**Labor hours and other inputs** : Data on labor hours, material inputs, IT capital, non-IT capital by industry-country-year come from EU KLEMS (Timmer, van Moergastel, Stuivenwold, Ypma, O’Mahony, and Kangasniemi, 2007). These data were originally reported for 28 industries, which were mapped into the sectoral classification of the IFR data (see Table A1).

**Replaceability** : Following Graetz and Michaels (2018), we constructed an industry-level measure of replaceability using data from IFR on robot applications, the US census of occupational classifications and the distribution of hours across occupations and industries from the 1980 US Census. The IFR distinguishes between different applications of robots, including (among others) welding, processing, and assembling (International Federation of Robotics, 2012). We take the 2000 Census three-digit occupations and assign a replaceability value of one to the three-digit occupation if the name and/or description of at least one of the SOC five-digit occupations included in it contains at least one of these IFR application categories and zero otherwise. Note that we assume that services occupations (occupations with SOC codes _<_ 45000) are not replaceable. In addition, this procedure inadvertently identifies some occupations as potentially replaceable by robots that presumably are not, such as “agricultural inspectors”, “infantry”, and “airport cargo handling supervisors”. These are typically occupations that include tasks and/or titles such as “repair”, “inspect”, “drive”, “maintain”, “actor” etc. We remove such cases from the list of potentially replaceable occupations.

We then map the resulting replaceability measure into the 1990 Census occupational classification, which is available for the 1980 and 2000 censuses. If several 2000 occupations map into one 1990 occupation, then we assign the 1990 occupation a replaceability value of one if and only if at least one of the corresponding 2000 occupations has a value of one. To arrive at a measure of replaceability at the industry level, we first assign individuals in the 1980 IPUMS Census a replaceability score based on the 1990 occupation they report (assuming the value 1 if the occupation is replaceable, and 0 if it is not). We then assign each individual to one of our 28 EU KLEMS industries based on a crosswalk to the 1990 Census industry classification. We compute the fraction of replaceable hours for each of the 16 robot-using industries by dividing the sum product of replaceability and annual hours worked by the total sum of hours worked (applying person weights both when computing the numerator and the denominator). The replaceability values represent an upper bound to the share of hours that is replaceable, because occupations are classified as replaceable if only a part of their work can be replaced by robots; this part need not be large.

**Bilateral trade data** : Product-level bilateral trade data come from BACI. This data set is the World trade database developed by the CEPII, building on original data provided by the COMTRADE database of the United Nations Statistical Division. BACI is constructed using an original procedure that reconciles the declarations of the exporter and importer. This harmonization procedure makes it possible to extend considerably the number of countries for which trade data are available. BACI provides bilateral values and quantities of exports at the HS 6-digit product disaggregation, for 224 countries and is available from 1995 onwards. CEPII developed original statistical procedures to reconcile data reported by almost 150 countries to the United Nations Statistics Division. First, as import values are reported CIF (cost, insurance and freight) while exports are reported FOB (free on board), CIF costs are estimated and removed from imports values to compute FOB import values. Second, the reliability of country reporting is assessed based on the reporting distances among partners. These reporting qualities are used as weights in the reconciliation of each bilateral trade flow twice reported. Due to the use of this double information on each flow, BACI ends up covering a large set of countries not reporting at a given level of the product classification. The data set gives information about the value (in thousands of US dollars) and the quantity (in tons) of trade. Gaulier and Zignano (2010) provide

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