everything that the government spends. In fact, when you think about it, does the government "produce" anything of real "net benefit" for the overall economy? 

The first estimate of GDP each quarter is made as a "Nominal" value, i.e. without any adjustment for inflation. After the calculation of the Nominal GDP, it is then adjusted lower by "some" amount of inflation using the GDP Deflater to arrive at the "official" value for "Real" GDP. But, how much should it be reduced? Like the Consumer Price Index, the GDP Deflater is one of the most corrupt and inaccurate statistics produced by the government which further taints the value of the Real GDP calculation.

Finally, after using many assumptions and estimates to calculate Real GDP, it is then revised two times before a "final" number is produced. This final number usually isn't available for about two months after the end of the quarter that it is "estimating", so GDP is also not a very timely statistic.

An Alternative Measure of Economic Strength:
"Total Federal Receipts" is an excellent alternative. It does not attempt to measure consumption, investment, government spending or net exports, but it is an excellent measure of private sector economic strength. Over 90% of these federal receipts come from individual income tax, corporate income tax and payroll taxes actually collected and paid each month to the U.S. Treasury, so this statistic should directly reflect how well the private sector is doing. The more robust the economy is, the higher these receipts will be.
"Total Federal Receipts" are "paid" and simply "counted" tax payments; they are NOT "calculations" or "estimates". In addition, this data is available monthly, not just quarterly like GDP, and it is available only 8 business days after month end, so it is also very timely. In addition, it is NOT seasonally adjusted like so much other government economic data.

Total Federal Receipts:

Many analysts look at the raw, un-smoothed data (see table below) for the last three months and find it quite troubling and certainly not supportive of the first estimate of 2Q Real GDP of 4.1%!
This raw monthly data is troubling, but monthly data is subject to wide swings, so this report will concentrate on the smoothed data shown below the table.

Month Total Federal Receipts
in Millions of Dollars
Month Total Federal Receipts
in Millions of Dollars
May 2017 $240,418 May 2018 $217,075 -9.71%
June 2017 $338,660 June 2018 $316,278 -6.61%
July 2017 $232,040 July 2018 $225,266 -2.92%

The first graph has been generated by calculating a backward looking 12-month rolling sum, of the previous 12 month's Total Federal Receipts collected, to smooth the data. 

The smoothed data clearly shows Total Federal Receipts collected topping out in April 2008, as the 2007-2009 financial crisis took hold, and then bottoming in January 2010 when the economy started to recover. After the 2010 bottom, Total Federal Receipts moved up for six years until their growth began to slow about February 2016.

Total Federal Receipts 12 Month Sum

To get a more "dynamic" and "internal" look at the uptrend in total federal receipts collected, the Year-Over-Year Rate of Change was calculated to discover how the current 12-month trailing sum of Total Federal Receipts collected compared to the sum 12 months ago throughout the period in question.

Clearly, the positive rate of change in Total Federal Receipts collected peaked in October 2005. The four years after that show the effect of the world-wide economic slowdown that preceded the financial crisis of 2007-2009, and then the crisis itself. Negative economic forces peaked in November 2009, and then the FED's unprecedented credit creation, in response to the crisis, allowed the economy to stage a dramatic recovery, but the rate of recovery peaked in June 2013 at a lower level of growth than that registered at the October 2005 peak. 

Although the amount of Total Federal Receipts collected continued to grow after June 2013, as shown by the previous graph, this rate-of-change graph demonstrates that the growth rate has been contracting for the last five years! 
In fact, the growth in Total Federal Receipts collected actually turned negative in December 2016, and bottomed in March 2017 at -1.25%; but it's back down to ONLY 0.40% in July!!

This pattern of contraction in the growth of Total Federal Receipts collected could certainly resolve itself with an upward spurt, and higher rates of collections, but a pattern of slowing positive momentum is often a signal that the economy is on the verge of going into decline, as happened between October 2005 and November 2009.

