In recent years a number of methods have been developed to assess the level of applied policies in services. Two approaches related to the creation of an index measuring the restrictiveness of service trade policies are worth noting: the first one, the Services Trade Restrictions Index (STRI) was developed by the World Bank; global patterns of policy restrictiveness revealed by that exercise were described in Borchert et al. (2014) and the Database is documented in Borchert et al. (2012). The data were released on the World Bank’s Open Data portal.<sup>18</sup> The second method, named Services Trade Restrictiveness Index (also STRI by its acronym) was developed by the OECD, and results were first published in 2014 (Grosso et al. 2014). Although both approaches use similar sets of underlying data, the methodology used to construct the respective indices differs in a number of ways.<sup>19</sup> Yet both STRI approaches measure the restrictiveness of an economy’s policy regime for the sectors and modes covered. The resultant restrictiveness indices depict overall patterns in policy, across economies, modes, and sectors.<sup>20</sup> The method used in the current paper is an updated version of the STRI developed by the World Bank a few years back. In updating the World Bank STRI, the main principles were maintained but a number of improvements were introduced, in particular the use of an algorithm and an automatized aggregation method to compute the STRI. Introducing these technical improvements removes the subjective bias that may have existed in the previous World Bank STRI. In particular, the aggregation methodology represents an innovation for practical and conceptual reasons: it entails the practical advantage of reproducibility as well as the conceptual advantage of capturing the combined restrictiveness of multiple measures in a well-defined and theory-consistent way. An additional improvement relates to the consideration of regulatory and competition policy measures. This improved methodology will be described below.

# **Basic principles**

The construction of the STRI follows the same steps as in Borchert et al. (2012):

- 1) the **selection** of key restrictions entering the STRI; 2) the **determination** of the level of restrictiveness of individual measures (or bundles of measures if they are conceptually intertwined, which we call ‘synthetic measures’); and

- 3) the **aggregation** of measures into indices at the sector-mode level, sector level, and economy level, respectively.

While the Services Trade Policy Database (STPD) described in the previous section has a very broad coverage of measures, the index is based on a subset of key restrictions on trade in services, approximately 115 regulations and policies. The selection of key restrictions entering the quantification exercise was driven by a number of considerations: 1) to cover the most significant restrictions – this was based on the previous analysis conducted by the World Bank as well as expert advice; 2) to respond to recent regulatory developments perceived as having a discernible impact on trade in services, e.g. screening policies, restrictions relating to cross-border data flows; 3) to ensure comparability with the 2008-2011 World Bank exercise; and 4) to adapt to – and be consistent with – the coverage of measures in the OECD database, which served as a fundamental source of information for economies covered by both the STPD and the OECD STRI. The list of measures selected for the construction of the STRI is provided in Annex 5.

Trade policies are assessed by looking at specific types of measures for each subsector and mode. For example, for commercial banking, we obtain separate measures for cross-border supply,

> 18 Accessible at https://www.worldbank.org/en/research/brief/services-trade-restrictions-database. 19 Country and sectoral coverage of both exercises also differ. More information on the OECD STRI methodology may be found in Services Trade Policies and the Global Economy, OECD (2017).

> 20 As opposed to bottom-up scoring methods described in the text, inference-based approaches have also been pursued, which attempt to quantify the degree of restrictiveness by estimating the effect of regulatory measures on outcome variables of interest, e.g. gravity-type regressions of services trade flows on restrictiveness indices.  When a price elasticity of demand is available, it is possible to convert such quantitybased estimates to ad valorem tariff equivalents of barriers.  While the outcome variables are often sectorspecific, e.g. the number of telephone mainlines in telecommunications, Dihel and Shepherd (2007) employ a sector’s price-cost margin, which enables them to consistently estimate the effect of trade-affecting measures across a range of services sectors.

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