Migration of Chinese scientists and their productivity 1998-2006--some preliminary findings

George Mason UniversitySchool of public policyFangmeng (Tim) Tian

10/19/2010

Introduction

A PhD candidate of policy study A student of migration Focus on skilled emigration Target population: Chinese scientists in the

Jiaotong 500 universities

Literature review I- Brain drain’s negative impacts

Lose skilled labor (Bhagwati et al 1974) Reduce economic scale (Miyagiwa1991) Change skill composition (Haque & Kim 1995) Distorting learning incentive (Maria &

Stryszowski, 2009) Hinder human capital accumulation (Wong &

Yip, 1999) Critique: many mathematical models,

unrealistic assumptions, a few empirical studies

Literature review II- Brain circulation’s positive impacts From human-capital approach to network

approach, particularly relevant to S&T At least some emigrants return and bring

back capital and technology (Kapur, et al. 2001; Saxenian, 2005).

The diaspora send back remittance and transfer knowledge (Ratha 2003; Thorn and Nielsen 2006 ).

Critique: more about organizations than individuals; lack of systemic evidence

Research design

Central question: How did migration of scientists affect Chinese researchers’ productivity and China’s science development in the period 1998 – 2006?

Research goals

1. evaluate the benefits of return migration and the scientific diaspora

2. examines the role of international migration on scientists’ productivity and career development

Three data sources

survey + CV + bibliometric data

Selected key questions

What were China’s direct and potential losses due to

emigration of its students and scientists? Were the scientists exchange between the U.S.,

China, and other foreign countries positively or negatively selected?

What kind of emigrant scientists are more likely to collaborate with domestic scholars?

Did returnees experience a productivity loss after they went back to China?

How much did returnees obtain productivity gain by overseas experience in the short and long term?

Dependent variables

Variable Definition

General productivity

Fractionalized number of SCI papers weighted by citation counts in a three-year window

Highest performance

Quality level of a scientist’s single most cited paper

International collaboration

Number of Internationally coauthored papers of overseas scientists

Collaboration with China

Number of an overseas scientist’s papers coauthored only with domestic scientists

Independent variables

Age/cohort (gra-year of BS) Quality of doctoral education (university

ranking of highest degree) Working environment (research ranking of

affiliated university) Professional status (assistant prof.-full prof.) Field: physics, biology, chemstry, math Migration status (stayers, returnees,

emigrants)

Target Population A scientist in the sample is required to be a Chinese

researcher currently employed by a global leading university in the English academia.

Chinese: those who were born in mainland China, and obtained a BS degree (Bachelor of Science) at a Chinese university after 1978.

English academia: United States, United Kingdom, Canada, Australia, New Zealand, Hong Kong and Singapore + mainland China

Global leading university: around 250 top universities in the seven English-speaking countries and about 20 Chinese universities

Only four fields: math, physics, chemistry, biology

Data Collection – Survey, CV, and SCI

The population size is about 7000: 5500 domestic scientists and 1500 overseas scientists.

By far I generated a sample of 305 scientists, all of whom got their PhD before 2008.

Collect SCI publication records in 1998, 2002, and 2006

Citation counts of each paper in the following three years

Collaboration with China/foreign partner of each paper

Education background1

BS

Rank

Example %

1 PKU, Tsinghua 9.41

2 Zhejiang,Fudan 25.95

3 Shandong 31.42

4 Tianjin 3.31

5 Rest 29.9

PhD Rank JT 500 rank %

1 1-50 11.66

2 50-100 6.75

3 101-150 3.44

4 151-200 2.7

5* 201-300 32.15

6 301-400 9.94

7 401-500 25.03

8 Not on the list 8.34

* Including CAS

1/3 of the scientists got their highest degree abroad (including Hong Kong).

Education background 2

BS gra-year % PhD gra-year %

1977/1983 16.84 1982/1989 5.79

1984/1989 24.35 1990/1996 20.32

1990/1996 33.81 1997/2002 36.08

1997/2003 25 2003/2008 37.81

Selectivity of doctoral education

BS Rank Domestic PhD (%)

Foreign PhD

(%)

1 5.66 16.42

2 22.27 32.85

3 34.18 26.28

4 2.93 4.01

5 34.96 20.44

Selectivity of employment

PhD Rank Domestic Foreign

1 1.85 31.47

2 1.23 20.26

3 1.65 5.17

4 0.62 5.6

5 36.63 23.71

6 12.35 6.47

7 35.8 7.33

8 9.88 31.47

Migration statusYear Stayer Returnee* Emigrant Brain drain

rate

(%)

Returning rate

(%)

1998(%) 59.1 9.8 31.1 31.1 24.0

2002(%) 56.2 5.4 38.4 38.4 12.2

2006(%) 59.5 8.2 32.3 32.3 20.3

*Returnee: those who got an overseas PhD degree.

If we define returnees as those who stayed abroad for at least two years, then the return rate can be boosted to over 50%.

Affiliation in 2006

Domestic Chinese scientists

UnivRank

JT 500 rank %

5* 201-300 44.65

6 301-400 12.14

7 401-500 40.74

8 Not on the list 2.47

Overseas Chinese scientists

Univ

Rank

JT 500 rank %

1 1-50 28.02

2 50-100 21.55

3 101-150 6.9

4 151-200 5.6

5 201-300 23.28

6 301-400 6.47

7 401-500 2.59

8 Not on the list 5.6

* Including CAS

Research output and average productivity

Research output of Chinese scientists by location

0

500

1000

1500

2000

2500

1998 2002 2006

Domestic Overseas

Average productivity of Chinese scientists by location

0.01.02.03.04.05.06.07.08.09.0

1998 2002 2006

Domestic Overseas

Individual and team highest performance (75% percentile)

Individual highest performance

0.0

1.0

2.0

3.0

4.0

5.0

6.0

1998 2002 2006

Domestic Overseas

Team highest performance

0.0

5.0

10.0

15.0

20.0

25.0

1998 2002 2006

Domestic Overseas

International collaboration

International collaboration of Chinese scientists

0.0

5.0

10.0

15.0

20.0

25.0

30.0

1998 2002 2006

%

domestic with foreign

overseas with domestic

Regression analysis

Using individual general productivity as the dependent variable, I found migration status (stayer, returnee, emigrant) is highly signficant.

The dummy value “returnee” is negative, which might indicate that returnees are negatively selected, after other factors are controlled.

Tentative conclusions

Chinese scientists live in a merit-based world, and the road to a prestigious position is highly selective.

In terms of both quantity and quality, the productivity gap between domestic and overseas Chinese is getting narrower.

International collaboration has grown proportionally between domestic and overseas Chinese.

Returnees contribute a lot to the research activities in China, but they might be negatively selected compared with emigrants.

What I’m going to do next…

Second wave of survey and expand the sample to be 500 observations.

Weigh the sample to be more representative Decompose the change of research output Design a mathematical model and explain the

conditions for an optimal research output Estimate the research output under different

conditions

Thank you!

Questions and comments?

Appendix: policy implication

Policy Sending country Receiving country

Higher education policy

Improve the quality of teaching

Target certain types of students from the sending country

Science

Policy

Provide conducive research environment; merit-based recruitment

Encourage collaboration with the sending country

Migration policy

Target certain types of returnees; mobilize diaspora

Change selection criteria

Foreign policy Enhance relationship with host countries

Facilitate brain circulation; particularly return migration