Total Federal Receipts YoY RoC

Even more troubling is the fact that these numbers show the "nominal" amount of Total Federal Receipts collected which corresponds to the nominal amount of economic activity. In other words, this data has not been "adjusted" for inflation by using some "estimate" of the current inflation rate to create the "real" (inflation-adjusted) rate of Total Federal Receipts collected. Since the July 2018 NOMINAL rate-of-change in Total Federal Receipts collected was only 0.40%, adjusting for the current "estimated" rate of inflation of at least 3.0% would  tend to indicate that the economy is already contracting on a "real" basis!

With the Year-over-Year rate-of-change of the smoothed Total Federal Receipts coming in with NOMINAL growth rates of 2.23% in May, 1.27% in June, and 0.40% in July this data raises real questions about the accuracy of the first estimate of 2Q Real GDP of 4.1%.

Monthly University of Michigan
Consumer Sentiment:
 Latest Update: 27 July 2018

The University of Michigan Consumer Sentiment Index provides an insight into how the country feels about its political and economic future. The all-time high in Sentiment occurred in January 2000 coincident with the peak in many stock indexes. As the NASDAQ Bubble burst in 2000-2002, the FED stepped in to bail out investors which eventually halted and reversed the stock market decline, but the excess credit created a real estate bubble.

However, even as the real-estate bubble reached unheard of heights and finally peaked in 2005-2006, and the new stock market rally hit a new high in 2007; this surge of recklessly-created credit did not make Americans feel nearly as positive as they did in 2000!

The stock market plunge from the fall of 2007 to the spring of 2009, and the on-going real estate decline drove Sentiment down into the mid 50's; 51% below it's former high!

The unprecedented credit creation by the FED since 2008 has created new stock and real estate bubbles, but the economy is still not as strong as in most typical post-WWII recoveries, which is why Sentiment is close to 100, again, but still below the January 2000 high.

Consumer Sentiment Monthly

Monthly Vehicle Miles Traveled:
 Latest Update: 29 July 2018

The Federal Highway Administration collects traffic data and publishes it monthly. This data should offer some useful insights into the growth or contraction of the economy. Traffic Volume Trends

"Traffic Volume Trends is a monthly report based on hourly traffic count data reported by the States. These data are collected at approximately 4,000 continuous traffic counting locations nationwide and are used to estimate the percent change in traffic for the current month compared with the same month in the previous year. Estimates are re-adjusted annually to match the vehicle miles of travel from the Highway Performance Monitoring System and are continually updated with additional data."

The first graph was
generated by calculating a backward looking 12-month rolling sum, of the previous 12 month's Vehicle Miles Traveled, to smooth the data. The scale on the graph needs to be multiplied by 1,000,000 to get the proper number.

The smoothed data clearly shows a generally upward trend throughout the entire period, however, this graph offers little useful information other than the fact that Americans have continued to drive more miles over the 48-year period for which data is available. Questions can certainly be raised about whether driving habits have changed due to commuting patterns, the use of mass transit, telecommuting, online shopping and its greater need for delivery services and whether any of these changes modify the relationships of current data versus earlier results. 

Vehicle Miles Traveled 12 Month

To get a more "dynamic" and "internal" look at the uptrend in Vehicle Miles Traveled, the Year-Over-Year Rate of Change was calculated to discover how the current 12-month trailing sum of Vehicle Miles Traveled compared to the sum 12 months ago throughout the period in question.

During the first 10 years of the study, the collapsing rate of growth from September 1972 to November 1974 and from April 1979 to April 1980 clearly foretold the economic contractions that were starting, as would be expected.

However, after that, the pattern is more puzzling. The first surprise was that the economic expansion from 1980 to 2000 saw the rate of growth of Vehicle Miles Traveled peak very early; in January 1989! The rate of growth peaks in February 1995 and August 2000 were progressively lower than the January 1989 top?

