Turning to our next set of labor policy variables, we experiment with each of the three composite _de jure_ measures of employment protection separately. Since each on its own is intended to be a comprehensive index of labor market regulation, including more than one at the same time, introduces multicollinearity. The estimated coefficients on the ILO’s measure are small and never reach conventional thresholds of statistical significance. The estimated coefficient on the EPL measure constructed by OECD-IADB, however, is large and statistically strongly associated with digital technology use by businesses, but not by households: more restrictions on the employment decisions of firms are associated with lower levels of digital technology usage. With respect to the size of estimated coefficient, our PCA index of employment protection from the Doing Business data performs similarly to the OECD-IADB measure, and shows the same levels of statistical significance (at the 1 percent level). A more restrictive regulatory framework on firms’ human resource decisions, as measured by Doing Business LMR composite variable, is strongly associated with less use of digital technology by firms. While the sign of the estimated coefficient on our PCA measure is also negative with respect to household usage, it is considerably smaller and the significance (at the 5 percent level) is not as strong.

A valid concern is that the strength and statistical significance of our Doing Business LMR PCA measure of employment protection might be driven by the much larger sample size of countries that it covers relative to the number covered by OECD-IADB’s EPL and ILO’s index. We test the robustness of our results to changes in the sample, by estimating the multivariate correlation using each of the three measures (along with the contextual control variables) but for a sample of the same countries. The OECD-IADB and our PCA measures cover 60 countries in common. The coverage overlap between our measure and that of the ILO is 71 countries. Running our multivariate correlations for our measure of digital technology use by businesses in a country, we find that our Doing Business PCA measure of employment protection remains negative and significant (at 1 percent) to this change in sample (see Table 6).

However, as discussed in prior sections, the composite measures of employment protection are useful, but blunt instruments for analysis. It is likely that different dimensions of employment regulation will affect firms’ decisions in different ways. This is clear in Alesina, et al., (2015) and in the differing signs on the coefficients we estimate for the statutory minimum wage and employment protection. There is further nuance in the effects of regulatory instruments to be found. We examine this possibility by replacing our PCA composite measure of employment protection with the four separate measures constructed from the Doing Business LMR data. Of the four, the strongest and most consistently significantly, negatively associated with firms’ digital technology use, is our measure of procedural difficulty of dismissing workers ( _ldif_firing_idx_ ). This contrasts with our PCA measure of the financial costs of dismissal, which is positive but does not appear statistically significant in any of the specifications.

As with the level of the statutory minimum wage, the possible economic explanation for this statistical relationship is straightforward. All other things equal, more onerous procedures on firms’ choices of productive inputs impede businesses’ ability to adopt and adjust to new technologies. If firms are more constrained in their human resource decisions, they will find it more difficult to embed new technologies into their production models, to adopt the processes that the new technologies entail, and to find the complementary labor and human capital they require to reach a new optimal level of operation. And although none of our other three PCA measures of 18