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When economists or policymakers talk about industrial policy, Korea usually enters the conversation. There’s no question that Korea has had remarkable economic success in recent decades. There’s no question that various government policies have contributed to that success. But there is continuing controversy over what broader conclusions to draw from this experience. Shahid Yusuf offers useful background by laying out what actually happened Korea’s development experience in “Could Innovation and Productivity
Drive Growth in African Countries? Lessons from Korea” (Center for Global Development, Working Paper 635, March 2023).

As a starting point, here’s a graph from the World Development Indicators database maintained by the World Bank. It shows per capita GDP for Japan and South Korea in inflation-adjusted dollars. In 1990, Japan’s per capita GDP was triple that of South Korea. By 2021, Japan’s lead was down to just 7%. I try to adhere to the creed of never making predictions, especially about the future. But it is not at all inconceivable that a few years down the road, Korea will surpass Japan in per capita GDP.

What policy lessons can be learned from Korea’s remarkable growth trajectory? Yusuf hits the key themes here, but I’ll quote some of his comments in an order of my own.

As a starting point, remember Korea’s situation after World War II and the Korean War that followed from 1950-53. As Yusuf notes, Korea had an egalitarian redistribution of land after World War II: “The distribution of land formerly owned by the Japanese to Korean farmers in 1949 may have contributed to the egalitarian distribution of income and political stability that buttressed Korea’s later development. This redistribution was undertaken by the US. Military Government.” Moreover, South Korea had an external enemy–North Korea–to unite against: “One should not overlook, the threat South Korea faced from its neighbor to the North, a threat that drove the government to accelerate industrialization. Industrial diversification and deepening enabled Korea to meet more of its defense requirements and neutralize the pressure from its hostile neighbor.”

In the 1960s, Korea’s government and business leaders determined to begin a drive to industrialization:

“The unwavering commitment of the political leadership and the business elite, starting with President Park Chung Hee in the mid 1960s and sustained by his successors, to a relatively inclusive, export-led industrial strategy entailing systematic diversification into more complex manufactures, is arguably the most frequently retailed. The strategy itself was choreographed and implemented by Korea’s economic bureaucracy headed by the Economic Planning Board (EPB) in consultation with the leading business groups. The Five-Year Economic Development and Science and Technology Comprehensive Plans spelled out the government’s vision and objectives. Presidential focus on industrial and export outcomes with reference to assigned targets and the attention given to cross sectoral coordination by the EPB mandarins, minimized failures that can short circuit linkage effects and stymie industrial change (Rodrik 1996).”

It’s useful to emphasize several themes about this broad policy approach.

1) There is a built-in emphasis on export-led development. This is a useful policy guideline, because a government can do a lot of things to favor its companies in their domestic sales, but expanding market share in international markets suggests genuine growth of competitiveness. Korean companies that couldn’t meet their targets in international markets found that their government subsidies were reduced or eliminated.

2) Korea’s development strategy was very broad-based, going way beyond offfering subsidies and cheap credit to certain industries. For example, World Bank data says that back in 1970, about 15% of the over-25 population in Korea had completed “upper secondary” education (basically the equivalent of high school. By 1990 the proportion was about half, and now it’s about three-quarters. “Education especially in STEM disciplines and the development of industrial skills was also a priority from the very outset. Thousands of Korean students went abroad to study and links with foreign universities also facilitated a sharing of information on curricula and teaching modalities. Industrial diversification could not have succeeded had the supply of human capital and workforce skills fallen short .”

This graphic shows a range of policies: interventionist support for manufacturing, but also development of human capital (including heavy use of vocational training, science and technology education, and overseas training and education), strong support for research and development; and policies to bring technology from around the world and diffuse it into Korean firms.

3) Korea followed a step-by-step approach to development, with each step building on the previous one.

Korea’s manufacturing in the 1960s revolved around light, labor intensive activities such as
garments, footwear, toys, food products, and light consumer electricals. The kind that were the norm in other low income economies. But starting in the early 1970s, Korea initiated a structural break and launched its heavy and chemical industry promotion plan (HCIPP) so as to diversify into more complex and technology intensive products. It constructed a state-owned iron and steel complex at Pohang financed in part by Japanese grants, a machinery production complex at Changwon, a petrochemical complex at Wulsan, an electronics complex at Kumi, and a major shipbuilding yard at Ulsan.

The development of individual industries followed a step-by-step approach. For example, Korea’s shipbuilding industry started with domestically produced steel, cheap local labor, and subsidized government loans. But then:

[L]eading shipyards such as Hyundai Heavy Industries sought foreign assistance on such
areas as ship designs, operating instructions, the design of dockyards, and production processes. They hired European engineers and technicians to assist with the running of the shipyard and training of the workforce and adopted quality control measures modeled on the best practices of leading competitors. This plus the recruitment of newly minted engineers from Korean universities—with some having received advanced training overseas—aided in the rapid upgrading of the workforce and allowed the shipyards to largely dispense with foreign assistance by the late 1980s. A more capable, tech savvy workforce plus learning by doing delivered substantial gains in productivity as well as in quality (Kim and Seo 2009). These have continued into the present day with Korean firms among the frontrunners in the production of smartphones, autos, consumer durables, and engineering equipment.

