D i ing licenses based on poin s sys ems: E ficien oad sa e y s a egy
o la es ashion in global anspo policy? A wo ldwide me a-analysis
Jose
´I. Cas illo-Manzano
n
, Me cedes Cas o-Nun
˜o
Facul ad de Ciencias Econo
´micas y Emp esa iales, Uni e si y o Se ille (Spain), A da. Ramo
´n y Cajal, 1, 41018 Se ille, Spain
a icle in o
Keywo ds:
Road sa e y
D i ing license
Poin - eco d sys ems
Me a-analysis app oach
abs ac
One o he mos popula coac i e measu es de eloped o p e en oad a fic acciden s in ecen
decades is he implemen a ion o d i ing licenses based on poin s sys ems (PS) which penalize epea
o ende s wi h suspension o wi hd awal o hei licenses. This pape analyzes hei apid sp ead
wo ldwide h ough an in-dep h e iew o he exis ing li e a u e. A comp ehensi e me a-analysis o he
e ec s o PS on oad a fic acciden s and he du a ion o hese e ec s has been conduc ed. The findings
show ha he s ong ini ial posi i e impac (15 o 20% educ ions in acciden s, a ali ies and inju ies)
seems o wea o in unde eigh een mon hs. This limi ed e ec i eness is ela ed o he absence o
complemen a y en o cemen o back up hese measu es. Wi hou hem, poin s sys ems could u n in o
a boome ang oad sa e y policy, and e en be abandoned a a la e da e. The implica ions o he
conclusions o legisla ion and u u e esea ch a e conside ed.
&2012 Else ie L d. All igh s ese ed.
1. In oduc ion
The ex ao dina y economic g ow h expe ienced h oughou
he 20 h cen u y has aised a es o mo o ehicle owne ship all
a ound he wo ld while, a he same ime, oad a fic acciden s
(RTA) ha e become one o he le hal epidemics a ec ing human-
kind, wi h 1.2 million people killed and up o 50 million mo e
inju ed e e y yea (WHO, 2009). This is, howe e , a silen kille
which o yea s has been he objec o much less media a en ion
han o he , less e e yday bu mo e eye-ca ching agedies, such
as ai acciden s o na u al disas e s.
Acco ding o he same sou ce, unless a p e en a i e s a egy is
adop ed on a global scale, RTA will become he fi h leading cause
o dea h wo ldwide by 2030. In many coun ies, he implemen a-
ion o inc easingly se e e oad sa e y policies, oge he wi h he
ac ha he cu en economic c isis has educed a fic olumes
(a leas in he sho e m), ha e p oduced a la ge all in he main
a fic acciden indica o s du ing he fi s decade o he 21s
cen u y (see OECD, 2010a,2010b). Howe e , his imp o emen
has no been uni o mly dis ibu ed in geog aphical e ms, wi h
huge di e ences be ween high-income coun ies and middle-
income/low-income coun ies (IRF, 2009). As hey ha e achie ed
a mo e-o -less es ed minimum deg ee o e ec i eness (WHO,
2009), he majo i y o he in e en ions in he de eloped coun-
ies ha e been p og essi ely imi a ed in de eloping coun ies.
We ound basically wo g oups o ac ions: fi s ly, s a egies ha
ocus on elemen s ha a e ex e nal o he oad use (such as
in as uc u e imp o emen s—analyzed by A
´l a ez e al., 2007 o
sa e ehicle design—s udied by Ch is ensen and El ik, 2007);
and secondly, s a egies ha ocus on p e en ing o co ec ing
unsa e oad-use beha io s, based on he e idence ha he
human elemen is he ac o ha explains he majo i y o
acciden s (S an on and Salmon, 2009).
This las block o ac ions, which has been g ea ly de eloped in
he academic li e a u e, can in u n be classified as: p e en i e
measu es ha seek o pe suade o dissuade h ough educa ion and
in o ma ion (such as communica ion campaigns and oad sa e y
ad e isemen s, conside ed by Cas illo-Manzano e al., 2012 and
Lewis e al., 2008); o co ec i e o sanc ioning measu es (mone a y
and non-mone a y) which y o in e nalize he social cos s o RTA
h ough coac i e dissuasion (Cas illo-Manzano e al., 2011). Apa
om he applica ion o se e e c iminal penal ies by Law (judicial
sen ences and imp isonmen ) o punish he se e es in ingemen s,
o he so e egula ions o mino in ingemen s based on economic
sanc ions (by fines and insu ance paymen s) and license dep i a ion
(by suspension o wi hd awal) also s and ou (Bou geon and Pica d,
2007). In oad a fic legisla ion in many coun ies, license dep i a-
ions ha e e ol ed in o a ype o d i ing license based on a poin s
sys ems (hence o h PS) which, despi e di e ences be ween coun-
ies, espond o a common philosophy ha can be summa ized
ollowing Nole
´nandO
¨s lin, (2008): se e al specific o enses com-
mi ed by d i e s cause he addi ion/loss o a ce ain numbe o
poin s and when he numbe o poin s eaches he maximum
allowed o all poin s a e los , he d i e ’s license is suspended.
Con en s lis s a ailable a SciVe se ScienceDi ec
jou nal homepage: www.else ie .com/loca e/ anpol
T anspo Policy
0967-070X/$ - see on ma e &2012 Else ie L d. All igh s ese ed.
doi:10.1016/j. anpol.2012.02.003
n
Co esponding au ho . Tel.: þ34 954 556727; ax: þ34 954 557629.
E-mail add esses: [email p o ec ed] (J.I. Cas illo-Manzano),
[email p o ec ed] (M. Cas o-Nun
˜o).
T anspo Policy 21 (2012) 191–201
Despi e hei widesp ead use in p ac ice, scien ific s udies on
he e ec i eness o PS a e no de eloped me hodologically in he
academic li e a u e o he same deg ee, and he e is a ce ain
amoun o con o e sy ega ding he du a ion o hei e ec s
(Cas illo-Manzano e al., 2010). The e a e some s udies ha a e
mo e op imis ic abou he impac and sus ainabili y o he
measu e’s posi i e e ec s o e ime, including con ibu ions o
he success o o he oad sa e y measu es (such as Zambon, e al.
2008 which a ibu e o i a majo inc ease in he wea ing o
sea bel s); while o he au ho s, such as Mon ag (2010), claim ha
i s impac is only sho - e m and ha , pa adoxically, he e migh
e en be some pe e se e ec s, ei he because a fic law en o ce-
men p oduces mo e isk- aking beha io s, o because he e is a
dec ease in he in ensi y o police ac i i ies due o us in he
de e en e ec o he sys em on i s own.
1
In his line, PS can
encou age undesi able beha io s, such as hi -and- un c ashes
(SWOV, 2010) and/o d i ing wi hou a alid license (Knox,
e al., 2003).
In ac , ollowing Engs ¨
om e al., (2003), e y li le is known
abou he e ec s o he PS on oad sa e y, because as SWOV
(2010) s a es, i is e y di ficul o isola e he impac ha hese
sys ems ha e om he e ec s o o he complemen a y ypes o
en o cemen being applied a he same ime (i.e., an inc ease in
police o law en o cemen , public campaigns).
The aim o his pape is o discuss some ea u es o he poin s-
eco d mechanism, while simul aneously de eloping an empi ical
amewo k o in es iga e in mo e de ail i his eally is an e ficien
global s a egy o imp o ing oad sa e y o simply a ashion
policy which is imi a ed om one coun y o ano he . We use a
me a-analysis app oach o in es iga e he e ec i eness and
sho - and long- e m e ec s o his sys em, de eloped in he
amewo k o a fixed-e ec s model and a andom-e ec s model.
