Capturing Knowledge: The Location Decision of New PhDs Working in Industry

1. Capturing Knowledge: The Location Decision of New PhDs Working in Industry Albert Sumell, Paula Stephan, James Adams SEWP 2005

2. Acknowledgements • Part of a larger project that was supported by a grant from the Andrew W. Mellon Foundation • Support has also come from the SEWP and NSF

3. Research Question • Paper examines degree to which new PhDs going to work in industry remain in the state or MSA where they received their training. • Uses data that has only recently been coded from the Survey of Earned Doctorates, NSF. • Focus on PhDs trained in S&E

4. Framing the Issue • Considerable interest in sources of knowledge inputs in the knowledge production function (Griliches) • Knowledge sources external to the firm have received considerable attention • Proximity to knowledge sources seen to be important in facilitating innovation

5. Studies of Knowledge Sources/Proximity • Knowledge sources often measured by such indices as university R&D expenditures in the state or MSA • Jaffe and others have shown there to be a significant relationship between proximity to knowledge sources and measures of innovation • Almeida and Kogut as well as Thompson have shown patent citations to be geographically concentrated

6. Knowledge Sources/ Proximity continued • Audretsch and Stephan flip question and examine extent to which available knowledge is utilized locally by examining the extent to which proximity plays a role in determining formal relationships between university scientists and biotech firms. • A&S find that proximity matters, but not that much; 70% of the ties were non-local. • The location decision of PhDs going to industry provides another lens for studying knowledge sources and the geography/proximity question.

7. PhDs as a Knowledge Input • PhDs possess new knowledge, much of which is of a tacit nature—acquired in the university lab. • Firms acquire knowledge by hiring new PhDs. One means by which knowledge is transmitted between universities and firms. • Placement of new PhDs also builds/reinforces networks and provides human capital to the firm. • Surveys indicate that placement of PhDs with industry is one means by which knowledge is transferred from the public sector to industry

8. Why States and Universities Care • Creating a highly skilled work force is one way universities contribute to economic growth • More generally, universities use the economic development argument as a lever for state funds. • Stanford’s role in Silicon Valley, MIT and Harvard’s role in Route 128; Duke and UNC’s role in Research Triangle. • To extent students who go to work in industry leave, one rationale for investing state and local resources in graduate programs is weakened. • Story may be different for private institutions that don’t get funding from state.

9. Overview of Presentation • Data • Summary of findings by state and MSA • Framework for analysis • Empirical results • Conclusions

10. Data • SED asks Ph.D. recipients to “name the organization and geographic location where you will work or study.” • Has never been coded for those going to industry; only coded for those going to academe. • We have coded the firm placements for years 1997-1999; currently updating to 2002. • Data misses individuals who take an academic postdoctoral position before going to industry as well as individuals who have not finalized their work plans at time questionnaire is filled out.

11. Summary of Data • 17,382 Ph.D.s in S&E during 1997-1999 period planned to work in industry. • 10,132 trained in “exact sciences” and engineering had made a definite commitment and identified specific firm

12. Firm Placement of New S&E PhDs by Field of Study

13. Industrial Employment Benchmarks for 1999 • 37% of all seasoned S&E PhDs were working in industry in 1999 • Greater than 50% in chemistry and in engineering • 33% in math/computer science • 25% in life sciences

14. Findings with Regard to Retention of Newly Trained PhDs • 37% remain in the state where trained • 20.5% remain in PMSA where trained • Substantial variation in retention rates across regions, states and MSAs

15. Percent Staying In State of PhD

16. Percent Gain or Loss In the State of PhD

17. Certain States and Regions Stand Out • Pennsylvania retains 23.9% • Indiana retains 12.2% • Wisconsin retains 18.8% • Pacific retains 69.4% • Much of this is a Midwest story—major source of new PhDs; Midwest states retain only 25%

18. Top 25 Producing MSAs of Industrial PhDs Top 25 Producing MSAs of Industrial PhDs

19. Top 25 Destination MSAs of Industrial PhDs

20. Considerable Overlap • Eighteen metropolitan areas are in the top 25 in producing and employing • Some major producers have low retention rates: • Urbana-Champaign—3.2% retention • Lafayette, Indiana—2.9% retention • State College, Pa—3.3% retention • Madison—7.7% retention

21. Top 5 Producing CMSAs

22. Next 6

23. Conclusions • Stay rates vary considerably by state • Pacific region is a net importer • California plays a special role: produces more, retains more and hires more from out of state • Major brain drain from Midwest. • Indiana PhDs most likely to find employment in other states: Stay rate is only 12%

24. Empirical Analysis • View migration as an investment decision • Analysis focuses on whether the PhD leaves either the state or the city of training • Individual is the unit of analysis

25. Variables • Three sets of variables: • Variables that reflect attributes of state and local area • Variables that reflect individual characteristics • Variables that reflect field differences, and institutional characteristics • Logit equations estimated; marginal effects reported