Design capabilities took longer to acquire—close to fifteen years. For some years ship designs were acquired from overseas and technology licensed to build new types of higher value ships such as LNG carriers. This dependence gradually tapered once in-house research and testing facilities had matured. During the latter half of the 1980s, Korean shipbuilders were responsible for advances in protective coatings, welding techniques and in core technologies related to ship propulsion, engine performance, and hull design to minimize pressure and friction drag.

4) Korea’s government invested heavily in infrastructure: seaports, airports, roads, rail. But as a more recent example, World Bank data shows that the share of Koreans using the internet went from 7% in 1998 to 73% just six years later in 2004–and the share has been above 90% and rising since 2016. A US-based techie friend of mind said to me: “We have the fastest home internet access available where we live, which means it’s almost as good as the crappy internet access in Seoul.”

5) Continual technological advance was seen as essential. Korea spends more of its GDP on R&D than just about any other country.

Technology was seen as essential to the success of industrialization and export mpetitiveness. MOST (Ministry of Science and Technology) and KIST (Korea Institute of Science and Technology) were established in order to promote technology transfer and absorption by Korea’s nascent manufacturing sector. Incremental institutional additions continued through the 1970s and the 1980s with the creation of the Korea Advanced Institute of Science (now KAIST, the leading S&T university), as well as a flock of specialized government research institutes (GRIs), many located in the Daedeok Science Town, which later morphed into the Daedeok Science Valley, housing public and private research entities employing thousands of highly trained professionals.

6) Korea had some advantages from its global neighborhood: “East Asian neighborhood effects that conferred reputational advantages and attracted the attention of foreign buyers and investors …”

How does one sum up this policy approach? It’s true that Korea’s government subsidized certain industries. As Yusuf writes: “”The state created a controlled environment in which competition among Korean producers was encouraged but the market was protected by tariff barriers, and by restrictions on the entry and exit of firms. Moreover, Korean exporters were assisted by export subsidies, tax benefits and subsidized financing.”

But the Korean government also did a good job of choosing the industries to be subsidized, in a way that didn’t just pump money into existing production or doomed sectors. It emphasized broad education and improving the skills of its workforce. It emphasized modern infrastructure. It emphasized moving up the technological frontier, by importing expertise when needed, but also by taking many steps to develop its own technology. Also, Korea embraced the continual evolution of technological expertise–and the continual disruption that it brings.

South Korea’s economy faces ongoing challenges moving forward, like other economies around the world. For South Korea, a big shift is that much of its economic growth has been based on large industrial conglomerates (“chaebol”) doing various kinds of increasingly sophisticated manufacturing. But for the world economy as a whole, with robotics and automation on the rise, economic growth is increasingly in the services side of production–innovation, design, and support services like finance and legal–not in the making of physical objects. Thus, Korea’s current government plans emphasize continued technological skills and sophistication, but also application of that technology in small- and medium-size enterprises, as well as in the services sector.

There’s an ongoing argument about whether the specific subsidies to industry were more important than the more general improvements in human capital, infrastructure, and support for high levels of investment and technological growth. I won’t try to untangle that knot. But it seems clear that the industrial subsidies by themselves, without the array of broad supporting policies, would not have had the same success.

About a decade ago, a concern emerged that China was dominant in global production of what are called “rare earth elements”–including notably yttrium, neodymium, europium, terbium, and dysprosium. (Giving the atomic number for each of these is left as an exercise for the reader.) These materials are, at least with current technology, essential for manufacturing certain clean energy technologies, like components of electric vehicles and wind turbines, as well as some materials used in defense-related technologies, like permanent magnets and certain coatings for jet engines.

In a post back in 2015, I pointed out that China had been making threatening sounds about refusing to export these materials, but also that market had been reacting to that threat by figuring out how to conserve on the demand side and how to find alternative sources and recycle on the supply side. A group of researchers from the Rand Corporation–Fabian Villalobos, Jonathan L. Brosmer, Richard Silberglitt, Justin M. Lee, and Aimee E. Curtright– provide an updated view of the situation in “Time for Resilient Critical Material Supply Chain Policies” (2022).

Here’s a figure offering a timeline of events. Focus your attention on the graph at the bottom, which refers to production of REOs, or “rare earth oxides,” which is the amount produced after the ore has been refined. From about 1998 up through 2013, more than 90% of the rare earths being produced originated from mines in China (black line). This was the period when China was threatening to limit or cut off supplies to the rest of the world. But starting around 2016, global mining of rare earths rose substantially (red line), while mining in China rose much less (blue line). China’s market share of rare earth elements remains high, but has now fallen to about 55%.

The Rand researchers emphasize that China’s market share remains large, but they also make the point that China’s share of processing these rare earth elements is even larger–a legacy of the years when China was almost the only global producer. They write:

Current production and processing activities demonstrate that China’s window for
disruption of these critical material supply chains may be narrowing, but not eliminated, and remains a strategic geopolitical tool for its leadership. …

As shown in Figure 2, China’s share of extraction peaked in the late 2000s, when it provided upward of 95 percent of global REE [rare earth element] output; it now accounts for 55 percent. However, China accounts for about 80 to 90 percent of processing and separates nearly all heavy REEs; because of this dominance in the market, the processing sector
is where the risk of disruption is greatest.28 is the same sector that China leveraged when Japan was threatened with REO restrictions in 2010. In fact, nearly all rare earth ore mined in the United States (43,000 tons in 2021) is sent to China for separation and purification. This dominance resulted from China’s ambitious mining programs, an inability to enforce national policies that led to illegal mines, and a disregard for pollutants and by-products that create
environmental waste.

