Month: November 2024

I have been the Managing Editor of the Journal of Economic Perspectives since the first issue in Summer 1987. The JEP is published by the American Economic Association, which decided back in 2011–to my delight–that the journal would be freely available online, from the current issue all the way back to the first issue. You can download individual articles or entire issues, and it is available in various e-reader formats, too. Here, I’ll start with the Table of Contents for the just-released Fall 2024 issue, which in the Taylor household is known as issue #150. Below that are abstracts and direct links for all of the papers. I plan to blog more specifically about some of the papers in the few weeks, as well.

_____

Symposium on Industrial Policy

“Export-Led Industrial Policy for Developing Countries: Is There a Way to Pick Winners?” by Tristan Reed

     Industrial policy prioritizes growth in specific sectors. Yet there is little agreement about how to target sectors in practice, and many argue that governments cannot pick winners. This essay observes that governments can and do identify tradable sectors where public inputs accelerate growth and generate economic benefits. These strategic sectors are: (1) those that are relatively more productive, and (2) those that are relatively less productive but require technology like the country’s existing technology and have rapidly growing markets and limited international competition. Since developing countries are productive in fewer sectors and have less technology, targeting can be more valuable for them. Export promotion agencies are institutions that have demonstrated effectiveness in coordinating public inputs to grow these sectors. Compared to protectionism, this alternative approach to ‘industrial policy’ is cheaper, less susceptible to capture by unproductive firms, and permissible under the rules of international trade agreements. Many countries’ development strategies adopt this approach.

“The Political Economy of Industrial Policy,” by Réka Juhász and Nathan Lane

We examine the ways in which political realities shape industrial policy through the lens of modern political economy. We consider two broad “governance constraints”: (1) the political forces that shape how industrial policy is chosen and (2) the ways in which state capacity affects implementation. The framework of modern political economy suggests that government failure is not a necessary feature of industrial policy; rather, it is more likely to fail when countries pursue industrial policies beyond their governance capacity constraints. As such, our political economy of industrial policy is not fatalist. Instead, it enables policymakers to constructively confront challenges.

“Industrial Policy: Lessons from Shipbuilding,” by Panle Jia Barwick, Myrto Kalouptsidi, and Nahim Bin Zahur

     Industrial policy has been used throughout history in some form or other by most countries. Yet, it remains one of the most contentious issues among policy makers and economists alike. In part, this is because the empirical evidence on whether and how it should be implemented remains slim. Scant data on government subsidies, conflicting theoretical arguments, and the need to account for governments’ short and long-run objectives, render research particularly challenging. In this article, we outline a theory-based empirical methodology that relies on estimating an industry equilibrium model to measure hidden subsidies, assess their welfare consequences for the domestic and global economy, as well as evaluate the effectiveness of different policy designs. We illustrate this approach using the global shipbuilding industry as a prototypical example of an industry targeted by industrial policy, especially in periods of heavy industrialization. Just in the past century, Europe, followed by Japan, then South Korea, and more recently China, developed national shipbuilding programs to propel their firms to global leaders. Success has been mixed across programs, certainly by welfare metrics, and sometimes even by growth metrics. We use our methodology on China to dissect the impact of such programs, what made them more or less successful, and how we can justify why governments have chosen shipbuilding as a target.

“Semiconductors and Modern Industrial Policy,” by Chad P. Bown and Dan Wang

     Semiconductors have emerged as a headline in the resurgence of modern industrial policy. This paper explores the political economic history of the sector, the changing nature of the semiconductor supply chain, and the new sources of concern that have motivated the most recent turn to government intervention. It also explores details of that turn to industrial policy by the United States, China, Japan, Europe, South Korea, and Taiwan. Modern industrial policy for semiconductors has included not only subsidies for manufacturing, but also new import tariffs, export controls, foreign investment screening, and antitrust actions.