26. Findings (Tables 6 and 7) • Certain demographic factors affect mobility in expected way: marital status, being a temporary resident. • Where you went to high school and college matters • Networks matter: those who worked are more likely to stay; those who are returning to a job are more likely to stay. • Those with debt more likely to leave

27. Some of these effects are quite large • Temporary residents 7 percent more likely to leave state or MSA. • Those who earn PhD in same state they went to college in are 12% more likely to stay in state; 4% more likely to stay in city. • Those who got PhD in same state they went to high school and college in are 18% more likely to stay in state

28. “Best” are more likely to leave • In five of ten fields studied (engineering, biology, chemistry, math and medicine) individuals trained at a top program are significantly more likely to leave state than are those from “non-top” programs • Marginal effects can be quite large—math 10% • Four of top program variables negative and significant in the PMSA equation • Individuals supported on fellowships more likely to leave

29. Technological Infrastructure Matters • More likely to stay in state higher are state industrial R&D expenditures • More likely to stay in PMSA higher the patent count; larger the Milken index • What we call absorptive capacity matters as well: • ABPhDi= (NPhDIi /PhDIi)/(ΣNPhDIi/ΣPhDIi)

30. Per Capita Income • Individuals are more likely to stay in states with higher per capita income. • We do not find per capita income to be significant in PMSA equation

31. Public Results • Limit analysis to public institutions • Results are reasonably similar • Finding that many of the “best” leave persists • In terms of quality • In terms of having been supported on a fellowship

32. Role of local amenities • Sumell is using data to explore the role that local amenities play in attracting PhDs to work in an area. • Estimates a nested logit model of location decision of new PhDs • Has numerous measures of amenities—including natural and publicly provided • We explore degree to which the decision to remain in PMSA is affected by relative desirability of local area with regard to sun light, temperature and humidity

33. Variables/results • Relative measure of January and July temperatures • Relative measure of January sunlight • Relative measure of July humidity • Results are counterintuitive: suggest individuals are more likely to leave sunny winter climates and stay where temperatures are considerably higher in the summer

34. Conclusion • States and MSAs capture knowledge but not at an overwhelming rate. • Whose knowledge is captured? Certain characteristics predispose individuals to stay • Married, returning to a job, home grown • “Best” are more likely to leave; • Quality of program • Fellowship support

35. Conclusion continued… • S&Es more likely to stay in high tech areas as measured by patent counts, R&D expenditures, etc. • Absorptive capacity matters

36. Proximity • When knowledge is tacit, proximity matters • But proximity to what? Simplifying assumption is that tacit knowledge sticks to its source: the University. • Our research reminds us that tacit knowledge is not as sticky to the university as some would think. • It’s proximity to scientists that matter and scientists—especially freshly minted scientists—are mobile; tacit knowledge becomes embodied in an input to the firm • Reminiscent of Audretsch and Stephan work that finds that proximity matters but it doesn’t matter that much. • University and state capture but a small piece of this.

37. Raises the Question: Is Proximity to the University Overemphasized? • Carnegie Mellon survey of firms asks for sources of public knowledge • The top source (publications/reports) does not require proximity to knowledge source. • Second source facilitated by proximity but proximity not essential (informal information exchange, public meetings or conferences and consulting) • Next tier includes recently hired graduate students—we’ve just shown proximity not that important.

38. Conclude • If firms know what they are looking for, proximity to the university is not that important. Firms can “buy” the input. (Relates to a Mansfield result) • Proximity to the university is most important when firm does not know what it is seeking or does not want to heavily invest in search.

39. Nonappropriability? • Discussion raises further question of degree to which spillovers result from nonappropriability • Tacit knowledge comprises an important component of the knowledge that new PhDs transmit to firms. • Yet tacit knowledge (Zucker, Darby, and Brewer 1998) facilitates excludability • Means that knowledge transmission can result from maximizing behavior of scientists who have the ability to appropriate the returns to this tacit knowledge rather than from nonappropriability

40. The state perspective: Why? • States often invest in higher education with conviction that it stimulates economic development. • Universities use such an argument as a lever for resources. • Our work casts doubt on benefits states realize from one piece of the investment: doctoral students.

41. Why continued… • Are benefits produced while students sufficient? • Meet state R&D needs? Purdue supplies 21% of Indianapolis industrial hires • Is halo of having a top rated program beneficial to state in other ways? • Is what we observe an indication of disequilibrium? • Can “Purdues” and “Illinoises” continue? • Are policy makers ignorant of degree to which it is a leaky system? • Is small firm lobby extremely effective? • Do results explain investment in the margin in science parks, venture capital funds, etc? Case of University of Minnesota

42. Usual Caveats • Data base misses individuals who do not have definite plans; individuals who go from post doc to industry are not counted in industrial employment. • Econometric issues: modeling spatial effects; selection bias in terms of who answers the questionnaire. • 1997-1999 were boom years in the U.S.; may cloud the results

43. Interested in the data? • Workshop sometime next fall • NSF/SEWP sponsored • Focus on uses and potential uses of SRS generated NSF data on scientists and engineers • Let me know if you or a student/young researcher are interested in participating