Conversable Economist

Fifteen years ago in 2008, Cass Sunstein and Richard Thaler published a best-seller called Nudge: Improving Decisions about Health, Wealth, and Happiness. The idea built on research in behavioral economics over the previous few decades which had shown that people’s decision-making is often subject to biases or limitations that cause them to make choices, which, on later reflection, they would prefer not to have made. The idea of “nudge” policies–sometimes called “liberal paternalism”– is to change the way certain decisions are presented and framed in a way that can counterbalance the pre-existing biases and limitations, but while still leaving individuals the choice to continue making the same decisions if they wish to do so.

If “nudge” policies work as intended, many individuals will be pleased that they were nudged, because it helped them to make the decision that they actually wanted to make. For example, people might be later on feel pretty good about nudges that encouraged them to quit smoking, or save more money, or eat a healthier diet.

However, a couple of active researchers in behavioral economics are now expressing some doubts about the role of “nudges” in public policy. Nick Chater and George Loewenstein have written “The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray” (Behavioral and Brain Sciences, published online September 5, 2022, still forthcoming in a future issue). They write:

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society’s most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities.

Their conceptual argument comes in two main parts. One is that while behavioral interventions often have some positive effect, the size of the effect is often small. They mention many papers on this theme, but as an illustration, consider the findings of Stefano DellaVigna and Elizabeth Linos “RCTs to Scale: Comprehensive Evidence From Two Nudge Units” (Econometrica, 2022, 90:1, pp. 81-116). They worked with data from two “nudge units”–that is, organizations that work with a wide range of US government agencies on nudge policies. One was a consulting firm called BIT North America, the other was the Office of Evaluation Sciences (OES), which is part of the US Government Services Administration. Here’s how DellaVigna and Linos describe their project:

In this paper, we present the results of a unique collaboration with two major “Nudge Units”: BIT North America, which conducts projects with multiple U.S. local governments, and OES, which collaborates with multiple U.S. Federal agencies. Both units kept a comprehensive record of all trials from inception in 2015. As of July 2019, they conducted a total of 165 trials testing 347 nudge treatments and affecting almost 37 million participants. In a remarkable case of administrative transparency, each trial had a trial report, including in many cases a pre-analysis plan. The two units worked with us to retrieve the results of all trials, 87 percent of which have not been documented in working papers or academic publications. This evidence differs from a traditional meta-analysis in two ways: (i) the large majority of these findings have not previously appeared in academic journals; (ii) we document the entirety of trials run by these units, with no scope for selective publication.

How did these programs work out? Chater and Loewenstein refer to behavioral nudges as “i-frame” interventions, meaning that they seek to change outcomes via a focus on individuals. Here’s their summary of the findings from DellaVigna and Linos:

I-frame interventions alone are likely to be insufficient to deal with the myriad problems facing humanity. Indeed, disappointingly often they yield small or null results. DellaVigna and Linos (2022) analyze all the trials run by two large U.S. Nudge Units: 126 RCTs covering 23 million people. Whereas the average impact of nudges reported in academic journals is large – at 8.7% – their analysis yielded a mean impact of just 1.4%. Why the difference? They conclude that selective publication in academic journals explains about 70% of the discrepancy. DellaVigna and Linos also surveyed nudge practitioners and academics, to predict the effect sizes their evaluation would uncover. Practitioners were far more pessimistic, and realistic, than academics, presumably because of their direct experience with nudge interventions.

In short, nudges based on research studies in behavioral economics have an positive effect, but in the real world, the average effect is pretty close to zero.

But as long as the nudge policies are cheap and the effects are at least mildly positive, why not do them? The second main part of the Chater-Loewenstein argument applies the behavioral economic concept of how a question is framed to energy behind public policy choices. They argue that behavioral economics creates an “i-frame,” with the emphasis on nudging individuals to make better choices. Once the problem and solution is framed in that way, it is harder for “s-frame” policies that focus on systemic changes to be adopted, or even considered.

In theory, there is no contradiction between, say, an i-frame policy of discouraging smoking by with warning labels and images on cigarette packages and also having s-frame policies like taxes on cigarettes and bans on smoking in workplaces and restaurants. But the authors cite research evidence that, for example, when people and policy-makers first consider a “nudge” i-frame policy toward using carbon-free energy, they are then less likely to support an s-frame carbon tax. Farmers who have taken steps to adapt to climate change can then be less likely to support government steps to reduce climate change. Indeed, Chater and Loewenstein argue that there is a pattern in which companies try to channel policy discussions toward i-frame interventions, and behavioral economists and government agencies line up to evaluate the potential nudges. For example, food companies that make unhealthy products often emphasize how individuals should eat in moderation. Energy companies like BP promote the idea of each individual considering their own carbon footprint, which emphasizes what individuals can do rather than government policy steps.

Chater and Loewenstein illustrate their argument with examples from various policy areas, including climate change, obesity, retirement savings, and pollution from plastic waste. They suggest that behavioral economists should refocus their attention, away from individual nudges and toward systematic tax and regulatory changes. They write: “We argue that the most important way in which behavioral scientists can contributed to public policy is by employing their skills to develop and implement value-creating system-level change.”

For a recent research working paper along these lines, I was interested in “Judging Nudging: Understanding the Welfare Effects of Nudges Versus Taxes,” by John A. List, Matthias Rodemeier, Sutanuka Roy, Gregory K. Sun (Becker-Friedman Institute Working Paper, May 15, 2023). The authors look at policies in three areas where both nudges and either taxes or subsidies have been used: cigarettes, influenza vaccinations, and household energy. They summarize: “While nudges are effective in changing behavior in all three markets, they are not necessarily the most efficient policy. We find that nudges are more efficient in the market for cigarettes, while taxes are more efficient in the energy market. For influenza vaccinations, optimal subsidies likely outperform nudges. … Combining nudges and taxes does not always provide quantitatively significant improvements to implementing one policy tool alone.”

For any society, productivity growth is the difference between living in a zero-sum polity, where gains for some can only come as a result of costs for others, and a positive-sum policy, where social arguments can be about the distribution of gains rather than the imposition of losses. I sometimes say that no matter what your economic issues are, it’s a lot easier to achieve them in a positive-sum world.

Martin Neil Baily has spent a career studying productivity growth. He offers an overview of how this area of research has evolved along with his own insights in “Lessons from a Career in Productivity Research: Some Answers, A Glimpse of the Future, and Much Left to Learn” (International Productivity Monitor, Spring 2023, pp. 120-149).

Here are a few figures to illustrate some of the background. The US economy since World War II has gone through four periods of labor productivity growth, as shown in the figure. A key insight here is that additional capital per worker can be measured in economic statistics, and “labor composition” can be approximated by factors like years of school completed and labor force experience. But the remaining productivity growth (the blue bars) is calculated as a “residual”–that is, the leftover part of GDP growth that cannot be attributed to changes in capital and labor is called “productivity.” In an old phrase (I think it traces back to Moses Abramowitz), productivity for economists is “a measure of our ignorance.”

