modestly larger θ values that are statistically significant. While the larger standard errors are evidence of non-trivial empirical strain from “doubling down” on the Anglo-Saxon exclusion idea, this robustness check is quite valuable for asserting that the measured effects do not display first-order evidence of reverse causality, recognizing the limits of empirical tests for ruling out these alternatives.

More deviation, however, is observed in Column 4 when using the technology-to-industry concordances that emphasize where manufacturing occurs, rather than where technologies are used. The main estimations focus on industry-of-use, affording a composite view of the technological opportunity developed for an industry. Keller (2002b) reports inter-industry R&D flows aid productivity growth significantly within OECD countries, equal to half or more of the ownindustry development. Estimations with manufacturing industries support the using-industry specifications in a weighted format, albeit with larger standard errors. Unweighted estimates have a zero-valued first stage that prevents further analysis. This difference emphasizes the importance of technology adoption behind the labor productivity results.

Columns 5-9 test variations on the construction of M %i,c,1980. Columns 5 and 6 show that very similar results are obtained when using first- or later-generation migrants for defining the spatial patterns of migrants. This comparability is not surprising given the persistence of ethnic enclaves in the United States and their attraction of new immigrants from the home country. This stability suggests that the results are not being influenced by endogenous migrant decisions about which cities will show particular strength in patenting growth for certain industries. Columns 7 and 8 show similar results when using bachelor’s educated workers from a country’s ancestry versus those without bachelor’s degrees, with the weighted estimations somewhat favoring the distribution of bachelor’s educated workers. Overall, these variations suggest a strong stability to this part of the IV’s construction. Finally, Column 9 shows the results strengthen slightly when using the 1990 city distribution of ancestry stocks for each country. The ancestry variable in the 1990 census is comparable to that in the 1980 census, albeit with slightly less detail. While it is better to focus on the 1980 distributions given that they are fully pre-determined for the sample period, this stability to using 1990 distributions is quite important given the substantial filed over the prior three years. This fixed window uses application years for patents and their citations. A threeyear window focuses on recent knowledge development; a fixed window is also important for having a uniform approach over the sample period, as the ethnicity of inventors can only be determined on patents granted after 1975 when the inventor records become digitized. From this citation set, the procedure next estimates the USbased inventor share of cited work that is not of Anglo-Saxon ethnicity. This is a share-based measure given that patents cite multiple prior patents and most patents have multi-inventor teams. The additional weighting applied to patents is one minus this share. This creates effectively a double weight that multiplies the share of the patent’s own inventor US-based team that is of Anglo-Saxon origin with the added weight based upon the patent’s citations.

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