international knowledge.<sup>10</sup> Moreover, we allow the standard errors to be adjusted for clustering at the country level to account for possible correlations in technology adoption decisions across firms within a country. Finally, we include sector fixed effects in the probit regressions since sector-specific differences in technology, product demand, or competition can be crucial in determining firms’ incentives to adopt new technology (Cohen and Levinthal, 1989).

A key methodological issue with our estimation needs to be raised at this point. Our main results from probit regressions for ISO-certifications and for web-use are shown in Table 2 using either the BEEPS 2002 sample or the BEEPS 2005 sample and in Table 5 using the BEEPS panel sample.<sup>11</sup> The results in Table 2 are based on cross-sections of firms in ECA countries in 2002 or 2005 and hence can identify systematic correlations but not causation between complementary inputs, market incentives, and access to international knowledge on the one hand and ISO certification or web-use on the other hand. For example, the estimated effects of some of the investment climate factors may reflect omitted managerial ability or other omitted firm characteristics or may suffer from reverse causality.<sup>12</sup> Our strategy to address this problem is threefold. First, our regressions include a large set of firm-level and location-level characteristics (i.e., all the factors linked to complementary inputs, to market incentives, and to access to international knowledge) therefore minimizing the possibility that the estimates suffer from an omitted variables bias. However, our findings based on the cross-sections of firms in 2002 and in 2005 could still be partly driven by unobservable firm characteristics. Second, to compute our infrastructure and governance indexes, we average firm responses to the corresponding survey questions (listed in Appendix Table 1) at the location level to correct for the potential endogeneity of firm perceptions on the quality of infrastructure and governance. The probit regressions can thus exploit the within-country variation in those investment climate factors. Third, we estimate our main specifications based on the BEEPS panel sample which allows us to control for unobserved firm invariant characteristics which may influence both the technology adoption decisions as well as their correlates. The disadvantage of this approach is the short panel dimension of the data (only two years of data per firm) and the smaller sample size of the panel relative to the cross-sections. With these caveats in mind we now discuss our main findings presented in Tables 2-5.

> 10 Including country fixed effects in the probit regressions is not feasible in our framework due to their collinearity with the infrastructure and governance indexes which are location specific.

> 11 All tables report the marginal effects from probit regressions at mean values of the independent variables. 12 Firms with more able managers are more likely to adopt advanced technology but are also more likely to hire a larger share of skilled workers and to participate in export markets. Thus, the effect of the share of skilled workers and of export shares in the technology adoption regressions may simply reflect omitted characteristics.

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