The higher productivity growth from 1995-2004 is typically attributed to an acceleration of productivity in the manufacturing of computers and electronics products, which includes semiconductors. But the question of why productivity growth dropped so sharply in the early 1970s, and why it has not rebounded more in the last couple of decades, remain open questions. Is it becoming harder to achieve technological gains? Are economic statistics not properly capturing those gains? These are active areas of study.

In thinking about the productivity, it’s important to remember that it’s an annual change. Thus, the gap between the good and the bad periods of US productivity is about 1.0-1.5% per year, each year. Over a decade, the higher productivity would mean that GDP was 10-15% higher.

The lower US productivity growth is actually a phenomenon across high-income countries. The productivity levels in this figure are “smoothed” to emphasize long-run patterns rather than chunks of time. But what’s striking is that for the EU, Japan, and the UK, productivity gains have essentially fallen to zero percent.

A substantial portion of Baily’s research has involved looking at productivity levels by industry and by company. Here are some main takeaways:

First, the studies found that there were large differences in the levels of productivity across countries in the same industry. … Second, a high level of competitive intensity forces firms to achieve the level of productivity of the best performers in their industry, or close to it. And if companies compete against the most productive companies world-wide, they move closer to that best-practice productivity level. Third, certain types of regulation, as well as trade and investment restrictions, can prevent an industry in a country from achieving best-practice productivity. Fourth, operating at large scale often provided a productivity advantage. And fifth, promoting high productivity is not a simple thing. The drivers of productivity or the barriers to productivity varied by industry and country. …

[T]he productivity studies found in most cases that the way factories or offices or retail facilities were operated were much more important to productivity than differences in the capital stock. Organizational or managerial capital was very important. And there were even examples where high levels of investment
had contributed almost nothing to productivity. The study of Korea, for
example, found that government development policies had, in some industries, encouraged overinvestment where machinery was underutilized. Another example came from Germany where union restrictions on shiftwork meant that companies had to invest in extra capital to produce a given level of output and capital utilization was low compared to the United States.

A further lesson that emerges from this research is that diffusion of productive methods across firms seems to have slowed. As Baily writes: “The distribution of productivity levels within industries has become wider. That is to say, the gap between the low-productivity establishments and the high-productivity establishments has increased.” To put it another way, the overall slower productivity growth is perhaps not the result of the technological leaders failing to make gains, but rather the result of other firms not keeping up in the kinds of organizational and managerial changes that spur productivity.

Looking ahead, a primary question is when or whether higher productivity will return. One theory is that productivity gains have gotten harder over time. But when one looks at scientific breakthroughs–say, in genetics, materials science, computing power, and others–it’s not obvious that the resulting economic growth should be rising more slowly.

Of course, the current hot topic is artificial intelligence. Baily points out that the new AI tools are both developing very quickly and being adopted very quickly. Baily points to the emerging evidence on how these tools might affect productivity. I’ve discussed much of this same evidence in “The New AI Techologies: How Large a Productivity Gain?” (May 22, 2023), “Biggest Economic Applications of Generative AI: McKinsey” (June 29, 2023), and “Technology and Job Categories in Decline” (July 14, 2022).

Baily mentions a couple of points worth emphasizing here. First, a common pattern in recent decades has been that improvements in information technology often tended to replace previously middle-class jobs and add to inequality. Back in the 1990s, there used to be a lot of middle managers whose job was essentially to collect information (say, about all the people doing sales in a certain territory) and then pass it along to upper management. But with information technology, those middle management jobs could largely be automated on to a computer “dashboard.” However, some of the evidence for the new AI tools is that they provide bigger benefits to the less-skilled, and thus they could potentially be a force for greater equality. As Baily writes: “Many people find it hard to write coherent emails or to do mathematics. As a result, they are forced to take manual jobs with low wages. The new technologies can potentially help them to be more productive. There are signs from some of the case study evidence cited above that generative AI can help those with weaker skills become substantially more productive.”

The other issues is that Baily, like most economists, has some tendency to separate questions of productivity and distribution. The ideas is to encourage and to accept the greater gains from rising productivity, and then to use a share of those gains helping those in need. Baily writes: “Rather than focus on the dangers of new
technologies it would be better to figure out how to take advantage of them, mitigate the adverse impacts and use these breakthroughs to improve the economic future broadly.”

We all have a feeling now and then that it would be nice–and less threatening–if the pace of change would just slow down. But the idea that government regulators have a good sense of how to shape the future of AI seems implausible to me. Imagine a similar set of government regulators in, say, 1985, trying to decide on how to regulate the shape of the internet. Special interests seeking to block change, or direct it to their own gain, are likely to be more powerful than shadowy and unknown future benefits across society as a whole. In a global economy, those who hold back will be overtaken by those who move ahead.

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A new journal is being launched, Health Affairs Scholar, described at the website as “a new fully open access, peer-reviewed journal dedicated to global health policy and emerging health services research.” I wish them success!

For non-researchers like me, one interesting part of the journal is the “Commentary” section. At the start of the first issue, the core members of the editorial group get the ball rolling with their essay, “Ten health policy challenges for the next 10 years,” by Kathryn A Phillips, Deborah A Marshall, Loren Adler, Jose Figueroa, Simon F Haeder, Rita Hamad, Inmaculada Hernandez, Corrina Moucheraud, and Sayeh Nikpay (July 2023) Like all such lists, this one is thought-provoking both for what it emphasizes, and for what it doesn’t. Let’s start with their list of 10 challenges: they have more to say about each challenge, with citations to the literature, in the essay.

Thinking beyond the insurance card: How do systemic barriers affect access to care and what we can do about it?

Despite reaching an all-time low uninsurance rate in 2022, a growing realization has started to set in across the United States that handing out insurance cards does not serve as the final step in the goal of increasing the health of all Americans. Indeed, enrolling individuals into health coverage is only meaningful if they can access the medical care they need, and if they can do so in a timely manner. …

New health care over-the-counter products: What will be required to meet consumer needs?

The market for over-the-counter (OTC) health products continues to expand dramatically. This increase is not only for products that have been on the market for decades, such as nutritional supplements, but also for new categories of products, such as online eye exams and prescription glasses, direct-to-consumer genetic and other types of screening tests such as those for COVID-19 infection, and online pharmacies. These trends are changing the relationship between consumers and health care in significant ways … A prime example of the advantages—and challenges—of the move to OTC health products is the recent US Food and Drug Administration (FDA) approval of the marketing of OTC hearing aids. There is a huge unmet need for affordable and accessible hearing device products as statistics show that the majority of individuals who would benefit from hearing aids do not use them …

Safety-net programs: Why do we make it so hard for families to receive social safety-net benefits?