Ra he han jus a simple s a e-o - he-a li e a u e e iew, we
selec academic esea ch om a wide sea ch o s udies de eloped
a ound he wo ld conside ed as ele an on he basis o he
me hodologies used and empi ical findings, and we summa ize a
esul . This unde s anding is conside ed o be especially use ul o
u u e expansion o he policy o de eloping o unde eloped
coun ies as i p o ides he keys equi ed o i s op imum design.
The pape is o ganized as ollows: ollowing his in oduc ion,
Sec ion 2 examines d i ing licenses based on PS as an in e na ional
s a egy o educing a fic acciden s. In Sec ion 3,weexplain he
design o he me a-analysis model applied, and discuss he findings.
In Sec ion 4 he main conclusions a e d awn and he implica ions o
oad sa e y ha de i e om his esea ch a e se ou .
2. Poin s sys ems o imp o e oad sa e y
D i ing licenses based on a poin s- eco d ha e hei p ede-
cesso s in he license endo semen sys ems ha we e in oduced
in he nine een- hi ies (Milulik, 2007). They ha e cu en ly been
ex apola ed o o he a eas o public poli ics no only ela ed o
he anspo a ion sec o ( o in ac ions in fishe ies ac i i y in
he Eu opean Union; o illegal immig a ion in coun ies such as
Canada, Aus alia and New Zealand; o s ic codes o discipline
a high schools in Hong Kong and India). In he p esen day, his
oad sa e y s a egy has been pa icula ly ecommended by
in e na ional ins i u ions because o i s po en ial, a leas in he
ini ial pe iod a e i s in oduc ion, (see Global Road Sa e y
Pa ne ship, 2008;SWOV, 2010). I has p og essi ely gained
popula i y and accep ance in public opinion wo ldwide (Nole
´n
and O
¨s lin, 2008) because i is conside ed o be mo e jus when
dealing mo e s ic ly wi h epea o ende s and ai e han a
mone a y fine, ( he eal e ec o which depends on he o ende ’s
pu chasing powe , ETSC, 2008). Acco ding o El ik and Vaa
(2004), his measu e o ms pa o a wide oad sa e y s a egy
ha includes wo o he en o cemen measu es: wa ning le e s
2
and d i ing license e oca ions. I is also an umb ella s a egy, as i
co e s all ypes o a fic iola ions compa ed o o he measu es
included in he gene al legisla i e sys em which a e exclusi ely
ela ed o one specific o ense a ea (speeding, alcohol).
A e iew o he PS in di e en coun ies e eals ha , al hough
hei s uc u es a e all simila , he e a e di e ences in hei
designs and applica ion (Nole
´n and O
¨s lin, 2008). F om hei
analysis i can be concluded ha hey a y conside ably in he
selec ion o o enses and hei sco ing, he ways o coun ing
poin s, he h esholds o disqualifica ion o du a ion o disqua-
lifica ion and adminis a ion p ocedu es. E en in he same coun-
y di e ences can be ound be ween s a es as, in ce ain
coun ies, hese a e sys ems ha a e ans e ed o he au ho i ies
o he a ious ju isdic ions. This is he case o he Uni ed S a es,
Aus alia and Canada. Fu he mo e, he punishmen applied by PS
o a a fic iola ion may no be s anda dized, as in coun ies such
as I eland and he Uni ed Kingdom he numbe o poin s can ise
o he same iola ion depending on whe he he d i e is ound
guil y in cou . The penaliza ion is he e o e adjus ed o each
iola ion depending on i s se iousness o whe he i is a epe i ion
o he same iola ion (ETSC, 2008).
3
The e a e wo equi alen a ia ions wi h di e en mechan-
isms used o compu e he poin s ha penalize o enses (see,
Nole
´n and O
¨s lin, 2008): (1) Penal y PS (PPS) o poin deduc ion:
all d i e s who possess a alid license a e alloca ed an ini ial
numbe o poin s om which poin s a e deduc ed depending on
he o ense commi ed. Once his ini ial c edi uns ou he license
is wi hd awn. ‘‘The poin is o gain no poin ’’ (ETSC, 2008); (2)
Deme i PS (DPS) o poin accumula ion: all d i e s who possess a
alid license s a om sc a ch, i.e., no poin s, and accumula e
poin s, depending on he o ense commi ed. The license is wi h-
d awn a e a ce ain numbe o poin s a e accumula ed.
In bo h cases, he deduc ion o appo ioning o poin s is o a
pe sonal na u e, ha is, i is di ec ly linked o he d i ing license
owned by he o ende so ha when she/he is caugh by he police
commi ing a a fic iola ion he poin s canno be used agains
he ehicle owne ia he ehicle egis a ion numbe (SWOV,
2010). Simila ly, in bo h o he e sions, all d i e s s a in he
same si ua ion (maximum poin s/ ze o poin s), al hough in some
coun ies like La ia o he Uni ed Kingdom, di e en ial sys ems
a e in place o g oups o d i e s wi h special ci cums ances, such
as no ice d i e s (wi h a s ic e sys em)
4
; o p o essional d i e s
(wi h a mo e pe missi e sys em).
Acco ding o Bou geon and Pica d (2007), in some cases such
as F ance o Spain, ‘‘ edemp i e sys ems’’ a e applied ha a e no
1
Acco ding o Dionne e al., (2011),‘‘y he police a e he mos impo an
en o ce s o he di e en incen i e schemes’’.
2
Gene ally-speaking, ‘‘wa ning le e s’’ a e an incen i e sys em used o
modi y negligen d i ing beha io in oad sa e y (Wilde and Mu doch, 1982)
when a d i e commi s a ce ain a fic o ense (e.g., exceeding he speed limi , o
in pho o ada en o cemen ). Howe e , in some coun ies o US s a es wi h poin s
sys ems, like F ance, Michigan (U.S.), On a io (Canada) and Spain, wa ning le e s
a e also used as ‘‘ad iso y w i en wa nings’’ which a e sen o d i e s who a e
beginning o app oach he limi o license wi hd awal (see, o example Cas illo-
Manzano e al., 2010 and Haque, 1990).
3
This modali y, which consis s o g adua ing he penaliza ion applied o each
iola ion depending on i s se iousness, is no en i ely sanc ioned by expe s such
as El ik and Vaa (2004), who belie e i is no e y eliable due o i s subjec i i y.
4
PS can be specifically a ge ed a no ice d i e s (Ne he lands and Finland) o
unde G adual Licenses (GDL) and p oba iona y sys ems, which consis o a fic
iola ions du ing an in e media e s age o licensing possibly delaying he no ice
d i e a aining a ull license (e.g., a new G adua ed Deme i Poin Sys em o
no ice d i e s in Aus alia, since Decembe , 2010).
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201192
only o a puni i e na u e bu also ha e a ehabili a i e aspec o
hem. In hese sys ems he d i e who has been penalized can
ha e he poin s she/he has accumula ed and emo ed, o eco e
hose ha ha e been los , once a ce ain pe iod o ime has passed
wi h no u he o enses being commi ed, a e a ending a e-
educa ion and oad-sa e y awa eness cou se sel -financed by he
o ende , and e en a e e aking he d i ing es o eco e
he license. On occasion, ex a poin s a e added o deduc ed om
he licenses o good d i e s who do no commi any o ense du ing a
ce ain pe iod o ime (Nole
´nandO
¨s lin, 2008); his is he case in
Malaysia, whe e he so-called KEJARA Sys em is applied, and Spain.
In ju isdic ions such as he s a e o New Sou h Wales (Aus alia), he
‘‘double penal y poin s’’ sys em is used o inc ease he le el o
penaliza ion o ce ain o enses (such as speeding) du ing holiday
pe iods (highe poin s du ing high- isk pe iods).
