The Hutchins Roundup brings the latest thinking in fiscal and monetary policy to your inbox. Have something you'd like us to include in the next Roundup? Email us and we'll take a look.
This edition was written by Sarah Ahmad, Tristan Loa, Jack Spira, and David Wessel.
Bumsoo Kim of Williams College, Marc De la Barrea of the University of Navarra, and Masao Fukui of Boston University find that China’s currency peg amplified the China shock between 2000 and 2012 by boosting Chinese exports. They estimate that under a floating exchange rate, 59% of the manufacturing decline in the U.S. attributable to the China shock would have been eliminated, as currency appreciation would have reduced China’s export competitiveness and muted substitution toward Chinese goods. The peg also increased the U.S. trade deficit and generated excess unemployment of 1.77 percentage points, though the unemployment effect dissipated once the shock plateaued. Despite these costs, the China shock produced a net welfare gain for the United States as consumers gained access to cheaper goods. China also benefited substantially, though its gains would have been slightly smaller under a floating regime, since the peg overheated the domestic economy to subsidize foreign consumption. The authors also find that the associated Chinese savings glut had only a limited impact on the U.S. economy, because the share of U.S. imports in total Chinese expenditure is small.
Productivity growth in Europe has lagged behind that of the U.S. for the last several decades, owing in large part to lower European investment in technological innovation. Using World Bank and OECD indicators to measure institutional and regulatory quality across countries, Jonathan Bothner of the European Central Bank and co-authors find that less effective institutional governance, more stringent labor protections, and more burdensome startup regulations inhibit investment in high-tech, high-patent, and AI-intensive sectors. They estimate that raising each European country's institutional and regulatory quality to the levels of the best performers in the E.U. would increase the share of investment allocated to innovation sectors by nearly 50% across the region.
Historically, technological innovations have tended to disproportionately benefit highly educated workers, widening gaps in employment and earnings. Guillermo Cruces of the Universidad de San Andrés and co-authors ask whether the same is true for generative AI. They conduct a randomized online experiment with around 1,200 adults of heterogeneous educational backgrounds, asking them to complete a business problem-solving task either with or without access to a GPT-based assistant. AI raised productivity for all participants, with larger gains for workers with lower education. AI access increased task scores by 1.24 standard deviations for lower-education workers compared to 0.83 standard deviation for higher-education workers—a 0.41 standard deviation gap. Without AI, the difference between educational backgrounds was 0.55 standard deviation, meaning that AI closed about three-quarters of the baseline difference. The remaining gap appears to reflect how participants interact with the tool—higher-education workers were more likely to prompt the assistant in more structured ways. The authors conclude that AI substitutes for cognitive inputs that are scarcer among lower-education individuals, operating as a “task-level equalizer” by reducing differences in execution capacity.
"Periods of rapid technological change are often accompanied by anxiety about the economic and social consequences of automation. Although new technologies often create winners and losers in the short run, history shows that in the longer run innovation leads to broadly shared increases in productivity and living standards that tend to support economic growth and a healthy labor market. As with other general-purpose technologies, the long-run effects of AI are likely to be profoundly positive. But in the short term, AI may deeply disrupt labor markets and harm some workers. The ultimate impact on workers will depend not only on the extent of the disruption and the length of time it takes for the long-term benefits to appear, but importantly on how we, as a society, navigate this transition...," says Michael Barr, member of the Federal Reserve Board.
"In the event that GenAI results in a long-lasting boost to productivity growth, wages and economic activity could grow more than would otherwise be the case without putting upward pressure on inflation. At the same time, demand for capital would rise because of the strong business investment required to take advantage of the technology, putting upward pressures on interest rates, and household savings could fall due to expectations of stronger real wage growth and thus higher lifetime earnings, also putting upward pressure on interest rates. All of this would imply a higher setting for the policy rate when the economy is at equilibrium, or what monetary economists call r*. Indeed, last year I raised my long-term estimate of r* modestly because of higher productivity. Moreover, in the short term, investment in AI could be inflationary—for example, if electricity supply constraints from inefficiencies in the power grid collide with strong energy demand from the building of data centers. For all of these reasons, I expect that the AI boom is unlikely to be a reason for lowering policy rates.”
Call for papers
We are seeking proposals for papers on the municipal bond market and state and local fiscal policy to be considered for the Municipal Finance Conference to be held in-person Tuesday, July 21, 2026 and Wednesday, July 22, 2026 in Washington, D.C.
About the Hutchins Center on Fiscal and Monetary Policy at Brookings
