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Should I Stay or Should I Go . . . North? First Job Location of U.S. Trained Doctorates 19572005 Christopher Ferrall Natalia Mishagina Department of Economics Queen's University November 18, 2008 . . 0. .0.0 I.

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SLIDE 1

Should I Stay or Should I Go . . .North? First Job Location of U.S. Trained Doctorates 19572005

Christopher Ferrall † Natalia Mishagina ‡ Department of Economics Queen's University November 18, 2008

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. Γ. →

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SLIDE 2
  • I. Introduction

International Mobility of New Doctorates

⋄ Research and graduate education take place at the international level. The

U.S. system of postgraduate education tends to concentrate `raw' product which it renes into PhDs that are allocated back throughout the world.

⋄ Public funding is an important factor either directly (fellowships) or indirectly

(quality of faculty).

⋄ Many of the benets from the human capital accrue to where graduates locate

(teaching, specic research)

⋄ The products of the system (the new doctorates) have complex motives: pur

suit of comparative advantage and a bias for returning home independent of career concerns.

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I.Introduction @. →

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SLIDE 3

New PhDs

⋄ Just earned a universally recognized credential ⋄ High degree of international mobility relative to the general population. ⋄ Face demand for their skills that is sensitive to local public policies related to

education, research and immigration.

⋄ The joint effect of these factors has not been considered previously, mainly

due to the limited access to data.

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I.Introduction @. →

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SLIDE 4

Questions of interest

⋄ Is the decision of international graduates to stay related to the background of

the student?

⋄ Is the relative economic situations of the home country important? ⋄ Is the countervailing ow of American graduates taking jobs in other countries

affected by similar issues?

⋄ Are noneconomic policies and attitudes important? ←

I.Introduction @. →

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SLIDE 5

Related Literature

⋄ Conversion of student visas to green cards

Huang (1988); Bratsberg (1995); Finn (2005)

⋄ Brain Drain and Globalization

Commander, Kangasniemi, and Winter (2004); Freeman (2005); Kuhn and McAusland (2006)

⋄ PostDoctoral Science Careers

Mishagina (2007)

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I.Introduction @. →

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SLIDE 6
  • II. Data

The National Science Foundation's Survey of Earned Doctorates (SED)

⋄ Census of all PhDs earned in the US since 1957. ⋄

In 2005 (last year we have):

⋄ 43,000 individuals ⋄ 400 doctorategranting universities ⋄ Response rate of 92%. ⋄ Demographic variables collected over various spans of time ⋄ Consistent questions about postdoctoral plans ←

II.Data @. →

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SLIDE 7

Postdoctoral Plans: Question gives the following choices ...

  • a. fellowship
  • b. research associateship
  • c. traineeship
  • d. residency or internship
  • e. employment
  • f. military service
  • g. other plans (writing a book, homemaking).
  • h. BLANK: coded as not having plans

Another question asks for the location of postdoctoral plans.

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II.Data @. →

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SLIDE 8

Table 1. Summary of Planned PostDoctoral Locations

By Citizenship Observations With Plans* For Those Plans* With Definite For Those Shaded area is the sub‐sample used in the main analysis in section 4.1‐4.2. *** Total Obs X (%With Plans/100) X (% Canada/100) **Other is also referred to as 3CN (third country nationals). *For definition of ʺplansʺ and ʺdefinite plansʺ see section 3 of the text. Other** Canadian American Overall 489,281 19,346 1,083,207 1,591,834 Total 85.1% 89.7% 85.4% 85.4% % With Plans* Location 62.9% 45.5% 96.9% 88.9% USA 1.3% 49.7% 0.7% 1.5% Canada 35.7% 4.8% 2.5% 9.6% Other 100% 100% 100% 100% Total 5,415 8,621 6,478 20,390 Canada*** Total Obs. to 61.8% 78.8% 78.1% 75.7% Definite* Plans are Location 63.3% 43.8% 96.9% 90.0% USA 1.5% 51.6% 0.7% 1.6% Canada 35.2% 4.6% 2.4% 8.4% Other 100% 100% 100% 100% Total

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II.Data @. →

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SLIDE 9

How Denite are Plans?

  • a. Returning to a predoctoral appointment
  • b. Has signed an employment contract
  • c. Still negotiating with one or more employers
  • d. Seeking appointment but no specic employers

Dene the rst two as denite plans.

