Figure 4 shows a negative relationship once we plot our data policy index of restrictiveness for each East Asian country against our preferred variable of innovation in the computer and related services sector that is found in the Enterprise Survey database. The figure selects the average of the h5 variable, but an equally sharp negative correlation appears for the other innovation variables that have been selected from the same database. Clearly, countries with higher levels of data restrictiveness appear to have lower innovation activities in the computer services sector. China is an interesting outlier in Figure 4. The country is very restricted in data as measured by our data policy index, but at the same time exhibits a very high degree of firm‐level innovation in computer services. This fact is little surprising given China’s fast‐moving activities in the digital field, but the figure also shows that the country is clearly an exception in the region.<sup>6</sup> Another interesting correlation is illustrated in Figure 5. We use a country‐specific variable that is plotted against our data policy index. We take a standard variable that measures how much East Asian countries import digital services as a share of their total commercial services imports. In this case too, we see that a tight negative correlation exists between the two variables. This suggests that countries which are more restricted regarding data policies exhibit a lower share of digital services imports. Although this variable of services trade is not taken up in our econometric analysis, it nonetheless points out to close the link between digital innovation and open markets. The services trade variable measures digital services imports performed over the internet such as software whilst the data policy index captures restrictive trade policies that target digital technologies such as the internet, data and online platforms.

However, in order to formally assess whether across the entire economy of each East Asian country firms in data‐intensive sectors are truly affected in their innovation activities as a result of higher data restrictiveness, the identification strategy takes into account the extent to which each sector is data‐intense by employing a sector’s software use as a proxy, as explained above.

# **3.5 Baseline Regressions**

As previously said, to measure whether the data policy index has any meaningful relation with innovation activities at the level of the firm in East Asian, we employ two regression approaches.

The first approach takes a cross‐country dimension in which we perform regressions for 10 East Asian countries for which we have data. Then, as the next step we select a number of countries for which we have specifically recorded firm‐level data from a national source and evaluate whether our cross‐country outcomes are consistent with these country‐specific regressions. There are two main reasons why we undertake this two‐step approach. One is that the cross‐country exercise tells us something about the differences of countries over time, whereas the country‐specific puts more emphasis on the development of the policy restrictions as such and therefore guides for a more specific policy advice.<sup>7</sup> Also, the two sources of data record different innovation variables, which

> 6 Furthermore, Table A1 in Annex A shows that China’s high innovation activities are not caused by an exceptionally high number of firms recorded in the Enterprise Survey database. Therefore, it means that aggregating the firm‐level innovation variables into an average by country and sector does is not influence China’s extreme position.

> 7 Moreover, there are also technical reasons for why we exploit these two dimensions of data. One is that the source for the cross‐country approach reports years with intervals, is survey‐based and is unbalanced, whereas the country‐specific data are more complete and census‐based. Although one could argue that the latter approach is more meaningful to analyze, exploiting the two approaches is useful because of the reasons

9