Labor Mobility Foster Innovation? Evidence from Sweden

1. Labor Mobility Foster Innovation?Evidence from Sweden Pontus Braunerhjelm, Ding Ding and Per Thulin Royal Institute of Technology Department of Industrial Economics and Management

2. Structure of the Presentation

3. Why is this interesting? (Motivation) Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Labor Market

4. Why is this interesting? (Motivation) Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Labor Market

5. Why is this interesting? (Motivation) Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Firm Labor Market Non-PatentingFirm Patenting Firm

6. Why is this interesting? (Motivation) Patenting Firms Patenting Firms Firms Non-Patenting Firms Non-Patenting Firms Turnover from Firm’s perspective

7. Why is this interesting? (Motivation) Patenting Firms Patenting Firms What if the job switching cross region? Firms Difference? Non-Patenting Firms Non-Patenting Firms

8. Why is this interesting? (Motivation) Patenting Firms Patenting Firms What if the job switching cross region? Firms Difference? ? Non-Patenting Firms Non-Patenting Firms

9. Why is this interesting? (Motivation) Patenting Firms Patenting Firms Firms Difference? ? Non-Patenting Firms Non-Patenting Firms What kind of workers we focus ?

10. Defined: R&D Workers According to Swedish Standard Classification of Occupations (SSYK). According to Swedish Educational Terminology (SUN2000).

11. Defined: R&D Workers According to Swedish Standard Classification of Occupations (SSYK). According to Swedish Educational Terminology(SUN2000).

12. Defined: R&D Workers • Support Worker： • Job Function as Technicians and associate professionals(head group NO.3) • Hold at least a bachelor degree or beyond in Nature, Technical, Agriculture or Health Science.

13. Defined: R&D Workers • Professional Worker: • Job Function as Professionals (Head Group No.2) • Hold at least a bachelor degree or beyond in Nature, Technical, Agriculture or Health Science. • Support Worker： • Job Function as Technicians and associate professionals(head group NO.3) • Hold at least a bachelor degree or beyond in Nature, Technical, Agriculture or Health Science.

14. Defined: R&D Workers • Intra-region • Inter-region

15. Defined: R&D Workers • Intra-region • Inter-region

16. Defined: R&D Workers • Intra-region • Inter-region

17. Defined: R&D Workers • Intra-region • Inter-region

18. Previous Research • Almeida and Kogut (1999) : In Silicon Valley, engineers who move inter-firm are the major patent holder. • Agrawaland Cockburn et al (2006) : Social relationship stimulate the knowledge flow. • Oettl and Agrawal (2008) : The former firm lost the human capital but receive the knowledge flow from worker’s new firms. • Kaiser and Kongsted et al (2011) : Between Danish firms, there exist positive relationship between labor mobility and the firm’s innovative activity. This relationship is stronger if workers join from innovative firms.

19. Hypotheses (Research Question) • Hypothesis 1: We expectinter firm labor movement of R&D workers increase the knowledge flow and represented as an increase of the number of patent application. • Hypothesis 2: We expect the effect the the labor mobility of R&D workers who comes or goes to a firm had patent application before, is stronger. • Hypothesis 3: We expect the effect the inter-regional labor movement is stronger, due to the knowledge similarity in same region. • Estimator: Negative Binomial Regression (Count data)

20. Methodology QL denotes quality-adjusted labor input, K refers to the physical capital stock. Normalizing marginal productivity for Stayers to one. Sub-index St denotes stayers, J,Pjoiners from patenting firms, J,NPjoiners from non-patenting firms, Gjoiners from tertiary education, Susupport workers, L,Pleavers to patenting firms and L,NPleavers to non-patenting firms, Oj other joiner without former firm’s information, Else the rest labor.

21. Pre-sample estimation (1987-2000) Equal to 1 if the firm had ever innovated during the pre-sample period.

22. Controls

23. Data From 1987, the data include 24,649 observations, 8573 unique firms and 154,642 patent application. Contains 1,137,028 firms and 1,214,900 establishments. • Exclude firms from public sector • Exclude firms founded during estimation period • Exclude firms without R&D workers • Covers 2001 to 2008

24. Descriptive Statistics Firms had no patent application during pre-sample period. Firms had patent application during pre-sample period.

25. Descriptive Statistics Firms had no patent application during pre-sample period. Firms had patent application during pre-sample period.

26. Descriptive Statistics

27. Descriptive Statistics

28. Descriptive Statistics

29. Descriptive Statistics

30. Descriptive Statistics High Turnover

31. Results-Joiner Different Types of R&D workers Different Types of R&D workers The number of total Employee The number of total R&D workers

32. Results-Joiner

33. Results-Joiner

34. Results-Joiner

35. Results-Leaver and Others

36. Results-Leaver and Others

37. Results-Leaver and Others

38. Results-Leaver and Others

39. Results-Leaver and Others

40. Results-Leaver and Others

41. Results-Firm Controls and Pre-Sample Controls

42. Conclusion • Labor Mobility increase the knowledge flow. • Joiners from patenting firms have stronger effect compare to joiners from non-patenting firms to innovation activity. • Inter-regional joiner from patenting firm have a stronger effect compare to intra-regional joiner to innovation activity. • Inter-regional joiner from non-patenting firms have a positive effect to innovation activity.. • Gradates, Other joiners and support workers have positive effects to innovation activity.

43. Conclusion • Inter-regional leaver to patenting firms have a positivity effect but less significant. • Leavers to non-patenting firms have a negative effect to innovation activity. • Robustness Test shows the result are stable.

44. Thank you very much.