Smorgasbord

Ana Margarida Fernandes and Tristan Reed provide a menu of 15 industrial policy tools, and how and when they are more or less likely to work, in Industrial Policy for Development: Approaches in the 21st Century (World Bank, April 2026, https://openknowledge.worldbank.org/entities/publication/9f8098d5-fa1f-4c1b-97b5-f04262818bb3).

“Industrial policy—the range of policy tools that governments use to shape what an economy produces rather than leave it to the discretion of markets alone—is back with a vengeance. Despite recent headlines, advanced economies are not the heaviest users of industrial policy. As this report documents, developing economies use it more intensively. New data show that among upper-middle-income economies—those with per capita incomes ranging from US$5,000 to US$14,000—total business subsidies now average 4.2 percent of gross domestic product (GDP), the highest on record. A review of the most recent national development plans of 183 countries reveals that all countries target growth of at least one industry, and that, on average, low-income countries target 13—more than twice the number in high-income countries. Interest in industrial policy has seldom been higher … Deciding which business activities are strategic is perhaps the most difficult and contested topic in industrial policy. As Nobel laureate Paul Krugman remarked about industrial policy in 1983: `While there is a valid case for targeting grounded in economic theory, the theoretical basis is too complex and ambiguous to be useful given the current state of knowledge’. Of course, the last four decades have seen significant progress in economic measurement, and recent years have seen a resurgence of interest in industrial policy among economists. Nonetheless, Krugman’s argument still largely holds.”

Christina D. Romer and David H. Romer provide "An early retrospective on monetary policy in the Powell era" (Brookings Institution, Hutchins Center Working Paper #106, June 2026, https://www.brookings.edu/articles/an-early-retrospective-on-monetary-policy-in-the-powell-era/). 

“To most economists—ourselves included—Chair Powell is a hero. … The continuing soundness of the U.S. economy, stability of our financial markets, and respect for the Federal Reserve are due in no small part to his effective leadership. For that we must all be grateful. But that gratitude does not mean that scholars should not evaluate policy in the Powell era with the same rigor and dispassion as they would the tenures of other Fed chairs. … [W]e focus on what we see as six relatively distinct policy episodes. These are: (1) the interest rate and balance sheet normalization in 2018 and early 2019; (2) the reversal of both these policies in mid- and late-2019; (3) the aggressive expansionary response to the COVID 19 pandemic in 2020 and early 2021; (4) continued loose policy in 2021 as inflation surged; (5) the rapid tightening in 2022 and 2023 to fight inflation; and (6) the interest rate cuts starting in mid-2024 and severe threats to Fed independence.”

In the Economic Survey 2025-26, the latest edition of the annual report from India’s Ministry of Finance (January 2026, https://www.indiabudget.gov.in/economicsurvey), I was struck by some comments from V. Anantha Nageswaran in the “Preface”:

“India’s export performance since the start of the millennium tells its own story. In general, services exports have outpaced goods exports. In particular, over the five years since 2020, the compounded annual growth rate of total exports has been 9.4%, while that of merchandise exports has been only 6.4%. Services have done much of the heavy lifting, creditable and macro-stabilising, but not a substitute for the goods-based export ecosystems that ultimately underpin durable external and currency stability. The Information Technology-Enabled Services Sector has been India’s mainstay for growth and exports since the dawn of the millennium. International experience indicates that while service exports are economically valuable, they do not systematically compel broad upgrades in state capacity, as successful firms can bypass weak institutions, relocate easily, and generate limited economy-wide pressure on governments to reform. Unlike manufacturing exports, they do not impose hard fiscal, employment, or logistical constraints on the State, allowing institutional weakness to persist even alongside globally competitive firms. So, manufacturing matters.” The report later notes: “[S]ervices are increasingly integrated into manufacturing through activities such as design, R&D, logistics, software development, and professional services, reflecting the growing `servicification’ of production systems. This is evident in products such as smart devices, whose value is driven by software ecosystems; medical equipment/wearables bundled with diagnostic and remote-monitoring services; and automobiles, which are increasingly described as “software on wheels”. As manufacturing becomes increasingly technology and data-intensive, services such as ICT, finance, compliance, and after-sales support account for a growing share of value creation. International experience suggests that this integration is a crucial channel for enhancing value addition, export competitiveness, and employment.”

David M. Cutler and Lev Klarnet address “Has the United States bent the health care cost curve?” (Brookings Papers on Economic Activity, Spring 2026, https://www.brookings.edu/articles/has-the-united-states-bent-the-health-care-cost-curve).

