**Table 1: Examples of measures, level of restriction and associated score**

|**Level of restriction**|**Examples**|**Score**|
|---|---|---|
|Not restrictive|No restriction on the type of legal entity, no foreign<br>equitylimitation|0.00|
|Not restrictive, but minimal<br>transparencyissue|No provision for prior notice of, or comment on,<br>regulatorychanges|0.125|
|Minor restriction|Acquisition of land and real estate by foreigners<br>prohibited|0.25|
|Neither minor nor major|Limit on number of suppliers|0.50|
|Major restriction|Service<br>provision<br>is<br>reserved<br>for<br>statutory<br>monopolyorgranted on an exclusive basis|0.75|
|Closed|Commercial presence is prohibited|1.00|

While in previous work (Borchert et al., 2012) five different levels of restrictiveness were used (0, 0.25, 0.5, 0.75, 1), the new STRI is based upon six numerical levels, with the objective of the newly added 0.125 bin being to accommodate regulatory measures around transparency that impart only a minor effect on restrictiveness (e.g. publication of draft regulation and opportunity to comment). The aim is to take account of measures that are aspects of the regulatory environment rather than restrictions, not even minor ones, in regard of the actual supply of services but that can nevertheless adversely affect the policy or regulatory environment in which firms operate.

Assigning a restrictiveness score to a single measure is insufficient in some special circumstances. This case arises when policies that we record as separate measures are intertwined and, hence, their restrictiveness can only be assessed by considering the entire bundle of such measures. For example, foreign suppliers can in principle enter through mergers and acquisitions or via greenfield investment, and it does not make much sense to score restrictions for each route in isolation, for they represent alternative options. Rather, the difficulty of entering a market is most plausibly assessed by looking at the admissible combinations of entry options, rather than individual routes. We call such bundles ‘synthetic’ measures as they consist of two or more individual measures that are separate entries in the database, but whose impact on restrictiveness is scored jointly for the purposes of constructing the STRI. Only when the assessment of restrictiveness, i.e. scoring, is complete at the measure level including synthetic measures, does the process of aggregation start.

# **2.3  Aggregation**

In the first version of the World Bank database (2008-11), the associated STRI relied on an assessment of groups of measures, which were encapsulated in a ‘policy summary’. The aggregation methodology described here is similar in spirit in the sense that the overall restrictiveness of a group of policy measures, e.g. at the sector-mode level for a given economy, results both from the types of measures applied as well as from the number of measures applied. The severity of measures is captured directly in the scores assigned to individual measures (Table 1). In a second step, the set of individual measure scores needs to be aggregated for a given sector-mode or even an entire economy.

Aggregation of this kind is a challenge in a wide range of fields, such as in consumer or production theory. One of the most widely used mappings in economics for both utility and production functions is the ‘Constant Elasticity of Substitution’ (CES) functional form, which generically combines an array of elements according to � .<sup>10</sup> With just one parameter ( ), the CES NN αα 1/αα function offers a parsimonious way of calibrating the marginal contribution of an additional unit to ii= (1, ... , NN) xxii XX= ��ii=1 xxii αα an aggregate of utilities, inputs or, in this context, policy restrictiveness. For instance, adding a restrictive measure to a set of other restrictive measures should increase the overall restrictions

> 10 The parameter takes on different interpretations according to the context in which the function is used; for instance, in consumer theory it is related to the elasticity of substitution among varieties consumed ( ). αα σσ

8