# **4. Empirical methodology**

where _Num_<sup>_M,T_</sup> _j_ is the number of import (“ _M_ ”) policy measures imposed by type (“ _T_ ” = liberalizing, restrictive) in implementing jurisdiction j; _Num_<sup>_X,T_</sup> _j_ is the number of export (“ _X_ ”) policy measures imposed by type (“ _T_ ” = liberalizing, restrictive) in implementing jurisdiction _j_ ; _Proc_ **_k_** _j_ is the vector of public procurement variables for country _j_ ; _z_ **_z_** _j_ is a vector of countryand country-sector specific control variables; is the constant term and ε _j_ is the error term. Equations (1) and (2) are estimated separately for liberalizing and restrictive measures imposed on medical products and personal protective equipment. αα The procurement vector comprises variables reflecting the timeliness ( _Total_timej_ ), administrative procedures ( _Total_stepsj_ ), efforts to lower transactions costs ( _Eprocj_ ) and commitments to open government procurement regimes to foreign competition. The first two variables denote the pre-crisis total time and number of steps to complete procurement processes in each country or jurisdiction. Use of e-procurement is measured as the frequency of the use of an e-procurement platform in total procurement by a procuring entity, based on the range categorization reported in the World Bank Doing Business Contracting with the Government indicator: less than 25%, 25%-50%, 50%-75% and more than 75%. Greater reliance on e-procurement may have a positive or negative association with resort to trade measures. It may facilitate a rapid response by making it easier for small and medium-sized enterprises (SMEs) – which account for a large share of the total number of firms in any economy – to sell essential supplies to the authorities (SMEs that do not already participate in PP may be able to retool relatively quickly if it is clear there is demand for their output). But this may also go the other way if the fixed costs associated with registration, certification and approval of new firms to bid to provide medical supplies are significant and take time to complete.

Openness of procurement regimes is proxied by a binary variable indicating GPA membership ( _GPAj_ ) and by the number of deep procurement agreements (DPAs) signed by each country with trading partners ( _Num_DPAj_ ). Membership of the GPA and the number of DPAs signed by a country implies more open PP regimes, which may be associated with a lower likelihood of imposing trade-restrictive measures. Conversely, transparency, due process and nondiscrimination commitments made in these agreements may impede rapid responses in procurement and induce governments to resort to export controls in the initial phase of the crisis.

> 12 We organize the data as a cross-section instead of a panel because the dependent variable is available by country on a weekly basis but all explanatory variables, except those on the incidence of COVID-19, are only available for each country annually in the year 2018 or before. The annual variation in our variables of interest will thus not explain the weekly or monthly variation in the count of trade policy measures imposed during the pandemic. This said, we account for the time dimension of the trade policy measures by computing the duration of the measures (where a removal date is reported in the GTA data set) and replacing the dependent count variables in equations (1) and (2) with their respective duration. Results are reported in Table 4.

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