The recent cooling of the U.S. economy has sparked a debate, with some commentators pointing to trade tensions and tariffs as the primary culprits. While it is true that tariffs can disrupt supply chains and raise costs, their impact on an economy the size of the United States is often overstated. Instead of focusing on external factors, a more accurate assessment of the current economic slowdown requires a look at domestic monetary policy. The Federal Reserve, by raising its federal funds rate and keeping it elevated for an extended period, has directly engineered a slowdown in economic activity. This policy tightens financial conditions, making it more expensive for businesses to borrow and invest and for consumers to purchase big-ticket items like homes and cars.
History provides a powerful precedent for this economic dynamic. In the early 1980s, under the leadership of then-Fed Chair Paul Volcker, the central bank aggressively hiked interest rates to combat rampant inflation. The federal funds rate soared to a staggering 20%, a move that successfully crushed inflation but also intentionally triggered a severe recession (see figure below: Fed Funds Effective Rate - Gross Domestic Product). This historical episode serves as a clear example of the Fed's immense power to slow down the economy through monetary policy. The current situation mirrors this playbook, albeit on a less dramatic scale, as the Fed's actions have systematically removed liquidity from the financial system and reduced demand.
To see this cause-and-effect relationship in action, one only needs to look at the data. A review of historical economic trends reveals a strong correlation between the federal funds rate and overall economic growth, as measured by GDP. The periods following sustained rate hikes often coincide with periods of economic contraction or slower growth. The data clearly shows that the real force at play in the current economic environment is not trade policy, but the deliberate and often-overlooked decisions of the central bank. For a brief discussion on this, along with a few other related topics, please refer to the video linked below.
This blog is about data analytics, statistics, economics, and investment issues. The "Warp" in the title refers to the nonlinear nature of investment instrument variations.
Showing posts with label initial jobless claims. Show all posts
Showing posts with label initial jobless claims. Show all posts
Thursday, August 28, 2025
Sunday, November 10, 2019
The initial jobless claims data may be very misleading: What really matters is the trend of the “second derivative”
Summary
- Initial jobless claims seems to be going down sequentially as of late.
- But the year-over-year rate of change is clearly going up, and fast.
- Recently the popular business media have been largely reporting the initial jobless claims measure as evidence that the job market is strengthening.
- The reality is that it is weakening, based on this measure, at an alarming rate.
Initial jobless claims
In the US data on initial jobless claims is released by the Department of Labor every week. The measure tracks the number of people who filed initial claims for unemployment benefits in the previous week. This measure is closely followed by the financial markets.
Since the measure is “noisy”, usually the 4-week moving average is followed. As you can see from the graph below, from the FRED (), it seems to go up prior to recessions. The latest data is circled on the right, and it looks like it is going down.
What really matters is the trend of the “second derivative”
The above trend is misleading because, as with most leading indicators of economic slowdowns (including recessions), what really matters is the trend of the change in the rate of change. This trend is frequently referred to as the trend of the “second derivative” of the underlying measure.
Look at the graph below, also from the FRED, which is the percentage change in initial jobless claims compared to the same period in the previous year. It is important to consider the year-over-year rate of change, as we do here, because of the seasonal nature of initial jobless claims.
As you can see on the right, this rate of change (the "second derivative") has been increasing steeply in recent months. This essentially means that the year-over-year rate of change in initial jobless claims has been increasing at a fast rate more recently.
The job market is weakening at an alarming rate
This is an unusual situation because the measure itself, initial jobless claims, seems to be going down sequentially as of late. But its year-over-year rate of change is clearly going up. This tends to precede recessions.
Recently the popular business media have been largely reporting the initial jobless claims measure as evidence that the job market is strengthening. The reality is that it is weakening, based on this measure, at an alarming rate.
A simple analogy
Imagine that you are driving from Houston to Austin. Where you are, at any given time, is the measure. The first derivative is the speed at which you are traveling. The second derivative is the acceleration.
Someone that is following only your location would see any movement toward Austin as progress. Positive speed is also seen as progress. However, if acceleration is negative, at some point you may stop and start going back to Houston ...
A final note
This blog discusses, among other things, simulation-based valuations of companies. Those valuations are based on fundamentals (e.g., earnings and revenues), and assume growth rates that are generally different from those seen in steep economic slowdowns or recessions.
If the stock market “sees” a recession coming, expectations about growth change drastically, usually for the worse. As a result, stock prices (and thus valuations) tend to drop precipitously, often regardless of fundamentals.
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