“Aggregating across a number of data sets and analyses, we highlight the role of five central factors in the [health care] spending slowdown. First, technological innovation has become more likely to save money over time. This shows up in medications that prevent acute events and in surgeries that can be performed cheaper and with fewer complications. We estimate the development of cost saving technology accounts for about 21% of the spending slowdown. Second, demand for some types of care has fallen. Demand changes might be due to changes in reimbursement, higher cost sharing, and tighter insurer restrictions on utilization. Together, demand changes accounts for 10-26% of the spending slowdown, with the range reflecting economic uncertainty about effects. Third, long-run supply elasticities tend to be greater than short-run supply elasticities, leading to price reductions over time. Examples of this include pharmaceuticals going off patent and imaging prices declining. These account for 6% of the spending slowdown. Fourth, health status has improved in other ways that we do not understand, but that may be due to reduced smoking and other preventive care. A healthier population needs less care than does a less healthy one. These trends account for 7% of the spending slowdown. Fifth, there was a reduction in the rate of price growth, from 1-2% above general inflation to about general inflation. This results in about 24% of the spending slowdown. … Considering our primary question, we conclude that the US has bent the health care cost curve. The role of technology in particular is fundamentally different from what it was in the past, and that means that cost growth has slowed relative to the past. That said, the cost curve has not bent as much as it could, or as much as it needs to.”

Yueran Ma, Mengdi Zhang, and Kaspar Zimmermann compile evidence on “Business Concentration Around the World: 1900-2020” (University of Chicago Becker-Friedman Institute for Economics, February 27, 2026, https://bfi.uchicago.edu/insights/business-concentration-around-the-world-1900-2020).

“In this paper, we document two sets of facts about the evolution of the organization of production over the past century. These facts hold broadly, across a variety of market-based economies where we can find comprehensive long-run data on the firm size distribution. First, sales, net income, and equity capital have become increasingly concentrated in the largest firms. In many countries, the largest 1% firms by sales now account for around 80% of economy-wide sales, up from around 50% in the early 20th century. The long-run increases of concentration also hold at the industry level. Second, employment concentration has been relatively stable. The largest 1% firms by employees account for roughly 50% of economy wide employment throughout the 20th century. One exception is retail/wholesale trade, where employment concentration has risen almost as much as sales concentration. These pervasive patterns … show that the rising dominance of large firms is a widespread phenomenon, not limited to the recent decades or the United States. Moreover, large firms scale not so much with labor, and possibly more with capital (except in industries like retail where expanding automation has been more challenging thus far).”

Jesse Tack, Jisang Yu, and Roderick M. Rejesus discuss “Recent approaches in agricultural production economics: Where the heck are the prices?” (Food Policy, May 2026, https://www.sciencedirect.com/science/article/pii/S0306919226000205).

“The purpose of this review is to offer a practitioner’s perspective on the evolution of empirical methods since the mid-twentieth century within the context of agricultural production economics. If there was a singular contribution it would rest on our presentation and discussion of research papers that have leveraged more recently developed/popularized empirical approaches outside of the traditional duality-based frameworks. However, we also (i) provide a backward-looking historical context of where these approaches fit within the general methodological landscape dating back to (at least) the 1960s; and (ii) discuss very recent innovations in structural approaches that suggest a path forward in which strengths of both “old” and “new” methods are blended together. The intended audience for this contribution is widespread: (a) people outside of the agricultural production economics arena can learn about the historical evolution of methodological approaches as well as important research contributions for a select group of topics; (b) younger researchers within the agricultural production landscape can gain an appreciation for how their approaches fit into the historical context and also begin thinking about how we might further evolve as a profession; and (c) more established researchers can gain an appreciation of how widespread these newer approaches have become and the types of questions they can answer.”

Stephan Haggard, Kyoochul Kim, and Munseob Lee discuss techniques of what they call “forensic economics” in “Studying economic black holes: Lessons from North Korea” (World Development, May 2026, 201: 107315, https://www.sciencedirect.com/science/article/pii/S0305750X26000045?via%3Dihub). From the abstract:

“Some economies are “black holes” where reliable data is scarce due to government control, low capacity, or conflict. Despite these challenges, researchers have found ways to gather useful information. This paper draws on the literature on North Korea to review six key methods: satellite imagery, reports from aid agencies, trade data, prices, refugee surveys, and official documents. These sources are imperfect, and require close attention to research design and measurement error. Nonetheless, they demonstrate that it is possible to extract information from economic black holes and to draw meaningful insights about them.”

Globalization and Its Imbalances

Finance & Development has published a five-paper symposium on “Geoeconomics” (June 2026, https://www.imf.org/en/publications/fandd/issues). Christopher Clayton, Matteo Maggiori, and Jesse Schreger contribute “Understanding Geoeconomics in a Volatile World.”

