A Closer Look at Q2 2020’s Historic GDP Decline: An initial look at how the U.S. economy fared under the more stringent period of national lockdowns is now available and it should come as little surprise the numbers are nothing short of terrible. On an annualized basis U.S. GDP declined 32.9%. From the Bureau of Economic Analysis’ news release, “The decrease in real GDP reflected decreases in personal consumption expenditures (PCE), exports, private inventory investment, nonresidential fixed investment, residential fixed investment, and state and local government spending that were partly offset by an increase in federal government spending… The decrease in PCE reflected decreases in services (led by health care) and goods (led by clothing and footwear). The decrease in exports primarily reflected a decrease in goods (led by capital goods). The decrease in private inventory investment primarily reflected a decrease in retail (led by motor vehicle dealers). The decrease in nonresidential fixed investment primarily reflected a decrease in equipment (led by transportation equipment), while the decrease in residential investment primarily reflected a decrease in new single-family housing.” While the headline number was not a shock to the financial community by any means (as evidenced by overall slight increases in all major indices since the report), the sheer magnitude of the decline reverberated across headlines heralding the largest ever drop in U.S. GDP.
Our Takeaways: The first thing to understand is where the headline GDP number for every quarter comes from. Quarterly GDP numbers are reported on a seasonally adjusted, annualized basis meaning that really what it is trying to express is what the change in GDP from Q1 of that year to Q1 of the following year would look like if the rate of change the economy has been experiencing were to persist. Generally speaking, this is a fairly informative way of presenting the data since normal conditions see quarterly changes of plus or minus in the range of zero to one percent equating to annual changes up or down in the low-to-mid single digit range.
However, during periods of extreme contraction (or expansion) when the quarterly rate of change becomes something in the mid to high single digits, it produces a somewhat deceptive headline number - as was the case this past quarter which produced an annualized decline of over 30%. This would lead many to believe that economic activity contracted by nearly ⅓, when in fact it was something closer to 9%. Semantics aside, a closer look at the data revealed some interesting information.
First, and somewhat ironically for a pandemic, healthcare spending declined meaningfully. Contraction in spending for this area, contributing about 9.5% to the annualized GDP decline, actually led the overall decline in personal consumption for services. The other big takeaway was just how large of an impact the government spending during the quarter aimed at propping up the economy actually made. According to the Brookings Institution’s Fiscal Impact Measure, which shows the effect of federal, state, and local spending on GDP, government spending added 14.6 points to second-quarter GDP growth. Yet, more than all of the lift came from federal spending because state and local government spending ended up contracting during the quarter.
Removing the drag from state and local governments (leaving just the impact of federal spending) brings the annualized addition to GDP up to 21.4%. Put another way, federal spending prevented a 47% annualized decline in GDP. What still remains unclear is the extent to which the support from the Federal Reserve contributed to mitigating further economic losses. Fed intervention is not captured in GDP measurement, but it’s not unlikely the effects could be indirectly observable in another area within GDP.
Yet Another Look Under the Hood for Unemployment: In July, the unemployment rate declined by 0.9 percentage points to 10.2 percent, and the number of unemployed persons fell by 1.4 million to 16.3 million. Or, as they say, “so the story goes.” That is at least how most of the financial press reported the Bureau of Labor and Statistics July Unemployment report. Now, this is not to say the reported numbers were not accurate reflections of the BLS’s report, but rather that - in the current environment - the finely tuned models of unemployment we rely on in normal times seem ill-suited to provide an accurate picture of the realities on the ground. For instance, if you compare the most recent BLS estimate (16.3 million unemployed) with the continuing claims for state unemployment insurance (16.1 million for the week ending 7/25/2020) things seem to line up. On the other hand, if you add in those receiving some kind of unemployment protection at the federal level the continuing claims number jumps from 16.1 million to 31.3 million. If this is closer to the true number of unemployed people, then that would of course nearly double the rate of unemployment to nearly 20%.
Our Takeaways: The difficulty of taking reported economic statistics at face value is they do not represent precise measurements of exactly what is reported to be measured. Take unemployment for instance. The BLS is not going around every month and surveying every household to see exactly how many unemployed persons they are. We know this from first principals because the only time this extent of data collection is undertaken is every 10 years for the census. According to the 2020 Census Operational Plan, the initial results (which are just a limited subset of the data focusing on population and housing units) will be ready by April of 2021.
So, how does the BLS know what the unemployment rate is every month? The answer is: finely tuned models. These models work very well during normal times when fluctuations in the data vary by at most a few percent a month. They are even able to provide fairly good estimates for 6 different levels of what they call “labor utilization.” Similar to the points raised above about reporting of GDP figures, some of this is semantic, but when simple back of the envelope calculations lead to figures so far removed from the reported results, it bears further scrutiny. And, as it happens, simply looking at some of the “alternative measures of labor utilization” provides some insight as to where the models may be going awry.