In some s a es in he US and Eu opean coun ies like Ge many
and I eland, PS can also p oduce o he ex e nal e ec s: insu ance
companies equi e d i e s’ poin s- eco ds o be epo ed o hem
o de e mine whe he o no o enew an insu ance policy (ETSC,
2008 is analyzing he opic). This is an a emp o c ea e a
s onge incen i e o eckless d i e s who do no espond o
ha o insu ance p icing (Dionne e al., 2011).
I espec i e o he pa icula ea u es o he PS a ian used,
Basili and Nici a (2005) highligh he ac ha he measu e also
aspi es o igge a numbe o a o able e ec s in d i e beha io :
1. De e ence o he abili y o make o ende s associa e epea
a fic iola ions wi h mo e se e e sanc ions o he poin ha hey
lose hei licenses (Zambon e al., 2008). I could be said ha he
epea ed iola ion o a fic egula ions is p oducing a g owing
ma ginal cos o he o ende ; 2. Selec ion o emo al o he mass
o d i e s who epea edly iola e a fic egula ions wi h
he objec i e o educing he likelihood o a fic acciden s
(Diaman opoulou e al., 1997); 3. Co ec ion o incen i e o
d i e s o ec i y hei inapp op ia e beha io a he wheel (Poli
de Figuei edo e al., 2001); 4. Educa ion o P e en ion, as d i e s
a e shown which a e he mos se ious punishable iola ions and
mos dange ous beha io s whils (in some coun ies) i is a he
same ime es ablished ha cou ses on oad sa e y ha e o be
a ended (Roca and To osa, 2008).
In Table 1, we use he agg ega ion o coun ies in egions
p oposed by WHO (2009) as an ini ial s udy c i e ion o dis in-
guish be ween coun ies wi h PS (44) whils also indica ing which
a ian has been implemen ed, PPS o DPS. The hi d column o
his Table also p o ides a sample o coun ies om each WHO
egion o which some kind o s udy has been ound on he e ec s
o he PS, i espec i e o he me hodology used o i s measu e-
men , and oge he wi h i s implemen a ion da e.
De ailed analysis o Table 1 has allowed a se ies o findings o
be de e mined:

The a eas whe e he de elopmen o he PS has been mos
widesp ead can be seen o be hose which include mo e high-
income coun ies (HIC), especially in he Eu opean Region. This
sugges s ha coun ies need o ha e he app op ia e echnical
means o implemen he sys em, as well as a ce ain deg ee o
oad sa e y cul u e (as desc ibed by Dodge and Ki chin, 2007).
Fu he mo e, he sys em ha is mos adop ed in he majo i y
o he coun ies conside ed is he DPS me hod, i.e., he
o iginal model.

Twen y- ou coun ies ha e op ed o he sys em in he
Eu opean Region. This measu e has become a gene alized
s anda d o oad sa e y in wes e n coun ies, whe eas i s
applica ion in Eas e n Eu opean coun ies has been much
mo e limi ed and mos ly confined o coun ies ha a e in
he EU, such as he Czech Republic o La ia, amongs o he s,
and also Tu key, which has applied o join. I seems clea ha
belonging o he EU and i s a ea o influence has been he
h ead ha has led coun ies o imi a e one ano he . Indeed, i
could be said ha a e he Eu opean Commission se a a ge
o a 50% educ ion in a fic a ali ies be ween 2000 and 2010
(Eu opean Commission, 2001), i was no so much an imi a ion
e ec ha could be spoken o among he g oup o measu es
ha Eu opean coun ies adop ed, bu a he a con agion
e ec .
5
The e a e also some EU coun ies whe e d i ing
licenses a e no in ac based on he PS, al hough hey do bea
many simila i ies. One example is Po ugal, whe e a d i ing
license can be wi hd awn i a cou decides he o ende has
been guil y o e y se ious o enses h ee imes, o o se ious
o enses fi e imes, in h ee yea s, and, u he mo e, d i e s
mus e ake hei d i ing es s o ge hei licenses back.

Ch onologically, a e i s pionee ing in oduc ion in he US o e
fi y yea s ago, he sys em sp ead o Asia and Aus alia and
he ea e o a Eu opean coun y (Ge many). I has only eally
expanded and been pe ec ed in ecen imes as i was in he las
decade ha he g ea es numbe o changes and con e s we e
seen, especially in Eu ope. The la es egions o in oduce PS ha e
been A ica and he Eas e n Medi e anean.

Finally, we find cul u al simila i ies in he PS a ian adop ed.
A e fi s being in oduced in he US, he DP sys em has been
eplica ed in o he Anglo–Saxon coun ies i espec i e o he
WHO egion o which hey belong (Aus alia, New Zealand,
Sou h A ica, Canada, UK, and I eland o hei o me colonies,
such as Hong Kong). In mo e ecen imes, i has been he PPS
ha has been implemen ed in La in Eu opean coun ies (F ance,
I aly and Spain), and o la e in hese coun ies’ o me Ame ican
colonies, such as Ecuado and A gen ina, al hough no in colonies
ha come unde he cul u al influence o he US, like Mexico and
Panama, which use he DPS. Resea che s such as P iya and U eng
(2009) find co ela ions be ween cul u al elemen s and acciden s
on he basis o li es yle and socioeconomic aspec s. These s udies
would uphold he idea ha he in e na ional sp ead o his oad
sa e y s a egy is no only explained by he imi a ion e ec ha
a ises be ween coun ies because o hei geog aphical p oxi-
mi y, bu also because o cul u al issues, as i would appea ha
he a ian ha is applied is closely linked o he peculia i ies o
each coun y.
3. Me a-analysis o e ec i eness o poin sys ems
mechanisms
One o he objec i es o his s udy is o syn hesize a se ies o
esul s on he size and du a ion o PS e ec s wo ldwide om
p e ious s udies ha ha e used a ious me hodologies. The me a-
analysis app oach has ad an ages o e a li e a u e e iew o his
because o i s s a is ical na u e and i s in e ence p ocess (Glass e al.,
1981). This app oach has been b oadly de eloped o e he las 20
yea s, basically in expe imen al sciences and en i onmen al eco-
nomics, al hough a a ie y o p eceden s can also be ound o i s
being applied o a ange o oad sa e y s a egies in ecen yea s (see
o example E ke, 2009, o ed-ligh came as; Høye, 2010, o on
ai bags; o Phillips, e al., 2011, o ad e ising campaigns). As a as
PS a e conce ned, he e is a p eceden in El ik e al. (2009),who
syn hesized a numbe o specific s udies ela ed o DPS-linked
elemen s and license suspensions (wa ning le e s, special d i ing
es s and imp o emen cou ses).
5
As has been seen om he measu es ha ha e been p og essi ely applied by
he a ious coun ies, acco ding o OECD, (IRTAD) (2010).
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201 193
3.1. S udy design: da a coding and a iables
An ini ial sea ch was conduc ed in he academic li e a u e o
iden i y he mos ecen esea ch on he opic o he e ec s o PS
a ound he wo ld, wi h he cons ain o he publica ion o m
(a icles in pee e iewed scien ific jou nals o ins i u ional
epo s).
6
Using gene al sea ch e ms in o de ha no s udy should
be excluded ap io i, hese s udies ha e been ound in he ollowing
sou ces: he epu ed T anspo a ion Resea ch In o ma ion Se ices
(TRIS) da abase (U.S. Depa men o T anspo a ion), PubMed
(online da abase o he U.S. Na ional Lib a y o Medicine), he ISI
Web o Knowledge, Scopus and Science di ec (Else ie s online
da abases), epo s om esea ch ins i u es such as SWOV (The
Ne he lands) and TRL (UK) and In e ne sea ches by Google Schola .
