# **3 Data and Summary Statistics**

We use UN Comtrade data that record bilateral exports in 5203 HS6 products. We aggregate into biennial (24-month) intervals (2014/2015; 2016/17; 2018/19), and refer to each 24-month period by its ending year. We restrict our sample to the top 50 exporting countries, excluding oil exporters. The resulting sample covers 95.9% of global trade (or 70.5% excluding US and China). We analyze exports from each of these countries to three destinations: the United States ( _US_ ), China ( _CH_ ), and the aggregate of all destinations except the US and China ( _RW_ ). We classify products into nine sectors: agriculture, apparel, chemicals, materials, machinery, metals, minerals, transport, and miscellaneous. Figure A.1 reports countries’ export shares by sector prior to the trade war.

We consider four sets of tariff changes as part of the US-China trade war: i) imposed by the US on China (the “US tariffs”), denoted as _TCH_<sup>_US_</sup> , _ω_<sup>, where</sup><sup>_ω_denotes an HS6 product code; ii) imposed</sup> by China on the US, _TUS_<sup>_CH_</sup> , _ω_<sup>(the “China tariffs”); iii) imposed by the US on each country</sup><sup>_i_other than</sup> China, _Ti_<sup>_US_</sup> , _ω_<sup>(e.g.,steeltariffsonMexico);andiv)most-favored-nation(MFN)tariffsimposedby</sup> China on all countries but the US, _Ti_<sup>_CH_</sup> , _ω_<sup>.Bown et al. (2019) argue that China’s MFN tariff cuts were</sup> likely influenced by the trade war with the US, so we include them in our analysis. The first three sets of tariffs are taken from Fajgelbaum et al. (2020) and extended through the end of 2019, and the last set is from Bown et al. (2019). We scale tariff changes in proportion to their duration within each 24-month interval. This scaling generates variation in tariff changes across products due to both the timing and magnitude of rate changes.

Figure A.2 illustrates the tariff variation. The US substantially raised tariffs on China, but except for two sectors (machinery and metals) it did not significantly raise tariffs on other partners. Panel B shows that China’s tariffs increased across all sectors on the US and decreased for non-US partners. For both the US and China, we observe substantial variation within sectors.

# **4 Average Export Responses**

Figure 1 presents binscatters that examine the exports of the 48 bystander countries to _US_ , _CH_ , and _RW_ against the US-China tariffs. Panel A shows the binscatter of exports to the US against the US tariffs: ∆ ln _Xiω_<sup>_US_</sup> = _α_ + _β_ ∆ ln _TCH_<sup>_US_+</sup><sup>_ε_</sup> _i_<sup>_US_</sup> . Panel B shows exports to China against the Chinese tariffs: ∆ ln _Xiω_<sup>_CH_</sup> = _α_ + _β_ ∆ ln _TUS_<sup>_CH_+</sup><sup>_ε_</sup> _i_<sup>_CH_</sup> . Panels C and D report exports to _RW_ against the US and China tariffs, respectively.<sup>12</sup> Panel A reveals that, on average, bystanders increased exports to the US in products with high US tariffs on China, with an elasticity of 0.31 (se 0.10). This growth rate is statistically distinct from the pre-war export growth rate from 2015 to 2017 (elasticity -0.19 and se -0.19). Panel B shows that, on average, countries did not reallocate exports into China in response to China’s tariffs on the US. Panels C and D show that exports to _RW_ increased with both tariffs, with an elasticity of 0.20 (se 0.08) for the US tariffs (Panel C), and of 0.29 (se 0.08) for the China tariffs (Panel D).

> 12Each binscatter includes exports from every country in our dataset, except for US and China. Figure A.3 confirms, as others have found, that the Chinese tariffs reduced US exports to China, and vice versa.

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