B. On the compatibility between the law data and the trade data and the interpretation of the empirical estimates Data on the value of bilateral trade by industry are sourced from the ITPD-E database. It collates only official and administrative data, and includes information on domestic trade. We consider annual data between 2000 and 2019, when trade in services is also measured. Considering this type of trade data that do not distinguish between different types of buyer (government vs others) has three main advantages over alternative approaches based on inter-country input-output (ICIO) tables that permit to split cross-border procurement from other trade flows. First, using aggregate trade data allows us to incorporate in our estimates the effect that protectionist laws in government procurement can have on the sourcing strategies of domestic firms. This is important because while governments might not vary much in their propensity to award contracts to domestic (rather than foreign) firms, they can impose different restrictions to the input sourcing of the awardees, for instance through “made in the country” provisions. Second, bilateral imports are computed from administrative data, while the trade data from ICIO tables are estimated based on different proportionality assumptions (Antràs and Chor 2022; Johnson 2018). Finally, data from ITPD-E database cover all countries in the world. We can thus include in the analysis all the countries for which we have coded information on procurement law (around 140 countries), whereas the ICIO data are generally available for a subset of countries. For these reasons, we carry out our baseline empirical analysis with the aggregate trade data, and discuss the results using estimated data for cross-border procurement flows from ICIO tables in the Appendix.

Before moving on to the econometric analysis linking the variable on protectionist rules in government procurement and the variable on cross-border trade flows, it is important to address some caveats that could limit the significance of a relationship between the two variables. First, it should be noted that the data resulting from the analysis of the text of national laws only captures ‘de jure’ protectionism. As with many coding of legal texts, there may be discrepancies between the text of the law and its implementation. Our investigation explores whether the legal provisions have empirical bite in reducing trade openness.

Furthermore, the text analysis only provides a static picture of the national law on government procurement as of 2021-22, whereas the annual trade data cover the 2000-2019 period. Although we know the year a decree was first promulgated, we have no information about possible amendments introduced or how the law looked before the decrees entered into force. Therefore, in our empirical analysis, we are assuming that the characteristics coded in 2021-22 apply over the entire period of the trade data. Any deviation from this assumption, which is not systematically related to the determinants of trade, could introduce measurement error and work against finding a significant association between our protectionism indicators and trade openness.

Another partial discrepancy between the law and the trade data concerns the object of discrimination, which can refer to either firms or the goods and services being procured. In 9