Solving the World's Demographic Crisis One Vacation at a Time

I frequently post on the demographic crisis facing the world's developed nations.  As many of us know, there simply are not enough children being born to replace those who are at the far end of life's journey.  This means that baby boomers who are about to retire and experience the years that cost governments substantial investments in health care and social entitlement programs will have fewer and fewer workers supporting them.

Denmark is a case in point.  Here is a graph showing Denmark's birthrate since 1970:

In 2011, Denmark's birthrate dropped to a 30 year low of 10.6 births per 1000 people.

For comparison, here is a look at the United States birthrate since 1970:

The trend looks fairly similar, doesn't it?  In 2011, America's birthrate dropped to a 40 year low of 12.7 births per 1000 people.

In contrast, here is a look at Indonesia's birthrate since 1970:

While Indonesia's birthrate has fallen from a rather stunning 41 births per 1000 people in the early 1970s, it is still well above the rates in the developed world, coming in at 19.63 births per 1000 people in 2011.

So, what is to be done about this problem?  Denmark seems to have the answer as shown on this video:

This novel promotion was launched by the Spies Travel Agency in Denmark.  The video notes two important factors working in favour of an increased birthrate; first, that Danes have 46 percent more sex when on holiday and second, that 10 percent of Danish children are conceived abroad.  If couples conceive abroad, they win a three-year supply of baby goodies and a child-friendly holiday on top of the fun that they already had!

Using Tower Building to Predict Stock Market Returns

An interesting paper by Dr. Guenter Loffler, a Professor of Finance at University of Ulm in Germany titled "Tower Building and Stock Market Returns" draws an interesting historical connection between the construction of a large number of buildings and the behaviour of the stock market.

For his study, Dr. Loffler selected buildings that are classified as either high rise or skyscrapers and excludes buildings such as city halls, courthouses, capitol buildings and county halls since the construction of government buildings should be less sensitive to economic cycles since they may well be built during economic downturns as part of a stimulus package.  Dr. Loffler also focuses on construction starts rather than construction completions because starts better reflect the economic situation at the time.  Dr. Loffler is also selective in his definition of which buildings qualify as noted here:

"As a measure of US tower-building activity, I examine the number of towers exceeding a threshold defined by the trailing average height of large buildings. Since the height of large towers is trending upward over time, this appears superior to the use of a fixed threshold such as 100 meters. Specifically, I define the threshold to be the average height of buildings of over 50 meters that were built in the thirty-year interval before the year in question. The choice of thirty years is motivated by the observation that building activity can follow relatively long cycles. For example, in the 20 years from 1933 to 1952, only 76 towers of over 50 meters were built, and these had an average height of 80.1 meters. This compares to an average height of 88.9 meters for the 473 towers whose construction began during the 1923-1932 period. Using a trailing average of thirty years makes the threshold less dependent on general cycles in building activity, and thus better suited to identifying buildings that would be considered tall."

The variable "LargeStart" is the measure of tower building activity and is calculated using these equations:

Here is the building activity of large buildings over the past century and a half as defined by LargeStart:

Using annual stock market returns over the period from 1871 to 2010 from Robert Shiller's website, Dr. Loffler's analysis shows that construction starts for skyscrapers show significant predictive ability.  His analysis shows that high levels of tower building activity goes along with low future returns; a one standard deviation increase in tower building activity lowers three-year stock market returns by 11.8 percentage points or 3.9 percent per year.

I found the data from the 1920s particularly interesting.  Here is a list of the towers that were expected to break the height record when construction began by year:

Notice the skyscraper building boom during the late 1920s just prior to the Great Depression.  Even though construction began in 1930, one could include the Empire State Building in the pre-Depression buildings since construction was planned during the late 1920s when John Jakob Raskob and his partners purchased the Waldorf-Astoria hotel that was on the site.  While there is some correlation between construction starts for record-breaking buildings and stock market performance prior to 1945, after World War II, the relationship is not as robust as the correlation between construction starts for large buildings and stock market performance.  This means that investors should focus on the building of large towers rather than record-breaking towers to predict future stock market direction.  Dr. Loffler notes that more recently, the number of towers over 100 metres in height on which construction was started in 2007 was more than twice the annual average of similar construction starts over the period between 1987 and 2006.  We all know what happened to the stock market in 2008, don't we?  One prime example of what happens during a building/stock market boom - bust cycle is the Chicago Spire.  This tower would have become the second highest tower in the world at 2000 feet (150 stories).  The design received final approval in 2007 and construction began.  In late 2008, construction was halted after the foundation was laid, largely because the global financial crisis negatively impacted the ability of the developers to get further financing. 

