<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Replication Data for: Tariffs as Electoral Weapons: The Political Geography of the US-China Trade War</dcterms:title><dcterms:identifier>https://doi.org/10.7910/DVN/1GGBBK</dcterms:identifier><dcterms:creator>Kim, Sung Eun</dcterms:creator><dcterms:creator>Margalit, Yotam</dcterms:creator><dcterms:publisher>Harvard Dataverse</dcterms:publisher><dcterms:issued>2020-10-19</dcterms:issued><dcterms:modified>2020-10-19T13:53:58Z</dcterms:modified><dcterms:description>In response to President Trump’s escalation of trade relations, China countered by issuing tariffs on over 6,000 products worth over $110 billion in U.S. exports. We explore whether China’s tariffs reflected a strategy to apply counter-pressure by hurting political support for Republicans, assess the strategy’s impact on the 2018 mid-term elections, and examine the mechanism underlying the resulting electoral shift. We find strong evidence that Chinese tariffs systematically targeted U.S. goods whose production is concentrated in Republican-supporting counties, particularly when located in closely contested Congressional districts. This apparent strategy was successful: targeted areas were more likely to turn against Republican candidates. Using data on campaign communications, local search patterns online and an original national survey, we find evidence that voters residing in areas vulnerable to the tariffs were more likely to learn about the trade war, recognize its adverse impact, and assign the Republicans responsibility for the escalating situation.</dcterms:description><dcterms:subject>Social Sciences</dcterms:subject><dcterms:date>2020-10-19</dcterms:date><dcterms:contributor>Matthews, Elana</dcterms:contributor><dcterms:dateSubmitted>2020-10-16</dcterms:dateSubmitted><dcterms:license>CC0 1.0</dcterms:license></metadata>