Institute for Labour Market Policy Evaluation, Sweden, 2006Iris J Y Wang, Kenneth Carling, Ola Nääshttp://www.ifau.se/upload/pdf/se/2006/wp06-14.pdf

Irina Trunova and Valeriya LopinaCentral European UniversityMay 27, 2010

Summer jobs are beneficial- they complement in-class education - they offer hints what to study and motivate - financial help- establishing a social network

Negative consequences of summer jobs◦ They may make students exhausted for the new

semester◦ Too easy money, no interest to study

Quasi-experimental data

Mid-size town of Falun, Sweden, 1995 – 2002 annually (except 1996)

Lottery: providing summer jobs to high school applicants

Average participation over the years• 2,700 students enrolled in high schools in Falun• 800 students apply for municipal jobs• 200 summer jobs are offered on a lottery basis

Number of students enrolled in high schools in Falun

3-week summer jobs in the municipality • Care of elderly people• Cleaning jobs• In 2002 teaching positions at the upper elementary schools

(but just a few)

Payment• 42 and 52 SEK (€ 4-5) per hour depending on age • 60 SEK (€ 6) per hour for tutors

Year Applicants Non-applicants Total

1995 158 2 582 2 740

1997 570 2 153 2 723

1998 878 1 949 2 827

1999 820 1 944 2 764

2000 823 1 937 2 760

2001 872 1 997 2 869

2002 689 2 233 2 922

Uniform until 1998, then shift to the left in the centre of distribution

The age distribution of applicantsAge/Year 1995 1997 1998 1999 2000 2001 2002

16 37 101 140 194 247 274 164

17 41 197 249 331 314 346 282

18 53 152 291 279 258 245 222

19 27 120 198 16 4 7 21

Total 158 570 878 820 823 872 689

Young students (16-17 years) Old students (18-19 years)

• Almost 100% of offers are accepted by the applicants• 60% denied applicants managed to find a summer job • The proportion of summer jobs if higher for older students

Non-applicants earn more than applicants- They may have stronger abilities - They may be better informed

Young students (16-17 years)

Old students (18-19 years)

• Difference between applicant and non-applicant is small

• Advantage of municipal jobs relative to private ones in 2001

• Difference between applicant and non-applicant is high (heterogeneity in skills)

Data set◦4,810 applications in total◦3,197 applicants (after excluding

students who applied several times)

Was the lottery fair? ◦6-month difference in age between

treatment and control groups ◦No significant difference in grades ◦Puzzling gender difference

Belief that the lottery was fair

Age Gendera Gradeb

Year Offer Non-offer Offer Non-offer Difference Offer Non-offer

1995  17.27 17.29 0.45 0.54 0.09 0.60 0.59(0.16) (0.16) (0.06) (0.05) (0.08) (0.03) (0.03)

1997  17.88* 17.39 0.34 0.43 0.09 0.56 0.62(0.11) (0.05) (0.02) (0.05) (0.05) (0.03) (0.01)

1998  18.11* 17.37 0.43 0.39 -0.04 0.59 0.62(0.05) (0.04) (0.02) (0.03) (0.04) (0.01) (0.01)

1999  17.65* 16.92 0.35 0.44 0.09* 0.60 0.60(0.04) (0.03) (0.02) (0.03) (0.04) (0.02) (0.01)

2000  17.41* 16.92 0.35 0.48 0.13* 0.61 0.60(0.05) (0.03) (0.02) (0.04) (0.04) (0.02) (0.01)

2001  17.39* 16.81 0.48 0.52 0.04 0.63 0.61(0.04) (0.03) (0.02) (0.03) (0.04) (0.02) (0.01)

2002 17.57* 17.04 0.37 0.49 0.12* 0.64 0.62(0.06) (0.04) (0.02) (0.04) (0.04) (0.03) (0.02)

a) The proportion of malesb) The student’s lower secondary grade, as a percentile rank

• Intention-to-treat analysis (ITT)“Analyze as randomized!” (Dallal, 2004)

◦Treatment group: who were offered the jobs

◦Control group: not offered by municipality

• On-treatment analysis (OT)◦Treatment group: who were offered the jobs

and who were not but found them

◦Control group: who rejected the job offers and who were not offered and failed to find jobs

• ITT = α1 – α2

• OT = β1 – β2

• Median of labour market earnings of the applicants – who were offered the job at the municipality (α1)

– who were not offered the job (α2)

– with a summer job (β1)

– without a summer job (β2)

Corresponding numbers of students are Nα1,Nα2, Nβ1, Nβ2

SJ Non-SJ

Offers Group-11 Group-12 α1 (Group-1)

Non-offers Group-21 Group-22 α2 (Group-2)

β1 (Groups 11and 21)

β2 (Groups 12and 22)

The effect of summer jobs on median earnings for high school students after graduation at the age of 19 years.Year

(t)

α1 α2 α1 – α2 β1 β2 β1 – β2

(Nα1) (Nα2) (Nβ1) (Nβ2)

t=0 53427 43730 9697* 49219 44067 5153

(940) (1202)   (1430) (712)  

t=1 45950 42030 3920 44443 42200 2243

(742) (966)   (1158) (550)  

t=2 47906 54700 -6794 51057 52600 -1543

(579) (687)   (884) (382)  

t=3 43900 53500 -9600 48408 53259 -4850

(387) (481)   (602) (266)  

t=4 50562 63000 -12438* 55975 59551 -3575

(237) (279)   (371) (145)  

t=5 97242 53000 44242 84750 42955 41795

(83) (141)   (174) (50)  

t=6 174055 76100 97955 142695 46411 96284

(39) (39)   (70) (8)  

t=7 218400 91500 126900 204200 69300 134900

(15) (11)   (23) (3)  

The effect of offer:

1iti1t1tit +O +=) ln(w a

2itp

P

1pipi2t2tit +O +=) ln(w

a

Wit – the earnings of the ith student t years after graduationOi equals one if the student was offered a summer job and zero otherwiseχ includes all the significant background variables (gender, age, log of family earnings)α1t and α2t – the parameters of interest which show the effect of the offer on the log earnings

The effect of a summer job:

3iti1t3tit +SJ +=) ln(w a

ita 4p

P

1pipi2t4tit +SJ +=) ln(w

SJi equals one if student i have had a summer jobOther parameters are similar to those in model of job offer

The effect of an offer and a summer job on the log-earnings for high school students after graduation. Year

(t)

α1 α2 β1 β2

(SE) (SE) (SE) (SE)

t=0 0.73* 0.89* 1.46* 1.72*(0.18) (0.18) (0.18) (0.19)

t=1 0.01 0.15 0.41* 0.62*(0.18) (0.18) (0.19) (0.19)

t=2 -0.14 0.1 0.33 0.57*(0.2) (0.21) (0.21) (0.22)

t=3 0.04 0.02 0.27 0.31(0.22) (0.24) (0.24) (0.24)

t=4 -0.60* -0.48 -0.12 0.05(0.3) (0.33) (0.33) (0.34)

t=5 0.69 0.5 1.03* 1.01*(0.44) (0.45) (0.5) (0.51)

t=6 0.64 0.58 3.16* 3.42*(0.91) (0.94) (1.47) (1.56)

t=7 1.73 1.42 3.24 2.59(1.55) (1.55) (2.37) (2.45)

Positive summer job effect The effect vanishes quickly From OT analysis no effect for all students

(might be due to selection bias)

Short-term advantage via early labour market contacts

No effect on student’s productivity

Other pattern in the US

Yes because of randomization

But we cannot extend these findings to other kinds of jobs which require other skills

all students

countries with different labour market structure