The Rand researcher go into some detail about risks of disrupted supplies, but in broad terms, the policy steps here are fairly straightforward. (You will be stunned to know that the Rand researchers believe a “whole-of-government approach” may be needed here. Personally, I’m not holding my breath for the announcement of some policy problem that is said not to require a “whole-of-government” approach.) For the short-run, having stockpiles of rare earth elements that could last a few months may be useful.

For the longer run, the answers involve allowing expanded mining for these rare earth elements, as well as finding ways to substitute other more common minerals for some of their uses and to recycle already-mined supplies. It also requires building processing plants for these materials. Some of this, like searching for substitute materials, the private sector will eagerly do on its own in response to supply shortages and higher prices. But for other parts–like opening new mines and processing facilities–governments are going to have to strike a balance between environmental concerns and actually allowing a reasonable number of such projects to go ahead at a reasonable time and cost. That part of the challenge may be more political than economic.

It’s been said that colleges and universities have an edifice complex: they like big buildings. Major donors like have having their names on buildings–or at least chiseled into the lobby. Faculty (setting aside the precarious position of adjunct faculty) feel that they need separate offices–even if they often work from home, or the laboratory or library, or even if they go off for a few weeks every year for seminars and lectures at other institutions. The conventional wisdom is that potential students, making their choices, judge by the evidence of their eyes whether the buildings of an institution seem stable and substantial.

My wife and I sometimes note that when you are a child, houses seem like nearly permanent objects, like the Egyptian pyramids. Then when you become a homeowner, it comes as a shock to discover that your house is instead a bunch of systems–roofing, windows, heating/air conditioning, water, electrical, large appliances, carpets, siding, painting–that are continually wearing out and breaking down. Across the country, many colleges and universities have been tempted to take a parallel approach to campus buildings: build them as if they were permanent and unchanging, and then be astonished at the concept of maintenance.

Scott Carlson provides a readable overview of the issues in “The Backlog that Could Threaten Higher Ed’s Viability: A Big Bill for Deferred Maintenance is Coming Due” (Chronicle of Higher Education, March 31, 2023). Carlson writes:

Meanwhile, bricks, steel, concrete, and mortar follow the laws of entropy. As a rule, buildings have two critical stages in their lifetimes: At 25 years, a building needs significant updates and renovations; at 50, a major overhaul of its structure and systems. In recent decades, colleges went through two peaks of construction, one in the early 1970s and another in the late ‘90s and early 2000s. Do the math: Two building life cycles will come due in the 2020s.

Lander Medlin, the president and chief executive of APPA, an association of higher-education facilities managers, points out that the construction costs of a building represent only about 25 percent of the total lifetime expenses. Recurring annual costs, like utilities, everyday maintenance, and operations, represent another 35 to 40 percent. The rest is periodic costs in the lifecycle of essential building systems: replacing the roof after 50 years, updating the heating and cooling system after 20, the plumbing and wiring, the building’s skin, and more.

Carlson cites a number of examples: for example, the major state university branch in my own metro area, the University of Minnesota-Twin Cities campus, “has a 10-year renewal need of $4.2 billion, with more than seven-million-gross square feet of space in poor or critical condition.” It is not an exceptional case.

Moreover, when money is tight, postponing some deferred maintenance often feels easier than the other options. But the number of college and university students has been declining for a decade now, and the combination of US demographic trends combined with pandemic and political factors that have made the US a less attractive choice for international students, the decline seems likely to fall. For a lot of what faculty members do, including the rise in online classes, work-from-home is a very plausible option.

Thus, the supply of space at institutions of higher education is to some extent already determined by the decisions of the past, and some major categories of demand for the use of that space have been in decline. At some places, it’s not just a matter of deferred maintenance for existing space, but of an overload of space. If you walk around a college campus during the standard workweek, you will often see a substantial office and classroom spaces not being used. At a lot of places, this underuse is especially apparent first thing in the morning, as well as Monday morning and Friday afternoon, when students and faculty would prefer not to be in class.

These issues have been around for awhile. Ronald G. Ehrenberg, an economist who ended up doing a stint as an administrator at Cornell, described some of the issues in a 1999 article: “Adam Smith Goes to College: An Economist Becomes an Academic Administrator” (Journal of Economic Perspectives, Winter 1999). With regard to academic buildings, he wrote:

[O]ur trustees have long been aware that new buildings add to the operating and maintenance cost of the university. A rough estimate is that if the building was expected to have a total project cost of a given amount, it would take an equivalent endowment to provide the funds for utilities, custodial services, and routine and planned maintenance over the useful life of the building. This estimate derives from these costs averaging roughly 4 percent of the project costs and 4 percent is what Cornell ‘‘targets’’ as the annual payout, after investment expenses, on its endowment funds. …

Cornell’s trustees have long required that a plan for meeting operating and maintenance costs be present before construction of a building can begin. Realistically, however, once a major donor has committed to funding half the cost of a building and it has been publicly announced that the building will be named after that donor, the idea that construction on the building would be held up because an endowment for maintenance had not been raised is a non sequitur. Furthermore, our ability to raise the additional construction costs, let alone the endowment for operations and maintenance, was somewhat uncertain and based upon forecasts of our development staff. So, while the university hoped that funds to endow a
maintenance fund for the building will be raised, we instead planned to pay for the needed operating and maintenance funds that will not come out of indirect cost recoveries from our annual operating budgets.