In his way almos fi y s udies wi h hese cha ac e is ics we e
loca ed al hough hey a e all g ea ly he e ogeneous, especially wi h
ega d o hei me hodologies. Some a e eminen ly heo e ical (such
as Basili and Nici a, 2005 and Bou geon and Pica d, 2007), whils
o he s a e based on a compa ison o be o e-and-a e s a is ics (Poli
de Figue eido e al., 2001).
Only a sample o sui able s udies was selec ed, using ypical
inclusion c i e ia in me a-analysis (see El ik, 1999), i.e., hose
which: 1. Include an es ima ion o PS e ec i eness and/o du a ion
using s a is ical o econome ic me hodology ha seeks o sepa a e
ou he e ec s o PS om o he a iables ha migh ha e had an
e ec du ing he pe iod analyzed (bo h me a-analyses and s udies
ha only e alua e elemen s such as wa ning le e s and e-
educa ion cou ses we e ejec ed since, as was indica ed in
Sec ion 2, hese a e no applied equally in all coun ies); 2. Repo
he s anda d de ia ion, confidence in e al, sample size o simila
s a is ical in o ma ion abou he accu acy and obus ness o he
esul s. The ini ial da a sample was efined by he applica ion o
hese quali y indica ions and a o al o 26 s udies om a ound he
wo ld we e finally included in he me a-analysis, many o hem
wi h mul iple ele an esul s which could be used o expand he
final sample. This sui able me hod o da a collec ion was cha -
ac e ized by a coding p ocedu e, as seen in Tables 2–5.
Following he me hodology desc ibed in Sec ion 3.2, below,
wo scena ios we e en isaged o he me a-analysis:
SCENARIO (I)Es ima ion o summa y e ec s o PS: To minimize
he likely he e ogenei y among he 26 sui able s udies, hese
we e classified in o 3 subg oups depending on he ype o
a iables ha we e conside ed o e alua ing he e ec s o he
PS. As he e a e s udies wi h mul iple esul s, he sample size will
be he o al numbe o esul s compu ed
7
:

I VTRA: Va iables ela ed di ec ly o RTA, in e ms o educ-
ions in he numbe o acciden s, casual ies, a ali ies o
inju ed. These a iables we e ound in 13 s udies wi h 24
esul s (m¼24).
Table 1
Coun ies wi h poin s sys ems in he who egions.
Sou ce: Au ho s. based on WHO (2009), ETSC (2008) and oad a fic legisla ion in each coun y.
WHO
egion
No. o coun ies/
income le el
Coun ies wi h a poin s sys em d i ing license (DPS o PPS) such asySelec ed coun ies/yea poin s
sys em implemen ed
141 (0 HIC, 11 MIC,
30 LIC)
Sou h A ica (DPS) Sou h A ica (in P e o ia, 2006)
232 (6 HIC, 26 MIC,
0 LIC)
A gen ina (PPS), Be muda (DPS), B azil (DPS), Canada (DPS), Ecuado (PPS), Jamaica (DPS), Mexico
(DPS), Panama (DPS), Pe u (DPS), Uni ed S a es o Ame ica (DPS)
– USA (s a e by s a e, i.e.
Connec icu , 1957)
– Canada (s a e by S a e, i.e.
Quebec, 1978)
– B azil (1998)
310 (0 HIC, 6 MIC,
4 LIC)
– –
420 (5 HIC, 12 MIC,
3 LIC)
Qa a (DPS), The Uni ed A ab Emi a es (DPS) The Uni ed A ab Emi a es (2008)
549 (25 HIC, 21
MIC, 3 LIC)
Aus ia (DPS), Bulga ia (DPS), Cyp us (DPS), The Czech Republic (DPS), Denma k (DPS), F ance (PPS),
Ge many (DPS), G eece (PPS), Hunga y (DPS), Iceland (DPS), I eland (DPS), Is ael (DPS), I aly (PPS),
La ia (DPS), Li huania (DPS), Luxembou g (DPS), Mal a (DPS), No way (DPS), Poland (DPS), Romania
(DPS), Slo enia (DPS), Spain (PPS), Tu key (DPS), Uni ed Kingdom (DPS)
– Ge many (1974)
– Uni ed Kingdom (1988)
– F ance (1992)
– Finland (1996)
a
– I eland (2002)
– The Ne he lands (2002)
a
– I aly (2003)
– Aus ia (2005)
– Spain (2006)
– The Czech Republic (2006)
626 (6 HIC, 15 MIC,
5 LIC)
Aus alia (DPS), China (DPS), Japan (DPS), Malaysia (DPS), New Zealand (DPS), Republic o Ko ea
(DPS), Singapo e (DPS),
– New Zealand (1967)
– Japan (1968)
– Aus alia (s a e by s a e, i.e.
Vic o ia, 1970)
– China (ju isdic ion by
ju isdic ion, i.e. Hong
Kong, 1984)
No es: DPS: Deme i poin sys em, PPS: Penal y poin sys em.
HIC: High-income coun ies; MIC: Middle-income coun ies; LIC: Low-income coun ies.
1. A ican Region; 2. Region o he Ame icas; 3. Sou h-Eas Asia Region; 4. Eas e n-Medi e anean Region; 5. Eu opean Region; 6. Wes e n Pacific Region.
a
Only Poin s Sys ems o no ice d i e s on p oba ion.
6
In o de o educe any possible bias, sou ces and bibliog aphy we e chosen
blindly by he au ho s o he s udy.
7
Following El ik and Vaa, (2004) we assume he independence hypo hesis
be ween mul iple esul s.
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201194

I VDB: Va iables ela ed o d i e beha io , in e ms o
educ ions in isky o dange ous conduc , d i ing less unsa ely
(a smalle pe cen age o d i e s no wea ing sea bel s, o
example) o a educ ion in law iola ions (speed limi s, d ink-
d i ing). These a iables we e ound in 8 s udies wi h 18
esul s (m¼18).

I VHCD: Va iables ela ed o heal h ca e da a, in e ms o
educ ions in RTA ela ed A&E admissions, su ge y o hospi-
aliza ions. These a iables we e ound in 5 s udies wi h
8 esul s (m¼8).
SCENARIO (II)Es ima ion o he du a ion o he PS e ec : The
a iable conside ed in his case (LENGTH OF EFFECTS) is he
du a ion o PS e ec s, in numbe o mon hs, es ima ed o each o
he s udies. As can be seen in Tables 2–5, no all he sui able
s udies analyze his issue. To be p ecise, we shall wo k wi h he
sample o 20 s udies ha do (m¼20).
3.2. Me hodological aspec s.
The es ima ion me hod used was he ‘‘log-odds model’’ ound
in El ik and Vaa (2004). In his me hod, he es ima ions o he
sui able s udies a e combined o ob ain a summa y-measu e
using mean weigh ing acco ding o he s a is ical weigh ( he
in e se o he p ecision o he s udy). Acco ding o he ollowing
o mula, he mean weigh ed e ec o ‘‘m’’ es ima ions ðYÞwill be:
Y¼exp P
m
i¼1
w
i
y
i
P
m
i¼1
w
i
 ð1Þ
When: y
i
¼log (i- h es ima ion ob ained by each s udy).
w
i
¼ he s a is ical weigh o he i- h es ima ion ob ained as
w
i
¼ð1=
i
Þ,when
i
is he a iance o each i- h es ima ion,
whe eby P
m
i¼1
w
i
¼1:
The possible he e ogenei y o he s udies can be aken in o
accoun using he andom-e ec s model (REM), o no included i
he fixed-e ec s model (FEM) is used. The FEM assumes ha he e
is one single e ec on he popula ion and does no ake in o
accoun he a iabili y o he esul s among he di e en s udies.
