Nathan Goldschlag

Wrapping it up in a person: Examining employment and earnings outcomes for Ph.D. recipients

Tracking the knowledge economy Although the U.S investment in scientific research can be documented readily, its output is harder to track. Zolas et al. combined data obtained from eight universities on their doctorate recipients with data from business registries and the U.S. Census Bureau. This allowed them to link Ph.D. recipients to all their subsequent employers. Doctoral recipients tended to stay in academia or join large companies with high salaries. Roughly 20% stayed in the state in which they received their degree. In the year after receiving a Ph.D., mathematicians and computer scientists received the highest salaries, and biologists received the lowest. Science, this issue p. 1367 Researchers’ career patterns can provide a means to move knowledge from the university to the broader economy. In evaluating research investments, it is important to establish whether the expertise gained by researchers in conducting their projects propagates into the broader economy. For eight universities, it was possible to combine data from the UMETRICS project, which provided administrative records on graduate students supported by funded research, with data from the U.S. Census Bureau. The analysis covers 2010–2012 earnings and placement outcomes of people receiving doctorates in 2009–2011. Almost 40% of supported doctorate recipients, both federally and nonfederally funded, entered industry and, when they did, they disproportionately got jobs at large and high-wage establishments in high-tech and professional service industries. Although Ph.D. recipients spread nationally, there was also geographic clustering in employment near the universities that trained and employed the researchers. We also show large differences across fields in placement outcomes.

Is Regulation to Blame for the Decline in American Entrepreneurship

Mounting evidence suggests that economic dynamism and entrepreneurial activity are declining in the United States. Over the past 30 years, the annual number of new business startups and the pace of job reallocation have declined significantly. We ask whether this decline in dynamism can be explained by federal regulation. We combine measures of dynamism with RegData, a novel dataset leveraging the text of the Code of Federal Regulations to create annual measures of the total quantity of regulation by industry. We find that rising federal regulation cannot explain secular trends in economic dynamism.

Business Dynamics Statistics of High Tech Industries

Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Technology sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. Tracking the performance of this sector is therefore of primary importance, especially in light of recent evidence that suggests a slowdown in business dynamism in High Tech industries. The Census Bureau produces the Business Dynamics Statistics (BDS), a suite of data products that track job creation, job destruction, startups, and exits by firm and establishment characteristics including sector, firm age, and firm size. In this paper we describe the methodologies used to produce a new extension to the BDS focused on businesses in High Technology industries.

An ‘Algorithmic Links with Probabilities’ Crosswalk for USPC and CPC Patent Classifications with an Application Towards Industrial Technology Composition

Patents are a useful proxy for innovation, technological change, and diffusion. However, fully exploiting patent data for economic analyses requires patents be tied to measures of economic activity, which has proven to be difficult. Recently, Lybbert and Zolas (2014) have constructed an International Patent Classification (IPC) to industry classification crosswalk using an ‘Algorithmic Links with Probabilities’ approach. In this paper, we utilize a similar approach and apply it to new patent classification schemes, the U.S. Patent Classification (USPC) system and Cooperative Patent Classification (CPC) system. The resulting USPC-Industry and CPC-Industry concordances link both U.S. and global patents to multiple vintages of the North American Industrial Classification System (NAICS), International Standard Industrial Classification (ISIC), Harmonized System (HS) and Standard International Trade Classification (SITC). We then use the crosswalk to highlight changes to industrial technology composition over time. We find suggestive evidence of strong persistence in the association between technologies and industries over time.

An Anatomy of U.S. Firms Seeking Trademark Registration

This paper reports on the construction of a new dataset that combines data on trademark applications and registrations from the U.S. Patent and Trademark Office with data on firms from the U.S. Census Bureau. The resulting dataset allows tracking of various activity related to trademark use and protection over the life-cycle of firms, such as the first application for a trademark registration, the first use of a trademark, and the renewal, assignment, and cancellation of trademark registrations. Facts about firm-level trademark activity are documented, including the incidence and timing of trademark registration filings over the firm life-cycle and the connection between firm characteristics and trademark applications. We also explore the relation of trademark application filing to firm employment and revenue growth, and to firm innovative activity as measured by R&D and patents. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Proximity and economic activity: An analysis of vendor-university transactions: GOLDSCHLAG et al.

This paper using transaction based data to provide new insights into the link between the geographic proximity of businesses and associated economic activity. It contributes to the literature by developing both two new measures of distance and a set of stylized facts on the distances between observed transactions between vendors and customers for a research intensive sector - universities. We show that spending on research inputs is more likely to be expended at businesses physically closer to universities than those farther away. That relationship is stronger for High Tech and R&D performing businesses than businesses in general, which is consistent with theories emphasizing the role of tacit knowledge. We find that firms behave in a way that is consistent with the notion that propinquity is good for business: if a firm supplies a project at a university in a given year, it is more likely to open an establishment near that university in subsequent years than other firms. We also investigate the link between transactional distance and economic activity and show that when a vendor has been a supplier to a project at least one time, that vendor is subsequently more likely to be a vendor on the same or related project.