“Alexander Hamilton’s Report on Manufactures and Industrial Policy,” by Richard Sylla

     Hamilton’s 1791 state paper on manufactures is a forward-looking argument for US industrialization supported by public policies designed to encourage it. Conventional wisdom circa 1790, along with static considerations of comparative advantage indicated that the United States should stick to farming, export its agricultural surpluses, and import European manufactures. Mercantilist trade policies of the major European empires, however, were barriers to US exports. Hamilton therefore contended that US manufacturing using the latest machine technologies would alleviate the effects of European trade restrictions by creating domestic demand for agricultural surpluses. His report specifies industries worthy of support, and policy measures to encourage their development. During the century that followed, US governments adopted nearly all of Hamilton’s recommendations. These measures contributed to an average annual rate of growth of industrial output of 5 percent during that century, helping the United States to become the world’s leading manufacturing nation.

Symposium on Behavioral Incentive Compatability

“Evaluating Behavioral Incentive Compatibility: Insights from Experiments,” by David Danz, Lise Vesterlund, and Alistair J. Wilson

     Incentive compatibility is core to mechanism design. The success of auctions, matching algorithms, and voting systems all hinge on the ability to select incentives that make it in the individual’s interest to reveal their type. But how do we test whether a mechanism that is designed to be incentive compatible is actually so in practice, particularly when faced with boundedly rational agents with nonstandard preferences? We review the many experimental tests that have been designed to assess behavioral incentive compatibility, separating them into two categories: indirect tests that evaluate behavior within the mechanism, and direct tests that assess how participants respond to the mechanism’s incentives. Using belief elicitation as a running example, we show that the most popular elicitations are not behaviorally incentive compatible. In fact, the incentives used under these elicitations discourage rather than encourage truthful revelation.

“Behavioral Incentive Compatibility and Empirically Informed Welfare Analysis: An Introductory Guide,” by Alex Rees-Jones

     A growing body of research conducts welfare analysis that assumes behavioral incentive compatibility—that is, that behavior is governed by pursuit of incentives conditional on modeled imperfections in decision-making. In this article, I present several successful examples of studies that apply this approach and I use them to illustrate guidance for pursuing this type of analysis.

“Designing Simple Mechanisms,” by Shengwu Li

     It matters whether real-world mechanisms are simple. If participants cannot see that a mechanism is incentive-compatible, they may refuse to participate or may behave in ways that undermine the mechanism. There are several ways to formalize what it means for a mechanism to be “simple.” This essay explains three of them, and suggests directions for future research.

Articles

“The Problem of Good Conduct among Financial Advisers,” by Mark Egan, Gregor Matvos, and Amit Seru

     Households in the United States often rely on financial advisers for investment and savings decisions, yet there is a widespread perception that many advisers are dishonest. This distrust is not unwarranted: approximately one in fifteen advisers has a history of serious misconduct, with this rate rising to one in six in certain regions and firms. We explore the economic foundations of the financial advisory industry and demonstrate how heterogeneity in household financial sophistication and conflicts of interest allow poor financial advice to persist. Using data on the universe of financial advisers and the Survey of Consumer Finances, we document who uses financial advisers and the prevalence of misconduct in the industry. Our findings suggest that a lack of financial sophistication is a key friction, making enhanced disclosure a potentially effective policy response. Supporting this, we show through a difference-in-differences approach that “naming and shaming” firms with high misconduct rates was associated with a 10 percent reduction in misconduct.

“Retrospectives: Friedman and Schwartz, Disaggregated,” by Jennifer Burns

       What was the contribution of Anna Schwartz to the landmark book she co-authored with Milton Friedman, A Monetary History of the United States, 1867–1960? A close examination of archival evidence suggests three primary contributions Schwartz made to the work, and to Friedman’s career more generally. The first was meeting the classic challenge of quantitative economic history: going into the field to locate and collect archival data that had been assembled for purposes unrelated to economic research, and deciding how best to use that data. Second, Schwartz had a decades-long role as technical sounding board and shaper of the statistical approach taken in the book. Schwartz’s third and arguably greatest contribution was to transform A Monetary History of the United States into a compelling narrative argument that made an impact far beyond the economics profession. Together, these findings show Schwartz to be a scholar who made significant and lasting contributions to monetary economics, economic history, and the broader field of economics.

“Recommendations for Further Reading,” by Timothy Taylor

To explain the high and rising price of housing, the standard economic intuition is that growth in supply isn’t keeping up with growth in demand. One piece of evidence supporting this intuition is the “vacancy rate”–that is, what share of owner-occupied housing or rental housing is empty?

