Why tariff inflation, if it comes, won't be just a blip

I am a Tariff Man,” declares President-elect Donald Trump. But wait! Won’t tariffs cause inflation? Yes, say the Wall Street Journal and other mainstream commentators. No, says Scott Bessent, the hedge fund manager that Trump has picked to be Treasury Secretary. At most, he thinks tariff inflation will at most be just a blip.

Who is right? The inflation experienced after Covid-19 offers some clues. The supply-chain disruptions that set it off were only transient, but the resulting catch-up inflation had a distressingly long tail. Three lessons learned from that painful episode – which may have cost the Democrats both Congress and the White House – suggest that any inflation driven by tariffs on the scale Trump has promised will be more than a blip. 

Lesson 1: Inflation has both a demand side and a supply side

Start by dissecting Bessent’s Panglossian view, as revealed in a recent radio interview. “Tariffs can’t be inflationary,” explained Bessent, “because if the price of one thing goes up, unless you give people more money, then they have less money to spend on the other thing, so there is no inflation. … Inflation comes through either increasing the money supply or increasing the government spending, and that’s what happened under Biden.”

There is a smidgen of truth in this, but just a smidgen. Yes, inflation is caused by too much demand chasing too much supply. Yes, policymakers can moderate demand by using monetary and fiscal policy. But those tools works best if excess demand is the origin of the inflation in the first place. The post-Covid inflation was different. The latest studies show that demand played only a small role in the upward surge of prices that began in the winter of 2021. Supply-chain disruptions played a much larger role. Tariffs, too, would mostly cause supply-side inflation.

When faced with supply-driven inflation, whether caused by factory closings and shipping bottlenecks or by tariffs, it is not enough just to hold the line on monetary and fiscal policy. To fully control inflation, the Fed would have to substantially crank up interest rates, preferably while Congress cut spending and/or raised taxes. In that case, we might get the Bessent result in which decreases in some prices offset increases in others. But such a strategy would come at the cost of falling real output and rising unemployment – even a major recession. Not what Bessent had in mind.  

Could a new misery index help explain the election outcome?

In 1970 everyone was feeling bad about the economy. How bad? To put a number to the pervasively negative vibe, Arthur Okun created the “misery index:” the sum of inflation and unemployment rates.

But now everyone is puzzled. Why was the economic vibe of 2024 bad enough to get the Democrats thrown out of office? After all, Okun’s misery index for the quarter leading up to the election stood at just 6.8, which was actually a whisker below its average of 6.9 for the Trump years. What is more, it had been falling almost continuously for nine quarters after peaking in April 2022.

Already six months before the election, when Okun’s index was still at 7.2, Paul Krugman wrote that for most Americans, the answer to the question, “Are you better off than you were four years ago?” should clearly be, “Yes.” But Krugman ruefully added, “for reasons that still remain unclear, many seem disinclined to believe it.” What went wrong?

Maybe part of the problem is that we need a new misery index. Maybe the Okun version just doesn’t capture what makes people miserable these days. In the many postmortems asking what Krugman and many others might have been missing, four factors come up repeatedly. In what follows, I use them as the building blocks of a 21^st century misery index.

Populism, State Capacity, and Why It Pays to Play by the Rules

 

Populism is on the rise around the world but the forms it takes can vary widely. Populists can align with the traditional left or right and can be liberal or conservative in their social values. What holds this diverse ideological family together is a sense that the will of the “true people” is being stymied by a corrupt elite — and that strong leadership is necessary to break that system. As tracked by a recent Ipsos poll, populist thought includes beliefs that “the system is broken,” “the economy is rigged to advantage the rich and powerful,” “traditional parties and politicians don’t care about people like me,” and “to fix our country, we need a strong leader willing to break the rules.”

