financial services industry. On the other side of the spectrum (not shown in the figure), sectors such as furniture, construction, sale of motor vehicles and wearing apparel are shown to be least data‐ intense. The middle‐range of sectors using software intensively is a mix of modern and traditional sectors such as transport services and various manufacturing industries such as basic metals.<sup>4</sup>

# **3.3 Data Policy Index for Digital Innovation**

<mark>The second term of our data linkage variable is the data policy index, which is based on a quantifiable set of country‐specific regulatory policies which are expected to have a restrictive impact on digital innovation. These restrictive policies relate to the use and transfer of data,</mark> IPR, intermediate liability, content access, as well as regulatory policies regarding the telecommunication marke <mark>t. We draw on Ferracane</mark> _<mark>et al.</mark>_ <mark>(2018a) and ECIPE’s Digital Trade Estimates (DTE) database to develop and construct this index.</mark><sup>5</sup> <mark>The policies used for the analysis are those considered to create a regulatory cost burden for firms relying on data for their innovation activities. The criteria for listing a certain policy measure as a restriction in the database are the following: (i) it creates a more restrictive regime for online versus offline users of data; (ii) it implies a different treatment between domestic and foreign users of data; and (iii) it is applied in a manner considered disproportionately burdensome to achieve a certain policy objective.</mark> The data policy index is composed of 6 different categories, each containing a set of policy restrictions related to a specific digital policy field which are: Intellectual property rights (IPR), cross‐ border data flows (CBDF), domestic use and processing of data (DP), intermediate liability (IL), content access (CA), and finally infrastructure and connectivity (INF). In our view, these categories of data‐related policies present the most important policy restrictions to digital innovation that can be found in East Asia. As said, each category has various specific restrictions which can be further found in Table 1. All restrictions are explained in Ferracane _et al._ (2018), which also provides further information on the motivation for why they form a restriction and discusses the way of scoring their level of restrictiveness. The index covers the years 2009‐2019. In addition, the policies in the index have been updated with new regulatory measures found in each country.

<mark>To build up the index, each specific policy measure receives a score that varies between</mark> 0 (completely open) and 1 (virtually closed) <mark>according to how vast its scope of restrictiveness is. A higher score represents a higher level of restrictiveness in data policies.</mark> While certain data policies can be legitimate and necessary to protect non‐economic objectives such as the privacy of the individual or to ensure national security, these policies nevertheless create substantial costs for businesses performing data‐related innovation activities and are therefore taken up in our index. <mark>Starting from the DTE database, the specific policies are aggregated into an index using a detailed weighting scheme adapted from Ferracane</mark> _<mark>et al</mark>_ <mark>. (2018b), which c</mark> an be found in the last column of Table 1.

4 One noticeable outlier in Figure 1 is the food products sector, which appears to have an extreme above‐ average data‐intensity. One potential reason is that the US Labor Statistics only records employment data for 10 out of a total of 85 6‐digit NAICS sub‐sectors for this industry that all fall into the 2‐digit ISIC industry of food products as measured by the concordance table. Hence, it is very likely that labor is underreported for this sector which as a result increases the data‐intensity given that our measure is expressed as a ratio in which labor forms the denominator. Therefore, in the regressions we exclude the sector of food products although including this sector does not significantly alter the main results.

5 The authors have contributed to the development of the database at ECIPE. The data set comprises 64 economies and is publicly available on the website of the ECIPE at the link: www.ecipe.org/dte/database.

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