LATEST UPDATES 12/08/19 (Sections II, V, and VI), and 01/16/20 (footnote at end of post).
Economic growth has several causes:
1. Hard work — The tradeoff here is with “non-work” activities, and the tradeoff can be costly. But those who choose wisely in sacrificing non-work activities then acquire additional cash income, which can be used to offset the loss of non-work time and/or to improve the tools of one’s trade.
2. Smart work — Working smarter requires education, specialized training, and on-the-job learning. Today’s workers are (on the whole) more productive than their predecessors because the education, training, and on-the-job learning of today’s workers incorporates lessons learned by their predecessors.
3. Saving and investment — Resources that are saved (not used to produce consumption goods) can flow into investment (services and goods such as pharmaceutical research and development, advanced computer and telecommunications technologies). It is investment that enables the production of new, more, and better consumer goods with a given amount of labor. (Government investment is an inferior alternative to private investment.)
4. Invention, innovation, and entrepreneurship — These are the primary activities through which saving becomes investment, usually via the medium of financial institutions. Inventors, innovators, and entrepreneurs (along with shareholders, creditors, and financial intermediaries) accept the risks associated with failure and the rewards of success. It is the prospect of rewards that encourages invention, innovation, and entrepreneurship — and the benefits they bestow on workers and consumers. (Invention, innovation, and entrepreneurship — like work — are “socially responsible” activities because the pursuit of gain is motivated by the satisfaction of wants.)
5. Specialization and trade — If A makes bread and B makes butter — and if both prefer buttered bread — both benefit from trade. Where they produce bread and butter matters not; A and B could be neighbors, live in different parts of the United States, or one of them could live in a different country. In any event, both are made better off through voluntary exchange.
6. Population growth — Given the foregoing, a larger population means more people to work “hard” and “smart”; more output that can be saved and invested; more inventors, innovators, and entrepreneurs whose activities can be leveraged into greater per-capita output; and a multiplication of opportunities for beneficial voluntary exchange.
7. The rule of law under a minimal state — Predation — whether by individuals, mobs, or governments — discourages everything that fosters economic growth. The more that government tries to direct the economy, the less it will grow to satisfy material wants. (See Part III.)
The record of economic growth in America since World War II captures the effects — negative and positive — of these factors. The result is a cautionary tale against governmental interference in the economy.
The Bureau of Economic Analysis (BEA) issues a quarterly estimate of constant-dollar (year 2009) GDP, from 1947 to the present. BEA’s numbers yield several insights about the course of economic growth in the U.S.
I begin with this graph:
The exponential trend line indicates a constant-dollar (real) growth rate for the entire period of 0.8 percent quarterly, or 3.2 percent annually. The actual beginning-to-end annual growth rate is 3.1 percent.
The red bands parallel to the trend line delineate the 95-percent (1.96 sigma) confidence interval around the trend. GDP has been running at the lower edge of the confidence interval since after the end of the Great Recession.
The vertical gray bars represent recessions, which do not correspond precisely to the periods defined as such by the National Bureau of Economic Research (NBER). I define a recession as:
- three or more consecutive quarters in which real GDP (annualized) is below real GDP (annualized) for an earlier quarter, during which
- the annual (year-over-year) change in real GDP is negative in all, or all but one, quarters during the span.
Thus the NBER places the Great Recession from December 2007 to June 2009 — 18 months in all; whereas, I date it from the first quarter of 2008 through the second quarter of 2011 — 42 months in all. The higher figure seems right to me.
My method of identifying recessions is more objective and consistent than the NBER’s method, which one economist describes as “The NBER will know it when it sees it.” Moreover, unlike the NBER, I would not presume to pinpoint the first and last months of a recession, given the volatility of GDP estimates.
The following graph illustrates that volatility, and something much worse — the downward drift of the rate of real economic growth:
It’s not a pretty picture. The uptick in the early part of Trump’s administration has been reversed. Despite significant deregulation, the dead hand of the regulatory regime still lies heavy on the economy. (See “The Rahn Curve in Action” below.)
Here’s another ugly picture:
Rates of growth (depicted by the exponential regression lines) clearly are lower in later cycles than in earlier ones, and lowest of all in the current cycle.
In tabular form:
Until the current cycle (indicated by the red diamond) there was a strong but negative relationship between the length of a cycle and the robustness of a recovery. The current cycle peaked early, but at a low rate of growth:
By now, it should not surprise you to learn that we are in the midst of the weakest cycle of all post-war cycles (though the previous one took a dive when it ended in the Great Recession):
Which brings me to the Rahn Curve.
This section hasn’t been updated.
