In all, therefore, we come up with the following augmented baseline specification in which we interact our services linkage, ������� , with an institutional variable varying by country and time, such that: ������� ������������ ���������� ∗������ ��� � ���� ϛ�� ������ (4) In the process of selecting an appropriate proxy variable for domestic institutions, our experience shows that the variables from the World Bank governance indicators database are highly correlated with each other. Based on Van der Marel (2016) and Beverelli _et al_ . (2015) we select both level of corruption and rule of law, plus a third indicator called regulatory quality and perform a factor component analysis so as to take out the common variation between the three institutional measures. The selection of the third variable is based on the fact that regulatory quality is important proxy indicator for strong and independent regulatory bodies that oversee services markets as outlined in Sàez _et al_ . (2015).

Furthermore, we provide additional interaction effects with variables varying at different levels. One is that we also include our time‐invariant firm‐level foreign share variable to see whether foreign firms are significantly more hurt by regulations, and for which type, as opposed to pure domestic firms. Second, we also develop an industry‐specific variable of see where goods and services sectors are placed in terms of their productivity relative to the so‐called technology frontier. Through this way we have three different types of interaction strategies to see whether essential country, sector and firm characteristics have any differential influence on the relationship between services regulations and downstream economic performance.

# **4 Results**

The results of our baseline estimations are presented in Tables 2 and 3. These tables report the results using our baseline regression as specified in equation (3) using the Ackerberg TFP since this is our preferred measure following the economic literature. Results for the alternative TFP measures (i.e. Olley and Pakes, Levinsohn and Petrin, and Hsieh and Klenow) are presented in the annex (Table A10). Table 2 shows the regression results using country‐specific input‐output coefficients as explained above. The results clearly show that the overall services linkage is significant and negative in column (1).<sup>18</sup> This result suggest that increasing restrictions in service regulation has a negative effect on productivity performance of firms active in both downstream services and manufacturing industries, i.e. the entire economy. When splitting up this overall services index into the two types of regulations of entry and conduct, Table 2 also shows that the variable of entry barriers remains insignificant when entered separately.<sup>19</sup> On the other hand, conduct regulation remains significant with an expected negative sign.<sup>20</sup> The services linkage using FDI restrictions are insignificant. When entering all variables together, conduct

> 18 Results for alternative TFP measures in Table A10 also show a negative sign for overall services linkages as can be seen in columns (1), (7) and (13).

> 19 The same happens for the Hsieh and Klenow TFPQ measure. Yet, the TFP specifications by Olley and Pakes and Levinsohn and Petrin show that entry regulations are significant when entered separately (see Table A10).

> 20 The negative sign of conduct regulation variable remains robustly significant throughout all the remaining three TFP measures although coefficient sizes vary depending on the specific TFP measures (see Table A10).

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