The unemployment rate, as it is traditionally reported, is actually the 3rd of the 6 different measures of labor utilization - otherwise known as U-3. The brief description of what this measure is meant to capture is simply “total unemployed, as a percentage of the civilian labor force.” Contrast this definition with U-1, which is the most stringent in terms of qualifications, where the measurement is meant to identify “persons unemployed 15 weeks or longer, as a percentage of the civilian labor force.” For July, the result of these definitional differences was about 5% with the U-3 measurement at 10.2% and U-1 at 5%. On the other end of the spectrum, we have U-6 which is defined as “total unemployed, plus all persons marginally attached to the labor force, plus total employed part time for economic reasons, as a percentage of the civilian labor force plus all persons marginally attached to the labor force.” The July print for this measurement was 16.5% which leaves us with an 11.5% spread. In terms of people this is about 18.4 million.
If we turn back the clocks to this past March, U-1, U-3, and U-6 were 1.2%, 4.4%, and 8.7% respectively. Since then, both U-3 (headline unemployment) and U-6 peaked in April at 14.7% and 22.8% respectively. However, U-1 has remained within 1% of its March number, at least until July.
Going forward, we expect the two most important indicators for unemployment will be U-1 and U-6. Because of how the BLS defines the different measures, U-6 will likely provide the most accurate measurement of how many workers are not gainfully employed in a stable job, and thus highly at risk to adverse economic shocks, unable to fully participate in the economy from a consumption perspective, and (at least under the current policy) represent further liabilities to state and federal budgets for unemployment insurance. U-1, on the other hand, will show what portion of the U.S. workforce has been significantly displaced since it has been 15+ weeks since they were previously employed and they are still seeking a job.
Liquidity and Credit: Over the last few months, the combined duo of the Federal Reserve and the U.S. Treasury has overseen the injection of trillions of dollars into various parts of the U.S. economy. Much of this has come from the Fed’s intervention activities in a variety of credit markets including U.S. Treasuries, corporate debt, and collateralized mortgage obligations (CMOs). Still yet another large portion of credit (or potential credit as it were) is the Fed’s Main Street lending program. This potentially $600 billion facility is meant to provide much of the same kind of support companies with access to public credit markets are able to utilize, but for private and oftentimes smaller “main street” businesses. Interestingly enough, and unlike the SBA’s Paycheck Protection Program facility whose first tranche of funding ran out in less than 2 weeks from its initiation, the Main Street program has seen an extraordinarily small portion of its total funding tapped. So far, only about $200 million of funding has occurred through this program - about 0.03% of total capacity. This begins to look even more strange when considered against the backdrop of small businesses across all industries, but particularly in the harder hit areas of hospitality/leisure, food service, event, and beverage, clamoring for more relief measures to help them weather the economic storm.
Our Takeaways: So, what is going on here? Why would you on the one hand have whole industries that are struggling just to survive and on the other hand have federal programs ready to supply hundreds of billions of dollars sitting idle in what is being deemed a “failure” by the overseeing congressional committee? In this case it would appear the failure lies in an inability to properly incentivize the distribution of the capital. The Fed’s Main Street program, like other loan programs run by the federal government, does not actually involve the Federal Reserve lending to businesses. What actually happens is a business would go to their local bank (if they qualify), or another lender approved for the program, and apply for a loan that would be eligible per the program’s guidelines. The lender would underwrite the loan and disburse funds to the borrower in a manner similar to how it would for a typical commercial loan. The lender would then turn around and sell 95% of the borrower’s obligation to repay the loan to the Federal Reserve. The lender would also receive origination fees (as is typical) for doing this but, ultimately, they receive 5% of the interest on the loan and the fees for taking their risk even though their exposure is only 5% of the loan amount.
As it turns out, most banks have decided this is either not a profitable enterprise for them, or that the risk is too high even when 95% of the exposure is taken off the table. At least anecdotally, the problems persist beyond the Fed’s Main Street program. The Small Business Administration (SBA) is typically responsible for providing lending support to small and medium sized enterprises (SMEs). They were the organization tasked with the PPP loan program, but again the actual funding mechanism is similar to what was outlined above where commercial lenders actually underwrite and provide funding to individual borrowers. Typically, the SBA will cover 50-85% of the exposure for a qualifying loan, which is theoretically a pretty good deal for banks. They collect full fees and some of the interest, but only have to keep 15-50% of the loan on their books.
For what we are hearing in the industry, this mechanism no longer seems to be functioning. In effect, SMEs are being shut off from access to capital regardless of borrower strength, industry, previous history, etc. This is an area we will continue to evaluate since it will likely take several quarters for the effects of this to manifest themselves. Although, since credit is essentially the lifeblood of the economy - particularly for growth and expansion - the road to full recovery could be further hindered if businesses are delayed access to capital.
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