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David NewhouseDaan PattinasaranyDaniel Suryadarma
Outline of presentation1. Motivation (vocational education expansion) 2. Data and estimation strategy 3. Effects of high school type
Entire sample Cohort vs. age effects
Vocational education in IndonesiaShare of vocational high schools (SMK) is shrinking
Planned expansion
Plan to expand enrollment in vocational high schoolsIncrease ratio of SMK:SMA students to 50:50 by 2010Up to 70:30 by 2015, moving 4.1 million students into SMKMotivated by desire to reduce unemployment.
Weak empirical support
Existing researchNo differences between SMK and SMA outcomes in:
South Korea (KRIVET, 2008)Singapore (Sakellariou, 2003)Romania (Malamud & Pop‐Eleches, 2008)
Evidence on gender differences is mixed Males: SMK earn higher in Egypt but lower in Singapore. (El‐hamidi 2006)Females: SMK earn higher in Singapore but lower in Egypt.
Past research in Indonesia“VTE results in neither advantage nor disadvantage with respect to earnings or employment” (Chen, 2009). But…
Wide confidence intervals: OLS: 0 to 60% of mean earnings IV: ‐50 to 150% of mean earnings
Sample restricted to adults under 2530 percent of sample still in college. Selection correction excludes head education, test scores, prior household income from earnings regression (?)
Few control variables (gender, rural, age)
Our contributionsSeparate men and women Distinguish between public and private schoolsMany cohorts (all born from 1940‐1980) Rich set of predetermined controls
Parental education (even if non‐coresident)District of Jr. High school dummies
Four main LM indicators Participation, unemployment, formal work, wage
OLS (for now), IV (hopefully coming later)
Main messages: Public VTE No significant wage effect. Confidence intervals: ‐10 to 13 percent for men‐7 to 22 percent for women
For women, increases chance of formal job For young men born 1973‐1980, worrisome recent fall in returns. ‐50 to 7 percent in 2000‐2 to ‐80 percent in 2007
Main results: Other types Public school premium
20 percent wage premium for menPrivate general education underperforming
Outcomes equal or worse than private VTE, despite observably more privileged students
Why do men attend private general schools? Market for information functions poorly? Non‐academic factors relatively important in determining preferences?
Data 4 rounds of Indonesian Family Life Survey
1993, 1997, 2000, 2007 7,300 households in 1993, 12,600 by 2007 13 provinces representing 83% of Indonesia in 1993 Retrospective data on school attendance
Type of schools for all levelsIncluding test scores for those born 1983 or later.
Limited to high school students
Data constructionMen Obs Women Obs
Eligible high school grads 2989 6972 2513 6035Reported school information 2790 6619 2360 5940
In labor force 2660 6001 1786 3507Employed 2495 5485 1546 2921
Reported earnings 2382 5109 1451 2718
Reported school information 2790 6619 2360 5940Old cohort (born 1940‐1963) 927 2608 585 1760Middle cohort (1964‐1972) 950 2066 838 1957Recent cohort (1973‐1980) 888 1494 947 1686
Of which reported test score 754 1276 777 1379
Choice of school type
iddpdiPiizi PPZT εβββ +++=• Tid = School Type
Public general, public VTE, private general, private VTE
• Zi = Predetermined characteristicsCohort, sex, age 12 residence (city, town, village), adult height, public jr. high, worked in jr. high, worked in elem, failed grade in jr. high, failed grade in elem, province of junior high)
• Pi = Parental education (both parents)Elementary, jr. high, high school, univ dummies Vocational dummy
• Pd = District parental education shares
Vocational school attract children of least educated parents
Men Women
Pub gen VTE
Prigen VTE
Pub gen VTE
Prigen VTE
Father elem 4.2 -1.4 4.0 -6.9* -6.1 -4.9 5.7 5.3Jr. high 6.0 -4.2 7.9 -9.8** -5.5 -8.9* 7.9 6.6High school 5.3 -7.1 14.0** -12.2*** -1.3 -8.8 11.0 -0.8University 18.5** -12.3*** 12.7* -19.0*** 6.1 -11.8** 7.5 -1.8
Mother elem 0.1 -4.4* 5.6* -1.3 6.6 6.9** -4.5 -9.0***Jr. high 2.5 -4.5 7.8* -5.9 12.9** -1.3 2.0 -13.6***
High school 5.2 -8.6* 1.9 1.5 10.1 5.0 -2.2 -12.9**University 18.8* -5.4 -4.4 -9.1 17.0* 7.6 -11.3 -13.3**
School type determinants: Young cohortFor youngest cohort, test scores are available.