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II.Data @. →

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SLIDE 10

Table 1. Summary of Planned PostDoctoral Locations

By Citizenship Observations With Plans* For Those Plans* With Definite For Those Shaded area is the sub‐sample used in the main analysis in section 4.1‐4.2. *** Total Obs X (%With Plans/100) X (% Canada/100) **Other is also referred to as 3CN (third country nationals). *For definition of ʺplansʺ and ʺdefinite plansʺ see section 3 of the text. Other** Canadian American Overall 489,281 19,346 1,083,207 1,591,834 Total 85.1% 89.7% 85.4% 85.4% % With Plans* Location 62.9% 45.5% 96.9% 88.9% USA 1.3% 49.7% 0.7% 1.5% Canada 35.7% 4.8% 2.5% 9.6% Other 100% 100% 100% 100% Total 5,415 8,621 6,478 20,390 Canada*** Total Obs. to 61.8% 78.8% 78.1% 75.7% Definite* Plans are Location 63.3% 43.8% 96.9% 90.0% USA 1.5% 51.6% 0.7% 1.6% Canada 35.2% 4.6% 2.4% 8.4% Other 100% 100% 100% 100% Total

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III.Empirical Framework @. →

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SLIDE 11

Table 2. Summary of Variables For Those With Any Plans

Mean By Citizenship Mean By Plans Other Cdn. Amer. Can. USA Mean Obs. Variable / Span of Years 1,072,007 Demographics / 57‐‐‐05 1991 1984 1983 1981 1985 1985 Graduation Year 32.8 34.1 35.1 33.7 34.7 34.7 Age at graduation 0.69 0.76 0.00 0.62 0.12 0.13 Temporary visa 0.96 0.13 0.05 0.24 0.20 0.20 Non‐English* 0.04 0.90 0.01 0.47 0.02 0.02 Francophone* 0.65 0.62 0.67 0.65 0.67 0.67 Married 0.76 0.74 0.67 0.78 0.68 0.69 Male 0.50 0.50 0.49 0.55 0.49 0.49 Married x Male 0.58 0.58 0.57 0.46 0.48 0.57 879,757 Dependents / 57‐‐‐05 0.47 0.47 0.44 0.37 0.33 0.44 Male x Married x Dep. Parents / 62‐‐‐02 0.32 0.23 0.31 0.27 0.31 0.31 Father has college degree 0.19 0.21 0.24 0.21 0.23 0.23 post‐graduate work 0.23 0.29 0.36 0.30 0.34 0.33 Mother has college degree 0.08 0.09 0.12 0.09 0.12 0.11 post‐graduate work 809,922 Race / 72 ‐‐‐‐ 02 0.62 0.08 0.03 0.15 0.14 0.17 Asian 0.05 0.01 0.04 0.01 0.04 0.05 Black 0.05 0.01 0.02 0.01 0.03 0.03 Hispanic 0.28 0.41 0.56 0.47 0.50 0.50 307,859 Has school debt / 82‐‐‐02 0.02 0.11 0.00 0.06 0.01 0.02 562,768 Non‐US‐funded / 86‐‐‐02 1,072,007 University Type** / 57— 05 0.13 0.24 0.11 0.20 0.11 0.12 Topschools & Carnegie 1 0.90 0.91 0.88 0.93 0.86 0.89 Carnegie Category 1 0.07 0.05 0.08 0.05 0.08 0.08 Carnegie Category 2 1,072,007 Field of Study*** / 57— 05 0.03 0.01 0.01 0.01 0.01 0.01 Computer sciences 0.05 0.03 0.02 0.04 0.03 0.03 Mathematical sciences 0.21 0.20 0.18 0.19 0.18 0.18 Life and Health sciences 0.18 0.11 0.11 0.12 0.12 0.12 Physical sciences 0.02 0.08 0.10 0.06 0.09 0.09 Social sciences 0.08 0.11 0.08 0.13 0.08 0.09 Psychology

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III.Empirical Framework @. →

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SLIDE 12
  • III. Empirical Framework

yCDN

io

= y⋆

iCDN − y⋆ iUS

(1) = f CDN

  • (

DEMOi, PGMi, UNIVi, FINi, yi, ERAy(i),∆Uy(i),∆R&Dy(i), ERAy(i)xDEMOi, ) . ⋄ Plan to remain in the U.S. is the default choice. The choice of Canada depends

  • n yCDN

io

, a latent value for graduate i, who has origin (citizenship) o.

⋄ Origin takes on the values American, Canadian, and Other (or 3CN, short for

thirdcountry national).

