8.5Summary of Findings and Discussion of Outcomes

The main findings of this chapter are summarized in Table 8.4. By using regression analyses at the state and county levels, I was able to estimate some externality effects associated with the location patterns of IT and non-IT employment.

Overall, it seems that the location of IT employment does have a positive effect on labor productivity. Surprisingly, results indicate localization diseconomies for traditional, non-IT, employment, and the coefficient corresponding is strongly significantly negative. Even though the data quality has been verified, results should still be interpreted carefully because of the detailed level of data that had to be estimated first and then aggregated. The results show that strong localization economies are associated with IT employment location quotient. This result is also confirmed by the positive effect of the ratio of the location quotients. This means that, with traditional employment remaining constant, if a county doubles its labor force in IT industries by attracting IT employees from other counties in the same state, then labor productivity could increase by 4.6% in that county. In the same fashion, if a county simply doubles its number of IT employees, allowing traditional employment to vary also, gains in productivity amount to 0.5%. Finally, looking at a state map, if the concentration of IT or non-IT employment doubles, then this state will increase its productivity level by 2.8%. Relatively, if the concentration of IT employment doubles, holding the concentration of traditional employment constant, state labor productivity should increase by almost 11%, which seems to be the strongest effect on productivity among all the measures of location patterns.