in Annex 6). Setting the aggregation parameter to unity in equation (1) yields the arithmetic average as a special case of the CES with weights. We are therefore not stepping outside the framework we have consistently employed thus far. However, the aggregation of scores from ρρ different modes is different from the aggregation of measure scores because in any sector one mode of supply will invariably be more important than others, so that the symmetric treatment of measure scores is no longer appropriate for this step of the aggregation.

The weights for aggregating scores by mode of supply follow largely the ones employed in the previous World Bank STRI database, although certain modifications have led to a slight re-balancing of modal weights. First, unlike the treatment of Mode 4 in the previous World Bank STRD, in which Mode 4 restrictions were confined to professional services sectors only, we now consider policy measures affecting the movement of persons (e.g. prohibition of, or quotas on, intra-corporate transferees) in _all_ subsectors.<sup>27</sup> This coverage is consistent with the OECD policy area “Movement of People” that cuts across all sectors and increases the comparability of restrictiveness scores across both projects.

Second, the more comprehensive coverage of policy measures in this update also improves modal coverage directly or indirectly. For instance, Mode 1 is now covered as well in distribution (wholesale/retail), rail and road sectors, respectively (only Mode 3 used to be covered in the previous World Bank STRD). In international air transportation (both passenger and air cargo), the WTO’s “Worldwide Air Liberalisation Index” (WALI) as of 2012 is used to cover Mode 1. The WALI results had to be rescaled to the scaling used in the STRI: rescaled_WALI = (50 - WALI) * 2. This is an imperfect approximation of policy restrictiveness. WALI does not reflect the MFN policy, but rather is a synthetic measure of openness which relates to all services agreements an economy may have signed, and it pre-dates the policy information collected for 2016.<sup>28</sup> However, the importance of cross-border supply for air transport services means that the use of an imperfect approximation results is a less serious distortion than the omission of Mode 1 altogether.

This completes the aggregation of scores from the level of individual measures to the subsector and economy level, respectively. We then aggregate subsector STRIs to obtain sector-level and economy-level STRIs, respectively, using the weights provided in table 6.1 of Annex 6. These are based on the value-added weights of services sectors of individual economies’ total value added for 2013.

# **Decomposition of changes in STRI scores in 2008-11 vs 2016**

In this section we offer a comprehensive decomposition of differences in STRI scores across 200811 and 2016, respectively, to transparently identify the reasons for those changes. It is tempting to attribute any observed change in STRI scores between two periods in time to a corresponding change in policy regime, but in fact it could also be due to improvements in the quantification method (i.e. introduction of the algorithm and use of the CES aggregation method), or changes in the sectoral scope of the STRI. Hence, for the 55 economies covered in both periods, we map the scores from the earlier (2008-11) World Bank database against the new scores in the STPD as of 2016 and disentangle the three components that each play a role—to a varying degree—in driving the overall observed change in scores: (i) changes in the quantification methodology, (ii) actual changes in policy regime, and (iii) changes in sectoral scope.

- i. For this first level of analysis we use the 2008-11 raw policy data and aggregate these scores alternatively with the original methodology previously used by the World Bank and the improved 2016 methodology (i.e. introduction of the algorithm and use of the CES aggregation method),

> 27 Cross-sectoral differences in the relevance of Mode 4 measures are accounted for at the level of individual measure scores.  For instance, a quantitative limit on intra-corporate transferees attracts a restrictiveness score of 0.125 in professional and transport subsectors and a score of 0.25 in all other sectors where the use of ICTs is more widespread.

> 28 WALI is a synthetic measure of the openness of the air transport policy of a given economy. It is calculated as an average of the air liberalization indices of all the Air Services Agreements concluded by that economy, weighted by the respective traffic they cover. WALIs are computed for all four ALI weighting systems. Further assumptions are required to utilize the BASA-based WALI for gauging restrictiveness in air <u>cargo transportation.  We assume that (1) roughly 50% of air cargo travels in the belly hold of passenger</u> aircraft, and (2) mode 1 trade using dedicated cargo carriers is essentially open.  Combining both, we use a weighted average of (0.5*rescaled_WALI + 0.5*0) for mode 1 air cargo transport. It is also important to note that the same index was used for 2008-11.

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