⋄ Index by o because our preferred specication has originspecic probits. ⋄ Comparison of American vs. Canadian coefcients reects bias for home with

3CN somewhere in between

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III.Empirical Framework @. →

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SLIDE 13
  • IV. North American Options

IV.A OriginSpecic Coefcients Estimate (1) separately for Americans, Canadians, and 3CNs.

⋄ A secular trend for more international mobility (integration) ⋄ Older graduates, females, and married graduates have stronger home bias:

(Respective coefcients are negative for Americans and positive for Canadi ans) For 3CNs: coefcients follow Canadian values in sign but are smaller (in some cases insignicant).

⋄ Graduates from francophone countries more likely to locate in Canada. ⋄ Parental education: only signicant for the much larger American sample.

Increases mobility.

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IV.North American Options A.Origin-Specific Coefficients →

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SLIDE 14

Local Conditions

⋄ Relative unemployment rates: ∆U has a positive coefcient for Americans and

3CNs(??); For Canadians the sign is negative (consistent with local demand correlated with the overall unemployment rate).

⋄ Relative R&D had no signicant effect in the sharedcoefcients model and

reduces the span greatly.

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IV.North American Options A.Origin-Specific Coefficients →

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SLIDE 15

Policy Eras

⋄ Vietnam War: Americans more likely to locate in Canada regardless of gender;

Canadian visa students more likely to move home although the net coefcient is relatively small. For 3CNs large negative effect.

⋄ NAFTA:AmericansandCanadianvisastudentslesslikelytolocateinCanada?? ⋄

post9/11:

⋄ Flow of Americans not signicantly different ⋄ Canadians and 3CNs from Muslim MidEast countries much more likely

to locate in Canada. The 9/11 coefcient is only a fraction of the size of the temporary visa and nonEnglish coefcients, but it is over 10 times the size of the oneyear time trend by origin.

⋄ The net effect for other countries is essentially zero. ←

IV.North American Options A.Origin-Specific Coefficients →

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SLIDE 16

Table 5a. OriginSpecic Coefcients, Part 1

  • program. Standard errors are in parentheses. * indicates significance at the 10% level.

Also included are variables in Table 5b and indicators for race, field of study, and university Estimates of equation of two specifications of (??). Additional variables listed in the following table.

Specification 2 Specification 1 Other Cdn Am Other Cdn Am Variable * 0.012 * 0.041 *

  • 0.014

* 0.009 * 0.043 *

  • 0.019

age

(0.002) (0.002) (0.001) (0.002) (0.002) (0.001)

*

  • 0.237
  • 0.023

*

  • 0.114

*

  • 0.475

*

  • 0.138

*

  • 0.085

non-English hs

(0.04) (0.05) (0.03) (0.03) (0.04) (0.02)

* 0.370 * 0.161 * 1.168 * 0.427 * 0.105 * 1.056 francophone hs

(0.04) (0.05) (0.04) (0.03) (0.04) (0.03)

* 0.770 * 1.649 * 0.800 * 1.686 temporary visa

(0.04) (0.05) (0.04) (0.04)

0.023 * 0.157 *

  • 0.050

* 0.070 * 0.134 *

  • 0.037

married

(0.04) (0.05) (0.02) (0.03) (0.04) (0.02)

* 0.071 *

  • 0.160

* 0.066

  • 0.007

*

  • 0.140

* 0.089 male

(0.03) (0.04) (0.02) (0.02) (0.04) (0.02)

  • 0.015

* 0.211 0.001 0.010 * 0.190

  • 0.009

x married

(0.04) (0.06) (0.03) (0.04) (0.05) (0.02)

  • 0.024

0.045 * 0.049 father college

(0.02) (0.04) (0.02)

  • 0.015
  • 0.015

* 0.058 father grad sch

(0.03) (0.04) (0.02)

0.023

  • 0.041

0.023 mother college

(0.02) (0.03) (0.02)

0.007

  • 0.049

* 0.039 mother grad sch

(0.04) (0.05) (0.02)

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V.Safe European Home @.Origin-Specific Coefficients →

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SLIDE 17

Table 5b. OriginSpecic Coefcients, Part 2

Specification 2 (cont.) Specification 1 (cont.)

significance at the 1% level for race, field of study, and university program. Standard errors in parentheses. * indicates Continuation of Table 5. Estimates of two specifications of (??) by origin. Also included are indicators