The theory behind the Rahn Curve is simple — but not simplistic. A relatively small government with powers limited mainly to the protection of citizens and their property is worth more than its cost to taxpayers because it fosters productive economic activity (not to mention liberty). But additional government spending hinders productive activity in many ways, which are discussed in Daniel Mitchell’s paper, “The Impact of Government Spending on Economic Growth.” (I would add to Mitchell’s list the burden of regulatory activity, which grows even when government does not.)
What does the Rahn Curve look like? Mitchell estimates this relationship between government spending and economic growth:
The curve is dashed rather than solid at low values of government spending because it has been decades since the governments of developed nations have spent as little as 20 percent of GDP. But as Mitchell and others note, the combined spending of governments in the U.S. was 10 percent (and less) until the eve of the Great Depression. And it was in the low-spending, laissez-faire era from the end of the Civil War to the early 1900s that the U.S. enjoyed its highest sustained rate of economic growth.
Elsewhere, I estimated the Rahn curve that spans most of the history of the United States. I came up with this relationship (terms modified for simplicity (with a slight cosmetic change in terminology):
Yg = 0.054 -0.066F
To be precise, it’s the annualized rate of growth over the most recent 10-year span (Yg), as a function of F (fraction of GDP spent by governments at all levels) in the preceding 10 years. The relationship is lagged because it takes time for government spending (and related regulatory activities) to wreak their counterproductive effects on economic activity. Also, I include transfer payments (e.g., Social Security) in my measure of F because there’s no essential difference between transfer payments and many other kinds of government spending. They all take money from those who produce and give it to those who don’t (e.g., government employees engaged in paper-shuffling, unproductive social-engineering schemes, and counterproductive regulatory activities).
When F is greater than the amount needed for national defense and domestic justice — no more than 0.1 (10 percent of GDP) — it discourages productive, growth-producing, job-creating activity. And because government spending weighs most heavily on taxpayers with above-average incomes, higher rates of F also discourage saving, which finances growth-producing investments in new businesses, business expansion, and capital (i.e., new and more productive business assets, both physical and intellectual).
I’ve taken a closer look at the post-World War II numbers because of the marked decline in the rate of growth since the end of the war (Figure 2).
Here’s the revised result, which accounts for more variables:
Yg = 0.0248 – 0.340F + 0.0773A – 0.000336R – 0.131P
Yg = real rate of GDP growth in a 10-year span (annualized)
F = fraction of GDP spent by governments at all levels during the preceding 10 years
A = the constant-dollar value of private nonresidential assets (business assets) as a fraction of GDP, averaged over the preceding 10 years
R = average number of Federal Register pages, in thousands, for the preceding 10-year period
P = growth in the CPI-U during the preceding 10 years (annualized).
The r-squared of the equation is 0.74 and the F-value is 1.60E-13. The p-values of the intercept and coefficients are 0.093, 3.98E-08, 4.83E-09, 6.05E-07, and 0.0071. The standard error of the estimate is 0.0049, that is, about half a percentage point.
Here’s how the equation stacks up against actual 10-year rates of real GDP growth:
What does the new equation portend for the next 10 years? Based on the values of F, A, R, and P for 2008-2017, the real rate of growth for the next 10 years will be about 2.0 percent. (The most recent year-over-year rate of growth is 2.3 percent.)
As the forgoing analysis suggests, the true multiplier — the “return” on an exogenous increase in government spending — is negative. See “Keynesian Multiplier: Fiction vs. Fact” for the whole story.
Although the central government’s tentacles reach deep into every State’s economy, there is still latitude for State and local action — or lack thereof. Republican-controlled States should have somewhat freer economies than Democrat-controlled ones. (See, for example, the Tax Foundation’s 2020 Business Climate Tax Index.) Republican-controlled States should therefore be more growth-prone than Democrat-controlled ones. Regional statistics support this hypothesis:
Constructed from the regional data tool of the Bureau of Economic Analysis, starting here.
The red lines represent regions that are dominated by Republican-controlled States; the blue lines, regions dominated by Democrat-controlled States. The constituent States of each region are as follows:
Far West — Alaska, California, Hawaii, Nevada, Oregon, Washington
Southwest — Arizona, New Mexico, Oklahoma, Texas
Rocky Mountain — Colorado, Idaho, Montana, Utah, Wyoming
Southeast — Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, West Virginia
New England — Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont
Plains — Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota
Mideast — Delaware, DC, Maryland, New Jersey, New York, Pennsylvania
Great Lakes — Illinois, Indiana, Michigan, Ohio, Wisconsin
With the exception of the Far West, the best-performing regions have been dominated by Republican-controlled States
The real unemployment rate is several percentage points above the nominal rate. Officially, the unemployment rate stood at 3.5 percent as of November 2019. Unofficially — but in reality — the unemployment rate was 9.4 percent.