Inevitably then, this new building will compete for funds with faculty positions, graduate student support and faculty salaries. The very same faculty members who vehemently argued that the institution needed the new facilities to remain competitive in the physical sciences and engineering are likely to turn around and chastise the administration for spending too much on buildings and not enough on faculty salaries, new faculty positions, and graduate student support. … Many faculty members understand the tradeoff between buildings and other costs, but apparently only after their unit’s new building is finished.

Raising money for a new building at a college or university can be difficult, but being able to put the donor’s name on the edifice helps. Maybe with some creativity, donors could put their name on the renovation of a building: The Smith Renovation (Re-Imagining? Resurrection?) of good old Jones Hall. Or in some cases, the right answer will be for the college or university to rethink and shrink its use of physical space, and the best answer will be the Smith Quadrangle (or playing field, or garden) which will be sitting in the space where good old Jones Hall used to be.

Credit Suisse was founded in 1856, and then shut down earlier this month by Swiss bank regulators, who forced the sale of the firm to UBS. Thus, there is some irony and even poignancy in looking at the just published 2023 yearbook of the Credit Suisse Research Institute, titled “Credit Suisse Global Investment Returns: Leading perspectives to navigate the future,” written by Elroy Dimson, Paul Marsh, Mike Staunton. A summary edition of the report is freely available online.

Each year, a main emphasis of the report is on long-term returns going back to about 1900. Here’s a graph showing nominal and inflation-adjusted returns for US stocks, bonds and “bills” (short-term government debt). Yes, investing $1 in a diversified portfolio of US stocks back in 1900 and reinvesting all dividends since then would have led to a real gain by a factor of more than 2,000 since then. (Notice that the vertical axis is logarthmic, rising by factors of 10.)

In addition, this long-term perspective–using annual data–puts some prominent events into perspective. The authors write:

The chart shows that US equities totally dominated bonds and bills. There were severe setbacks of course, most notably during World War I; the Wall Street Crash and its aftermath, including the Great Depression; the OPEC oil shock of the 1970s after the 1973 October War in the Middle East; and four bear markets so far during the 21st century. Each shock was severe at the time. At the depths of the Wall Street Crash, US equities had fallen by 80% in real terms. Many investors were ruined, especially those who bought stocks with borrowed money. The crash lived on in the memories of investors for at least a generation, and many subsequently chose to shun equities.

The top two panels of Figure 10 set the Wall Street Crash in its long-run context by showing that equities eventually recovered and gained new highs. Other dramatic episodes, such as the October 1987 crash, hardly register; the COVID-19 crisis does not register at all since the plot is of annual data, and the market recovered and hit new highs by year-end; the bursting of the technology bubble in 2000, the Global Financial Crisis of 2007–09 and the 2022 bear market show on the chart but are barely perceptible. The chart sets the bear markets of the past in perspective. Events that were traumatic at the time now just appear as setbacks within a longer-term secular rise.

But it’s also worth remembering that the US investment experience is extraordinary. As the authors put it, it would be “unwise for investors around the world to base future projections solely on US evidence.” Here’s a figure with international comparisons. Although two tiny stock markets, South Africa (ZAF) and Australia (AUS), have outperformed the US stock market over time, the US market has dominated world returns. For the record, most of the abbreviation here are for countries, but WLD is the index for the entire world, WXU is the world leaving out the US, EUR is Europe, DEV is developed markets, and EMG is emerging markets.

The extraordinary growth in the US stock market since 1900 means that, when it comes to global equity markets, the US stock markets dominate the world. Here are the sizes of stock markets around the world in 1900 and in 2022.

The American public is in favor of less total government spending, but it would prefer to avoid reducing spending in almost every category. Here are two figures showing results from an AP/NORC poll (March 29, 2023).

The first figure shows results for whether people believe the government is overspending as a whole. Overall, 60% of the public thinks government spends “too much” and 16% says “too little,” with 22% in the “about right” category.

But when you ask about specific categories, the public wants to see expanded spending in most areas. The only area which has a clear majority for spending “too much” is assistance to other countries. Other surveys have typically found that the public vastly overestimates the amount spent in this category, usually thinking that it covers about 25-30% of total federal spending–when it actually is only about 1% of all federal spending.

The conflict between these results–which are from the same survey!–suggests that the public wants politicians who advocate both for less total spending and also more spending in many individual categories. On this subject, in other words, the public is wide-open to embracing demagoguery.

Many of us comment on China by reading the second-hand literature published in English. Yasheng Huang is Professor of Global Economics and Management at MIT’s Sloan Business School, who came from China to the United States in the 1980s and has thus had the freedom and a front-row seat to study China’s evolution since then. Tyler Cowen has one of his “Conversations with Tyler” with Huang “on the development of the Chinese state” (March 8, 2023, audio and transcript available). Much of the discussion is about how the tradition of China’s civil service examinations evolved over the centuries, and the effects on literacy, creativity, and commerce. Here, I’ll focus on some of Huang’s comments more related to current events:

What is a big misconception about China’s economy?