Si = Score tertile (on jr. high exit exam)
idisdpdiPiizi SPPZT εββββ ++++=
Public schools attract high scorers• Public VTE attracts high scoring student•Private VTE attracts lowest‐scoring students
Men Women
Pub gen VTE
Pri genVTE
Pub gen VTE
Pri genVTE
Test middle tercile 13.3*** 8.2** -2.6 -18.9*** 5.1 8.9** -2.6 -11.3***Test upper tercile 24.0*** 16.6*** -17.8*** -22.7*** 19.4*** 13.0*** -9.6** -22.7***
Observations 749 772Pseudo‐r2 0.201 0.219
Selection: Summary RankingsRanking Parental education Test scores
Top Private general Public general and VTE Second Public generalThird Public VTE Private generalBottom Private VTE Private VTE
Estimating labor market outcomesidisttddiPiizit TDDPZY εβββββ +++++=
i = person, t = year, d = district
Ti = dummies for pub VTE, pri gen, pri VTE.Zi = Predetermined characteristicsPi = Parental education Dd = District of jr. high dummies Dt = Year dummies Yi = Four outcomes:
• Participation, Unemployment (conditional on participation) • Formal job, Log wage/profit (conditional on working)
Estimating labor market outcomesReweight using inverse propensity scores
Propensity scores taken from multinomial logit of school type Helps balance observables across school types
Protects against bias from linear functional form assumption
Students in different types of school appear different based on observables. Loss of efficiency
Important to separate by genderDifferences in both participation and vocational education majors
Women tend to study business or tourism rather than technical orindustrial subjects.
Public VTE: No discernible effect on LFP or Unemp
Men WomenLFP Unemp LFP Unemp
Public VTE 0.014* -0.010 0.028 -0.015
(0.007) (0.011) (0.029) (0.012)
Private 0.011 -0.005 -0.068** 0.019*
general (0.008) (0.008) (0.032) (0.011)
Private VTE 0.004 0.008 -0.030 0.001
(0.009) (0.013) (0.035) (0.013)
Pub gen prob 0.965 0.051 0.684 0.046r2 0.077 0.149 0.188 0.223Observations 6,158 5,963 5,387 3,478
High public school wage premium for men
Men WomenFormal Wage Formal Wage
Public VTE 0.032 0.011 0.058** 0.075
(0.023) (0.057) (0.028) (0.072)
Private -0.058** -0.172*** -0.080** -0.043
general (0.027) (0.060) (0.039) (0.073)
Private VTE 0.029 -0.192*** 0.003 -0.013
(0.024) (0.064) (0.037) (0.080)
Pub gen prob 0.743 0.748r2 0.188 0.223 0.245 0.313Observations 5,696 5,102 3,324 2,709
Public wage premium robustWage premium for median female VTE
But no jr. high district fixed effects in LAD estimates
Men WomenOLS LAD OLS LAD
Public VTE 0.011 0.028 0.075 0.118**
(0.057) (0.039) (0.072) (0.049)
Private -0.172*** -0.262*** -0.043 -0.203***
general (0.060) (0.043) (0.073) (0.070)
Private VTE -0.192*** -0.184*** -0.013 -0.076
(0.064) (0.040) (0.080) (0.066)
Observations 5,102 5,102 2,709 2,709
Age and cohort effectsInteract with years, separately by cohort
C = cohort Old: 1940‐1963Middle: 1963‐1972Recent: 1973‐1980
Interact type with all four years (omit main effects) Graph estimated effect vs. mean age for each cohort and year
idtiTdpdiPiizic DTPPZY εββββ ++++= *
Age and cohort effects: LFPMen Women
Age and cohort effects: UnempMen Women
Age and cohort effects: Formality
Men Women
Age and cohort effects: WagesMen Women
Partly robust to median regMen Women
SummarySelection
Rank on test score: Public, private general, private VTE Rank by parent education: Private general, public general, Public VTE, private VTE
OutcomesPub VTE boosts female formality For men, private school grads face 20 percent wage penalty.
Suggests that test scores and peer effects are important determinants of future earnings for men
SummaryPrivate general graduates are underperforming
Perform as poorly or worse than private VTE grads despite more educated parents.
Male VTE penalty increasing among recent grads Industrial and technical VTE less relevant in an increasingly service‐oriented economy?
Policy implicationsExpansion should proceed with caution, given recent fall in male graduates’ earnings
If anything, more important to expand access to public schools than VTE specificallyRe‐examine industrial public VTE curriculum
Private VTE appears to be effective at preparing the weakest students
Scope for vouchers?
The puzzle of private general schools
Why is there a private school wage penalty for men but not women?