Here are a couple of figures from the ever-useful FRED website managed by the St. Louis Fed, with the first showing national vacancy rates for owner-occupied housing and the second showing national vacancy rates for rental housing. As you can see, vacancy rates spiked higher during the Great Recession of 2007-09, but now are near historically low levels for the last half-century.

When people say there is a “housing shortage,” what they are often referring to are estimates that if there had been sufficient housing construction in the past to bring the vacancy rate up to historically average levels, then housing would not feel so costly and unaffordable. David Wessel offers a crisp overview of existing estimates in “Where do the estimates of a `housing shortage’ come from?” (Hutchins Center at the Brookings Institution, October 21, 2024).

Estimates of the size of the housing shortage will differ according to various factors: the underlying assumption about a “normal” vacancy rate; whether the calculations are being made at a national-, state-, or census-district level; whether the estimates include only metropolitan areas or also rural areas; and so on. Here’s a set of estimates on the size of the housing shortage from the National Association of Home Builders and others. The first three estimates are based on the “vacancy” method. The last estimate, from a study commissioned by the National Association of Realtors, is based on the fact that about 1.5 million per year home were added to the total housing stock annually from 1968-2000, but only about 1.225 million homes were added to the housing stock each year since then.

The constraints on home-building, whether owner-occupied or rental, typically happen at the state and especially the local level. I won’t try here to delve into the range of proposals in metropolitan areas in the US and around the world for building more housing. But I will note that when vacancy rates are very low, subsidizing home-buyers or renters for their housing costs will only drive up the price. One way or another, making housing affordable needs a supply-side solution.

Every now and then, I hear proposals to fund some program by taxing the wealthy–or even just confiscating wealth above a certain level. For the purposes of this post, I’m not interested in the question of whether this tax would be a good idea. (Shocking disclosure: I don’t think it’s a good idea.) I just want to know how money is is out there at the top of the US wealth distribution. Here’s a figure from the ever-useful FRED website maintained by the Federal Reserve Bank of St. Louis.

The top line shows total net worth for the top 1% of the wealth distribution, which totals about $44 trillion. The blue line focuses on the top 0.1% of the wealth distribution, which totals about $20 trillion. For perspective, the US has something over 120 million households. Thus, the top 1% is 1.2 million households, which have average wealth of $36 million. The top 0.1% is 120,000 households, which have average net worth of $166 million. There are about 800 US households with more than a billion in net worth, which is something less than .001% of the US population, who hold a combined $5.7 trillion in net worth.

Obviously, the total wealth held by the very wealthy adds up a really large chunk of change. Just for the sake of illustration, say that we could scoop up all $44 trillion in wealth of the top 1%, or all $20 trillion of the wealth of the top 1%, and go on a spree.

(Of course, even proposing such a step is wildly impractical. It’s worth emphasizing that taxing wealth is a tricky business, because the wealth takes the form of ownership of corporate stock or companies, or in some cases land, real estate, and natural resources. Thus, somehow requiring that trillions in wealth should be paid to the government would require that these assets be sold–but if wealth is being taxed at very high rates, it’s not clear who would buy them. There’s a reason why countries that have taxes wealth typically do so at rates of 1% per year, or less, and there’s a reason why most of the European countries that experimented with wealth taxes for a time have repealed them, as discussed here and here).

Remember, we can only do this once: when the wealth has been taken, it’s not there to take again, and the incentives to build up such wealth (in a form that could be taxed) would be greatly reduced. But to put the amount in perspective, here are some potential uses for spending the wealth of the top top 0.1%).

We could take $20 trillion and give all 330 million Americans a check for $60,000. Again, we could do this once.

We could take $20 trillion and pay of about half of the accumulated US federal debt.

We could take $20 trillion and pay off most of the expected shortfall for Social Security over the next 75 years.

Of course, one can add a number of other programs and priorities here, from education to the electricity grid and everything else. My point is that even the combined wealth of the very wealthy is not an infinite amount. The US GDP in 2024 will be about $28 trillion, so $20 trillion is about 8-9 months of US economic output. The federal budget for 2024 is nearly $7 trillion, so even $20 trillion is about three years of federal spending. Of course, if the $20 trillion in wealth was taxed at 1% per year, it would be about $200 billion per year–a real chunk of money, but a little more than the US budget deficit for any given month.

