Migration Intentions and NZ
Graduates: Preliminary evidence
from modelling survey data
Michael Krausse
with
Dave Maré
Jacques Poot
Frank Scrimgeour
Key questions
• Are recent graduates, per se, more inclined to
leave NZ than other residents?
– Controlling for other influential factors
• Are there some groups more or less inclined
to leave?
• What factors influence their decisions?
2
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Graduate migration: what do we know?
• PLT departures (Papadopolous 2012):
– 1.5-2.0% of the population (4-5% of 20-24 year olds), higher than most
OECD
– In 2010 approx. 53% of these (both overall and 20-24 years olds) were to
Australia, up from 38% and 43% in 2004
– Some evidence that migrants to Australia were less-skilled than others
• OECD analysis (Dumont & Lemaitre 2005)
– High proportion of highly skilled population is expatriate
– Higher proportions of NZ expatriates and overseas born resident New
Zealanders are highly qualified than of NZ born resident New Zealanders
• Census data (Haig 2010)
– Australian resident New Zealanders similarly qualified to NZ residents
– Qualification level of NZ emigrants to Australia rose between 2001 and
2006
– More highly qualified are slightly less likely to return
– Some occupational selectivity (health, mining, construction)
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PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Who are the gradute migrants?
• Longitudinal cohort (Milne et al. 2001)
– Emigrants “higher IQ scores, better qualified, leaner, fitter, happier and
less stress-prone personalities”
– 63% plan to return in less than 5yrs. Those who didn’t were more likely to
have left for better work opportunities, and more likely to have gone to
Australia
• IDS on Student Loan Scheme Borrowers (Smart 2006)
– Older, Maori & Pasifika, lower level and agriculture / environment /
education borrowers less likely to be overseas. Doctoral level most likely
to be so
• IDI Graduate Migration (Papadopolous 2012)
– More highly qualified are more likely to leave and to be still away 3 years
later
4
PANZ 2013 – Krausse, Maré, Poot & Scrimgeour
Survey of Dynamics and Motivations for Migration
All respondents (23,465)
(Who, Where)
Moved within NZ
in last 2 years (5,628)
(Why, Outcome)
Moved to NZ in last 2
years (750)
(Why, Outcome)
Plan to move within next 2 years
(3,589)
(Why, When, Where)
5
Not moved in last 2
years (17,087)
(Why, Outcome)
Plan not to move within next 2 years
(19,876)
(Why)
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Pointers: Who is intending to emigrate?
NZ residents
(20-59 yrs)
Intending to move offshore
Recent graduates
Total
20-24 yr olds
Level 1-3 qualified
Level 4-6 qualified
Degree qualified
Postgrad qualified
NZ born
Overseas born
European
Maori
Pasifika
Asian
6
All other residents
4.7%
2.3%
9.2%
7.7%
2.9%
2.8%
3.7%
2.2%
8.4%
3.4%
2.2%
3.9%
4.8%
2.1%
4.3%
3.0%
4.5%
2.1%
4.2%
2.5%
6.8%
2.7%
4.8%
3.5%
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Pointers: Where are they intending to go?
NZ residents
(20-59 yrs)
Total
20-24 yrs
NZ born
Overseas born
Level 1-3
Level 4-6
Degree
Postgrad
European
Maori
Pasifika
Other
7
Offshore Destination
Recent graduates
All other residents
Australia
48.8%
43.2%
52.2%
36.8%
66.7%
60.0%
39.3%
*
44.8%
72.7%
37.5%
35.7%
RoW
51.2%
56.8%
47.8%
63.2%
33.3%
40.0%
60.7%
*
55.2%
27.3%
62.5%
64.3%
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Australia
49.5%
39.7%
56.2%
34.4%
63.6%
51.0%
27.5%
55.6%
50.7%
70.3%
37.8%
36.8%
RoW
50.5%
60.3%
43.8%
65.6%
36.4%
49.0%
72.5%
44.4%
49.3%
29.7%
62.2%
63.2%
Pointers: Why might they go?
Main reason
Recent graduates
Social
8.1%
13.0%
3.5%
2.7%
52.3%
35.8%
3.5%
5.1%
0.0%
0.3%
2.3%
9.6%
24.4%
26.3%
5.8%
7.2%
Education
Employment
Housing economics
Housing quality
Environment
Other reasons
No response
8
All others
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Binomial and Multinomial probability functions
• Logit model:
exp⁡(𝛼 + 𝛽𝑖 𝑥𝑖 )
Pr 𝑦 = 1 𝑥 =
1 + exp⁡(𝛼 + 𝛽𝑖 𝑥𝑖 )
• Explanatory variables:
– graduate, age, qualification, ethnicity, household
– income, change in income, change in relationship, looking
for work, mobility history
– place based ratings, regional dummy variables
• Multinomial logit model:
Pr 𝑦 = 𝑚 𝑥 =
9
exp⁡(𝑥𝛽𝑚|𝑏 )
𝐽
𝑗=1(𝑥𝛽𝑗|𝑏 )
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Intentions of recent graduates vs the rest
0
.05
.1
.15
.2
.25
Predictive Margins of age#graduate with 95% CIs
520_24ys 625_29ys 730_34ys 835_39ys 940_44ys 1045_49ys1150_54ys1255_59ys
Age
Others
10
All Graduates
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Ethnicity?