Are privately schooled low‐earnings women more likely to not work?
Why do well‐educated parents send their children to private general schools?
Poorly functioning market for information on quality of private general schools? Vocational curricula and private status are complements?
Public VTE has become less popular
Men WomenPub gen VTE
Pri gen VTE
Pub gen VTE
Pri gen VTE
Middle cohort 4.5* ‐12.7*** 9.1*** ‐0.9 ‐0.5 ‐15.8*** 9.9*** 6.4**
Recent cohort ‐2.6 ‐13.1*** 3.8 11.9*** 2.2 ‐19.6*** 8.2*** 9.2***
Failed grade in jr. high ‐3.1 ‐2.5 5.8 ‐0.2 3.3 ‐13.8 2.3 8.2
Small town at age 12 1.3 0.2 ‐1.3 ‐0.2 4.3* ‐3.6* ‐2.3 1.6
City at age 12 4.3* ‐0.6 ‐3.0 ‐0.7 6.0** ‐1.4 1.6 ‐6.3***
Height ‐0.0 ‐0.2 0.4** ‐0.2 0.1 ‐0.1 0.3 ‐0.2
Base probability 12.8 30.8 18.4 38.0 50.6 19.8 17.7 11.9
Observations 2,716 2,303
Pseudo‐r2 0.089 0.108
“Formal job" is a meaningful outcome
Definition of formal job (Simplified national definition)
Defined for all workers (incl. 7% unpaid family)Formal jobs tend to have higher wages and benefits.
Status Industry
Non‐Agriculture Agriculture
Family worker Informal Informal
Self‐employed alone Informal Informal
Self‐employed with temporary workers Formal Informal
Employers or Employees Formal Formal
Omitting scores has little effect(on young cohort of men, conditional on school type)Men, Young Cohort LFP UnemployedTest Scores included? Yes No Yes No
Public VTE 0.039 0.017 -0.038 -0.063(0.028) (0.028) (0.041) (0.045)
Private 0.021 0.012 -0.015 0.008general (0.025) (0.026) (0.033) (0.036)
Private VTE -0.010 -0.005 -0.009 0.013(0.025) (0.028) (0.039) (0.043)
Observations 1,493 1,275 1,382 1,176
Omitting scores has little effect (on young cohort of men, conditional on school type)Men, Young Cohort Formal WageTest Scores included? Yes No Yes NoPublic VTE 0.021 0.033 -0.284*** -0.304***
(0.041) (0.046) (0.092) (0.094)
Private -0.001 -0.003 -0.063 -0.048general (0.038) (0.050) (0.086) (0.101)
Private VTE 0.061 0.058 -0.092 -0.046(0.041) (0.049) (0.085) (0.095)
Observations 1,180 1,001 974 819
Omitting scores has little effect (on young cohort of women, conditional on school type)Women, Young Cohort
LFP UnemployedTest Scores included? Yes No Yes No
Public VTE 0.022 0.024 -0.026 -0.025(0.048) (0.049) (0.034) (0.034)
Private -0.040 -0.017 0.024 0.042general (0.053) (0.055) (0.042) (0.045)
Private VTE -0.016 0.010 0.033 0.059(0.051) (0.052) (0.035) (0.038)
Observations 1,376 1,376 872 872
Omitting scores has little effect (on young cohort of women, conditional on school type)Women, Young Cohort Formal WageTest Scores included? Yes No Yes NoPublic VTE 0.000 -0.004 -0.138 -0.126
(0.060) (0.059) (0.129) (0.132)
Private -0.129** -0.140** -0.129 -0.106general (0.060) (0.065) (0.136) (0.132)
Private VTE -0.023 -0.036 -0.179 -0.181(0.052) (0.057) (0.119) (0.132)
Observations 761 761 580 580
Outcomes by test scoreMen Formal WageTest score Low High Low High
Public VTE 0.143 -0.001 -0.282 -0.371***(0.088) (0.055) (0.220) (0.143)
Private 0.024 0.048 -0.196 -0.321**general (0.086) (0.099) (0.151) (0.157)
Private VTE 0.146 0.101 -0.109 -0.489***(0.090) (0.081) (0.161) (0.174)
Observations 583 592 495 483
Outcomes by test scoreWomen Formal WageTest score Low High Low High
Public VTE 0.049 -0.025 0.376 -0.238(0.094) (0.100) (0.358) (0.196)
Private -0.093 -0.098 0.238 0.077general (0.093) (0.103) (0.281) (0.253)
Private VTE -0.061 -0.021 0.281 -0.362*(0.106) (0.098) (0.188) (0.203)
Observations 403 403 292 351