HomeSocietyNo reason to get panicky about inflation ... yet

No reason to get panicky about inflation … yet

First, gas prices spiked. Then lumber prices took off. By April, the Consumer Price Index was 4.2% higher than in April 2020. Now everyone is worried about a return to the double-digit inflation of the 1970s.

While ‘70s-grade inflation is still a long way off, it’s good to be cautious.

The headline figure from the CPI report – the 4.2% increase from last April – is the largest year-to-year increase since September 2008. And the price pressure has picked up steam, with the CPI rising 0.8% in April, on the heels of a 0.6% surge in March.

Adding to the anxiety is massive federal deficit spending. Prior to President Biden’s recent $1.9 trillion COVID-19 relief package, the federal government had already increased the national debt by $4.5 trillion in 2020.

The $1.9 trillion package drew a rebuke from former Obama adviser Lawrence Summers, who pointed out that this World War II-size stimulus could have “inflationary pressures of a kind we have not seen in a generation.”

The Biden administration’s answer? Two new spending proposals totaling an additional $4.5 trillion.

All this federal spending has increased per capita disposable personal income 14% between January and March, far greater than the average first-quarter increase (0.43%) during the last decade. It is hardly surprising, therefore, that people are worried about inflation from “too many dollars chasing too few goods.”

Nonetheless, while it certainly appears that the risk of higher inflation has now arrived, the inflation numbers do not yet suggest that a return to 1970s-style inflation is imminent.

First, it is important to remember that inflation refers to a rise in the economy’s overall price level, not the prices of essential consumer goods, or even key commodities. While price increases in those categories could eventually turn into higher overall inflation, there is no strict relationship that guarantees such an outcome.

Gas prices, for instance, typically fluctuate a great deal, and large increases during the last few decades have not resulted in high inflation.

It is also wise to keep in mind that many consumer prices fell during the pandemic when demand dried up. Some price increases, therefore, should be expected as demand revives, especially in those sectors that were hardest hit.

For example, car-rental companies sold parts of their fleets during the pandemic, and now used car prices have surged as demand has picked up. Used car prices alone explain 13% of the rise in the CPI.

Spending in another handful of categories – including restaurant meals, hotel lodging, and airfares – accounts for another 12% of the April CPI increase. In fact, spending in just seven categories of goods (including gasoline) explains 54% of the April-to-April CPI increase.

Americans should take some comfort in the fact that none of these individual increases are incredibly unusual, and that the overall CPI figures have been nothing like they were in the 1970s. Even the lowest annual increase in the CPI between 1966 and 1980 (3.01% in 1971) is far below the average during the last two decades (1.89% using the CPI).

Yes, inflation trends can change suddenly and unexpectedly, but the Federal Reserve has spent the last few decades struggling to reach its inflation target.

This last fact is reason for both comfort and concern, especially given the Fed’s latest interpretation of its price stability mandate. While the Fed could calm inflation fears by committing to, for example, 2% inflation over the next 12 months, it has not yet done so.

The Fed’s post-2008 operating system only adds to the anxiety because that framework requires the Fed to pay interest on reserves – potentially hundreds of billions per year to large banks – to hold back inflation.

The best thing for Congress and the administration to do is to get federal spending under control and require the Fed to normalize monetary policy.

• Norbert J. Michel is the director of The Heritage Foundation’s Center for Data Analysis.

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