The size o he s udy and i s own a iance (in a-s udy a iabili y)
a e he only de e minan s o i s weigh in he me a-analysis. The
De simonian and Lai d Q s a is ic (1986) is calcula ed o e i y he
alidi y o his hypo hesis, dis ibu ed in acco dance wi h a Chi-
Squa e wi h m-1 deg ees o eedom (m¼no. o combined
es ima ions):
Q¼X
m
i¼1
w
i
y
2
i
ðP
m
i¼1
w
i
y
i
Þ
2
P
m
i¼1
w
i
ð2Þ
I he null hypo hesis is ejec ed (H
0
: non he e ogenei y) i is
ecommended ha REM be used as his does ake in o accoun
Table 2
Selec ed s udies in he Ame icas egion: coded da a.
Sou ce: Au ho s.
Coun y/
income
le el
Resea che /place P oxy
o
e ec s
Me hodology Resul s TIME se ies
s udied/– ime–
span o e ec s
B azil (MIC) Libe a i e al. (2001)/
(ci y o Lond ina)
VTRA Be o e/ A e analysis using
Chi-squa ed and Fishe ’s es s.
A educ ion o 20% o ca and 9.1% o mo o cycle acciden
ic ims. An inc ease o 39% in use o sa e y bel s and o 112% in
use o helme .
(1997–1998)/6
mon hsVBD
Ma ei de And ade
e al. (2008)/(ci y o
Lond ina)
VTRA Linea eg ession. A 28.4% g ea e educ ion in mo ali y le els han unde o he
p e ious measu es.
(2000–2005)/12
mon hs
Canada (HIC) Chen e al. (1995)/
(B i ish Columbia)
VTRA Logis ic eg ession. The esul s showed a consis en inc ease in pos pe iod acciden s
pe d i e wi h inc easing p e pe iod numbe o c ashes.
(1985–1990)/24
mon hs
Dionne e al. (2011)/
(Quebec)
VBD P opo ional Haza ds Model. The equency o a fic iola ions was educed by 15% and he
isk o a RTA a e a a fic o ense was 20% lowe .
(1985–1996)/12
mon hs
Redelmeie e al.
(2003)/(On a io)
VBD Case-c osso e s udy The isk o a a al c ash in he mon h a e a con ic ion was
abou 35% lowe .
(1988–1999)/2
mon hs
Uni ed S a es
o Ame ica
(HIC)
Gebe s and Peck
(2003)/(Cali o nia)
VBD Bo h mul iple linea eg ession
analysis and canonical
co ela ion.
An imp o emen o 14.9% in classifica ion o p edic ing and
iden i ying acciden -in ol ed d i e s.
(1992)/No
quan ified pe iod
o e ec s
HIC: High-income coun y; MIC: Middle-income coun y; LIC: Low-income coun y.
VTRA: Va iables ela ed di ec ly o RTA, in e ms o educ ions in he numbe o acciden s, casual ies, a ali ies o inju ed; VBD: Va iables ela ed o d i e beha io , in
e ms o educ ions in isky o dange ous conduc , d i ing less unsa ely o a educ ion in law iola ions; VHCD: Va iables ela ed o heal h ca e da a, in e ms o educ ions
in RTA- ela ed A&E admissions, su ge y o hospi aliza ions.
Table 3
Selec ed s udies in he Eas e n-Medi e anean egion: coded da a.
Sou ce: Au ho s.
Coun y/
income le el
Resea che /
place
P oxy
o
e ec s
Me hodology Resul s Time se ies s udied/ ime-span o
e ec s
The Uni ed
A ab
Emi a es
(HIC)
Mehmood
(2010)/(Al
Ain)
VBD Independen
sample - es
using SPSS.
The DPS has s a is ically no significan impac on he speeding
beha io o d i e s because o he lack o e ec i e a fic moni o ing
sys em.
(3 mon hs be o e/3 mon hs a e
in oduc ion)/No quan ified pe iod
o e ec s
HIC: High-income coun ies; MIC: Middle-income coun ies; LIC: Low-income coun ies.
VTRA: Va iables ela ed di ec ly o RTA, in e ms o educ ions in he numbe o acciden s, casual ies, a ali ies o inju ed; VBD: Va iables ela ed o d i e beha io , in
e ms o educ ions in isky o dange ous conduc , d i ing less unsa ely o a educ ion in law iola ions; VHCD: Va iables ela ed o heal h ca e da a, in e ms o educ ions
in RTA- ela ed A&E admissions, su ge y o hospi aliza ions.
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201 195

possible he e ogenei y by conside ing ha he e ec s o expo-
su e/in e en ion on he popula ion a e a ied and ha he
e ec s analyzed by he included s udies a e only a andom
sample o all possible e ec s. Weigh ing s udies wi h REM
conside s no only hei own a iance (in a-s udy a iabili y),
bu also he a iance ha migh exis be ween s udies (in e -
s udy a iabili y):
s
y¼½Q2ðm1Þ
cð3Þ
whe e: Q¼De simonian and Lai d s a is ic. m¼no. o es ima ions
conside ed. c¼es ima o calcula ed as c¼P
m
i¼1
w
i
½P
m
i¼1
w
2
i
=P
m
i¼1
w
i
whe eby he a iance and he s a is ical weigh o
each i- h es ima ion would be, espec i ely
n
i
¼
s
yþ
i
and w
n
i
¼1=
n
i
In bo h cases (FEM and REM), he uppe /lowe limi s o he
confidence in e als (CI) (in ou case, a 95%), a e calcula ed by
he o mula (4):
CI ¼exp Y71:96
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Ps a is ical weigh s
p
!
ð4Þ
Any possible publica ion biases can be iden ified analy ically
using he Begg (Begg and Mazumba , 1994) and Egge (Egge e al.,
1997) es s, which es he null hypo hesis o he lack o said bias.
Table 4
Selec ed s udies in he Eu opean egion: coded da a.
Sou ce: Au ho s.
Coun y/income
le el
Resea che /
place
P oxy
o
e ec s
Me hodology Resul s Time se ies s udied/–
ime–span o e ec s
Czech Republic, The
(HIC)
Mon ag
(2010)/
VTRA S anda d di e ences-in-
di e ences me hodology.
Fa ali ies we e abou 30% lowe du ing fi s h ee
mon hs a e he law was in oduced.
(2004–2008)/3 mon hs
I eland (HIC) Bu le e al.
(2006)
VHCD S a is ical analysis using a
wo- ac o ANOVA and
Chi-squa ed es .
In he fi s 6 mon hs, he e was a significan educ ion
(48.4%) in RTA- ela ed spinal admissions. In he fi s
yea , he e was a 25% educ ion in dea hs.
(1998–2004)/6 mon hs
Healy e al.
(2004)
VHCD S a is ical analysis wi h a
Chi-squa ed es .
The numbe o RTA- ela ed admissions ell o 17
compa ed o an a e age o 33 in he p eceding 4 yea s.
(1998–2003)/6 mon hs
Hussain e al.
(2006)
VHCD Re ospec i e coho s udy. Six y-one pe cen educ ion in ope a ions on inju ies
caused by collisions.
(2001–2003)/12 mon hs
Saeed e al.
(2010)
VHCD S a is ical analysis was
pe o med using he Chi-
squa ed es .
A e he o ense o no wea ing a sea bel was added
o he DPS in 2003, he e was a 60% decline in he
p opo ion o admissions o RTA- ela ed eye-inju ies.
(2001–2007)/No
quan ified pe iod o
e ec s
I aly (HIC) Benede ini
and Nici a
(2009)
VTRA 3SLS eg ession and
Poisson Reg essions.
A s ong ‘announcemen e ec ’ wo yea s be o e he
implemen a ion o he PPS. A dec ease o 72.87% in
speeding icke s, o 17.80% in o al RTA and 26.42% in
a al RTA.