How can I say that the real unemployment rate was 9.4 percent, even though the official rate was only 3.5 percent? Easily. Just follow this trail of definitions, provided by the official purveyor of unemployment statistics, the Bureau of Labor Statistics:
Unemployed persons (Current Population Survey)
Persons aged 16 years and older who had no employment during the reference week, were available for work, except for temporary illness, and had made specific efforts to find employment sometime during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed.
The unemployment rate represents the number unemployed as a percent of the labor force.
Labor force (Current Population Survey)
The labor force includes all persons classified as employed or unemployed in accordance with the definitions contained in this glossary.
Labor force participation rate
The labor force as a percent of the civilian noninstitutional population.
Civilian noninstitutional population (Current Population Survey)
Included are persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces.
In short, if you are 16 years of age and older, not confined to an institution or on active duty in the armed forces, but have not recently made specific efforts to find employment, you are not (officially) a member of the labor force. And if you are not (officially) a member of the labor force because you have given up looking for work, you are not (officially) unemployed — according to the BLS. Of course, you are really unemployed, but your unemployment is well disguised by the BLS’s contorted definition of unemployment.
What has happened is this: Since the first four months of 2000, when the labor-force participation rate peaked at 67.3 percent, it declined to 62.3 percent in 2015 and leveled off below 62.5 percent before jumping above 63 percent in 2018:
The decline that began in 2000 came to a halt in 2005, but resumed in late 2008. The economic slowdown in 2001 (which followed the bursting of the dot-com bubble) can account for the decline through 2005, as workers chose to withdraw from the labor force when faced with dimmer employment prospects. But what about the sharper decline that began near the end of Bush’s second term?
There we see not only the demoralizing effects of the Great Recession but also the growing allure of incentives to refrain from work, namely, disability payments, extended unemployment benefits, the relaxation of welfare rules, the aggressive distribution of food stamps, and “free” healthcare” for an expanded Medicaid enrollment base and 20-somethings who live in their parents’ basements*. That’s on the supply side. On the demand side, there are the phony and even negative effects of “stimulus” spending; the chilling effects of regime uncertainty, persisted beyond the official end of the Great Recession; and the expansion of government spending and regulation (e.g., Dodd-Frank), as discussed in Part III.
A second factor, though of less significance, is a decline in the percentage of employed persons who are working full-time. It dropped from 83.3 percent in 2000 — its highest level since 1989 — to 79.9 percent in 2010 before rising jaggedly to 83.0 percent in November 2019. A shift from full-time to part-time work is really a form of disemployment, and ought to be reflected in the unemployment rate.
I constructed the actual unemployment rate by adjusting the nominal rate for (a) the change in the labor-force participation rate and (b) the change in the percentage of workers in full-time status. The disparity between the actual and nominal unemployment rates is evident in this graph:
Derived from SeriesLNS12000000, Seasonally Adjusted Employment Level; SeriesLNS11000000, Seasonally Adjusted Civilian Labor Force Level; Series LNS11300000, Seasonally Adjusted Civilian labor force participation rate; and Series LNS12500000, Employed, Usually Work Full Time. All are available at BLS, Labor Force Statistics from the Current Population Survey.
It will not have escaped your notice that the Obama regime is responsible for much or most of the damage done to the workers of America. It remains to be seen whether and to what extent Mr. Trump can undo that damage.
* Contrary to some speculation, the labor-force participation rate is not declining because older workers are retiring earlier. The participation rate among workers 55 and older rose between 2002 and 2012. The decline is concentrated among workers under the age of 55, and especially workers in the 16-24 age bracket. (See this table at BLS.gov.) Why? My conjecture: The Great Recession caused a shakeout of marginal (low-skill) workers, many of whom simply dropped out of the labor market. And it became easier for them to drop out because, under Obamacare, many of them became eligible for Medicaid and many others enjoy prolonged coverage (until age 26) under their parents’ health plans. For more on this point, see Salim Furth’s “In the Obama Economy, a Decline in Teen Workers” (The Daily Signal, April 11, 2015), and Stephen Moore’s “Why Are So Many Employers Unable to Fill Jobs?” (The Daily Signal, April 6, 2015). On the general issue of declining participation among males aged 25-54, see Timothy Taylor’s “Why Are Men Detaching from the Labor Force?“, (The Conversible Economist, January 16, 2020), and follow the links therein. See also Scott Winship’s “Declining Prime-Age Male Labor Force Participation” (The Bridge, Mercatus Center, September 26, 2017).