[O]ne of them is that they look at the Chinese R&D spending, and they look at, for example, some of the impressive technological progress the country has made, and then they drew the conclusion that the Chinese economy is driven by productivity and innovations. In fact, studies show that the total productivity contributions to the GDP have been declining in the last decade and even more. As China has begun to invest more in R&D, the economic contributions coming from technology, coming from productivity have been actually declining. In the economic sense, it’s not a productivity-driven economy. It is an overwhelmingly investment-driven economy.

I think that’s one of the biggest misunderstandings of Chinese economy. It entails implications about the future prospects of the country, whether or not you can sustain this level of economic growth purely on the basis of massive investments.

Huang also offers some thoughts on the nature of political protest in China and how the Communist Party shapes the form of protests in a way that helps the Party hold on to power.

There’s a difference between a civil society consisting of isolated individual actions and a civil society that consists of organized activities that have a program, that have financial support, that have the capability to operate independently. By the second criterion, China has none of that.

If you look at the recent protests against Zero-COVID controls, let’s keep one number in perspective. By various estimates, in 2022 there were probably 400 million people under some sort of long-term quarantine. And let me just concretize that word quarantine. That means you’re essentially locked up in your home, sometimes for weeks, and in some cases, for two months. That’s the level of the suffering, and sometimes you can’t get food. Sometimes you cannot get patients into the emergency room because the hospitals also shut down, refused to take in patients who are tested positive or who cannot show a negative test on COVID. Some people have died. There are suicides, there are fires, and all these collateral damages from the Zero-COVID control.

Relative to that, China experienced a wave of protests — by one estimate, in 17 cities. I don’t really have a good idea how many people were involved, but we are not talking about millions of people. We’re talking about maybe 10,000 people, or tens of thousands of people.

Contrast that with Iran. In the case of Iran, one woman died in the hands of the moral police. There were other grievances, but that was the trigger. The protests are still going on. Millions of the people took to the street. … If you look at the color revolution in Tunisia, it started with a peddler whose assets were confiscated by the government official, and then he committed suicide. That sparked the color revolution.

Those kinds of brutalities toward small peddlers happen almost on a daily basis in China. It’s very important to specify, relative to the grievances and the level of the misery . . . We’re not talking about large-scale social movements here. These are individual actions. …

If you look at what the CCP has been doing, it is actually quite clever. It’s not the case that they don’t take input from the society. They create portals, they create websites, and they create phone numbers for the citizens to call in. They also do surveys. What they want to do is, they want to solicit opinions and information from the citizens without creating conditions for the citizens to get organized. If you think about all these opinions expressed to the government through the government control portals, you are doing it as an individual. You’re not doing it as a member of a larger group. The CCP has no problem with that, and sometimes those opinions can be quite negative. The CCP has no problem with that. …

Yes, China has had a lot of protests, but those protests tend to happen in rural areas, in less urban settings, in isolated situations, and on single issues. Usually, in the 1990s, it was about the land that the government took away. And then it was about the salary, that employers were late in paying my salary, so there were protests about that — very single-issue, very focused.

This time around, you’re talking about people demanding the CCP to step down, demanding Xi Jinping to step down. That’s just something entirely different from what we saw before. …

The reason for that is, I think — although it’s a little bit difficult to generalize because we don’t really have many data points — one reason is the charisma power of individual leaders, Mao and Xiaoping. These were founding fathers of the PRC, of the CCP, and they had the prestige and — using Max Weber’s term — charisma, that they could do whatever they wanted while being able to contain the spillover effects of their mistakes. The big uncertain issue now is whether Xi Jinping has that kind of charisma to contain future spillover effects of succession failure.

This is a remarkable statistic: Since 1976, there have been six leaders of the CCP. Of these six leaders, five of them were managed either by Mao or by Deng Xiaoping. Essentially, the vast majority of the successions were handled by these two giants who had oversized charisma, oversized prestige, and unshakeable political capital.

Now we have one leader who doesn’t really have that. He relies mostly on formal power, and that’s why he has accumulated so many titles, whereas he’s making similar succession errors as the previous two leaders. Obviously, we don’t know — because he hasn’t chosen a successor — we don’t really know what will happen if he chooses a successor. But my bet is that the ability to contain the spillover effect is going to be less, rather than more, down the road, because Xi Jinping does not match, even in a remote sense, the charisma and the prestige of Mao Zedong and Deng Xiaoping. There’s no match there.

I always gain some additional useful perspective from reading Huang’s work. Back in 2012, he wrote  “How Did China Take Off?” for the Journal of Economic Perspectives, where I work as Managing Editor. He made a persuasive case that most of us tend to see China’s economic takeoff as a matter of foreign trade and exports. However, he argues that the early stages of China’s burst of economic growth, through the 1980s and 1990s, were actually led by rural industry in the form of “township and village enterprises” that were led by private entrepreneurs in the context of a high degree of financial liberalization. At this time, China’s economic growth was driven primarily by a rise in China’s domestic consumption, not by export sales. However, in the early to mid-1990s, Huang argues, China’s leadership switched from a rural to an urban focus, took over the financial sector, and essentially drove the rural-based township and village enterprises out of business in favor of expanding state-financed and -controlled urban enterprises.

