A paper on Generation Y and driving license: how to explain youth are taking their driving license later and later ?

1. 1
Mobility ‘Y’: The Emerging Travel
Patterns of Generation ‘Y’ [the
‘Millennial’ Generation]
Dr. Scott Le Vine
www.imperial.ac.uk/people/s.le-vine
SUNY New Paltz (USA) and Imperial College London (UK)
2nd Armand Peugeot Chair International Conference
Electromobility: Challenging Issues
18th/19th December 2014
Reporting on various studies undertaken in collaboration with: Qinyi Chen,
Charilaos Latinopoulos, Peter Jones, Tobias Kuhnimhof, John Polak, Tom Worsley
Research sponsored by: Imperial College, RAC Foundation, Independent
Transport Commission, Office of Rail Regulation, Transport Scotland, Institute for
Mobility Research, Welsh Assembly

2. 2
‘Peak Car’?
• Public sector: Future
roads/rail policies &
investments
• Private sector: How
are markets for
mobility (and those
linked to it) changing?
0
100
200
300
400
500
600
700
800
0
100
200
300
400
500
600
700
800
1950 1960 1970 1980 1990 2000 2010 2020 2030
0
100
200
300
400
500
600
700
800
1950 1960 1970 1980 1990 2000 2010 2020 2030
Taro Hallworth, formerly DfT (now CCC)
Tobias Kuhnimhof: “Are young men responsible for Peak Car?”

3. 3
Young people, esp. men, are the ones to watch
Le
Vine
and
Jones
(2012)
‘On
the
Move…’

4. 4
Headline trends (Int’l., #1)
Tobias Kuhnimhof: “Are young men responsible for Peak Car?”

5. 5
Headline trends (GB)
• Young male licence-
holding has fallen
(but appears to now
have stabilised), as
has mileage per
driver
• Each accounts for
roughly half of their
pre-recession 30%
drop in car mileage
From 6,500 mi./year
in 1995/7 to 4,500 in
2005/7 (across GB)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Males
aged
17
-­‐ 29
Females
aged
17
-­‐ 29
Full-licence holding (ages 17-29), GB

6. 6
Hypotheses for inc. in non-driving
1. The rise of phased licence-acquisition regimes (GDL)
2. Increased rates of participation in higher education
3. Decreased levels of economic activity (linked with #2)
4. Concentration of young adults in dense cities (where
car-free lifestyles are most viable)
5. Modern information and communication technologies
(online activity, texting, etc.)
6. Heightened environmental awareness among today’s
young adults
7. Historically-high levels of international migration
8. Deferred family formation

7. 7
Hypotheses for inc. in non-driving
Let us categorise the hypotheses into two categories:
1. Speculative hypotheses (new and/or different
relationships)
• Growing sensitivity to sustainability issues
• Impacts of new technology (Smartphones,
Internet, etc.)
2. Classical hypotheses (relationships that we
understand and have traditionally taken into account)
• Economic activity (GDP, employment, etc.)
• Prices (e.g. petrol/gasoline, public transport
fares)

8. 8
Trends in env’t. sensitivity (US)

9. 9
As previous – but only ages 18-34
©
Gallup,
1984-­‐2014.
Used
with
permission
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1984
Sep
28-­‐Oct
1
1990
Apr
5-­‐8
1991
Apr
11-­‐14
1995
Apr
17-­‐19
1997
Jul
25-­‐27
1998
Apr
17-­‐19
1999
Mar
12-­‐14
1999
Apr
13-­‐14
2000
Jan
13-­‐16
2000
Apr
3-­‐9
2001
Mar
5-­‐7
2002
Mar
4-­‐7
2003
Mar
3-­‐5
2004
Mar
8-­‐11
2005
Mar
7-­‐10
2006
Mar
13-­‐16
2007
Mar
11-­‐14
2008
Mar
6-­‐9
2009
Mar
5-­‐8
2010
Mar
4-­‐7
2010
May
24-­‐25
2011
Mar
3-­‐6
2012
Mar
8-­‐11
2013
Mar
7-­‐10
2014
Mar
6-­‐9
NB:
X-­‐axis
not
proportional
Environment
Economic
growth

10. 10
Trends in env’t. sensitivity (GB)

11. 11
Electronic connectivity? (1)
hCp://thecityfix.com/blog/on-­‐the-­‐move-­‐younger-­‐generaMon-­‐mobility-­‐
trends-­‐akshay-­‐mani/young-­‐generaMons-­‐on-­‐the-­‐move-­‐embarq/