Since the American population has continued to grow throughout this entire period, and this data is NOT presented on a per capita basis, it was expected that the rate of change of Vehicle Miles Traveled should maintain relatively high rates of growth even if it was ONLY due to the increasing population! In addition, the number of registered motor vehicles stood at about 190,000,000 in 1989 and had grown to 225,821,000 in 2000, so the number of vehicles kept increasing, too. Either something fundamentally changed in the way vehicles were being used, after 1989, or the internal strength of the economy may have actually peaked in 1989? Number of Registered Motor Vehicles

The next surprise was that the "economic recovery" from 2003 to 2007 started with a sideways pattern in the rate of change in Vehicle Miles Traveled rather than a upward trend? Then the weak sideways pattern resolved into an outright decline into August 2007; the second 21st Century stock market top? Once again, the number of registered motor vehicles increased to 254,403,000 by 2007 even as the rate of change in Vehicle Miles Traveled declined? From August 2007 to February 2009 the rate of change in Vehicle Miles Traveled did collapse into negative territory as expected due to the 2007-2009 Great Recession.

After the February 2009 bottom, growth in the rate of change persisted into October 2016, but it peaked at a very tepid 2.66% confirming the internal weakness of the recovery off the 2009 low, even as the number of registered  motor vehicles increased from 254,212,000 to 268,799,000. From there, the rate of change began to decline to where it currently stands at only 0.69%, in May 2018; the latest available data.

Vehicle Miles Traveled YoY RoC

Monthly Electric Power Generation Index:
 Latest Update: 31 July 2018

The Federal Reserve compiles electric power generation data and publishes it in a monthly index. This data should offer some useful insights into the growth or contraction of the economy. 

The first graph was
generated by calculating a backward looking 12-month rolling sum, of the previous 12 month's Electric Power Generation Index, to smooth the data. Since the American population has continued to grow throughout this entire period, and this data is NOT presented on a per capita basis, it was expected that the total amount of electric energy generated would continue to grow, due to population growth, even if the economy was not growing.

Therefore, it was very surprising to find that the Electric Power Generation Index peaked in July 2008, and it has been trending sideways to lower for the last 10 years! Questions can certainly be raised about whether electricity use has changed due to more efficient devices and more conservation, but people seem to be using even more devices, that run on electricity, and air conditioning use continues to threaten brown outs. Are there any changes in electricity use that modify the relationship of current data versus earlier results? See also

Electric Power Generation

To get a more "dynamic" and "internal" look at the trend in the Electric Power Generation Index, the Year-Over-Year Rate of Change was calculated to discover how the current 12-month trailing sum of the Electric Power Generation Index compared to the sum 12 months ago throughout the period in question.

The next graph is truly baffling! It clearly shows that the highest positive rate- of-change in the Electric Power Generation Index occurred in September 1977! From there, the rate of change went through the usual peaks and valleys, but with a series of progressively declining peaks?

The strong economy of the 1980s saw the
rate-of-change in the Electric Power Generation Index peaking early in June 1984, and then declining into June 1997 to at -2.43%.

The rebound into the 1999-2000 period also peaked early in April 1999 and then moved lower to sideways into a lower peak in May 2006 before declining into a bottom in July 2009 at -3.56%.

From there the rate-of-change has entered another sideways pattern fluctuating above and below zero growth!

Whatever electricity usage may be telling us about the true internal strength of the economy, it certainly doesn't look very robust since the September 1977 top, and having the usage peak in July 2008 and the rate-of-change running
sideways fluctuating above and below zero growth since then seems to indicate that the economy still has not fully recovery from the 2007-2009 Great Recession!
Electric Power Generation Yoy RoC

Quarterly Productivity:
 Latest Update: 25 July 2018

Productivity is a measure of the efficiency of the American labor force. The labor force must maintain its current level of Productivity in order to maintain its standard of living. The only way for the country to increase its standard of living is to increase its Productivity. The rate-of-change in the growth of Productivity has been slipping in recent years which has lead to questions about whether future generations will enjoy a higher standard of living than today, or will they be the first in our history to have a lower standard of living than their parents.

It's interesting to note that even without any knowledge of the government's measurement of Productivity, many younger people already sense the possibility that they will NOT enjoy an increasing standard of living like previous generations.