Just to be clear, I’m not arguing here against (or for) having those with very high wealth (or very high income) pay more in taxes. I’m pointing out that in the context of the broader US economy, the potential revenue available from taxing only billionaires is not huge, and even the revenue from taxing hundred-millionaires has its limits. It’s not a bottomless purse that can be tossed, over and over, at every political want.

Afterthought: There is an arithmetically illiterate comment, which sometimes makes the social media rounds, that because Jeff Bezos (or Elon Musk or Bill Gates) has a net worth of say, $100 billion and there are 7.5 billion people in the world, then that rich person could just give everyone in the world $1 billion, and still have $92.5 billion left over. I will leave it to the reader to locate the error in this calculation.

Government attempts to assist household with low incomes face an inevitable practical problem. As income for a household rises, it will be necessary to phase out the government assistance. But what happens if–at least over a certain range of incomes–a previously low-income household that increases its earnings discovers that its government benefits are being decreased by the same amount? In effect, this household faces an effective tax rate of 100%, because any increase in earnings from a job is being 100% offset by a decline in the value of government assistance.

Maybe this scenario sounds hypothetical and extreme, but Elias Ilin and Alvaro Sanchez of the Federal Reserve Bank of Atlanta point out that it holds true for low-income households in Washington, DC. (“Mitigating Benefits Cliffs for Low-Income Families: District of Columbia Career Mobility Action Plan as a Case Study,” NO. 23–1, September 2023, Community and Economic Development Discussion Paper).

This table looks at the situation of a single parent with two children. If the household earns $11,000, it is eligible for the benefits shown in the first column. If the household earns $65,000, then its eligibility for most of these benefits is phased out, as shown in the second column, and the taxes owed by the family rise as well. For those who don’t live and breathe these acronyms: TANF is Temporary Assistance for Needy Families (commonly called “welfare”), EITC is Earned Income Tax Credit, CTC is Child Tax Credit, SNAP is Supplemental Nutrition Assistance Program (often called “food stamps”), WIC is Special Supplemental Nutrition Program for Women, Infants, and Children, FRSP is Family Re-Housing Stabilization Program,  LIHEAP is Low Income Home Energy Assistance Program,  CCDF is Child Care and Development Fund, CHIP is Children’s Health Insurance Program, and ACA Premium Subsidy refers to the Affordable Care Act passed in 2010.

In passing, it seems appropriate to note that the administrative burden that this group of programs places on low-income households is quite real. Of course, as income levels or life circumstances change, support from these programs shifts as well.

But the main point here is that as household earnings for this D.C. household rises from $11,000 to $65,000, the decline in benefits and rise in taxes almost completely offsets the higher earnings. As the authors write:

[B]etween $11,000 and $65,000 our hypothetical family experiences no overall financial gain from an increase in earnings. … [A]n increase in income from $11,000 to $65,000 results in a complete or partial loss of most of the public assistance programs and tax credits. Paired with an increase in tax liability, these losses fully offset income gains. … We observe that at certain levels of employment income within the $11,000 to $65,000 range the family’s net resources dip. It means that the combined loss of public assistance programs outweighs the gain in income, meaning the family faces benefits cliffs. The first dip occurs at $22,000 when the family loses access to SNAP. A second benefits cliff occurs at $27,000, where the family loses TANF. That is followed by several small benefits cliffs that occur due to the loss of school meals, WIC, federal and state EITCs, Medicaid for Adults, and Medicaid for Children/CHIP. Finally, at $61,000 the last and the largest benefits cliff occurs, which entails a loss of the CCDF childcare subsidy.

The authors call this a “benefit cliff.” I have sometimes called it a “poverty trap” (for example, here and here), because of the work disincentives it provides to poor and near-poor households. There’s no simple way to address this situation. Cutting benefits to low-income households has an obvious downside for those families. Phasing out the benefits more slowly, as income rises, will mean providing benefits to more households and will cost substantially more. Ultimately, I think our society ends up relying on the fact that many low-income households would actually like to be self-supporting, to work, and to avoid or minimize their use of government assistance. But for other low-income households, the work disincentives of the poverty trap will bite.