It is increasingly recognized that social factors like poverty and housing are key determinants of health. Yet, the United States dedicates a smaller percentage of its Gross Domestic Product (GDP) to social spending on families than the average Organization for Economic Co-operation and Development (OECD) country (0.6% vs. 2.1% in 2019). … Another major understudied component of this problem is that it is challenging for economically disadvantaged families to access the benefits for which they are eligible….

Ensuring access to care for patients with limited ability to pay: What are the unintended impacts of poorly targeted support for the health care safety net?

All countries, regardless of their specific health payment approach, must consider how patients can equitably access care. Even countries with publicly funded systems have gaps in access. For example, although the United Kingdom has the world’s largest government-run and -funded health care system, a recent survey found that and one in eight adults paid for private insurance because waits were too long. These issues are particularly acute in the United States, with its complex mix of private and public insurance programs. …

Are structural inequities hampering hospitals’ ability to address social determinants of health?

Hospitals and health systems have the potential to play a significant role in addressing health inequities in the communities they serve. … Emerging evidence, however, raises substantial concern that structural inequities may hamper the ability of safety-net hospitals, which disproportionately serve low-income and racially/ethnically minoritized populations, to address their patients’ and communities’ social needs. These inequities are, in part, driven by structurally discriminant factors at the core of our current hospital financing system. Our current hospital reimbursement system effectively assigns a lower dollar amount for the care of low-income, Black, and Latino people, given their disproportionate enrollment in insurance plans like Medicaid, which reimburse hospitals less. …

With mergers of insurers and pharmacy chains and growth of online generic retailers, can community pharmacies survive?

Pharmacies play a crucial role in the provision of medications and patient-centered medication management services, as demonstrated in the COVID-19 pandemic. Pharmacy accessibility is indispensable for equity in health care access, as pharmacies can reach individuals who do not interact with other health care providers. Pharmacy access is jeopardized by the increasing trend in pharmacy closures observed in the past few years. …

The private equity “takeover” of health care: What does it mean?

Private equity investment into health care accelerated rapidly over the last decade and shows no signs of slowing down. Private equity firms now play a meaningful role across the health care industry, from hospitals and nursing homes to physician practices and dental clinics to biotechnology, medical devices, and information technology. This infusion of capital offers the potential for investments that may improve patient care and generate economies of scale, but private equity’s focus on short-term profits and efficiency also raises concerns about patient harms and higher costs. Numerous news stories have identified examples of fraudulent activity, overtreatment, aggressive billing practices, and widespread use of noncompete and nondisclosure agreements associated with private equity–owned facilities and medical groups. Also, recent empirical evidence suggests that private equity acquisitions of medical practices lead to higher prices and, perhaps more concerningly, that their acquisitions of nursing homes tend to increase mortality rates. …

The road ahead for health policies on genomic testing and precision medicine: Much accomplished but what remains to be addressed? …

[G]enomic testing and the general field of “precision medicine”—which uses information about a person’s genome and advanced computing tools for data aggregation to precisely target prevention, diagnosis, and treatment—have made great advances. Genomic testing is routinely used in a range of clinical scenarios, including cancer risk screening for BRCA1/2, noninvasive prenatal testing for fetal anomalies, and genomic sequencing of tumors to target effective treatments and to diagnose rare diseases in newborns. Yet, much more health policy research is needed, both on existing uses of genomics and those that are emerging.  …

“Nothing about us without us”: How can patient engagement contribute to meaningful health policy research?

Several global initiatives have emerged to recognize the value of patient-centered care. … Health care delivery and health policy change that does not actively engage patients is no longer acceptable. With the ongoing challenges facing health care systems, patient engagement in health policy research to inform health policy changes will become increasingly important to the delivery of effective and financially sustainable health care to an aging population with complex chronic care needs. …

Building a truly global perspective: How can researchers contribute?

Recent phenomena have made apparent the interconnectedness of our global community; what happens in one country touches us all, whether the spread of COVID-19 infection and of technologies to combat it, or crises from wars to climate change and their humanitarian consequences. … However, the public health and health policy literature has long been dominated by authors and perspectives from high-income countries: over 80% of the world’s population lives in low- and middle-income countries (LMICs), yet authors from LMICs are underrepresented in the scientific literature, particularly in meaningful authorship roles. …

I especially appreciate the concreteness of this list. It sometimes feels to me as if health policy disputes are phrased in terms of “spend more” or “spend less,” without consideration of specifics. For example, thinking about to improve people’s practical and actual access to health care in ways that go beyond the starting point of health insurance coverage, like what people know about how to obtain information and care, or whether they can get to a pharmacy, seems important to me. The issue of over-the-counter health care is in the news right now because of the FDA has for the first time approved an over-the-counter birth control pill. But there has been a dramatic rise in what’s available over-the-counter, and our aging society would benefit if hearing aids were more widely available and used.

A list like this is also an expression of encouragement to researchers. Thus, including items like genomic treatments, patient engagement, and health care provision in low- and middle-income countries are both important in themselves, and also a sign of topics that the journal presumably seeks to publish.

But with encouragement duly given, my own personal list of health policy challenges would include (at least) two items not listed here. One is the set of issues arising from online provision of health care, which exploded in size during the pandemic, now seems to be getting scaled back. Even more patients are probably getting their online health care advice from a Google search or ChatGPT or an advocacy website. The issues arising from dramatically expanded access to health care information of highly varying degrees of quality–and how players in the system from health care providers to for-profit companies to government interact with that information–are only growing in size.

The other set of issues is cost control. The list from the editors of the new journal is heavy on issues of access, systemic barriers, structural inequality, limited ability to pay, pharmacies closing down, Medicaid not paying enough, health care needs in other countries, and so on. But it’s just a fact that US health care spending is nearly one-fifth of the entire US economy. There have been studies for years suggesting that as much as 25% of US health care spending doesn’t provide any therapeutic benefit. The incentives to produce new health care technologies that cost a lot and will be covered by insurance are substantial; the incentives to develop new technologies and practices that reduce costs by a few percent each year, if you can get health care providers to adopt the, are minimal. Finding ways to hold down costs related to some of the biggest health care issues–like encouraging patients with chronic conditions to stick to their meds and diet, or addressing the opioid epidemic, or helping the elderly to age at home where possible–will require policies outside the conventional health care delivery system. If the US health care bill was a lot lower, then expanding access would be a lot easier. As it is, US health care spending is a main driver of the projections for federal budget deficits in the years ahead.

Where the list of 10 health care policy challenges mentions cost-cutting or efficiency– say, the role of private equity or health care mergers–it’s skeptical of their benefits. I’m skeptical, too. But finding some cost-cutting measures that could be broadly supported seems like a worthy policy challenge.

William Kearney interview Ben Bernanke (Nobel ’22) in “Real Policymaking Involves a Lot of Other Things Besides Pure Technical Analysis” (Issues in Science and Technology, Summer 2023). The discussion moves from one big subject to another, but here are a few points that caught my eye. The questions are mine: the answers are Bernanke.

Should the Federal Reserve become involved in issues like climate change and economic inequality?