Sometimes “industrial policy” is defined very broadly, as when people say: “Every country has an industrial policy–even not having an industrial policy is a kind of industrial policy.” But in a more specific meaning of the term, “industrial policy” doesn’t include, say, support of K-12 education or university research and development or a well-regulated banking system. Instead, it refers to when government targets the growth of specific industries with subsidies or trade protection, in the belief that these industries will repay the near-term government support by leading to stronger growth that benefits the broader economy in the future.

In the more limited use of the term, the United States is embarking on a major experiment in industrial policy. The Creating Helpful Incentives to Produce Semiconductors (CHIPS) and Science Act focuses $280 billion over the next decade on building a domestic semiconductor manufacturing industry. The Inflation Reduction Act (IRA) commits $579 billion over the next 10 yearswith a heavy focus on promotion of noncarbon methods of producing electricity from non-carbon sources (mainly solar and wind) and supporting energy users in switching to the use of such energy (including subsidies for electric cars). The Infrastructure Investment and Jobs Act (IIJA) commits $1.2 trillion over the next decade to standard infrastructure like roads, bridges, rail, and transit, which don’t fit into a narrow definition of infrastructure, but also includes less-discussed infrastructure like broadband, electrical power, and support for non-gasoline infrastructure for cars.

In an article from Deloitte Insights, William D. Eggers, John O’Leary and Kevin Pollari discuss “Executing on the $2 trillion investment to boost American competitiveness” (March 16, 2023). They emphasize that the new laws involve large amounts of money, with many different funding streams, all with different compliance standards, that need to be run and coordinated across a large number of federal agencies. In addition, the chances of success will often depend on interactions between these programs, not on the sum of the individual programs.

It stands to reason that industrial policy isn’t simple. If industrial policy was as simple as tossing a log on the fire and getting the desired heat, then every nation would be able to do it. Having a boom in manufacturing jobs, or union jobs, or strong industries related to semiconductors, green energy jobs, steel, or cars, would just be a matter of passing the legislation. But it’s obviously not that simple and easy for industrial policy to work, not in the United States and not in other countries either.

There are many examples of these complexities and constraints: I’ll just give a couple of examples here. The Deloitte authors write about the infrastructure act:

Under IIJA alone, more than 45 federal bureaus and 16 federal agencies and commissions are allocated funding for 369 new and existing programs. Grants fund more than 200 programs and represent 78% of the total funding. … These three new laws establish more than 160 entirely new programs. IIJA alone has created 129 new programs with more than $226 billion in funding. Seven existing programs worth $275 billion have been substantially revised or expanded. In the IRA, out of the total $228 billion appropriated across 18 federal agencies, more than $80 billion was appropriated for 34 new programs.

Thus, the basic workability of the new laws depends an ability to administer the money across these bureaus and agencies and commissions and grants–ranging across federal, state, and local government actors as well as universities and the private sector–and to do so in a way that actually boosts competitiveness and isn’t just a money trough for the politically connected.

As another example, “The CHIPS and Science Act, for example, has earmarked $10 billion for the Department of Commerce to create 20 regional technology hubs across the United States  in partnership with universities and private businesses.” I’m a supporter of funding for regional technology hubs, but I’m not fool enough to think that organizing them is easy.

It’s not just bureaucratic constraints, either. The Deloitte authors note an estimate that the “the country will need one million additional electricians for the clean-energy transition.” Maybe that estimate is overstated? Maybe we only need several hundred thousand more electricians. But all the plans for installing new public and home charging stations, as well as building new electricity charging facilities and transmission lines, are going to fall flat if there aren’t plenty of electricians to do the work. In turn, the electricians won’t be able to do their work without getting necessary permits, which in turn will have to pass zoning, land-use, and environmental regulations and lawsuits.

Moreover, all of this needs to happen in a way that is accountable and, if not fraud-proof, at least fraud-resistant. The authors call this the “thieving squirrel problem”:

The “thieving squirrel” problem: You put seeds into the birdfeeder, but clever, agile, and highly motivated squirrels manage to eat a big share. The only answer is a birdfeeder designed to limit access and frustrate raiders. With funding levels this large, the problem of waste, fraud, and abuse is real. Especially for agencies that are disbursing sizable grants for the first time, controls baked in up front will be critical. Governments need to ensure proper compliance, reporting, and transparency—or risk rewarding the squirrels and undermining overall trust in the process.

Around the world and over time, “industrial policy” narrowly understood doesn’t have a great reputation. There are a few successes, and a distressingly large pile of failures. It’s worth remember that the resources committed to industrial policy–including money, capital, and human talent–could have been spent on other uses. For example, a big chunk of the $200 billion per year or so being spent on these programs could have gone into supporting pregnant mothers and infant children, or rebuilding public schools, or training a few hundred thousand electricians. Perhaps setting up a steady increase in taxes related to pollution and carbon emissions over time, and then letting the incentive effects of such taxes percolate through the economy, would be more effective–but spending more money is always a more popular way of seeking change.