12. 12
Electronic connectivity (2)
• Using data from Scotland (2005/6), we were unable to replicate
cross-national results from Sivak & Schoettle (2012)
• We found a strong and statistically significant POSITIVE cross-
sectional ceteris paribus relationship between internet usage
and licence-holding/car-driving-kms
0
1
2
3
4
5
6
7
8
9
10
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Odds
ratio:
Net
effect
of
Internet
usage
on
each
person's
predicted
odds
of
holding
a
full
driving
licence
Percentile
of
internet
users,
ordered
by
strength-­‐of-­‐estimated-­‐effect-­‐on-­‐licence-­‐holding
1.58
• Others are now reporting
similar empirical results
suggesting
complementarity between
ICT use and physical
mobility: Kroesen and
Handy (2015), Taylor et al.
(2014), Aguilera et al.
(2012)

13. 13
Economics (GB) – Trend in GDP
Corry
et
al.
2011§

14. 14
Economics (GB) – HMRC data
Analysis
of
Survey
of
Personal
Incomes

15. 15
Economics (USA)
hCp://www.pbs.org/newshour/businessdesk/2013/10/why-­‐millennials-­‐are-­‐struggling.html

16. 16
Drop in economic activity begins early in
teenage years (GB again)
0%
25%
50%
75%
100%
11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
Percentage
that
perform
at
least
one
work-­‐related
journey
Age
(years)
1995/7
2000/2
2005/7
2008/10
Males Females
Analysis
of
Na9onal
Travel
Survey
diary
data

17. 17
‘Main’ reasons for not driving, by age
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Age
17–29 Age
30–59 Age
60+
Percentage
of
adults
age
17+
who
do
not
have
a
full
car
driving
licence
Currently
learning
to
drive
(question
not
asked)
Put
off
by
theory/practical
test
Cost
of
learning
to
drive
Cost
of
insurance
Cost
of
buying
a
car
Other
general
motoring
costs
Family/friends
drive
me
when
necessary
Other
forms
of
transport
available
Too
busy
to
learn
Not
interested
in
driving
Environmental
reasons
Safety
concerns/nervous
about
driving
Physical
difficulties/disabilities/health
problems
Too
old
Busy/congested
roads
Driving
without
licence
Other
Analysis
of
Na9onal
Travel
Survey
data,
reproduced
from:
LaMnopoulos,
Le
Vine,
Polak
and
Jones
(2013)
‘On
the
Move
Scotland…’

18. 18
Pass rates for practical driving test fell
Barbara
Noble:
Why
are
some
young
people
choosing
not
to
drive?
(2005)
• Average British young adult spends 1.7 years (20+ months)
in ‘learning to drive’ status between ages 17 and 29
• Average test-passer has spent c.£1,000 on driving lessons
• Today’s (2013/4) pass rates: 52% (theory test),
47% (practical test)

19. 19
Conclusions & looking forward (1)
• Speculative hypotheses: Available evidence suggests attitudes-
to-sustainability & online-activity are not associated with young
adults’ decreased ‘auto-mobility’ (but we must be cautious and
open-minded)
• We need to better understand New manifestations of the
Classical hypotheses:
• The puzzle is that young adults ‘auto-mobility’ fell during the
2000s despite rising GDP/capita. But their GDP/capita was not
increasing – they’ve been in recession since 2001.
• The run-up in fuel prices in the 2000s affected all ages. But the
increasing cost/difficulty of acquiring a driving licence
disproportionately affected young people (older adults were
‘grandfathered’).
• We speculate that a similar ‘grandfathering’ phenomenon from
the run-up in British home prices may be associated with young
people’s concentration in urban flat-renting arrangements

20. 20
• Nearly all analyses are cross-sectional, so provide limited
insights into the time-trend and tell us nothing about the
direction of causality (AàB, or BàA, or AßàB)
• Big, important research questions remain:
• Are the ‘new’ manifestations of ‘classical’ hypotheses the
whole story (in a statistical sense) – or is there still, after
taking them into account, an ‘X’ factor that requires
further explanation?
• How trustworthy are the data? (e.g. has intentional mis-
representation of status/behaviour increased?)
• Are they happy? What happens when they ‘grow up’?
• Have wider outcomes (labour force participation,
housing, etc.) been impacted – if so, how and how are
effects distributed across the population of young adults?
Conclusions & looking forward (2)