Note: All regressions include importer-year and exporter-year fixed effects. Columns (3) to (10) include also country-pair fixed effects. In columns (3) and (4), the _TA_ dummy equals one if the two countries in the pair belong to the same TA (with or without provisions on government procurement). Data are for the years 1995, 1999, 2003, 2007, 2011 and 2015. Coefficients in bold are statistically different between the ‘Gov.’ and ‘Priv.’ regressions. Robust standard errors clustered at the country-pair level are in parentheses. Significant at: *10%, **5%, ***1% level.

Table 2: PPML Gravity estimates, Services

||(1)<br>Gov.|(2)<br>Priv.|(3)<br>Gov.|(4)<br>Priv.|(5)<br>Gov.|(6)<br>Priv.|(7)<br>Gov.|(8)<br>Priv.|(9)<br>Gov.|(10)<br>Priv.|
|---|---|---|---|---|---|---|---|---|---|---|
|Same country|**6.992*****<br>(0.183)|**5.802*****<br>(0.196)|||||||||
|Contiguity|0.186|0.394***|||||||||
||(0.114)|(0.128)|||||||||
|Common language|0.647***|0.608***|||||||||
||(0.106)|(0.102)|||||||||
|Colony|0.674***<br>(0.184)|0.890***<br>(0.180)|||||||||
|Ln Distance|-0.446***<br>(0.053)|-0.380***<br>(0.057)|||||||||
|Common legal origin|0.075|0.067|||||||||
||(0.071)|(0.081)|||||||||
|TA|0.353**|0.401***|**0.543*****|**0.087****|**0.318*****|**-0.207****|**0.317*****|**-0.206****|**0.314*****|**-0.208****|
||(0.158)|(0.144)|(0.057)|(0.041)|(0.086)|(0.100)|(0.085)|(0.099)|(0.085)|(0.099)|
|TA w/ procurement|-0.104|-0.071|||**0.572*****|**0.148*****|**0.390*****|**0.094****|**0.326*****|**0.034**|
||(0.118)|(0.121)|||(0.064)|(0.041)|(0.056)|(0.043)|(0.056)|(0.044)|
|WTO GPA|**1.001*****|**0.736*****|||||**0.427*****|**0.132*****|**0.302*****|**0.041**|
||(0.113)|(0.105)|||||(0.058)|(0.049)|(0.055)|(0.052)|
|EU|0.032|0.110|||||||**0.669*****|**0.337*****|
||(0.128)|(0.116)|||||||(0.085)|(0.065)|
|Obs|20,886|20,886|20,886|20,886|20,886|20,886|20,886|20,886|20,886|20,886|

Note: All regressions include importer-year and exporter-year fixed effects. Columns (3) to (10) include also country-pair fixed effects. In columns (3) and (4), the _TA_ dummy equals one if the two countries in the pair belong to the same TA (with or without provisions on government procurement). Data are for the years 1995, 1999, 2003, 2007, 2011 and 2015. Coefficients in bold are statistically different between the ‘Gov.’ and ‘Priv.’ regressions. Robust standard errors clustered at the country-pair level are in parentheses. Significant at: *10%, **5%, ***1% level.

The baseline results rely on the use of dummy variables to identify the presence of provisions on government procurement in TAs. The DTA database of Mattoo et al. (2020) however provides also detailed information on the inclusion of specific provisions in each TA. We thus exploit this information to gain a better understanding of the type of measures that can drive the average trade effect of covering government procurement in a TA. The database includes one hundred questions about the treatment of government procurement in the legal text of TAs. We consider the ‘horizontal’ depth of the government procurement chapters (if any) and exclude information about the treatment of certain provisions that are difficult to classify as moves towards opening up the market.<sup>25</sup> After this cleaning of the data, we end up with 39 distinct provisions on government procurement.

> 25Specifically, we drop questions that measure ‘vertical’ depth – i.e., those about the content of phasing in provisions for developing countries, that compare the content of the provision with the corresponding article of the (revised) WTO GPA, and combine some questions that are mutually exclusive (e.g., whether the chapter covers only goods or goods and services).

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