[T]he really big steps that are needed to avert climate change—such as developing new energy technologies and retrofitting old buildings and creating new infrastructure for electric vehicles—all those things are the province of the private sector or more likely the government. And by government, I mean broadly, like Congress. I think the Fed properly should focus most of its attention on its mandate, on the objectives given to it by Congress, which are full employment and price stability.

I think inequality is a similar issue in its complexity. The Fed is paying more attention to inequality and is monitoring unemployment rates across different groups. For example, during the pandemic the Fed appeared to put more weight on employment because of the benefits that has for people who are lower-income workers. But again, the Fed really only has one instrument—namely, financial conditions being tighter or easier and then promoting or slowing economic growth—and it can’t use that one instrument to achieve many different objectives at the same time. It can’t ease policy for one group and tighten policy for another group. It has to have the same policy for everyone in the country.

This is not to deny that inequality and climate change are first-order, very important issues politically and socially, but the Federal Reserve is just one agency, and it should focus primarily on the goals that Congress sets forth for it and the tools it has to achieve those goals.

What are the main factors driving changes in how the Federal Reserve conducts policy in the last 15 years or so?

[A]fter the 2008 crisis, we needed new tools to stimulate the economy; and new players in the financial system meant our lending strategy had to evolve. Very low inflation and a low underlying interest rate structure, starting around 2004, left the Fed with relatively limited space to cut rates to deal with economic slowdowns. When I was Fed chair, we cut the federal funds rate almost to zero in late 2008 amid the financial crisis—but the severe recession continued through 2009 and it was a slow recovery after that. So we needed new ways to stimulate the economy, which led to two principal tools. The first was quantitative easing [in which the Fed buys bonds and other financial assets to keep longer-term interest rates low, thereby stimulating the economy]; the second was forward guidance [to signal the likely direction of future monetary policy], which always existed to some extent at the Fed but became a much more central part of its toolkit.

The second change has to do with the fact that the financial system has changed since the Fed was created. Originally, banks and trust companies provided most of the credit in the economy. Since then, the financial system has evolved to include lots of other kinds of institutions to the point where banks provide less than half of all the credit that goes to Americans. The Fed was set up to provide liquidity and be a lender of last resort only to banks. And so the global financial crisis was a watershed moment because the crisis was most severe in the non-bank financial sector—what’s called shadow banks, including investment banks, various kinds of mortgage companies, and so on. The Fed had to develop a whole new set of tools to be a lender to other kinds of financial companies.

What is the overlap between being an academic researcher and being chair of the Federal Reserve?

On the one hand, my background as an academic provided me with a lot of knowledge and a lot of information that was helpful. When your research illuminates certain relationships or behavior of the economy, that helps you think about policy. And it helps to know history because it shows how others handled, or didn’t handle, previous crises.  On the other hand, academic analysis by its very nature tends to strip problems down into their simplest components. It tries to study relatively simple or straightforward examples of various phenomena. Real policymaking involves a lot of other things besides pure technical analysis. It involves politics. It involves working with colleagues. It involves dealing with enormous amounts of uncertainty. It involves dealing with imperfect data and models, so there are elements of judgment and interpersonal negotiations that are really not part of what academia prepares you for necessarily. … It was also very important to understand issues like communication and cooperation, working with central banks from other countries, working with Congress, working with the president. All those things had to be learned basically on the job—and that’s why being a Federal Reserve chair is a very difficult job.

When China’s Belt and Road Initiative was announced a decade ago in 2013, it had an appealing intuition behind it. China would help to finance the building of land and sea infrastructure links across Asia and Africa. It seemed plausible to believe that, on average, infrastructure spending in that rapidly growing part of the world economy would have a reasonable payoff.

But as I looked into it further, the economics looked more dicey. As it turned out, many of the projects that China was financing had been proposed to other banks and development agencies, but had been turned down. Thus, China was in effect becoming the subprime lender to infrastructure projects in that part of the world. China’s motives for these projects clearly had a substantial political dimension. For example, the loans that China was providing to other countries were often paying for Chinese construction firms to do much of the work. China’s lenders often seemed more concerned with expanding the Chinese political footprint than with issues like how these large-scale projects affected local workers and the environment in the borrowing countries.

I laid out some of the issues over the last few years in “China’s Belt and Road Initiative: Grand or Grandiose?” (September 10, 2018), ”China’s Belt and Road Initiative: The Perils of Being a Subprime Global Lender” (July 30, 2019),  ”China’s Belt and Road Initiative: Could It All Come Crashing Down?” (November 18, 2019), and “China’s Belt and Road Initiative Collides with Pandemic Realities” (December 9, 2020).

When countries took out big loans from state-owned Chinese banks to build these infrastructure projects, it was all smiles and rainbows. But as we reach the stage where loans are due for repayment, there’s a lot less cheeriness. China has recognized that the international reputation of the Belt and Road Initiative is on the line: Is it a win-win arrangement for financing infrastructure, or a cover for a Chinese political power grab? China has been actively bailing out Belt and Road borrowers. Sebastian Horn, Bradley C. Parks, Carmen M. Reinhart, and Christoph Trebesch provide the evidence in “China as an International Lender of Last Resort” (AIDDATA: A Research Lab at William & Mary, Working Paper 124, March 2023.”

From the abstract:

This paper shows that China has launched a new global system for cross-border rescue lending to countries in debt distress. We build the first comprehensive dataset on China’s overseas bailouts between 2000 and 2021 and provide new insights into China’s growing role in the global financial system. A key finding is that the global swap line network put in place by the People’s Bank of China is increasingly used as a financial rescue mechanism, with more than USD 170 billion in liquidity support extended to crisis countries, including repeated rollovers of swaps coming due. … In addition, we show that Chinese state-owned banks and enterprises have given out an additional USD 70 billion in rescue loans for balance of payments support. Taken together, China’s overseas bailouts correspond to more than 20 percent of total IMF lending over the past decade and bailout amounts are growing fast. However, China’s rescue loans differ from those of established international lenders of last resort in that they (i) are opaque, (ii) carry relatively high interest rates, and (iii) are almost exclusively targeted to debtors of China’s Belt and Road Initiative.

In the past, when countries experienced a debt crisis, international agencies like the IMF would take a leading role in negotiating a resolution. It was recognized that if debt burdens just drove the national economies of the borrowers further into recession, then the lenders weren’t going to be repaid much. However, if a negotiation could lead to a situation where some of the debt could be forgiven and restructured, along with a dose of economic reform from the borrowers, then both the borrowers and lenders could end up better off.

