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on China |
| By: | Irina Balteanu (Banco de España); Maximiliano Moreno (Banco de España and Paris School of Economics); Francesca Viani (Banco de España) |
| Abstract: | This paper investigates whether US tariffs on China diverted Chinese exports towards the EU, exploiting the first US-China trade war as a setting that permits clean identification of trade diversion effects. Applying difference-in-differences local projections to highly disaggregated tariff, import and unit value data, it shows that trade diversion occurred but was limited in size. For each dollar reduction in US imports from China, 9 cents were redirected to the EU market in real terms. The effects varied substantially across products and destination markets. Trade diversion was strongest for complex capital goods and homogeneous intermediate inputs, and was more pronounced in EU markets with greater import exposure to China and weaker competition from alternative suppliers. Products experiencing effective diversion also exhibited significant price declines, with competitive pressures concentrated in lower-price market segments. These findings suggest that tariffs of a magnitude comparable to those imposed by the United States in 2025 could redirect Chinese exports towards the EU, potentially contributing to a second “China shock” in Europe. While the aggregate effects are modest, diversion and price pressures may be considerably stronger in specific product categories and destination markets. |
| Keywords: | trade diversion, tariffs, trade war, EU imports, import prices, China shock |
| JEL: | F14 F6 E31 |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2634e |
| By: | Yuting Chen; Xuancheng Qin |
| Abstract: | Administrative boundary reforms in China alter the assignment of local authority and growth incentives without changing physical geography. We study two reforms with opposite institutional content---county-to-district (centralization: a county absorbed into a municipality as an urban district) and county-to-city (empowerment: a county upgraded to a county-level city)---using a firm-year pollution panel (1998--2013) and a border-pair research design that compares firms on opposite sides of the same county border. Centralizing reform lowers local NOx intensity by 14.8% through cleaner production, without shrinking output or employment; empowering reform raises COD, dust, and wastewater levels by 87--95\% through dirty growth. The local abatement is not net abatement: NOx rises in same-prefecture neighbor counties (+0.77, p |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.06374 |
| By: | John S. Ahlquist; Eric Thai |
| Abstract: | Unions are important economic and political actors at the local level, but the primary source on US union membership, the Current Population Survey (CPS), is unreliable below the state level. Researchers have therefore turned to union-reported membership in federal "LM" filings, geolocating unions and aggregating their reported membership to estimate union density for counties, commuting zones, and congressional districts. We ask whether this practice is sound. We develop and defend multilevel regression with poststratification (MrP) on the CPS as a benchmark, then validate LM-based estimates against it from the state level down. LM, CPS, and MrP are highly correlated at the state level, but this correlation is roughly halved at the congressional-district, commuting-zone, and county levels. The breakdown is driven in part by reporting "lumpiness, " which produces improbable values, including union densities exceeding 100%. Missing public sector union members explains only a small part of this divergence. These issues are substantively consequential: in a standard commuting-zone "China shock" regression, swapping density measures changes the import-exposure coefficient enough to alter its magnitude, significance, and sign. We conclude that LM records remain a rich resource for studying unions as organizations, but aggregating LM-reported membership is not a reliable way to measure union density at fine geographic resolution. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.06774 |