If you tune into your favourite cable news network long enough, you will eventually hear about the great American Economic Recovery – a virtually unprecedented span of gross domestic excitement and stock market booms and bulls. This excitement is regularly compounded by metrics relating to the usual suspects, such as the unemployment rate, inflation, GDP, Consumer Confidence, etc., falsely influencing us to believe, at least for the past nine years or so, that economic cycles are nothing more than the tall stories made for fiction novels, as opposed to the truth about the American businessperson. Nevertheless, I hate to burst your bubble, but this joy ride, as tantalizing it may seem, will not last forever. We, as financial professionals, need to be ready for an eventual bubble-burst and be prepared to offer a sound explanation when it happens.
Now, let’s be real – the economy is complex. “Anyone who says otherwise is selling something” (The Princess Bride, 1987). And, as a trained economist, I will be the first to confess that, to understand the economy, you must first accept that it is not simple, but rather a fancy, convoluted muddle of interlocking equations, expectations and emotions. This is the reason why I practice as a “positive” economist [https://bit.ly/2oPpyTs]. And this, as a final confession, is why I am posting this blog in the first place – to help others [1] parse through the avalanche of economic jargon that is carelessly thrown their way and [2] be mindful of how we economists utilise variables in our day-to-day business analysis. So, without further ado, let’s dive into our first of the "usual suspects” -- the unemployment rate.
The unemployment rate, which is at par with other economic factors such as the “GDP”, the “Dow Jones”, the “S&P500”, the inflation rate, consumer index, etc., is a macroeconomic variable that tries to indicate the health of a region’s economy. At first glance, how could there be anything suspicious about this metric because, logically speaking, if the rate goes down this means people have more labour hours each week, which in turn means higher earning potential that leads to increased spending, which hopefully translates into more growth (as far as GDP is concerned), leading to more jobs and reduced unemployment. Sounds great! But, unfortunately, that’s not always the case.
Based on the U.S. Bureau of Labour Statistics, the “official” unemployment rate for June 2019 is not 3.7%, but 7.2%, which is 3.5% higher than what you are likely to read or hear about on your favourite cable news network. Yikes! The higher unemployment rate, i.e., which is the true unemployment rate, accounts for not only those who are actively looking for a job, but also those who are classified as “marginally attached workers”, including those who are “employed part time for economic reasons”. Economists call this measure of unemployment “U6”.
For us economists, there are actually six different measures of unemployment and the most often cited one is known as “U3”, which is a convenient half-way measure betwixt “U1” (1.3% – denoting all persons unemployed fifteen weeks or longer, as a percent of the civilian labour force) and the “U6” measure as mentioned above. If you ever wondered why there still seems to be so many more people in search of work during this recovery – many more than what an unemployment rate of 3.7% seems to suggest – “U6” gives us a clue. That 3.5% jump that characterises “U6” is due to the underlying shifts in our economy (e.g. entire sub-sectors that do not need or value labour anymore or as much), which means that it’s an unemployment rate that is unlikely to reduce during “economic recoveries”.
In closing to this first part of my series of several posts to come, financial markets are, above all else, an economic problem; and, the study of economics is that of learning to appreciate the margins – meaning, depending on which measure of unemployment you choose to calibrate your growth models, for example, you may be in for a shock. At a 3.5% underappreciated difference in unemployment rates, that means approximately 5.6 million American workers are stuck in an under/unemployment zone. From a positive economics perspective, this is a big deal and critically important when adjusting our economic or business models to reflect how this sector of American workers will impact our analysis. How so? Let us recall that it took about 4 million foreclosures to define the “Subprime Mortgage Crisis”, and the economic realities of households then show parallels to those of today:
[1] a close “U6” in 2007 to that of today [https://fred.stlouisfed.org/series/U6RATE],
[2] a housing market that continues to gamble with lower credit [today’s “non-prime” loans – https://cnb.cx/2GWQV9m],
[3] flexible, compounding interest rates on long-term debt packages beyond housing [https://bit.ly/2zLHjuH] and
[4] a looming stagnation in consumption from stagnant wages [https://pewrsr.ch/2U3mrJt].
The goal here is not to wedge our data intake with fear, but to show a different way to approach our understanding of this messy network that we call “the economy”. Thank you for taking the time to read this piece!
Kent Bhupathi
https://www.linkedin.com/in/kentob/
https://www.kentbhupathi.com/
For more insights, check out Chunyu Qu:
https://www.linkedin.com/in/chunyu-chester-qu-109519b4/
https://www.charlieq.net/