Some of the bigger recipients of bailouts include Argentina (!), Belarus, Mongolia ,
Suriname, and Sri Lanka, Pakistan, Egypt, and Turkey. The authors write (citations omitted):

We therefore find that China has emerged as a key lender of last resort for a growing number of developing countries. However, its role in the international financial system is less central, by far, than that of the established global lenders of last resort. China’s bailouts are small compared to the IMF’s global lending portfolio and dwarfed by the sweeping international USD liquidity support extended by the U.S. Federal Reserve (Fed) since 2007, primarily to advanced economies. We also find that Beijing has targeted a limited set of potential recipients, as almost all Chinese rescue loans have gone to low- and middle-income BRI [Belt and Road Initiative] countries with significant debts outstanding to Chinese banks.

In sum, China has developed a system of “Bailouts on the Belt and Road” that helps recipient countries to avoid default, and continue servicing their BRI debts, at least in the short run. China’s role as an international crisis manager can therefore be compared to that of the US Treasury during previous Latin American debt crises or to a regional financial institution like the European Stability Mechanism, which helped to avert, delay, or resolve defaults by highly indebted borrowers, rather than to a global financial backstop with “deep pockets” …

A challenge that arises here is that Belt and Road borrowers may also have borrowed heavily from countries outside of China as well (as in the case of Argentina). When a debt crisis for such a country comes to a head, there will be calls for the IMF to step in and facilitate negotiations. But negotiating debt relief with a range of financial institutions including China’s state-owned banks will not be easy. China tends to view the IMF and other international agencies as controlled by US and European interests (and it’s not obviously wrong to do so).

In 1939, Poland was invaded on both sides: by Germany from the west and by the Soviet Union from the East. Germany controlled Poland during much of World War II, but with Germany’s defeat, the Soviet Union stepped in and established control of both its politics and economy. Although Soviet control was shaken at various times, including by the Solidarity labor movement in the 1980s, Poland does not recover its full autonomy until the 1990s. Thus, Poland experienced about five decades of a primarily planned economy, now followed by three decades of a primarily market-oriented economy.

What does this natural experiment show? It’s worth remembering that the promise of government economic control, then and now, is that it will ultimately make people better off. By the 1980s, after five decades of a planned economy, that promise had clearly failed in Poland. But after three decades of market orientation. in February, the UK opposition leader Keir Starmer caused a stir by noting that on trends estimated by the World Bank, Poland was on a pace to surpass the United Kingdom in per capita income by 2030.

For an overview of the Polish economic experience, a useful starting point is The Road to Socialism and Back: An Economic History of Poland, 1939–2019, by Peter J. Boettke, Konstantin Zhukov, Matthew Mitchell (June 2023, published by the Fraser Institute. Here, I’ll first share some graphs that give away the plot of what has happened.

Here’s a picture of trends in per capita GDP. The dashed blue line projects the trend in per capita GDP from 1970 up through 1992. The darker dashed line shows the trend since 1992–more than double where it was projected to be.

Here’s a graph comparing unemployment rates in Poland to some other nearby countries and to the average of OECD countries.

Other measures of well-being have improved dramatically as well. For example, here’s life expectancy at birth. The gray dashed line show the trajectory that Poland was on. The rest of the figure shows Poland catching up to the OECD average.

But doesn’t the transition to a market orientation generate much more inequality? Back in the 1990s, the answer was probably “yes.” But income is now more equal in Poland than the OECD average.

When it comes to poverty down to “social expenditures”–pensions, disability, and support for the poor–Poland’s spending (as a share of GDP) is similar to the OECD and roughly twice as high as it was during the planned economy era (and remember, per capita GDP was much lower at that time, too).

I’m of course not trying to pretend that Poland is without its problems or that it has become a heaven on earth. But looking at the broader picture, the standard of living of the Polish people was barely creeping upward during the time of the planned economy, and now has made dramatic gains.

The report from Boettke, Zhukov, and Mitchell goes through considerably more detail over the decades: the nationalization of Poland’s economy after World War II how the planned economy functioned, the pushback on planning at various times from different sectors, the rise of Solidarity in the 1980s, the “shock therapy” reforms of the 1990s, and ongoing issues like improving the current education and health systems in Poland. Here, I’ll just mention a few points that jumped out at me.

1) In some ways, the essence of the planned economy was a claim that if the market economy was allowed to do what it wanted, people would ultimately end up worse off. If consumers were allowed free rein, the argument went, they would fail to save and instead would spend on frivolities. Thus, for the economy to grow, consumers needed to be pressured or required to save, and then the government would direct these savings to investment in what it viewed as the important industries for development like coal, steel, and electricity.

With government planners making the economic decisions, Poland’s heavy industries did expand, but were perpetually inefficient. In addition, decades of de-emphasizing what consumers wanted took their toll. By the 1980s, the waiting list for house was 15-30 years. “In the early 1970s, for every 100 telephone subscribers
in Poland, there were another 34 people waiting for service. By the 1980s, there were 57 Poles waiting for service for every 100 subscribers.” Transactions for consumer goods often involved trading vodka, chocolate, or even toothpaste, or getting in line at a certain hour day after day, hoping to be allowed to purchase an appliance.

2) Not only did the government’s version of growth override what consumers wanted, it was deeply concerned that workers wouldn’t try hard enough. Thus, in the late 1940s and into the 1950s, the required work-week rose from 40 to 46 hours, and “social parasites” who didn’t work hard enough could be sentenced to two years of compulsory labor at any location the government designated.

3) The push for industrialization didn’t only ignore what consumers wanted, it also also ignored environmental concerns. Here’s one example of the results:

The socialist record of pollution was notorious and industrial pollution in Poland was especially bad. A 1991 article in the Washington Post described Warsaw’s tap water this way: “It spurts yellowish-brown from the tap, laced with heavy metals, coalmine salts and organic carcinogens. It stains the sink, tastes soapy and smells like a wet sock that has been fished out of a heavily chlorinated swimming pool” (Harden, 1991). The same article reported that Warsaw tap water had double the World Health Organization’s limits on chloroform concentration; a quarter of Poland’s big industrial plants had either no waste-water treatment or used treatment devices with insufficient capacity; 57 percent of the Vistula river was classified as unfit for any purpose and the average concentration of mercury was nine times greater than the Polish norm for safe drinking water (Harden,
1991).

4) In the 1990s, Poland followed what was called the “shock therapy” approach to transitioning away from the planned economy. There was a considerable controversy over time over whether it was better to do such transitions quickly or more slowly. Remember, the transition involves many steps: market-determined prices, wages, interest rates, and exchange rates; shifting firms to private ownership opening to trade with countries outside the former Soviet bloc; implementing a tax code; and much more. The immediate disruption in Poland was extreme: for example, inflation hits 250% one year.

But even as the previously favored heavy industries took a big hit as their government support was withdrawn, other industries that had been disfavored like food processing, passenger cars, home appliances, and consumer tech expanded dramatically. Looking back, it seems hard to make the case that if Poland had torn off the planned economy band-aids more slowly, the outcomes would have been substantially better.

5) A word of warning for the unwary: A substantial part of the discussion in the report is a review of the theoretical arguments for why planned economy socialism doesn’t work well. Personally, I’m always happy for a ramble through Marx and Hayek, Kornai and Mancur Olsen, and so on and so on. But shockingly enough, my tastes are not universal.