The growth of Productivity is determined by capital accumulation and deployment. Capital comes in two forms: physical (equipment) and human (knowledge and skills). One person with a shovel can move a certain amount of dirt in one hour; the same person with a bulldozer can move a lot more dirt in the same period. Likewise, one person with no mathematical training can perform some basic counting and analysis whereas one person with mathematical training can do much more in the same time period.

Measuring Productivity accurately is both important and difficult. The federal government defines Productivity as "real output per hour of all persons". Output itself is not easy to accurately quantify. It is similar to measuring GDP. To make the measurement of Productivity "real", it has to be adjusted by some amount due to inflation. All government measurements of inflation are dishonest, because they are designed to make inflation appear to be far lower than it really is to maintain their political support. Finally, how can the government accurately determine the number of hours worked in a given time period, especially when salaried  employees and business owners are part of the computation?

Considering all of the problems with measuring Productivity accurately, the following graph shows the nation's Productivity (as computed by the federal government) every quarter since 1947. This data clearly shows an upward trend in Productivity over the post WWII period.

However, after plotting 70+ years of rising Productivity, it is difficult to draw any specific conclusions from this data, so a rate-of-change calculation is normally employed to see what it might reveal.

To get a more "dynamic" and "internal" look at the uptrend in Productivity, the Quarter-Over-Quarter Rate of Change was calculated to discover how the Productivity for the current quarter compared to the previous quarter throughout the period in question. The next graph shows this data.

Unfortunately, the rate-of-change done on a quarterly basis creates too many wild fluctuations to be useful, so the data needs to be smoothed by using the quarterly data to create yearly data.

The next graph has been generated by calculating a backward looking 4-quarter rolling sum, of the previous 4 month's Productivity, to smooth the data. Then the Year-Over-Year Rate-of-Change was calculated using this rolling sum.

This data clearly shows the rate of Productivity growth declining from 1950 into the 1974 and 1982 recessions. From the 2Q 1982 low, the rate of Productivity growth was able to exceed 4 percent again in late 1983, and it has oscillated between 0 and 4 percent ever since. Notice that the rate of Productivity growth peaked in 1Q 2004, and it's been lower ever since (14 Years). More recently, the rate of Productivity growth slowed to between 0 an 1% for the LAST FIVE YEARS! 

A handful of astute analysts have been very concerned about America's declining Productivity for the last 10-15 years. One such analyst is the editor of He decided to look at America's entire history of Productivity growth; not just the post-WWII data that the federal government data base covers. His calculations of Productivity growth were done by simply using the GDP per capita as a proxy for the modern definition of Productivity, since he could perform this calculation from 1790 up through 2015, when his article was published.

The graph of his data (click the link below the graph to see the full-sized version) looks at Productivity growth during five specific time spans listed in the gray box in the upper right hand corner of the graph.

Note that from 1790 to 1840, the U.S. was primarily an agrarian economy made up of small family farmers with very little capital to support their operations. Farm mechanization was in its infancy and most farmers were uneducated, so the average annual growth rate of Productivity was only 0.7%.

From 1840 to 1875, when industrialization was first taking hold, annual Productivity growth jumped to 1.2%.

From 1875 to 1975, which was the heart of the Industrial Revolution, annual Productivity growth doubled to 2.4%! In addition, Bawerk found that Productivity growth peaked in 1972, the year after Nixon cut the final ties with the "gold standard".

Finally, from 1975 to 2015, average annual Productivity growth slowed to 1.2% and from 2010 to 2015 average annual Productivity growth was down to 0.8%! His shocking conclusion was that America's modern high-tech economy now has almost the same rate of Productivity growth as the country experienced when small family farmers were working a plow behind a mule!

This analysis certainly provides one explanation for the current economic weakness.

The most obvious reason for this catastrophic decline in the rate of the growth in Productivity is the debasing of the currency by the FED and the intervention in and the regulation of the economy by the government. The result of these activities has been a decline in real capital available to boost Productivity and the mis-allocation of capital to politically-favored enterprises that do not enhance Productivity; in fact they often simply consume capital (for example: residential real estate).

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