“The academic study of geoeconomics dates most prominently to 1945, when economist Albert Hirschman published National Power and the Structure of Foreign Trade. In it, he examines how Nazi Germany had structured its economy to maximize leverage over its neighbors during the interwar period. He rejected the naive view that because trade is voluntary and mutually beneficial, it is geopolitically harmless. Benefits can be mutual, Hirschman argues, without being symmetrical. And asymmetry is how power builds. Since Hirschman’s time, economists have left the study of global power dynamics largely to political scientists and historians, who have led the development of this area of research. Though almost every economics student encounters the Herfindahl-Hirschman Index, few know it was invented to measure the economic power of nations, not firms. … Our work shows that there is a trade-off between gains from trade and economic security. The same mechanisms that are the classic foundations of the gains from trade—economies of scale and specialization—also generate economic dependence. The domestic alternatives that countries did not build up are poor substitutes for globally dominant inputs, such as Chinese manufacturing or US financial services and technology. This lack of alternatives leaves the countries exposed to coercion. As the global economy increasingly relies on goods and services that have strategic complementarities and economies of scale, these mechanisms are likely to increase in importance.”

Steven A. Altman and Caroline R. Bastian survey the extent of globalization in the DHL Global Connectedness Report 2026. (https://www.dhl.com/global-en/microsites/core/global-connectedness/report.html).

“The DHL Global Connectedness Index does not indicate a shift from international to domestic activity across trade, capital, information, and people flows. Global connectedness reached a record high in 2022 and has not changed appreciably through 2025. … U.S. tariff increases only modestly reduced forecast global trade growth. Other countries supported trade growth by not raising tariffs, and many negotiated new trade deals to secure access to alternative markets. … The world remains far from a split into disconnected geopolitical blocs. Only 4-6% of global goods trade, greenfield FDI, and cross-border M&A have shifted away from geopolitical rivals over the past decade. Trade flows shifted more toward neutral countries than to close allies, implying more ‘de-risking’ than ‘friendshoring’. … Prominent narratives about deglobalization are driven more by politics and public policy than by actual shifts in cross-border flows. While the risk of deglobalization has risen and the pattern of connectedness is shifting, the world overall remains as connected as ever.”

The IMF offers a guide to “Understanding Global Imbalances” (April 5, 2026, https://www.imf.org/en/publications/policy-papers/issues/2026/04/06/understanding-global-imbalances-575234).

“Global imbalances have been a recurrent feature of the global economy since the 1870s and countries have switched positions over time … The United Kingdom, for example, ran sustained surpluses prior to World War II—reflecting colonial trade and large investment income—before shifting into a structural deficit position after 1945. More recently, the US transitioned from surplus to deficit in the 1970s, while Germany and Japan moved into surplus. … Four economies—the US, China, Germany, and Japan—account for roughly two-thirds of global imbalances. The US deficit—equivalent to 4 percent of GDP as of 2024—has been financed by capital inflows and portfolio investors seeking dollar assets. Germany and Japan’s surpluses have been driven by high saving rates, joined by substantial surpluses in China beginning in the 2000s. Oil-exporting countries’ surpluses fluctuate with commodity prices, creating episodic contributions to global imbalances. … While current account surpluses and deficits can be appropriate when they reflect economic fundamentals and desirable policies, the buildup and persistence of large imbalances raise concerns when they are driven by policy distortions and unwind in a disorderly manner.”

Hélène Rey, Beatrice Weder di Mauro, and Jeromin Zettelmeyer have edited a collection of 17 essays in Paris Report 4: The New Global Imbalances (Centre for Economic Policy Research, 2026, https://cepr.org/publications/books-and-reports/p398). From the introductory essay by di Mauro and Zettelmeyer:

“In sum, global current account imbalances reflect domestic saving–investment gaps. They can support growth when financed sustainably and directed toward productive uses, but they become risky when large, persistent, and tied to rising leverage or asset bubbles. What matters for these risks is not bilateral trade balances but the underlying macroeconomic conditions. Durable adjustment therefore requires domestic policy changes, not trade measures alone. … The ideal adjustment would involve the main systemic economies – at least the United States, China, and Europe – rebalancing simultaneously and in a coordinated manner. Such an approach would reduce the risk that adjustment in one economy simply shifts imbalances elsewhere or triggers destabilising spillovers. In simple terms, the required policy mix is well known. The United States would raise national saving, primarily through credible fiscal consolidation, thereby reducing its reliance on external financing. China would lower excess saving by rebalancing toward household consumption – strengthening social safety nets, boosting disposable income, and shifting away from investment- and export-led growth. Europe, for its part, would increase investment, particularly in infrastructure, defence, and the green transition, thereby absorbing more domestic and global savings.”