It’s impossible to prove that industrial policy can’t ever work, for the same reasons that it’s often very difficult to prove a negative. Thus, even if this particular US industrial policy experiment fails, I expect that its supporters will just explain that with more money or commitment or vision or energy or an improved structure, it could easily have succeeded. So this post is just laying down a marker: When these pieces of industrial policy legislation were passed, the comments of supporters often suggested that this iteration of industrial policy was nearly as simple as tossing a log on the fire–virtually certain to succeed. If the programs are only mild success, or a considerable failure, the supporters should have to eat their words.

I hope the supporters are correct. I would prefer to see public money well-spent. In a few years, we can evaluate the results. But the administrative, political and economic conditions for success of industrial policy are a difficult set of obstacles to cross. The Deloitte author do not predict success or failure, but they do say: “Once a law is passed, there is a temptation to assume that desired results will follow. But much will depend on how government actually executes its strategy.”

For those not familiar with the Economic Report of the President, it is published each year by the White House Council of Economic Advisers. In turn, the CEA is led by academics, who are appointed by the president but typically plan to head back to their ivory towers in a few years. Thus, they are clearly a partisan and pro-administration group, but they also have reason to care about their own reputation for expertise and for relatively dispassionate analysis. This tension plays itself out each year in the report.

The parts of the ERP each year that offer a partisan defense of the president aren’t that interesting to me, no matter who the president is, because of how one-sided and perfunctory such defenses tend to be. Of course, if you are looking for talking points to support the economic policies of the Biden administration or if you want to take target practice against those policies, you may be attracted to those parts of the report. But each year, the report also includes facts and nuggets about the US economy and its trends and patterns that have emerged from discussion from thoughtful academics, and some of these can be worth passing on. Here’s one from the first chapter of the 2023 Economic Report of the President, showing the long-term average for US economic growth going back to 1790.

The figure breaks down overall economic growth into three chunks: growth of population (which means more workers and consumers), changes in labor force participation (the share of the adult labor force that either has a job or is looking for a job), and output per worker, which changes according to improvements in human capital (education and skills), physical capital available to workers, and “total factor productivity,” which is econo-speak for productivity improvements. Here are a few reaction to the figure:

1) The slowdown in overall economic growth in in the 2000s is readily apparent. But in a broad historical perspective, it’s also apparent is that a lot of this slowdown is due to a slower rate of population growth (shorter dark blue bars) and also a decline in labor force participation due in part to the aging and retirement of the “baby boom” generation born in the 15 years or so after the end of World War II (the light blue bars in negative territory on the graph). At least in the last decade, output per worker hasn’t been rising at an especially slow rate.

2) For political scientists and those interested in global politics, the sheer size of the US economy matters–the total height of these bars. But for economists, what matters more is a gradually rising standard of living for the average person, which is roughly captured over time by the gain in output-per-worker.

3) The future of US economic growth isn’t likely to come from population growth; instead, it will need to be generated by higher output per worker. The US economy had a mass expansion into high school education from about 1910 to 1940, and a mass expansion of higher education after World War II, but no mass expansions of education since then. US capital investment seems OK, but a lot of one’s thinking around that issue revolves around placing an economic value on information technology and internet access, which isn’t easy to do. Productivity gains are calculated as the residual of what is left over, unexplained, by forces like labor force growth, human capital and physical capital–and by that measure, the US economy isn’t doing especially well since the early 2000s.

4) The 1870s appear on the graph as a time of rapid growth. I confess that I don’t understand this. The report emphasizes that the 1870s are a time of expanding the railroad and the telegraph, along with new inventions. However, the standard dating of US business cycles suggests that the US economy was in the “Long Depression” from October 1873 to March 1879. Maybe it was just a really extraordinary economic boom in the early 1870s in the aftermath of the Civil War?

5) From the perspective of decade averages, the Great Depression of the 1930s looks less “great,” in the sense that overall growth during the decade of the 1930s was similar to that of the 1910s and 1920s. In part, this is probably because we tend to understate the multiple deep recessions of these earlier decades, including three recessions in the 1910s and another three in the 1920s, as well as understating how the US economy recovered from the Great Depression in the later part of the 1930s (albeit with a recession in 1937-38). It may seem odd that labor force participation doesn’t fall noticeably in the 1930s, given the ultra-high unemployment rates of the time. However, the unemployed are counted as “participating” in the labor market–to be outside the labor force participation rate, you need to be not looking for work (say, retired or working in the home by preference).

6) In the 1970s and 1980s, you can see that a noticeable chunk of overall economic growth was the rise labor force participation, mainly due to growing participation of women in the (paid) labor force.

There’s a remarkable economic story behind every bar and line in this graph.

Each year, the Swiss Re Institute has been publishing an annual report on the natural catastrophes of the previous year, of particular interest to specialists, and some long-run trendlines, which are more interesting to me. This year’s report is “Natural catastrophes
and inflation in 2022: a perfect storm” (Sigma, 2023, No. 1).

Here’s the number of catastrophes around the world. in the last half-century. Natural catastrophes include “floods, storms, earthquakes, droughts/forest fires/heat waves, cold waves/frost, hail, tsunamis, and other natural catastrophes.” Man-made catastrophes do not include war, but instead are divided into the categories of “major fires and explosions, aviation and space disasters, shipping disasters, rail disasters, mining accidents, collapse of buildings/bridges, and miscellaneous (including terrorism).”

