to the year 2019. Data are available for all 133 jurisdictions reported to have used trade measures in the first half of 2020 in the GTA trade policy data set (Appendix Table 1).<sup>15</sup> PP processes in richer countries tend to require both a smaller number of steps and less time for completion on average (Figure 3, bottom panels). The total number of steps range from a low of 12 (Singapore) to a high of 21 (Honduras, Hungary, the Islamic Republic of Iran, the Lao People’s Democratic Republic, Myanmar and Oman). The total time taken to complete a procurement process ranges from 270 (Korea) to 2062 (the República Bolivariana de Venezuela) days. The sample mean is 18 steps and 717 days, respectively. Richer countries also tend to use e-procurement more on average (Figure 3, top right panel). The share of e- procurement in total procurement ranges from less than 25% for most African countries to more than 75% for EU and ASEAN Member States.

_GPAj_ is constructed using information on membership of the WTO’s Agreement on Government Procurement as of July 2020; and _Num_DPAj_ is constructed using data from Shingal and Ereshchenko (2020), which cover all PTAs in effect until March 2017.<sup>16</sup> On average richer countries tend to be members of more DPAs (Figure 3, top left panel). The number of non-zero DPAs ranges from 1 for West Asian countries to 26 for the EU. There are 32 WTO GPA members in the sample, mostly comprising high-income countries. E The control variables are sourced as follows: population and GDP data are from the World Bank World Development Indicators; market penetration ( _MPj_ ) is computed using bilateral distance data from CEPII (Head et al. 2010); and government effectiveness ( _GEj_ ) is sourced from the Worldwide Governance Indicators (Kaufmann et al. 2011). Trade data to construct the import share and RCA variables are from UN Comtrade. Import tariffs are from UNCTAD TRAINS/WITS. Data on COVID-19 cases are from the WHO <u><mark>(https://covid19.who.int/table)</mark></u> . Appendix Table 2 reports summary statistics for all variables used in the analysis. Apart from COVID-19 cases and deaths that pertain to the third week of July 2020, all control variables are the average for the years 2017 and 2018.

# **6. Results**

Table 1 reports the results from PPML estimation of equations (1) and (2) separately for liberalizing and restrictive measures imposed on medical goods, with standard errors clustered by country in each case. Results reported in Table 2 replicate the analysis in Table 1 but distinguish between measures that were imposed and subsequently removed within the sample period and those that remained in effect as of mid-July 2020. Table 3 reports the results from the PPML estimation of equations (1) and (2) applied to specific types of trade measures, i.e., restriction or liberalization of exports or imports, respectively. Finally, based on the dates of implementation and removal, Table 4 reports the results from estimating equations (1) and (2) using as dependent variable the duration of the respective measure and not the total number of measures.

> 15 Jurisdictions imposing measures include the Eurasian Economic Union, the EU, and the South African Customs Union (SACU). Measures imposed by these blocs are allocated to their member states for the purpose of analysis. 16 Shingal and Ereshchenko (2020) measure the “depth” of procurement provisions in PTAs on the basis of seven broad attributes: non-discrimination; coverage in terms of goods, services (including construction) and type of procuring entity (central, sub-central government and utilities); procedural disciplines; ex-ante and ex-post transparency, dispute settlement; and new issues (e-procurement, sustainable procurement, SME participation, adoption of safety standards, and cooperation on matters of public procurement).

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