For those who believe that a combination of markets, flexible prices, and private property can and should play a prominent and useful role in societies, the experience of Poland will only tend to reinforce earlier beliefs. But of course, many are also dubious about markets. In my experience, this group is quick to admit that the Soviet style of planned economy did not work well. But they often cling to the idea that a different and better version of a planned economy would work better–often citing various European economies as a model. In my own view, there are lots of flavors of capitalism: American, Canadian, British, Japanese, German, northern European, southern European, and others. I’m open to a number of arguments about what the different versions of capitalism might learn from each other. But all of these countries primarily build their standard of living not on government planning, but on the dynamics of market economy.

The standard story of economic development at the national level has been fairly consistent, albeit with some local twists, for the last couple of hundred years. A less developed country starts off with most of its workers in agriculture. It first shifts to low-wage manufacturing, then builds the skills and capabilities for high-wage manufacturing, and from there moves into service and knowledge industries.

But there are real concerns over whether this approach can work in the 21st century economy, at least for more than handful of countries. In many industries, robots can take over manufacturing jobs. For sophisticated manufacturing, a large share of the economic benefit goes to the designers, scientists, and engineers behind the innovation–or to the company that owns the intellectual property–not to the workers on the assembly line. Thus, development economists have been struggling with the question: Can at least some developing countries use digital technologies and the connectness of the internet to skip past the manufacturing stage and go straight to exports of services in global markets?

In a joint report, the World Trade Organization and the World Bank tackle this question in “Trade in services for development: Fostering sustainable growth
and economic diversification” (2023).

Here’s a figure that helps to illustrate the standard development pattern. Notice that high-income countries have the lowest share of jobs in agriculture, while low-income countries have the highest share. Everywhere, jobs in agriculture are decreasing over time. But the biggest sector for job gains is not industry–which has actually been shrinking as a share of jobs in high-income countries–but rather jobs in services.

The report makes case for optimism about the possibilities of developing countries using trade in services as an engine for economic growth. Here’s some background information:

Services trade has been the most dynamic component of world trade for the last 15 years. Such dynamism provides developing and least-developed economies significant opportunities for export-led growth, economic diversification, inflows of foreign direct investment (FDI) and integration into global value chains.
Services trade promotes greater inclusiveness, particularly for female and young workers and entrepreneurs as well as micro, small and medium-sized enterprises (MSMEs). In 2021, 59 per cent of employed women worked in the services sector, and 9 out of 10 services firms were MSMEs. Today, the services sector generates half of employment worldwide and two-thirds of global GDP – more than agriculture and industry combined. These changes in the structure of the global economy challenge long-held perceptions of services as a less desirable path to economic growth and development compared to manufacturing. …

Fuelled by advances in information and communications technologies (ICT), exports of commercial services almost tripled between 2005 and 2022, with exports of digitally delivered services experiencing the fastest growth, increasing almost four-fold. During the same period, developing economies accounted for an increasing share of global services trade, as least-developed economies’ exports of commercial services grew more than four-fold between 2005 and 2002, while those of other developing economies more than tripled. The expansion of developing economies’ exports is increasingly tied to services supplied across borders through digital means. And developing economies account for an increasing share of non-traditional service exports.

What exactly is meant by “services” in this context? It was conventional wisdom for some time that international trade in services might be difficult, because lot of services are locally provided. For example, you can’t outsource the taxicabs in one city to be provided by drivers in another city. But for that taxicab company, it is possible to do record-keeping, back-office services, and even answering calls with a base in another country. This form of international trade in services is delivered over the web. However, tourism is also counted as a “services export:” for example, when a US tourist visits Kenya, services sold in Kenya are being provided to US buyers.

In the future, services including health care and education may be divided up, with some portion of those services being provided across national borders. If you are using “telemedicine” to contact a health care provider on-line, they don’t need to be residing in your country. If you are willing to travel to a provider in a different location for your medical care procedure, then that provider can be outside the country as well. Here’s a comment from the report on “medical tourism:”

Medical and wellness tourism has expanded significantly in recent decades, propelled by improved telecommunications and transport services. Countries such as Brazil, Cuba, India, Jordan, Malaysia, the Republic of Korea, Singapore, Thailand and the United Arab Emirates have become major medical hubs, receiving foreign
patients from both developed and developing countries. For example, India has become a popular destination for medical travel, and hosted around 3.5 million foreign patients from 2009 to 2019. Foreign patients from developed countries such as the United Kingdom and the United States, as well as from developing countries such as Bangladesh, Nepal and Sri Lanka, go to India in search of less
costly, high-quality treatment.

Thailand is another popular destination for medical tourism. It has developed a large medical tourism sector geared towards foreign patients, with 61 hospitals bearing the Gold Seal of Approval from the Joint Commission International, an organization which assesses hospital standards around the world. In 2019, Thailand received 172,265 international medical tourists, according to estimates by its National Statistical Office. In order to mitigate the internal brain drain risk caused by the expansion of an industry geared towards attracting international tourists, doctors and nurses are required to serve three years in the public system, including in rural areas, prior to working in private hospitals, in return for public funding of their education. The government has also increased the salaries of physicians, nurses and dentists in all community hospitals to encourage these professionals to stay in the public health sector and maintain the quality of public healthcare services.

I do not yet have a good sense as to the role that exports of services can play in broad-based economic development. In part, my problem is that the general area of “services” is almost inconceivably broad, and understanding what kinds of services exports might work well for countries with different locations and strengths is a complex problem. But I do suspect that the old-style route to development via low-wage manufacturing is not as workable as it used to be. In addition, the path to economic development for countries with lower per-capita GDP has typically involved finding ways to trade with countries with higher per-capita GDP.

I frequently read or hear a claim that the United States needs a more aggressive industrial policy to keep pace with China’s industrial policy. On its face, the claim is a curious one. After all, China’s “industrial policy” didn’t work very well from the 1950s up through the 1970s. It was only when China’s industrial policy started involving considerably less government control over the economy in the early 1980s that China’s impressive surge of economic growth began. There are a bunch of different ways to compare per capita GDP across countries (depending on the exchange rate between currencies that seems most relevant), but on World Bank estimates, China’s per capita GDP is still only about 20-25% of the US level.

Thus, from an overall perspective, China’s economic success looks a lot less like a carefully directed move forward and more like a bunch of political leaders trying to scramble up to the front of the economic parade so that they can claim to be leading it. And while I’m willing to take my economic lessons from wherever they emerge, the question of what lessons the US economy should be learning from an economy that has grown over four decades to reach maybe one-quarter of US per capita GDP are less than obvious.

But what if we dig down into the details of what China’s government has actually done to favor certain industries, and what lessons might be learned? Chad Bown interviews Lee Branstetter on this subject in “Is China’s industrial policy working?” (Trade Talks podcast, April 23, 2023, audio and transcript available).