(2001–2008)/24 mon hs
be o e in oduc ionVBD
De Paola
e al. (2010)
VTRA Reg ession discon inui y
design.
A educ ion o abou 10% in RTA and o abou 25% and
15% in a fic a ali ies and inju ies, espec i ely.
(2001–2005)/No
quan ified pe iod o
e ec s
Fa chi e al.
(2007)/(The
Lazio Region)
VHCD Poisson models. Twel e pe cen ewe RTA A&E isi s; hospi aliza ions
dec eased by 16% and RTA- ela ed dea hs dec eased by
4%.
(2001–2004)/6 mon hs
Zambon e al.
(2007)/
(Vene o
Region)
VBD Time-se ies analysis wi h
ARIMA model.
An inc ease in sea bel use o 51.8% among d i e s, o
42.3% among on passenge s and o 120.7% among
ea passenge s. The numbe o RTA a ali ies and
inju ies declined, wi h a educ ion o 18% and 19%
espec i ely.
(1999–2004)/18 mon hs
VTRA
Zambon e al.
(2008)/
(Vene o
Region)
VBD Poisson models. An inc ease in sea bel use o 83% o d i e s and 76%
o passenge s.
(2003–2005)/15 mon hs
Spain (HIC) Apa icio-
Izquie do
e al. (2011)
VTRA Time-se ies analysis wi h
ARIMA models.
A mean educ ion in a ali ies o be ween 11.27% and
13.9%.
(1995–2009)/E ec s
main ained h oughou
he s udy pe iod
Cas illo-
Manzano
e al. (2010)
VTRA Time-se ies analysis wi h
unobse ed componen s
model.
An a e age educ ion o 12.6% in he numbe o dea hs
in RTA.
(1980–2007)/24 mon hs
( o dea hs) and 12 ( o
inju ed)
No oa e al.
(2010)
VTRA Quasi–Poisson eg ession
models.
The o e all numbe o people inju ed showed a
educ ion o 5% and 4% among men and women,
espec i ely, and an 11% and 12% educ ion o
se iously inju ed people.
(2000–2007)/18 mon hs
Pulido e al.
(2010)
VTRA Time-se ies analysis
h ough ARIMA models.
A educ ion o 14.5% in o e all a ali ies. (2000–2007)/18 mon hs
Uni ed Kingdom
(HIC)
Simpson
e al. (2002)
VBD Ques ionnai e su ey and
empi ical analysis using
Chi-squa ed es .
The esul s o a new PPS o no ice d i e s led o a
dec ease in he pe cen age o d i e s (5.8 o 4.5)
o ending in hei 2nd yea o pos - es d i ing.
(1992-94; 1997–1998)/
24 mon hs
HIC: High-income coun ies; MIC: Middle-income coun ies; LIC: Low-income coun ies.
VTRA: Va iables ela ed di ec ly o RTA, in e ms o educ ions in he numbe o acciden s, casual ies, a ali ies o inju ed; VBD: Va iables ela ed o d i e beha io , in
e ms o educ ions in isky o dange ous conduc , d i ing less unsa ely o a educ ion in law iola ions; VHCD: Va iables ela ed o heal h ca e da a, in e ms o educ ions
in RTA- ela ed A&E admissions, su ge y o hospi aliza ions.
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201196
This analysis mus be complemen ed wi h an in e p e a ion o so-
called unnel plo s diag ams o a oid any alse posi i es o alse
nega i es due o he loss o powe o de ec ion ha hese es s can
be subjec o in small samples (S e ne e al., 2000).
A unnel plo is a ool used o compa e he es ima ion in a
g aph using some p ecision measu e, such as a s anda d e o
unc ion, o example. I he g aph is symme ical, in an in e ed
‘‘V’’ shape, i is in e p e ed as p oo o he e p obably being no
publica ion bias. I he g aph is asymme ic, i is in e p e ed as
publica ion bias p obably exis ing.
3.3. Resul s
Table 6 shows (in columns) he main esul s ob ained o he
4 me a-analyses o mula ed in all he scena ios (in ows), using a
o al sample o m¼70 indi idual es ima ions o 26 sui able s udies.
In o de o analyze he he e ogenei y o he sample he alues a e
aken o he De simonian and Lai d Q (1986) s a is ics and he
Takkouche e al. (1999) R
I
coe ficien (¼p opo ion o he o al
a iance due o be ween-s udy a iance). The pooled odds a ios
ob ained (OR) o each scena io wi h FEM and REM, espec i ely
(wi h he confidence in e al limi s) a e se alongside he Begg and
Egge es p- alues enabling he p esence o publica ion biases ha
al e he final esul o be iden ified.
All he Q s a is ics a e significan . This would, in p inciple, allow
he homogenei y null hypo hesis o be ejec ed a 99% in all cases.
Following Takkouche e al. (1999), gi en ha in he h ee analyses
done o scena io I, R
I
is clea ly g ea e han 0.75, we unde s and
ha he De simonian and Lai d Q s a is ic is su ficien ly powe ul o
de ec he e ogenei y, o e coming he limi a ions ha his s a is ic
p esen s o small samples (see Fleiss, 1993). The e o e, o scena io
I, he OR es ima ed by REM is mo e eliable (which is why columns
7and8o Table 6 wi h he REM esul s ha e been highligh ed). This
p esence o andom elemen s means i can be deduced ha he
esul s o he in e en ion analyzed a e in eali y a ied, and ha he
es ima ions o e ed by he a ious s udies included in ou me a-
analysis a e only a andom sample o possible e ec s. The di e -
ences om one coun y o ano he would be based on he coun ies’
own peculia ea u es, such as he ad e ising campaigns o he
o he mo e o ce ul en o cemen measu es (fixed speed came as,
lowe blood alcohol limi s, fines and hea ie legal sanc ions, poli-
cing) ha accompany he applica ion o PS.
In any case, in quan i a i e e ms no significan di e ences can
be app ecia ed be ween he esul s ob ained wi h FEM and REM,
which enables us o conclude ha ou es ima ions a e obus , as is
Table 5
Selec ed s udies in he Wes e n-Pacific egion: coded da a.
Sou ce: Au ho s.
Coun y/
income
le el
Resea che /place P oxies
o
e ec s
me hodology Resul s Time se ies
s udied/– ime–
span o e ec s
China
(MIC)
Wong e al.
(2008)/(Hong
Kong)
VBD Mul inomial logi model. An inc ease in penal y poin s p oduced a posi i e de e ence e ec in
comba ing ed ligh iola ions (coe ficien ¼0.0959).
(2005–2006)/12
mon hs
Sze e al. (2011)/
(Hong Kong)
VTRA Binomial eg ession model. The numbe o ed ligh o ense RTA and casual ies d opped by 23% and
29%, espec i ely.
(2005–2007)/12
mon hs
Aus alia
(HIC)
Diaman opoulou
e al. (1997)/
(Vic o ia)
VTRA Logis ic eg ession model. Adding a d i e ’s p io o enses (whe he as deme i poin le els o
ca ego ies o o ense) in o his model p oduced he bes p edic i e abili y
in iden i ying d i e s wi h u u e RTA.
(1991–1994)/No
quan ified pe iod
o e ec s
VBD
Haque (1990)/
(Vic o ia)
VBD Poisson model using
maximum likelihood
es ima ion me hods.
The es ima ed mean in e -o ense ime in e al be ween 2
nd
and 3
d
o enses o d i e s was significan ly longe han he in e al be ween 1
s
and 2
nd
o enses.
(1982–1985)/No
quan ified pe iod
o e ec s
HIC: High-income coun ies; MIC: Middle-income coun ies; LIC: Low-income coun ies.
