# **4. Results**

This section reports the results of both approaches in similar subsequent manner. The results of the cross‐country regressions are given in Tables 3 and 4 in which the LPM and Probit results are reported respectively. The country‐specific results are provided in subsequent tables.

# **4.1 Cross‐Country Results**

For the LPM regressions in Table 3, results are in all but one occasion insignificant, meaning that in most cases no statistically significant correlation is found between the data linkage variable and firms’ innovation activities. That is, restrictive policies in data do not show any meaningful correlation with respect to the firm’s choice to introduce a new product or service as shown in column 1, or to introduce a new organizational procedure as reported in column 2, or to spend more on R&D as shown in column 4. However, the data linkage variable does come out statistically significant in column 3 which shows that restrictive data policies are significantly negative correlated with whether a firm takes on a technology that is licensed from a foreign company.

The results for the Probit regressions reported in Table 4 are consistent in the sense that the coefficient result in column 3 are now estimated with precision. This means that more restrictive data policies are significantly correlated with a lower likelihood of firms to acquire a technology licensed from a foreign company. Taking into account that the marginal impact of changing the data policy index is not constant, a one‐unit increase in restrictions as part of the data‐linkage index variable is therefore associated with a lower probability by firms to use foreign‐licensed technology. The other three innovation variables remain again insignificant even though the sign in columns 1 and 4 give a negative direction, which in the LPM regression was not the case. Note as well that the coefficient sizes increase substantially compared to the LPM results.

The fact that the variable of foreign licensed technology is significant may raise potential suspicion. For instance, one could suggest that the foreign technology that is licensed may also include software, which therefore may be correlated with our data policy index. This is because of the multiplicative term of the data‐linkage variable in equation (2) also includes the extent to which each sector uses software. However, a closer look at the Enterprise Survey variable description states the survey question as: “Does this establishment at present use technology licensed from a foreign‐ owned company, excluding office software?” Hence, we are assured that no artificial or spurious correlation is being picked up in our regressions.<sup>10</sup> On the contrary, given that the coefficient results are significant, it seems likely that foreign licensed technology as part of a firm’s innovation activity is related to a country’s framework of regulatory policies in data. Moreover, higher levels of data restrictiveness found in countries appear to hamper firm‐level innovation in sectors that are more intense in using software.

> effectively means that mathematical computations of our econometric performance exceed the limit for the largest number representable when an attempt is made to calculate the binomial coefficient. 10 See the Enterprise Surveys Indicator Description, page 112, which can be found here:

‐ <u>https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Indicator Descriptions.pdf.</u> 12