This commentary focuses on the last of these beliefs, the need for a strong leader willing to break the rules. Ipsos found that 49 percent of respondents in 28 countries agreed with this sentiment. In the United States, the breakdown was 40 percent “agree” vs. 27 percent “disagree.” (See page 27 of the report.)

Climate Inflation is Coming. How Should Central Banks Respond?

The impacts of climate change are visible everywhere — wildfires in California, preseason hurricanes in the Caribbean, insufficient water in the Panama Canal, populations on the move everywhere from North Africa to Central America. Inflationary shocks are another looming worry. Food prices will become increasingly volatile, while property insurance rates will escalate — or insurance simply won’t be available. Labor costs will rise as employers spend to shield workers from hotter weather or raise wages where workers balk at heat exposure.

It all points not only to more inflation, but also to greater variation and less predictability across sectors and regions. In fact, that’s already happening. The figure below uses data from the Atlanta Fed to divide prices into half that are “sticky” in the sense that they rarely change and half that are “flexible,” meaning they go up or down with every bump to supply or demand. Since the late 1990s, the volatility of flexible prices has exceeded that of the “great inflation” of the 1970s. Even sticky prices are showing some ominous wiggles.

In the years ahead, more volatile inflation will make it harder for the world’s central banks, America’s own Federal Reserve Bank included, to meet their commitments to stabilize prices. Will they be up to the job? Not without some changes in strategy.

Good data on good government: Reformers should take note as political philosophy meets statistics

Good government has been a focus of political philosophers for centuries, but times change. Today’s thinkers, unlike Plato or Ibn Khaldun, can draw on abundant data to test and refine their theories on the merits and drawbacks of various regimes. And data is not just for theorists. Good data can provide would-be reformers with practical insights in their day-to-day efforts to make government more effective and strengthen democracy. A profusion of indexes compete to measure quality of government, state capacity, state fragility, liberal democracy, electoral democracy, varieties of democracy, and more. Which one is the best? Or are they all so alike that the choice doesn’t matter? 

But where to start? This paper offers a map through the thicket of governance data. The first section deals with some key terms and concepts. The second develops a pair of benchmark indexes that are closely aligned with the theoretical categories of state capacity and liberal democracy. The third examines the similarities and differences among a sample of widely used quality-of-government measures, and their implications for the relationship between liberal democracy and state capacity. The fourth section looks at what we can learn by looking beyond statistical regularities to specific country outliers. Finally, the conclusion takes up the question of how best to integrate theoretical, practical, and quantitative approaches to the study of good government.

South Royalton, 50 years later

Fifty years ago I had the honor to serve as the organizer of a conference on Austrian economics, held in the small town of South Royalton, Vermont. Recently the Mises Institute hosted a retrospective on the conference, which included a panel with five of the surviving participants in the conference, hosted by Peter Klein. The panel is posted on YouTube, along with a transcript. I recommend that anyone interested in Austrian economics take a look at it: South Royalton: Looking Back.

In the course of the panel, the question came up as to why the event was held in South Royalton. The hypothesis Peter gives about Dartmouth is essentially correct. I was teaching at Dartmouth at the time. When I was asked to organize the conference, I first approached the proper authorities in the administration at Dartmouth to see if their facilities were available. I was assured they would be. Unfortunately, it did not occur to me that I needed to get ideological clearance from my colleagues in the econ department. Except for Colin Campbell, a Chicago PhD who was enthusiastic about the project, the rest viewed Mises and Hayek as too far to the right for academic respectability. I was urged to drop the idea of the conference in order not to bring disrepute on the department.

By that time, plans were well advanced and it was clear that there was a lot of interest among potential participants. It seemed a shame to cancel the conference altogether. My wife and I had lived on and off in South Royalton – a picturesque, charming, and friendly village that we much preferred to Hanover NH – and we knew the owner of the South Royalton Inn. He and I patched things together as best we could. As the date approached, interest in the conference continued to grow. I remember being repeatedly pressured to enlarge the list of participants beyond what the facilities could reasonably hold, but our host at the Inn did his best. By arranging with neighbors to use their spare bedrooms, and by putting some of the overflow in housing where no one had recently been living, we did not have to turn anyone away.