Dr. Loffler suggests that there are two possible reasons for the connection between tower building and returns on the stock market:

1.) It proxies for market sentiment (i.e. potential overvaluation).

2.) It captures the credit market conditions at the time (i.e. potential over-exuberance).

This analysis shows that the over-optimism that is present in the economy during boom periods impacts both the stock market and the building of skyscrapers.  During periods when businesses and individuals are less concerned about risk, it is easier to finance large-scale construction of office towers just as it is more likely that individuals will enter the stock market and bid up share prices.

The relationship between the construction of skyscrapers and the future direction of the stock market is rather compelling.  It provides investors with an additional tool that can be used to assist in gaining a sense of where the market could be heading at a time when an increasing number of large tower construction makes the economy appear to be immune from any correction.

The Stagnant Wage - Modest Economic Growth Conundrum

A recent study, "Wage Woes" by Russ Koesterich at BlackRock examines what is missing in the post-Great Recession recovery and how this missing factor is going to impact growth rates in the economy.

Let's open with a look at two key aspects of the economy; real disposable personal income and real personal consumption expenditures.  Here is a graph showing how real (after inflation) per capita disposable personal income has changed since the Great Depression:

Notice how the curve flattens after 2007 - 2008?  Let's look at that in a bit more detail.

Here is a graph showing the year-over-year annual percentage change in real per capita disposable personal income:

Over the 85 year period, real personal disposable income grew at an average annual rate of 2.06 percent even when all recessions are included.  This growth rate dropped substantially after 1998 as shown by the red arrow; between 2008 and 2013, growth dropped to an average of 0.4 percent per year over the six year period, hitting a peak of 1.6 percent in 2011 and a low of -1.3 percent in 2008.  Even in 2013, four years after the "recovery", real per capita disposable personal income did not grow at all.

Here is a graph showing real personal consumption expenditures:

After a spending slowdown during the Great Recession, America's consumers are now spending with total real personal consumption expenditures of $10.831 trillion in the fourth quarter of 2013.  

Here is a graph showing the year-over-year growth rate of real personal consumption expenditures:

Note how the red arrow on this graph tracks the red arrow on the second graph?  The Great Recession saw the greatest contraction in personal consumption expenditures all the way back to the 1940s and since the end of the recession in mid-2009, annual growth in personal expenditures has risen at an average of 2.2 percent compared to the annual average of 3.3 percent back to the late 1940s when all recessions are included.  The graph also shows us that the latest "recovery" has been the most modest when comparing the growth rate of real consumer spending between recessions back to 1948. 

Now, let's go to the study.  The author notes that real median family incomes have been on the decline since long-before the Great Recession; in fact, the vast majority of American households have had stagnant real incomes since around the year 1998 as shown on this graph:

Obviously, when real household income drops, real disposable income drops.  Between 1973 and 2011, a median male working full-time experienced a 5 percent contraction in inflation-corrected income, dropping from $50,000 to $48,200.  This means that after adjusting for inflation, an average American male worker has not had a raise in the past 4 decades.

What will change this situation?  The author notes that the number of jobless claims is directly related to growth in real income.  Historically, when initial jobless claims around around 320,000, real income growth of between 3 percent and 3.5 percent is likely.  However, even though the economy is in that level now, there are other factors at play.  One key factor, thanks to Washington, is the continuing high level of political and policy uncertainty as measured by the Economic Policy Uncertainty Index (EPUI) as shown on this graph:

Higher levels of political and policy uncertainty leads to lower consumer and business confidence which leads to lower capital spending and lower levels of hiring.  The lack of hiring results in much lower upward pressure on wages.  The author estimates that the current high level of political and policy uncertainty alone has subtracted half a percent from annual real wage growth.  Thanks for nothing Washington!