0
.05
.1
.15
.2
Predictive Margins of ethnicity#graduate with 95% CIs
Eur
Maori
Pacific
Asian
Ethnicity
0No
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PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
PacAs
1Yes
EurMao
Other
And Household Type?
0
.05
.1
.15
Predictive Margins of hhtype2#graduate with 95% CIs
1IndSF
2IndSH
3IndCpl
4SPCh
HH composition
0No
12
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
1Yes
5CplCh
6NoCat
Does qualification make a difference?
0
.05
.1
.15
.2
.25
Predictive Margins of age#quals with 95% CIs
520_24ys 625_29ys 730_34ys 835_39ys 940_44ys 1045_49ys1150_54ys1255_59ys
Age
1None
3Lvl4to6
5Lvl8to10
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PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
2Lvl1to3
4Lvl7
6
6
5
5
4
4
3
2
1
0
-1
Housing
Employment
opportunities
Standard of
living
-2
-3
-4
3
2
1
0
-1
Housing
Employment
opportunities
Standard of
living
-2
-3
Binary satisfaction rating
Graduates
14
Social life
Marginal effect on P(labour market move)
Marginal effect on P(labour market move)
(Dis)satisfaction and the probability
of a move in labour market
-4
Others
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Binary dissatisfaction rating
Graduates
Others
Social life
Movement Intentions by Destination
Probability of moving (%)
6
5
4
3
2
1
0
Inter-region
Variable Overall
15
Australia
Recent qualification Yes
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
RoW
Recent qualification No
Where do the highly skilled intend?
Probability of moving (%)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Inter-region
No qualification
16
Australia
L1-3
L4-6
RoW
L7
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
L8+
Overall
Intended movements by ethnicity
6.0
Probability of moving (%)
5.0
European
4.0
Maori
Pasifika
3.0
Asian
Pasifika - Asian
2.0
Overall
European - Maori
1.0
0.0
Inter-region
17
Australia
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
RoW
4.5
Probability of moving (%)
4.0
3.5
3.0
Other household
One person household
2.5
Couple only or with others
2.0
One parent with child(ren)
1.5
Couple with child(ren)
Overall
1.0
0.5
0.0
Inter-region
18
Australia
RoW
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
6.0
6.0
5.0
5.0
4.0
4.0
3.0
2.0
1.0
0.0
Housing
Employment
opportunities
-1.0
Social life
3.0
2.0
1.0
0.0
-2.0
-3.0
-3.0
Binary satisfaction rating
Inter-region
Aus
Housing
Employment
opportunities
Standard of
living
-1.0
-2.0
-4.0
19
Standard of
living
Marginal effect on P(labour market move)
Marginal effect on P(labour market move)
What makes the difference? Push factors
-4.0
RoW
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Binary dissatisfaction rating
Inter-region
Aus
RoW
Social life
What makes the difference? Pull factors
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Inter-regional
20
Australia
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
RoW
What makes the difference? Pull
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Envmnt
Travel
Inter-regional
21
SatNR
Australia
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
RoW
"Change"
What does this all mean? Does it matter?
• What have we found?
– Individual characteristics
– Push factors
– Hold factors
– Pull factors
• Distinctives in destination choices
• Distinctives by representative groups
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PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Questions Arising
• Intentions vs. actuals
– How is this reflected in the size and composition
of actual flows?
– Particularly for significant groups: highly skilled
(not just qualified), Maori, Pasifika, single parent
families
– How is it reflected in the short and long run
impact of those flows?
• What are the implications for circular flows
and long run impacts?
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Lew 2012 – Krausse, Poot & Scrimgeour
Acknowledgements
• Funding for this research was provided by the NZ Ministry of Business,
Innovation and Employment (MBIE) as part of the 2013-2014 joint Massey
University & Waikato University Nga Tangata Oho Mairangi (NTOM)
project.
• Access to the data used in this research is gratefully acknowledged. It has
been provided by Statistics New Zealand in accordance with the security
and confidentiality provisions of the Statistics Act 1975 for the purposes of
bona fide research or statistical purposes in relation to a matter of public
interest. Data used for this research was confidentialised to protect
individual people from identification prior to its provision. Provision has
been on the basis of maintaining strict confidentiality protocols.
24
Thank you!
Survey of Dynamics and Motivations for Migration
Plan to move within next 2 years
(3,589)
(Why, When, Where)
New qualification
in last 2 years (752)
Plan to move beyond
current region
(319)
26
Plan to remain
in region
(433)
Others
(2,837)
Plan to move beyond
current region
(929)
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Plan to remain
in region
(1,908)
Sample bias: Gender by Age
0.06
0.06
0.05
0.05
0.04
0.04
0.03
0.03
0.02
0.02
0.01
0.01
0
0
Male (DMM)
27
Male (C2006)
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
Female (DMM)
Female (C2006)
Sample Bias: Qualification by Age
DMM
2500
Census06
350000
300000
2000
250000
1500
1000
200000
150000
100000
500
50000
0
28
0
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
What makes the difference? Pull
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Ptnr
Fam&Fr Indep SocOthr OwnEd OthrsEd
Inter-regional
29
Australia
PANZ 2013 – Krausse, Maré , Poot & Scrimgeour
RoW
InEd
EdOthr