Fifty years later, listening to some of the remarks about the town and the facilities, I am reminded of how, at the time, my wife and laughed about the way some of the visitors from Planet New York reacted to the experience of life on Planet Earth. Imagine the horror! Life without subways! Without all-night delis! Without multiple deadbolts on every bedroom door! I guess we can all laugh about it now.

The panelists also mention Milton Friedman’s unexpected visit to the opening banquet. My recollection is that it was Colin Campbell’s last-minute idea to invite his former dissertation adviser, who had a summer house nearby. I okayed the idea. Friedman was in no way “crashing someone else’s party.”

What everyone remembers now was Friedman’s famous quip, “There is no Austrian economics – only good economics and bad economics.” I have always thought that Friedman was right. I am happy that over the years participants in the South Royalton conference, and their students in turn, have produced much work that we all can recognize as “good economics.” 

If there is anything that disappoints me, it is that some Austrian economists make too much effort to build fences rather than bridges between themselves and the rest of the profession. As fondly as I remember Murray Rothbard as a mentor and a friend, I am afraid that by temperament, he was more of a splitter than a unifier. Going forward, Austrian economics could use less Rothbard and more Hayek.

Redefining Poverty: Towards a Transpartisan Approach

 

A new report from the National Academies of Science, Engineering, and Medicine (NASEM), An Updated Measure of Poverty: (Re)Drawing the Line, has hit Washington with something of a splash. Its proposals deserve a warm welcome across the political spectrum. Unfortunately, they are not always getting it from the conservative side of the aisle. 

The AEI’s Kevin Corinth sees the NASEM proposals as a path to adding billions of dollars to federal spending. Congressional testimony by economist Bruce Meyer takes NASEM to task for outright partisan bias. Yet in their more analytical writing, these and other conservative critics offer many of the same criticisms of the obsolete methods that constitute the current approach to measuring poverty. As I will explain below, many of their recommendations for improvements are in harmony with the NASEM report. Examples include the need for better treatment of healthcare costs, the inclusion of in-kind benefits in resource measures, and greater use of administrative data rather than surveys.

After some reading, I have come to think that the disconnect between the critics’ political negative reaction to the NASEM report and their accurate analysis of flaws in current poverty measures has less to do with the conceptual basis of the new proposals and more with the way they should be put to work. That comes more clearly into focus if we distinguish between what we might call the tracking and the treatment functions, or macro and micro functions, of poverty measurement. 

The tracking function has an analytic focus. It is a matter of assessing how many people are poor at a given time and tracing how their number varies in response to changes in policies and economic conditions. The treatment function, in contrast, has an administrative focus. It sets a poverty threshold that can be used to determine who is eligible for specific government programs and what their benefits will be.

There are parallels in the tracking and treatment methods that were developed during the Covid-19 pandemic. By early in 2020, it was clear to public health officials that something big was happening, but slow and expensive testing made it hard to track how and where the SARS-CoV-2 virus was spreading. Later, as tests became faster and more accurate, tracking improved. Wastewater testing made it possible to track the spread of the virus to whole communities even before cases began to show up in hospitals. As time went by, improved testing methods also led to better treatment decisions at the micro level. For example, faster and more accurate home antigen tests enabled effective use of treatments like Paxlovid, which works best if taken soon after symptoms develop.

Poverty measurement, like testing for viruses, also plays essential roles in both tracking and treatment. For maximum effectiveness, what we need is a poverty measure that can be used at both the macro and micro level. The measures now in use are highly flawed in both applications. Both the NASEM report itself and the works of its critics offer useful ideas about where we need to go. The following sections will deal first with the tracking function, then with the treatment function, and then with what needs to be done to devise a poverty measure suitable for both uses.