Interviews

Erika McEntarfer was Commissioner of the U.S. Bureau of Labor Statistics until August 1, 2025. Neale Mahoney discusses the experience with her and what comes next for federal statistics in “The hidden backbone: The data behind the economy” (Stanford Institute for Economic Policy Research, “Econ to Go,” March 26, 2026, https://siepr.stanford.edu/av/Econ-To-Go-podcast-hidden-backbone-data-us-economy). On her interaction with the Department of Government Efficiency, McEntarfer says:

“I actually had a whole basket of AI related projects when DOGE arrived early in the administration. The early word was they were gonna help us with AI. And I was like, `Great, we could use some more resources here.’ So, you know, I had this whole list of projects for them and instead I wound up sitting across the table from a member of DOGE and they were like, `So we want to fire all of these statisticians and replace them with the AI.’ And I was like, `I don’t think that’s actually possible, but if you can explain to me how it is possible, I am all ears.’ And then they would just stare at me blankly and tell me that I was not cooperating with their vision. I was like, `No, I don’t actually understand how you replace a time series statistician with an AI model, but if you can explain it to me, I’m all ears.’”

Tim Sablik interviews “Ellen McGrattan: On measuring what businesses do, developing effective tax policy, and searching for answers beyond the lamppost” (Econ Focus: Federal Reserve Bank of Richmond, First/Second Quarter 2026, https://www.richmondfed.org/publications/research/econ_focus/2026/q1-q2_interview). On total factor productivity (TFP), McGrattan says:

“In some sense, I’ve been struggling with trying to look inside the black box of TFP all my career. … My interest in business cycles partly stems from trying to measure what goes into TFP. … What is TFP? It’s what we don’t know, it’s the part that we need to fill in. It’s not just some magic dust that’s in the air. … If you buy, say, a computer, it has to be put on your balance sheet. But if you’re a dentist and you spend time building your patient list, that’s not put on any balance sheet. That patient list is the thing you sell when you retire or relocate, and that asset contributes to the value in the business, but we never see it until it gets sold or transferred somehow. There are 40 million active businesses in the United States, and most have assets that we can’t see. Assets like customer bases or trademarks — until there’s a transaction, we can’t see them. You might have a good accounting system that you developed within your business, or you’re a chef and you have recipes, and we can only see those things if you trade them. But most ongoing businesses don’t list these assets on a balance sheet, so we never get to see them. And that’s why we need a theory to infer it. … It all ties back to work I was doing to measure movements in the economy over the business cycle, but now I would say the bigger issue is how to measure all activity in the U.S. economy.”

Discussion Starters

Virginia Postrel tells the story of “Engineering the disposable diaper: Benjamin Spock told mothers in the mid-twentieth century to buy six dozen cloth diapers and a covered pail. Within a decade, both were obsolete” (Works in Progress, April 24, 2026, https://worksinprogress.co/issue/engineering-the-disposable-diaper/).

“After buying Charmin Paper Company in 1957, Procter & Gamble began looking for ideas for new paper products. Motivated by the less pleasant aspects of spending time with his new grandchild, the company’s director of exploratory development, Victor Mills, suggested disposable diapers. After analyzing existing products and conducting consumer research, P&G created a dedicated diaper research group. The research this group conducted, like that of its successors and competitors, wasn’t glamorous. It didn’t advance basic science. It wasn’t even an obvious route to profit. … It was a high-stakes gamble that required solving difficult engineering problems. How that happened represents the kind of hidden progress that leads to everyday abundance.”

Anton Korinek and Patrick McKelvey as “Where is AI in GDP Statistics (Peterson Institute for International Economics, May 2026, https://www.piie.com/publications/policy-briefs/2026/where-ai-gdp-statistics).

“We estimate … that nominal AI compute spending grew by more than 140 percent per year each in 2024 and 2025, raw compute capacity by more than 200 percent per year, and quality-adjusted AI output by more than 2,000 percent per year. The divergence between this picture of the AI economy and the one drawn by conventional GDP statistics is itself an informative macroeconomic signal. Treating the AI sector as a coherent economic entity in its own right yields a preliminary estimate of nominal AI GDP of roughly $250 billion in 2025—comparable in size to the US scheduled passenger airline industry—yet growing at approximately 2,600 percent per year in quality-adjusted terms. We argue that US statistical agencies and economic policymakers should start now to assemble better data on AI activity in AI satellite accounts—focused subsets of the national economic statistical accounts … They should begin to incorporate AI productive-capacity measures into medium-term projections and scenario analysis.”