Their discussion starts off with a quick overview of why even many market-oriented economists think it’s appropriate and productive for the government to play a role in supporting research and development (through some combination of intellectual property laws, subsidies and tax breaks), as well as education and infrastructure. Thus, the focus here is on “industrial policy” that focuses not on the overall economic climate, but on support for specific chosen industries. In addition, as Branstetter points out, China’s economic policy through the 1980s and 1990s was mostly about less government intervention, or on supportive conditions for extremely broad areas of the economy–like manufacturing. As Bown describes this time: “China reformed and became more market oriented. The government is still giving out a lot of subsidies, but in terms of industrial policy, those subsidies were not precisely targeted. And I suppose when you are subsidizing everything, you are preferencing and targeting nothing.”

But then China’s leadership becomes more involved in targeting specific industries. Branstetter describes the kind of research he has been doing in this way:

In 2007, China made it mandatory for companies listed on a Chinese stock exchange to disclose in their annual reports the subsidies that they received from the Chinese government. What that means is that starting in 2007, at least for China’s list listed companies we can get pretty rich firm-level data on the subsidies they received, and we can actually use that data along with all the other data disclosed by these firms to their investors to try and get a sense of how subsidies are correlated with firm characteristics, especially productivity. If the focus of Chinese industrial policy after the mid-2000s was really to strengthen the
innovative capacity of these national champions, then it should be making firms more productive.

It’s then possible to look at whether China is targeting firms that already have high productivity, and trying to push them ahead, or whether it is targeting firms with lower productivity to help them catch up. In either case, one can look at the connection from subsidies to later productivity gains. It turns out that subsidies were mainly going to lower-productivity firms, and didn’t seem to help their productivity. Instead, firms were being chosen for subsidies because they were large. Branstetter says:

We find that the Chinese government is not giving subsidies to initially more
productive firms. If anything, the statistical association is actually negative. The Chinese government is, on average, giving more subsidies to less productive firms. …

Chinese firm’s annual reports do often include language that describes what particular subsidies were for. But if we focus on that subset of subsidies that are meant to promote research and development, or the subset of subsidies that are meant to support upgrading of equipment, even for these specific subsidies, we find no relationship with productivity. It’s not the case that firms that are more productive are more likely to receive these subsidies in the first instance. And it’s not the case that firms that receive these subsidies become more productive later. …

Firms that are larger, as measured by total assets or employment, appear to be somewhat more likely to receive these subsidies. As we dug into this data, it became
increasingly clear to us that the subsidies provided to Chinese firms had lots of objectives, many of which were not connected to productivity. We see significant quantities of subsidies going into declining industries like mining. We see significant subsidies that appear to be designed to support employment in large firms. … It’s understandable why the government would pursue this objective, but it’s also crystal clear that the pursuit of this objective directly undermines the pursuit of turning the already more productive firms into super innovators. The money that’s given to prop up failing firms is money that cannot be given to support the technology leaders of the future, and the more you do the former, the less resources you have to do the latter.

In 2015, China announces a “Made in China 2025” policy, which is clearly seeking to have products produced with a wide range of technologies in other countries be produced in China instead. It turns out that this group of subsidy-receiving firms is more likely to have patents–which sounds as if industrial policy may be at work. But at least for the first few years of the program, the firms getting subsidies don’t seem to improve productivity and don’t seem to be taking out new patents at a faster rate. As Branstetter says:

And given how easy it is for firms to get patents in China, given the strong incentives they have with subsidies available at the local government level and elsewhere to take out these patent applications, it’s really surprising that we just don’t see any impact that these subsidies are making these farms more innovative or more productive. … When we try to evaluate the net benefits, if any, of Made in China 2025, it’s hard, at least on the basis of our analysis, to come to a very positive conclusion. Resources have been expended, but the desired innovative outcomes have not yet emerged.

These kinds of arguments may seem counterintuitive, because the conviction that that China’s industrial policy is a sweeping success has become so embedded. For those who would like to dig in more, the study on subsidies is available as NBER working paper #30699, the study on Made in China 2025 as NBER working paper #30676, and a draft of an overall essay on China’s industrial policy is also at the NBER website.

The fundamental point, of course, is that industrial policy can’t be evaluated by pointing to a few companies that are success stories and that also received subsidies. Conversely, industrial policy also can’t be evaluated by looking at a few spectacular failures of companies that got subsidies, either. You need to look at the full array of companies receiving subsidies, see what mixture of political and economic factors guided that choice, and then look at later outcomes for the group as a whole.

Cryptocurrency is new in some ways, but in other ways, if it’s going to be “money” then it will share some of the problems of money in the past. Daniel Sanches discussed the traditional division between “outside” and “inside” money, and the inherent flaws of each one, in “New Moneys in the Digital Era” (Economic Insights: Federal Reserve Bank of Philadelphia, Q2 2023, pp. 2-10)

“Outside money” refers to money that is either not backed by anything (“fiat money”) or backed by something that is not a liability for anyone in the private sector, as in the case of money backed by government-held supplies of gold. “Inside money” is created “when two private parties engage in a transaction that involves the issuance of a liquid debt claim (that is, a claim that can circulate as a medium of exchange).” For example, when the two parties are me and my bank, and I deposit money in the bank, then we have created inside money that can be used to buy. Sanches writes:

To sum up, in the modern monetary system, central banks control the amount of outside money created in the economy, and private financial firms issue inside money to facilitate private transactions. Inside money is usually a promise to pay outside money, and each dollar of outside money is backing several dollars of inside money.

The classic problem with outside money arises when the quantity available of such money doesn’t adjust to economic conditions. For money to work well as a medium of exchange, it needs to have a (roughly) fixed value–that is, not much inflation or deflation. But there are historical examples (during the gold standard, the Great Depression) where the US economy was dramatically slowed down because the supply of outside money as limited or declined, which caused the economy to slow as well.

Some major cryptocurrencies like Bitcoin have an outside money problem. The quantity of these currencies in circulation is governed by the software behind the currencies themselves (that runs the “blockchain). As a result, the quantity of these currencies can’t adjust to demand. When demand goes up or down, the price of Bitcoin also zooms up or down. If you are serious about having money that has a more-or-less stable value, then this inability to adjust to demand makes Bitcoin unsuitable as money. Sanches writes: “Based on the accumulated experience and the theoretical research in monetary economics, it is hard to believe that any existing cryptocurrency will soon emerge as a sound monetary system, as opposed to a speculative investment vehicle.”