Other Cdn Am Other Cdn Am Variable *

  • 0.029

*

  • 0.046

*

  • 0.018

*

  • 0.013

*

  • 0.023

* 0.003 yr of graduation

(0.004) (0.01) (0.003) (0.002) (0.002) (0.001)

* 0.056 *

  • 0.036

* 0.014 * 0.062 *

  • 0.021

* 0.020 D UE

(0.01) (0.01) (0.01) (0.01) (0.01) (0.01)

* 0.210 * 0.134 * 0.173 0.050

  • 0.062
  • 0.001

US/CDN FTA

(0.05) (0.07) (0.03) (0.04) (0.05) (0.02)

* 0.516 * 0.513 * 0.173 * 0.294 * 0.179 *

  • 0.131

NAFTA

(0.08) (0.11) (0.04) (0.06) (0.08) (0.03)

0.101 * *

  • 0.012

xMexican

(0.13) (0.11)

*

  • 0.220

*

  • 0.552

* *

  • 0.251

*

  • 0.598

x visa

(0.06) (0.07) (0.05) (0.07)

0.072 *

  • 0.404
  • 0.022

* 0.137 *

  • 0.171

* 0.291 Vietnam war

(0.14) (0.18) (0.05) (0.08) (0.10) (0.03)

0.002 0.200 * 0.106

  • 0.019

0.067

  • 0.042

x male

(0.13) (0.15) (0.05) (0.06) (0.08) (0.03)

0.156 0.125 * 0.177 * 0.194 x visa

(0.10) (0.14) (0.06) (0.07)

0.104 0.297 0.205 0.009 * 0.138 0.025 Post 9-11

(0.10) (0.30) (0.21) (0.03) (0.05) (0.03)

0.062 * * 0.175 x Mid East.

(0.06) (0.10)

141696 11097 656902 167701 16078 886651 Nobs

  • 11103
  • 5869
  • 20744
  • 14918
  • 8266
  • 33629

log-likelihood

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V.Safe European Home @.Origin-Specific Coefficients →

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SLIDE 18
  • V. Safe European Home

V.A EU15 Subsample

⋄ Subset of 3CNs: citizens of the EU15 countries 1982 ⋄ Trivariate choice: U.S., Canada, `home' ⋄ Consider both unemployment rate and R& D expenditure per capita as

determinants of local demand for doctorates

⋄ Include variables on foreign nancing of education and whether grad

uate has schoolrelated debt.

←

V.Safe European Home A.EU-15 Subsample →

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SLIDE 19

Table 6. Selected Variables for the EU15 Sample

Mean By Plans Can. USA EU-15 Mean Variable 32.3 32.7 32.0 32.5 Age at graduation 0.86 0.60 0.93 0.70 Temporary visa 0.79 0.80 0.90 0.83 Non-English* 0.22 0.13 0.13 0.13 Francophone* 0.06 0.10 0.16 0.12 Has school debt 0.31 0.33 0.27 0.32 Non-US-funded 0.07 0.04 0.02 0.03 Computer sciences 0.09 0.05 0.07 0.06 Mathematical sciences 0.16 0.16 0.15 0.16 Life and Health sciences 0.17 0.14 0.18 0.16 Physical sciences 0.03 0.04 0.03 0.03 Social sciences 0.18 0.11 0.14 0.12 Psychology 0.07 0.15 0.17 0.15 Engineering 0.14 0.26 0.18 0.24 Humanities and Law 0.20 0.20 0.22 0.21 Topschools & Carnegie 1 0.93 0.93 0.94 0.93 Carnegie Category 1 ←

V.Safe European Home B.Nested Logit Model →

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SLIDE 20

V.B Nested Logit Model

zNA

i

= g(DEMOi, PGMi, UNIVi, FINi, yi) (2)

yUSA

io

= λNAzNA + h(U US

y(i), R&DUS y(i))

yCDN

io

= λNAzNA + h(U CDN

y(i) , R&DCDN y(i) )

yEU

io = λEUzEU + h(U EU y(i), R&DEU y(i)).

