As the global slowdown in economic growth continues and starts to bleed into many US economic data points, not many analysts dismiss the idea that the US economy is slowing anymore.
There is a healthy debate around the severity of the slowdown and whether a move from 3% growth to 2% growth is something to worry about, but the idea that growth in the US is softening is settled and empirically observable in a wide array of data points, including housing, auto sales, retail sales, and more.
The conversation has shifted from a possible slowdown in growth to the probability of a soft landing as we had in 2015-2016 or a recession (hard landing).
In this note, I want to use a data-driven approach to demonstrate the true level of recession risk that is empirically observable in the data at this point.
At the conclusion of this note, which will be based on data, not opinion, we should agree to the level of recession risk in the economy at this moment in time. Of course, this data is dynamic and will change with each passing day.
Also, recession risk is different than growth rate cycle risk.
I monitor three distinct time-durations as well as the interconnectedness between each time duration.
The growth rate cycle, which typically spans 12-36 months, occurs within the business cycle. Periods of decelerating economic growth lead to risk in financial assets and corrections in the stock market but do not result in a recession. This economic cycle has had three distinct slowdowns in economic growth, one currently underway, and none has resulted in recession, but all have resulted in major stock market turmoil. Monitoring the growth rate cycle is extremely important.
The business cycle, which typically lasts 6-10 years, results in larger swings in economic growth, typically ending with contractions in growth (recession) as a result of an exhaustion of pent-up demand. Recessions, more often than not, are disastrous for risk assets.
Both the growth rate cycle and the business cycle oscillate around trend GDP potential which is comprised of secular (10+ year) forces, namely population growth and productivity growth.
The chart below very loosely outlines this economic framework. The reason trend GDP is illustrated in a downward trend is because the US is in a secular decline of growth that started in the 1980s.
A Framework of Economic Trends:
While members of EPB Macro Research receive frequent and detailed updates on all three of these time durations, the shortest time frame we consider being 12-36 months, in this note, we will focus in on just the business cycle to understand how close or far away a recession might be.
While the common definition of a recession is two consecutive quarters of negative GDP growth, that is actually not based on facts but rather a quick rule of thumb.
The actual definition from the National Bureau of Economic Research, the agency that officially defines recessions, is as follows:
A recession is a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales.
The NBER goes on to elaborate in more detail some of the critical components to look at for defining a recession.
The committee places particular emphasis on two monthly measures of activity across the entire economy: (1) personal income less transfer payments, in real terms and (2) employment. In addition, we refer to two indicators with coverage primarily of manufacturing and goods: (3) industrial production and (4) the volume of sales of the manufacturing and wholesale-retail sectors adjusted for price changes.
With the official definition and the metrics that the NBER suggests most accurately define a recession, we can honestly assess how close the economy is to the dreaded recession.
With the data in the above section, we can create a composite index to measure the probability of a recession in rate of change terms. I do not put percentages on a recession, such as 25%, but rather speak in terms of the rate of change. The risk of a recession is either increasing or decreasing.
Also, it is worth noting that this index is a coincident measure of economic activity and not a leading indicator of economic activity. The purpose of this composite index is not to forecast a recession but rather have a real-time gauge of recession risk.
For leading indicators of recession, you need to understand the growth rate cycle trend, as well as the business cycle trend, which we will look at in a later section below.
With four critical components to look at on a monthly basis: real personal income, employment, industrial production, and some measure of real consumption (retail sales or total personal consumption), we can gauge very accurately how close the economy is to a recession.
If the confluence of these four indicators in contracting, or near a contraction, a recession is close. If the growth rate of these four indicators is decelerating, we can say the probability of a recession is rising.
We will take a look at a composite measure of these factors, but first, I want to look at examples of when one or two indicators suggest a recession, but the aggregate index does not, thus validating the importance of a composite index approach rather than looking at all four measures in isolation.
Starting in early 2015, there was a severe deceleration in economic growth occurring globally, starting in China that resulted in a deep contraction in manufacturing activity, but not a recession.
Below is a look at the year over year change in the industrial production index in which the magnitude of the decline in 2016 was clearly recessionary based on history.
The contraction in manufacturing activity was larger than the 1990 recession. Also, there is not a period of time throughout history in which there was a manufacturing contraction that lasted as long as 2015-2016 without a recession.