Some cryptocurrencies instead have tried to be inside money. For example, a “stablecoin” is a cryptocurrency backed by by US dollar-denominated financial asset. The quantity of this currency can rise if the market so desires–just buy more financial assets to back the new currency. It can also contract if the market so desires. However, there is no regulation or guarantee of exactly what assets are being used to back these stablecoins. Are the assets something very safe and easy to sell, but with a low rate of return, like US Treasury bonds, or something riskier which pays a higher return? Sanches writes:

In reality, it is not clear what types of assets stablecoin issuers hold as collateral for their tokens. Many stablecoin issuers claim that their tokens are fully backed by U.S. dollars, but the issuers do not specify the types of dollar assets it holds, so it is not clear whether all dollar assets backing stablecoins are safe assets, such as bank deposits and government bonds, or risky assets, such as commercial paper. No regulatory mechanism verifies the types of assets and corresponding balances in custodial accounts.

As a result of this kind of uncertainty the issue for inside money stablecoins is bank runs. What happens if investors fear that the financial backing of the stablecoin is insufficient, and start pulling out their money? Sanches tells the recent story:

The recent run on two major stablecoin issuers demonstrates the problems associated with creating inside money outside of the regulated financial system. TerraUSD is a stablecoin hosted by the Terra Network and created by South Korea’s Terraform Labs. Investors were attracted to TerraUSD because they could earn returns of nearly 20 percent annually by lending their TerraUSD holdings via Anchor Protocol, a decentralized bank for crypto investors. Until May 2022, TerraUSD’s value remained very close to $1, as intended by its issuer, and it was the third-largest stablecoin, with a market capitalization of $18 billion. But on May 9, its value declined suddenly to 90 cents following large withdrawals from Anchor Protocol. As in a typical bank run, the initial withdrawals on May 9 led to further withdrawals, and within a few days TerraUSD was trading at approximately 20
cents. TerraUSD has not recovered from that crisis and, as of the writing of this article, was trading at roughly 2 cents.

If you are a short-term investor looking for newfangled financial assets that might make big moves up or down–so that you can capitalize on these changes–crypto makes sense. But if these kinds of financial instruments are going to eventually become a form of money that is in widespread use, these classic problems need to be addressed. Sanches sums up this way:

It is likely that in the not-so-distant future, our money will be entirely digital, and cryptocurrencies will likely play an important role in this new monetary system. However, this transition will inevitably be slow and bumpy, requiring both experimentation and prudence. At the very least, a stable cryptocurrency standard requires that unbacked digital tokens—which are, despite their novelty, just another outside money—acquire the properties of an elastic currency, as defined in this article. And without government regulation, such as a requirement that stablecoins be fully backed by short-term government bonds, digital tokens that take the form of demand deposits via currency pegs—which, despite their novelty, are just another inside money—are likely to suffer runs.

Aurelian Craiutu is a professor of political science at Indiana University, who has spent a good chunk of his career thinking about what “moderation” means–from the perspective of someone who grew up in communist Romania during the rule of Nicolae Ceaușescu. Geoff Kabaservice talked with him for a podcast in April 2022. I’ll quote here from the transcript (“Why the leading challengers to liberalism and moderation come from the West, with Aurelian Craiutu,” Niskanen Center, April 29, 2022).

Craiutu’s comments resonated with me in part because of his clear-eyed view moderation is a “difficult virtue that requires a great dose of courage, nonconformism, and risk.” My sense is that when you get together a room of people who share a common view, a dynamic can emerge in which people compete to show their degree of allegiance to the shared view, and in doing so, some of the people will stake out ever-more-extreme positions. In such a setting, being a moderate isn’t easy. Here are some comments from Craiutu:

I don’t want to identify moderation with centrism. The way in which I think about moderation is that it can be found on both sides of the political spectrum. There are moderates on the left, in the center, and on the right. It’s not necessary to be a centrist in order to be a moderate. So that’s something that I think can be demonstrated by looking at thinkers in the past, politicians and agendas. …

I’ve always been fascinated by moderate thinkers who are concerned with maintaining the balance of the ship. Keeping the ship on an even keel is, I think, one of the best definitions of what political moderation is all about — hence the image of the trimmer. The trimmer is the person who trims the sails in order to prevent the ship from capsizing.

There is no algorithm, there is no science that could explain what to do, when to act, when not to act. You have to have political judgment. You have to have political flair. You have to be like a tightrope walker. And in this regard, I think it’s one of the riskiest things to try to act as a moderate when passions run high, when reason is overcome by passion and most people just want to shout and express their dismay, their concerns and so forth, without concern for political moderation. It’s a virtue, as a title of my book says, a virtue only for courageous minds. It’s a paradox. The image of moderation is that of a weak virtue. And I think, and we can talk at length about this, that it is a difficult virtue that requires a great dose of courage, nonconformism, and risk. …

It’s one of the most difficult concepts to define because moderation constitutes an archipelago. There is political moderation, so we look at the institutional aspects of moderation: What are the institutions and mechanisms that limit power, that prevent power from being abused? And we know what those are: checks and balances, constitutionalism, freedoms, freedom of the press — a very important freedom — freedom of association, constitutionalism, bicameralism. And there are others: federalism maybe, decentralization, subsidiarity. All of those constitute what I would say is the institutional archipelago of moderation.

But there’s also, when we talk about moderation, a host of ideas related to its ethical part. What does it mean to be a moderate? Well, there are lots of things here that can be said. One thing that I would emphasize is that to be a moderate is the opposite of being a fanatic. A fanatic is someone who doesn’t put things in perspective; that subsumes everything under one category, one principle; that is ready to sacrifice everything for the pursuit of that single value, be that liberty, equality, pro-life, pro-choice, low taxes, you name it. So that’s one.

There is also implied in the ethical component of moderation a good dose of skepticism and awareness of one’s fallibility — which is a form of modesty, if you wish, and a form of humility. Moderates are people who tend to be modest and display a good dose of humility, understanding very well that they may be wrong, that they may have only a portion of the truth. …

And there is also the third aspect of moderation, which is religious moderation. Now that’s a topic that I have not written about, and I’ve thought a little bit about it, but there is a whole continent of religious moderation that I think needs to be rediscovered today. To be religious and to be moderate are two different things, but they’re not incompatible — on the contrary. Reinhold Niebuhr is one of the thinkers that comes to mind here. He was able to combine both political moderation and religious moderation. But there are others as well. …

I’ll give you an example, a concrete example here. … Raymond Aron was a great French political thinker, sociologist, and journalist who at some points in his career acted as a trimmer. For example, in 1968 he criticized the university system for being sclerotic. The university was then, as it probably is still now, very anchored in old practices that didn’t serve the student needs. And he thought that professors should be more available to students, they should put less emphasis on exams and more on engaging with students. So he was for reform in the system.

On the other hand, he was vehemently against the students’ revolt in ‘68 because he thought that they were interested in carnival rather than real reform. So he was a trimmer. To the students, he talked the language of the university administrators, arguing for finding a modus vivendi between their claims and the university’s needs and constraints. And to the university administrators, he spoke the language of the students, pushing for reform against the sclerotic practices and habits of the professoriate. So I think that it’s possible to be a trimmer, and a principled one. It doesn’t mean that everyone who claims to do some trimming will be successful in avoiding the charge of opportunism. But Aron, for example, was a successful one.