VTRA: Va iables ela ed di ec ly o RTA, in e ms o educ ions in he numbe o acciden s, casual ies, a ali ies o inju ed; VBD: Va iables ela ed o d i e beha io , in
e ms o educ ions in isky o dange ous conduc , d i ing less unsa ely o a educ ion in law iola ions; VHCD: Va iables ela ed o heal h ca e da a, in e ms o educ ions
in RTA- ela ed A&E admissions, su ge y o hospi aliza ions.
Table 6
Me a-analysis ou comes.
Sou ce: Au ho s.
Scena io Sample size Q s a is ic
(p- alue)
R
Ia
OR
b
(FEM)/
CI limi s 95%
Resul
d
(FEM)/
CI limi s 95%
OR
c
(REM)/
CI limi s 95%
Resul
d
(REM)/
CI limi s 95%
Begg’s es
(p- alue)
Egge ’s es
(p- alue)
I (VTRA) m¼24 0.0000
nnn
0.9944 2.9588
(2.9444; 2.9734)
19.2748
(18.993; 19.5583)
2.7570
(2.5516; 2.9789)
15.7525
(12.8276; 19.6662)
0.1574 0.3945
I (VBD) m¼18 0.0000
nnn
0.9998 3.4592
(3.4536; 3.4647)
31.7915
(31.6140; 31.9669)
3.3119
(2.9009; 3.7811)
27.4372
(18.1905; 43.8643)
0.2889 0.8765
I (VHCD) m¼8 0.0000
nnn
0.9992 4.0938
(4.0909; 4.0967)
59.9673
(44.1282; 61.6825)
3.9510
(3.7871; 4.1220)
51.9873
(59.7937; 60.1415)
0.7105 0.1318
II (LENGTH OF EFFECTS) m¼20 0.0002
nnn
0.6912 2.8088
(2.7305; 2.8893)
16.5900
(15.3406; 17.9807)
2.7663
(2.5602; 2.9840)
15.8997
(12.9384; 19.7667)
0.1119 0.2286
No es: Defini ion o a iables o Scena ios: VTRA: Va iables ela ed di ec ly o RTA, in e ms o educ ions in he numbe o acciden s, casual ies, a ali ies o inju ed; VBD:
Va iables ela ed o d i e beha io , in e ms o educ ions in isky o dange ous conduc , d i ing less unsa ely o a educ ion in law iola ions; VHCD: Va iables ela ed o
heal h ca e da a, in e ms o educ ions in RTA- ela ed A&E admissions, su ge y o hospi aliza ions; Leng h o e ec s: numbe o mon hs.Significance a
nnn
1%,
nn
5%,
n
10%,
espec i ely.
a
R
I
indica es he p opo ion o he o al a iance due o be ween-s udy a iance.
b
Odd Ra ios o fixed-e ec s model and andom-e ec s model exp essed in loga i hm.
c
Odd a ios o fixed-e ec s model and andom-e ec s model exp essed in loga i hm.
d
Resul s (exponen ial OR) exp essed in % o all a iables o Scena ios I and numbe o mon hs o Scena io II.
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201 197
also shown by he sensi i i y analyses done.
8
In bo h models, he
a iables ha expe ience a mo e posi i e e ec wi h he coming
in o e ec o he PS a e he VHCD (wi h educ ions o o e 50%
bo h in he numbe o hospi aliza ions and in A&E admissions),
ollowed by he VBD (wi h a educ ion in he numbe o eckless
beha io s o a ound 30% on a e age). Meanwhile, he weakes
e ec seems o be on he VTRA (wi h educ ions in acciden s,
a ali ies and inju ies o be ween 15 and 20%), i.e., he a iables
mos di ec ly ela ed o oad a fic acciden s.
Conside ing scena io II, a numbe o doub s could be aised
abou which o he wo me hods o es ima ing he Leng h o
E ec s is mo e app op ia e as, despi e he Q s a is ic ejec ing he
homogenei y null hypo hesis a 99%, he R
I
coe ficien is sligh ly
unde 0.75, indica ing ha i s de ec ion is less powe ul
(Takkouche e al., 1999). No wi hs anding, his p oblem is i ele-
an gi en how simila he es ima ions by bo h FEM and REM a e,
wi h a di e ence o only 21 day be ween hem (16.6 mon hs
compa ed o 15.9 mon hs e ec s du a ion). In any e en , he
du a ion o he e ec s o PS is on a e age less han one and a
hal yea s.
When his esul is es ed agains Tables 2–5, i can be seen
ha o he 26 assessmen s analyzed in 11 di e en coun ies, 20
de e mine he leng h o he e ec s o a PS, and o hese 9 gi e
du a ions o o e 12 mon hs. E en in hese cases no e ec las ed a
pe iod o o e 2 yea s, and he e was simply an in e im e ec
compa ed o o he oad sa e y measu es wi h mo e s uc u al
e ec s (see e.g., Apa icio Izquie do e al., 2011 o policing and
Cas illo-Manzano e al., 2010 o manda o y sea bel use in
Spain). Ano he in e es ing aspec is ha 7 o hese 9 e alua ions
wi h e ec s o o e 12 mon hs a e o he same wo Eu opean
coun ies, I aly and Spain, which s a ed ou wi h oad acciden
a es ha we e highe han he mean o he Eu ozone (WHO,
2009). The sys em’s implemen a ion in hese coun ies was also
accompanied by widesp ead dissemina ion o ad e ising cam-
paigns in he ins i u ional media and in all p i a e news media,
which shaped a a o able pe cep ion as a as public opinion is
conce ned (No oa e al., 2010 o Spain; Benede ini and Nici a,
2009 o I aly). Specifically in he case o I aly, Benede ini and
Nici a (2009) ound he e was an e ec e en be o e he PPS law
came in o o ce, wi h he media in e es b inging abou a posi i e
‘‘announcemen e ec ’’, i.e., he e ec s o PPS in oduc ion we e
an icipa ed e en be o e i had been e ec i ely adop ed as law.
The emaining 11 s udies coincide in 12 mon hs being a qui e
likely du a ion o he e ec s o he measu e and ha he e ec s
would no emain s able h oughou his pe iod o a yea , bu
would g adually dec ease. Specifically, a e a majo ini ial shock
du ing he mon hs ha immedia ely ollowed PS coming in o
o ce, he e ec s quickly wane wi h ime. The e is clea e idence
ha his majo shock was no ed e en in coun ies whe e he
e ec s immedia ely fizzled ou . In Canada, o example (see
Redelmeie e al., 2003), al hough i was es ima ed ha he
e ec s only las ed 2 mon hs, he e was a 35% all in he isk o
a a al c ash and in he Czech Republic (see Mon ag, 2010),
despi e he e ec s being limi ed o only 3 mon hs, a ali ies we e
abou 30% lowe .
The p- alues ob ained in he Egge and Begg Tes s in Table 6
show ha , in p inciple, ou es ima ions could be s able om he
poin -o - iew o publica ion biases, as he lack o bias null
hypo hesis canno be ejec ed in all he scena ios. Howe e , as
hese de ec ion me hods a e known o no always be e y
powe ul (e.g., S e ne e al., 2000), i is ecommended ha he
es s a e complemen ed wi h an in e p e a ion o he unnel plo s
diag ams (Palma-Pe
´ ez and Delgado-Rod ı
´guez, 2006) which a e
included o all he analysis scena ios in Figs. 1–4.
The pa ame e s anda d e o (SE) is ep esen ed on he x-axis,
he pa ame e o each s udy (odds a io,OR) on he y-axis and
each es ima ion by a poin . The esul is a unnel which na ows o
he le as highe p ecision s udies (smalle SE, equi alen o a
la ge sample size) a e on he le -hand side o he figu e and
he e is less a iabili y be ween hem. A symme ical figu e ising
om a ho izon al axis ha passes h ough he pa ame e ’s
weigh ed alue would indica e he absence o his e o .