In closing, here is a graph that shows how much of an impact consumer uncertainty has had on the percentage of consumer spending in GDP:

Between 1970 and 2010, the personal consumption component of GDP grew from 60 percent to 68 percent.  Since 2010, there has basically been no change; the very modest growth level in consumer spending simply is not contributing more to GDP which results in lower GDP growth which leads to more uncertainty which leads to less capital spending by businesses which leads to less hiring etcetera ad infinitum.

America's economy is caught in a loop from which there appears to be no easy means of extrication.  The Fed's pumping and dumping has done relatively little to prod either consumers or businesses to spend, invest and hire, resulting in a situation where there is absolutely no motive for businesses to speed up the pace of wage growth.  Without real wage growth, consumers will not spend, businesses will not invest and the economy will not grow.  It's as simple as that.

Who Are America's Long-Term Unemployed?

As has been repeatedly pointed out, the employment picture in this recovery is different than other recoveries and, as shown on this graph, is largely due to the elevated number of Americans that are unemployed for long-periods of time:

A paper "Are the Long-Term Unemployed on the Margins of the Labor Market" by Alan B. Kruger, Judd Cramer and David Cho looks at what has happened to America's long-term unemployed since the so-called "end" of the Great Recession and who they are.

America's long-term unemployed are a persistent problem for the economy as you can readily see in the first graph from FRED, and are pushing up the overall unemployment rate.  As you can see on this graph, a very significant 37 percent of America's total unemployed workers have been unemployed for 27 weeks or more:

While this is down from its post-Great Recession peak of 45.3 percent in April 2010, it is still three times the average level of long-term unemployed seen between 1948 and the beginning of 2008. 

In contrast, as shown on this graph, the number of civilians unemployed for 5 to 14 weeks (the short-term unemployed) is very close to normal levels looking back to the mid-1970s:

Here is a graph showing the percentage of total unemployed Americans that have been unemployed for 5 to 14 weeks:

It's interesting to see that the percentage of workers who have been out of work for 5 to 14 weeks is nearly the smallest proportion of the total unemployed looking all the way back to 1948.

Certain parts of the economy have a higher proportion of long-term unemployed than others; 36 percent were previously employed in sales and service and 28 percent were employed in blue collar jobs.  When these long-term unemployed do return to work, they tend to return to similar occupations that they held prior to being laid off.

Among workers who had been unemployed for 27 weeks or longer in a given month in the period between 2008 and 2012, fifteen months later:

- 30 percent were unemployed and looking for work

- 34 percent weren't working and weren't looking for work

- 36 percent were employed

Drilling down further into the data, of the 36 percent that were employed:

- 11 percent had been employed full-time for at least 4 months

- 14 percent had been employed for at least 4 months but at least 1 month was part-time

- 11 percent had been employed for some but not all of the previous 3 months

Long-term unemployed workers have problems finding jobs in all states, even those with low unemployment rates; among the 14 states with the lowest unemployment rate (average of 4.4 percent), long-term unemployment grew to 4.5 times its historical average.  In general, the authors found the following about the long-term unemployed:

1.) They tend to be younger with 40 percent of the long-term unemployed being between the ages of 16 to 34, 29 percent being between the ages of 35 and 49 and 31 percent being older than 50 years of age.

2.) They tend to be less educated with 18 percent having no high school, 35 percent having a high school diploma, 20 percent having some college and 18 percent having a Bachelor's Degree or higher.

3.) They tend to be unmarried with 44 percent having never been married, 37 percent being married and 19 percent being widowed, divorced or separated.

4.) Racially, there is a strong connection with long-term unemployment as shown here:

African-Americans make up 22 percent of the long-term unemployed compared to just under 13 percent of the total population and Hispanics make up 19 percent of the long-term unemployed compared to 16 percent of the total population.

In general, the longer that a worker is unemployed, the less time they spend looking for a job as the frustration over not having employment builds, compounding the problem.  Because of this, they become increasingly marginalized, particularly since the data shows that, in a given month, only 11 percent had achieved full-time employment for a continuous four month period since they returned to employment.  Sadly, many of these discouraged workers simply choose to leave the workforce simply because there are not sufficient job openings to accommodate them.