Industrial Production Index Year over Year %:
If you had looked at the industrial production index, you would have been right to conclude that recession risk was rising sharply and that there was a potential for such a contraction in manufacturing activity to result in a loss of employment, income and thus cause a recession but years later, we now know that no recession occurred.
Let's look at the other factors to understand why.
If we study employment using non-farm payrolls, there has not been a recession since 1940 without a contraction in the year over year growth rate of non-farm payrolls. While this is not a necessary criterion for a recession, and there was, in fact, a sharp deceleration in employment growth in 2016, there was never a loss of jobs.
Non-farm Payrolls Growth:
We can go through the last two items in the four component outline by the NBER, but let's skip to the composite index.
At EPB Macro Research, we use a composite index to measure the growth rate cycle, the business cycle, and recession risk with several indices for each. The reason for the composite index approach should be clear based on the above information. First, no single indicator will ever be 100% accurate. The idea of pulling out one leading indicator and saying it did not work here is a silly argument that stems from a misunderstanding about how economic data flows.
By using a composite index, if the composite index turns lower, meaning the confluence of all the metrics on average are moving lower or higher, false signals are greatly reduced.
The four-factor coincident recession indicator takes the criteria outlined by the NBER, including industrial production, non-farm payrolls, personal income, and personal consumption, all in real terms, and adjusted for standard deviation.
The chart below looks at these factors in nominal terms, not in rate of change terms.
Four-Factor Coincident Index:
The chart above clearly outlines the 2008 recession, but there was no meaningful contraction in 2015-2016 based on the composite.
In 2015-2016, there was a meaningful slowdown in the growth rate of this composite. It was accurate to suggest recession risk was rising substantially, but the data troughed before contracting in aggregate.
Today, there has been a cessation in the acceleration of the coincident data but not a significant decline yet.
Four-Factor Coincident Index Year over Year:
One issue to point out is that we are still waiting for personal income and personal consumption data to be updated due to the government shutdown. These two data points will be updated on Friday, which is likely to show at least modest decelerations based on the leading indicators and more updated data points. In other words, 50% of this index has not been updated since the November reporting period.
As soon as that data is released, we will have an updated view on if the deceleration in the leading indicators has bled more significantly into the coincident data.
As mentioned, the coincident index above is exactly that, a coincident index and a real-time measure of the state of the whole economy. We can properly identify the level of recession risk, but for economic cycle forecasting and trying to beat the crowd to inflection points, we also need to use leading indicators to forecast changes in the coincident index.
While I use several metrics to measure the 12-36 month growth rate cycle, I also use several indices to measure the business cycle to understand the level of cyclical risk in the economy that tends to lead the coincident data.
When measuring the business cycle, I look to gauge the level of pent-up demand. If pent-up demand is exhausted, the level of cyclical risk in the economy rises.
The best areas to measure pent-up demand are in the housing, auto, and durable goods consumption sector. These three categories share three characteristics that make them informative sectors to measure in aggregate (not as stand-alone measures). Each sector is a large item in the consumer basket (the largest items actually), is sensitive to interest rate changes (that rise at the end of the economic cycle) as they are typically purchased with financing, and is subject to the concept of pent-up demand. You can think of this as once you have a car, you don't need 3, 4, and 5 cars, so once demand is satisfied, there is a cyclical slowdown in these sectors.
The measure of the business cycle always slows before the coincident measure and bottoms in the middle of a recession rather than at the end or after.
This measure takes various components from the housing, auto, and durable goods consumption space.
The goal of this business cycle index is to measure pent-up demand.
As the chart below shows, the business cycle index, in growth rate terms, peaked well before the coincident index and bottomed several months before the economy turned higher.
Business Cycle Index Vs. Coincident Index Year over Year:
Today, while the level of recession risk remains rather muted, the business cycle index is moving lower, near the lowest level of this economic cycle.
Pent-up demand is slowing sharply, which raises red flags for the economic cycle.
The growth rate cycle is also trending lower.
We currently have a situation where the growth rate cycle is trending lower both domestically and globally, the business cycle is showing signs that pent-up demand is exhausted raising cyclical risk, but the coincident data is not recessionary yet.
This sequence of data implies that there will be a notable slowdown in the coincident data and that recession risk will be rising throughout 2019, but the conclusion of a hard or soft landing remains to be seen in the data.
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