As can be seen in Figs. 1–4, mo e o less asymme ical figu es
a e ob ained o all scena ios which con adic he es s done in
Table 6 and indica e he exis ence o publica ion biases. Howe e ,
cau ion should be used when in e p e ing his. In ac , acco ding
o Tho n on and Lee (2000), symme y can be subjec i ely defined
by he esea che , especially when he e a e small numbe s o
poin s. He e ogenei y be ween he es ima ions can also in e e e
when assessing o publica ion bias.
No wi hs anding, ollowing Høye and El ik (2010) publica ion
biases a e e y equen ly ound in me a-analysis o e alua e he
e ec s o a oad sa e y measu e. These au ho s s a e ha he e a e
ce ain p ejudices abou omi ing he publica ion o s a is ically
nonsignifican s udies o hose wi h ad e se esul s, as i is no
easonable o public opinion o expec a oad sa e y measu e ha
has no e ec . Ano he possible sou ce o hese publica ion biases
could be he s ic fil e applied o selec he s udy sample o he
S anda d E o (SE)
E ec Es ima ion
Fig. 1. VTRA scena io. No e: E ec es ima ion in log scale.
Sou ce: Au ho s.
S anda d E o (SE)
E ec Es ima ion
Fig. 2. VBD scena io. No e: E ec es ima ion in log scale.
Sou ce: Au ho s.
8
The esul s o he sensi i i y analysis a e a ailable om he au ho s upon
eques .
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201198
me a-analysis (see Sec ion 3.1). Ce ain s udies om se e al
coun ies ha e been delibe a ely omi ed ei he because he
me hodologies ha hey applied we e no e y igo ous (be o e
and a e s a is ical compa isons), o because hey we e ‘suspi-
cious’ o ha ing been ca ied ou by go e nmen al o ganiza ions
and no being widely dissemina ed academically.
4. Conclusions and implica ions o oad sa e y
Since hei pionee ing implemen a ion in he US in he mid
20 h cen u y, d i ing licenses based on poin s sys ems ha e
apidly expanded o coun ies wi h high and medium income
le els on all con inen s, especially in he Eu opean egion. As
Nole
´n and O
¨s lin, (2008) and ETSC (2008) s a e, hei popula i y
and social accep ance as one o he ai es co ec i e and punish-
men measu es o in e nalizing he social cos s o oad a fic
acciden s seem o be he key o hei wide- anging de elopmen
o e he las decade. Despi e ecommenda ions om p es igious
in e na ional o ganiza ions, e y li le is known in he academic
li e a u e abou he e ec s o poin s sys ems on oad sa e y,
because i is e y di ficul o isola e hei impac om he e ec s
o o he concu en complemen a y ypes o en o cemen applied
(SWOV, 2010) (policing, laws o ad e ising campaigns). In his
ega d, s udies such as Cas illo-Manzano e al. (2010) poin o he
mos con o e sial aspec o poin s sys ems linked o hei o e all
e ec s in he sho - and long- e m.
Ou s udy analyzes whe he poin s sys ems eally a e e ec i e
o b inging down he a fic acciden a e o whe he his is jus a
ashionable policy ha coun ies in close geog aphical p oximi y
o wi h simila cul u al pa e ns imi a e. The e ec s o poin s
sys ems and he du a ion o he e ec s ha e been es ima ed by
applying a me a-analysis app oach o a sample o 70 es ima ions
aken om 26 scien ific assessmen s om 11 coun ies. Al hough
i migh esul in publica ion bias, a s ic sample selec ion
c i e ion was op ed o and a numbe o suspicious and possibly
less scien ifically igo ous s udies we e omi ed.
The esul s o he sensi i i y analyses enable i o be obus ly
s a ed ha all he a iables benefi om he implemen a ion o a
poin s sys em. To be p ecise, educ ions o o e 50% in numbe s o
oad a fic acciden - ela ed eme gency admissions, su ge y and
hospi aliza ions a e eco ded. Reduc ions o a ound 30% in he
numbe o law iola ions and isky and dange ous d i e beha-
io s a e also es ima ed. Howe e , he mos significan e ec ,
(gi en ha he ou comes a e di ec ly linked o oad a fic
acciden s), is he educ ion be ween 15 and 20% seen in he
numbe o acciden s, a ali ies and inju ies. By con as , he high
expec a ions ha poin s sys ems gene a e among public opinion
and he oad sa e y au ho i ies wi h ega d o du a ion in ime
ha e no been subsequen ly suppo ed by long- e m esul s as, in
gene al e ms, he e ec s wea o in less han 18 mon hs. Only
7 o hese s udies s a e ha he e ec s ha e du a ions o o e 12
mon hs, bu also indica e ha hey las unde 2 yea s. Mos o
hese se en s udies, inciden ally, e e o Spain and I aly, coun-
ies, p ecisely, whe e he sys em has been accompanied by majo
ad e ising campaigns, as shown by No oa e al., (2010) and
Benede ini and Nici a, (2009). I seems ha his measu e has
only a majo ini ial shock on a wide ange o oad sa e y a iables
and indica o s, al hough he e ec quickly declines o e ime
when he e a e no o he complemen a y en o cemen measu es.
In sho , as Twisk and S acey (2007) s a e, many o he coun e -
measu es ha a ec a licensing p ocess a e no e ec i e wi hou
en o cemen ha inc eases he eeling ha you could be caugh ,
and complemen ed wi h media co e age ha educes he incen-
i e o o ende s o pe sis in hei unsa e beha io s.
Gi en ha he benefi s seem o be unning ou in e ms o oad
sa e y, i is necessa y o compu e he es ima ed cos o imple-
men a ion. To da e, li le has been p o ided ega ding quan ifica-
ion o he han, acco ding o El ik and Vaa, 2004, ha hese cos s,
a p io i, logically seem o be heo e ically lowe han o o he
oad a fic acciden p e en ion me hods, such as oad imp o e-
men s. Fo El ik. e al. (2009), he lack o a ull es ima ion o hese
cos s would explain why o da e a mo e- han- equi ed Cos -
Benefi Analysis has no been conduc ed o his measu e.
Fo all hese easons, a u u e line o esea ch ha begs o be
sugges ed is a ealis ic es ima ion o he cos s o his measu e.
This es ima ion should ake in o accoun bo h he design o he
in o ma ion campaigns ha suppo hem and changes in he
coun y’s policing, legal and adminis a i e sys ems ha esul
om hei applica ion. Wi h espec o he in o ma ion cam-
paigns, hese ha e o be ex ended o co e he whole o he
popula ion and also need o be in ensi e in o de o deal wi h all
aspec s o he sys em, om he a ious iola ions ha a e
en isaged, o he license wi hd awal p ocess and i s la e eco -
e y. Wi h ega d o he policing and legal-adminis a i e sys ems
being adap ed, o p e en injus ices he e should be ull coope a-
ion be ween all he au ho i ies esponsible o oad sa e y wi h
he aim o ensu ing ha he moni o ing, de ec ion and eco ding
o all sanc ions is s anda dized whe e e hey ake place.
I he measu e is implemen ed in a way ha is lacking in his
espec i could lead ei he o he measu e being u ile, as would
seem o ha e been he case in The A ab Emi a es (see Mehmood,
2010), o ha sys ema ic injus ices a e commi ed among
S anda d E o (SE)
E ec Es ima ion
Fig. 4. VHCD scena io. No e: E ec es ima ion in log scale.
Sou ce: Au ho s.
S anda d E o (SE)
E ec Es ima ion
Fig. 3. VHCD scena io. No e: E ec es ima ion in log scale.
Sou ce: Au ho s.
J.I. Cas illo-Manzano, M. Cas o-Nun
˜o / T anspo Policy 21 (2012) 191–201 199