It’s wise to interpret these numbers with care. After all, the global population has more than doubled since 1970, which more-or-less fits the rise up to the early 2000s, although it doesn’t explain the spike in the mid-2000s or the more recent decline (which precedes the pandemic). Also, if a natural event that would be a catastrophe if it happens in a heavily populated area occurs instead in a lightly populated area, does it count as a catastrophe of the same scale? The world’s apparatus for discovering and reporting natural catastrophes was clearly less developed a half-century ago. That said, it appears that man-made disasters have been declining in the last decade or so, while natural catastrophes have been trending up over time.

What about the costs? Let’s look first at lives lost. Notice that the vertical scale is logarithmic, not arithmetic (that is, it rises by factors of ten). The report notes: “Worldwide, 35 157 people are believed to have died or gone missing in disaster events in 2022. Natural catastrophes claimed over 32 600 victims, and man-made disasters over 2500.”

Here, the general pattern seems to be that deaths from man-made disasters are both an order of magnitude lower than natural disasters, and also declining. There doesn’t seem to be any particular trend to deaths from natural disasters, just a pattern of big spikes when an especially awful disaster occurs somewhere.

Finally, here’s an estimate of total financial costs of these disasters, and because Swiss Re is a reinsurance company, the share of those costs covered by insurance. These costs are adjusted for inflation. The sharp rise is because of economic growth and rising property values: for example, a hurricane hitting Florida now will have a higher financial cost than the same hurricane hitting in 1970.

It’s also worth remembering that financial costs will depend on local prices, such that financial costs will be higher in high-income, high-price countries. The report notes that the gap between insured financial losses and total financial losses seems to be rising: it was 53% in 2022, down from 59% over the average of the last ten years.

David A. Price interviews Annamaria Lusardi “on financial literacy, seniors versus scammers, and learning from the mistakes of NFL players” (Econ Focus: Federal Reserve Bank of Richmond, First Quarter 2023, pp. 24-28). Lusardi notes:

[W]e have witnessed a highly important change in the United States and around the world, which is that more and more, we have shifted the responsibility to save for retirement from the employer to workers. I am talking about the shift from defined benefit pensions to defined contribution pensions, such as individual retirement accounts and 401(k) plans. In the past, it was the employer who had to manage the pension of the employees; the wealth was managed by a CFO or by other financial experts. Now we ask individuals to make these decisions about their wealth. So even more than when I was an assistant professor, there’s the question of whether people have the skill to manage their money.

Lusardi and Olivia Mitchell have designed a 28-question test to measure financial literacy, which has become a widely used research tool. For a flavor of the kinds of questions, consider what they call the “Big Three.” In their early work, an advantage of having just three questions is that it was practical to add three questions to piggyback on preexisting surveys.

THE “BIG THREE” FINANCIAL LITERACY SURVEY QUESTIONS

1. Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years, how much do you think you would have in the account if you left the money to grow?

• More than $102
• Exactly $102
• Less than $102
• Do not know/Refuse to answer

2.Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per year. After 1 year, how much would you be able to buy with the money in this account?

• More than today
• Exactly the same
• Less than today
• Do not know/Refuse to answer

3. Please tell me whether this statement is true or false. “Buying a single company’s stock usually provides a safer return than a stock mutual fund.”

• True
• False
• Do not know/Refuse to answer

NOTE: Correct answers are (1) “More than $102,” (2) “Less than today,” and (3) False.
SOURCE: Annamaria Lusardi and Olivia S. Mitchell

The ongoing research in this area suggests both that financial literacy is low.

Together with a team at the World Bank, I eventually designed questions similar to the big three that were applied to a sample of more than 140 countries. I would say there are several interesting findings. One is that even though the U.S. is the country with the most advanced financial markets, it actually doesn’t score very high in terms of financial literacy. And this has been true in other surveys, as well. The second thing is that overall financial literacy is not high in other countries, either. Overall, the level of financial literacy globally is really low; only one-third of people around the world are financially literate. …

[W]hat we did recently — and it took us a good many years to do this project — is a meta-analysis of financial education programs. … Because the literature was so extensive, we then decided to concentrate on the most rigorous evaluations. So we looked at only the randomized control trials. … So you expose a group to financial education; you don’t expose the other, similar group; and then you compare what happened to the group you treated. What we found, looking at the evidence in as many as 33 countries, is that financial education works and works well — meaning it does translate into higher knowledge and also better behavior in savings and managing credit and in other areas, including insurance and money transfers. And we also found that it is cost effective. This is due to the fact that many educational programs do not cost very much.

This work has implications reaching in a number of directions. Prominent examples include professional athletes who, even in a relatively short career, might earn as much as the average college-educated person will earn in a lifetime. But these athletes are young adults, their financial literacy is no greater than average, and they are easy targets for financial “advisers” and “planners” who charge high fees for high-risk options. A less prominent but much larger group are the elderly near retirement age, at a stage when they probably have the highest level of assets for their lifetime, but again, their financial literacy is no greater than average, and at they can often find themselves to be targets for high-fee and high-risk “advisers” and “planners.” Indeed, Lusardi’s work has found that the current elderly are often taking more debt into their retirement than previous generations.