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V.Safe European Home B.Nested Logit Model →

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SLIDE 21

Table 7. EU15 Nested Logit

EU/US/Can America North z

university type. * indicates significance at the 10% level. Estimates of nested logit in equation (2). Contintent equation also includes race, program and

Standard Error Estimate Variable Level 0.2801 * 2.1030 R&D 10.2492 *

  • 72.8884

UE 0.0060 *

  • 0.0220

age 0.0792 *

  • 0.6081

non-English hs 0.0770 * 0.1448 francophone hs 0.0811 *

  • 2.0954

temporary visa 0.0931

  • 0.0274

married 0.0738

  • 0.1145

male 0.1097

  • 0.1375

x married 0.0543 * 0.1787 debts 0.0663 *

  • 0.3654

foreign_fund 0.0002 * 0.0016 yr of graduation 0.0420 0.0066 EU 0.0547 * 0.2304 North America 27,597 Nobs

  • 5534.3

log-likelihood

←

V.Safe European Home C.Results →

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SLIDE 22

V.C Results Reject nonnested model: there is a bias for returning to Europe.

⋄ Older EU15 citizens on temporary visas with foreign funding from non

English and nonFrench countries strongly favor a return to Europe. Students from francophone countries still favor Europe but much less than those from nonEnglish countries.

⋄ Foreignfunding is important. So is debt, but as a push to North Amer

ica.

⋄ Other demographic variables are not signicant. ←

V.Safe European Home C.Results →

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SLIDE 23

Having controlled for preferences for Europe versus North America:

⋄ Unemployment rates and per capital R&D expenditures help explain

locations.

⋄ Signs are as expected: less local UE and more local R&D help explain

location of Europeans across the U.S., Canada and Europe.

←

V.Safe European Home C.Results →

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SLIDE 24
  • VI. Conclusion

←

VI.Conclusion @.Results →

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SLIDE 25

Recap

⋄ Locations that involve more movement across international borders are more

likely over time, even after controlling for many factors not usually available with other data sources.

⋄ The Vietnam War and post9/11 eras had expected effects on international

location of new U.S.trained doctorates.

⋄ The effects of the North American Free Trade Agreement are less clear. ⋄ Also less clear: extent to which current labor market conditions and overall

expenditure on R&D play a role in attracting new doctorates.

⋄ Factors that should increase a graduates ties to their home country have the

expected effect, including language demographics and foreign funding.

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VI.Conclusion @.Results →

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SLIDE 26

Table A.1. Eras

= 1 in Years Era Variable 1988 — 1993 US/Canada Free Trade Agreement US/CDN FTA 1994 — 2005 North American Free Trade Agreement NAFTA 1964 — 1974 Vietnam War Draft Vietnam War 2002 — 2005 Post attacks of September 11, 2001 Post 9‐11

←

VI.Conclusion @.Results →

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SLIDE 27

Table A.2. Policy Variables

  • St. Dev.

Mean Span Definition Var. Variable 81 — 05 Unemployment Rate U UE 0.016 0.096 Canada 0.014 0.074 US 0.014 0.060 EU‐15 81 — 05 R&D Expenditure / GDP R&D R&D 0.254 1.346 Canada 0.101 2.564 US 0.076 1.694 EU‐15 0.0151 ‐0.015 58 — 05 (US ‐ Canada) UE Δ U ΔU 0.0025 0.0097 81 — 05 (US ‐ Canada) R&D Δ R&D Δ R&D

←

VI.Conclusion @.Results →

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SLIDE 28

Table A.3. School Categories

Description University Category disciplines or at least 20 doctoral degrees per year overall. School awarded at least 10 doctoral degrees per year across 3 or more Category 2 15 disciplines. School awarded 50 or more doctoral degrees per year across at least Category 1 Columbia, Cornell, Stanford, or Princeton Category 1 AND Cal Tech, UC Berkeley, Yale, Harvard, MIT, Top School

←

VI.Conclusion @.Results →

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SLIDE 29

Table A.4. Country Categories

Details Source Variable Azerbaijan Excluding: Israel, Georgia, Armenia, and Emirates, Yemen. Turkey, Turkmenistan, United Arab Lebanon, Oman, Qatar, Saudi Arabia, Syria, Bahrain, Egypt, Iran, Iraq, Jordan, Kuwait,

blrmideast.htm /library/maps/ geography.about.com

Middle Eastern Non‐English is all other countries. Africa, New Zealand. UK, Canada, Australia, Ireland, South

/wiki/English_language en.wikipedia.org

English c) a former French colony.. b) an administrative language or a) one of the official language where French is: de la Francophonieʺ including only those Members of ʺLa Organisation Internationale

/wiki/Francophonie en.wikipedia.org

Francophone Sweden, UK Luxembourg, Netherlands, Portugal, Spain, Germany, Greece, Ireland, Italy, g as of 1995 European Union EU‐15

←

VI.Conclusion @.Results →

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SLIDE 30

←

VI.Conclusion @.Results →

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