STATE-LEVEL INVESTMENTS IN EARLY CHILDHOOD EDUCATION:

EVIDENCE OF SHORT- AND LONG-TERM IMPACTS

Jade Marcus Jenkins

May 8, 2019

State Early Childhood Policy

It’s a very exciting time:

●Explosion of research in early childhood

development and education

Huge Impacts of ECE Demonstration Studies

Perry Preschool Abecedarian

Knudsen, Heckman, Cameron & Shonkoff, 2006

Intervention Group

Control Group

State Early Childhood Policy

It’s a very exciting time:

●Explosion of research in early childhood

development and education

● Investments in early childhood education

○ Federal: $20.5 Billion; California: $4.7 Billion

●Expansions in age-4 state prekindergarten programs

….But it is also a mess

Why so messy?

Mess #1: State ECE funding and governance is

complicated

• ECE dispersed across state agencies

• Different government agencies responsible for

different aspects of ECE policy (Kagan & Rigby, 2003; Waldfogel 2006;

Witte and Trowbridge 2005; Jenkins & Henry, 2016)

• Haphazard, idiosyncratic, incoherent (Pianta, Barnett, Burchinal,

Thornburg, 2009)

California’s ECE system

Learning Policy Institute, 2017

Every state does ECE differently

Bipartisan Policy Center, 2018

State Early Childhood Systems

• Limited research on state ECE systems

• Disorganization hinders alignment and synergy of state policies

• Some dispersion across agencies OK for kids outcomes, but not too much (Jenkins & Henry, 2016)

Coordination possible if limited # of agencies involved

Single organization may be ”master of nothing”

• Call for stronger coordination and alignment at state and local levels

• ACF Preschool Development Grants; RttT-ELC

Mess #2: Long-run impacts of scaled-up state pre-k not conclusive

Phillips et al., 2017

Scaled-up

pre-k is not

Perry or

Abecedarian

Learning Policy Institute, 2017

What types of long-run outcomes might we expect from state-level

ECE programs?

THE RETURNS OF AN ADDITIONAL YEAR OF SCHOOLING:

THE CASE OF STATE MANDATED KINDERGARTEN

Jade Jenkins - UC Irvine

Maria Rosales – Rutgers University

Motivation

●Expansions in age-4 state prekindergarten programso Voluntary part- or full-time educational programs

o Third-party delivery systems

• Public, Private for-profit, Private non-profit, CBOs

o Primarily means-tested (e.g., NJ, NC), some universal (e.g., GA, OK)

Short term evidence, ✔️; Long-term evidence, …

●Trend mirrors the origins of kindergarten programs○ Voluntary part- or full-time educational programs

• Moved from private to public school provision

●Some states evolved to compulsory kindergarten

attendance○ Others, 1st grade (age 6-7) compulsory schooling begins

Our Study

● Several states began adopting compulsory KG during the 1970-90s ○ Between 1970-2000, 13 states adopted (e.g., AR, DE, VA, GA, OR, LA)

○ Shift in the minimum school entry age from age 6-7 (1st grade) to 5-6 (KG)

● Understand impacts of requiring an extra year of early education Insight into the returns from expansions in pre-k attendance

What are the effects of state mandatory kindergarten

requirements on long-run human capital and self-sufficiency

outcomes?

Do these effects vary across key subpopulations?

Contributions

● At-scale, universal early childhood intervention vs. small, targeted, high-intensity intervention (e.g., Heckman et al. 2010; 2012)

● Examine heterogeneity with large, representative samples

● Departure from literature examining impacts of individual age-within-cohort at school entry on long-run outcomes (e.g.,

Angrist and Krueger, 1991; Bedard & Dhuey, 2012; Black et al., 2011)

● Complement studies that look at KG expansion grants for school districts (Cascio 2010; Dhuey, 2011)

● Similar to compulsory schooling literature, but extra year of schooling is during early life vs. adolescence (e.g., Devereux and Hart,

2010, Grenet, 2013, Harmon and Walker, 1995, Oreopoulos, 2006)

Data

First Stage: Did KG attendance increase as a result of

the mandates?

●State-by-year kindergarten attendance mandates● Collect complete history of state mandates

History of state mandates

Data

First Stage: Did k attendance increase as a result of

the mandates?

●State-by-year kindergarten attendance mandates● Collect complete history of state mandates

●State-by-year kindergarten enrollment rates● Digest of Education Statistics

●State-by-year covariates● e.g., Population, State GDP, Poverty rate, Per-pupil educational expenditures, School entry cutoffs

First Stage Results

Did KG attendance increase as a result of

the mandates?

Yes, by 8.5 percentage points

Data

Second Stage: Did KG mandates affect long-run

individual-level outcomes?

Census/ACS (Public & Restricted Use)

ACS: 2007-2015: State-of-birth repeated cross section• Born 1965-1990, KG 1970-1995

• Ages 24-50 when observed in ACS as adults

Assignment to MKG exposure• State of birth & Quarter of birth (DOB in the RDC data)

Outcomes• Educational attainment

• Earnings

• Poverty status

Second Stage Results: Public Use Data

Note: Cannot precisely assign individuals to K entry cohorts with QOB; need DOB from RDC.

(1) (2) (3) (4) (5) (6)

High School Some College Assoc. or BA

degree

Poverty^ Wage

Income (ln)

Total

Income (ln)

Exposed to

MKG Policy0.003 0.006 0.014** -0.003 0.008 0.008

(0.005) (0.005) (0.005) (0.003) (0.012) (0.010)

Y mean 0.93 0.66 0.40 0.15 10.10 10.03

Observations 6,399,390 6,399,390 6,399,390 5,498,065 4,351,094 4,351,094

Did MKG affect long-run outcomes for affected

individuals?

Somewhat; increased degree attainment by 1.4 percentage points

0.22

-0.6

4.75*

0.00

3.07*

12.10*

0.01

-0.45

12.01*

0.25

-1.73

-4.21*

-1.20

2.46*

19.39*

-5

0

5

10

15

20

Per

cen

tage

po

int^

dif

fere

nce

in o

utc

om

e fr

om

MK

G

College Degree Poverty

StatusTotal Income^

Notes: Estimates for White, Black, & Hispanic are interaction coefficients that capture the differential impact of MKG for the particular subgroup. * Statistically significant at .05 level. ^ Total income impacts shown as percentage increases.

High School

Degree Some College

Public Use Second Stage ResultsHeterogeneity by Race/Ethnicity

-0.02

0.93*0.03

1.76*1.22*

0.25

-0.81+

0.65

-0.02

6.11*

-5

0

5

10

15

20

Pe

rce

nta

ge

po

int^

dif

fere

nce

in

ou

tco

me

fro

m M

KG

College Degree Poverty Status Total Income^

Notes: Estimates for White, Black, & Hispanic are interaction coefficients that capture the differential impact of MKG for the particular subgroup. *

Statistically significant at .05 level; + Statistically significant at .10 level. ^ Total income impacts shown as percentage increases.

High School

Degree

Some College

Public Use Second Stage ResultsHeterogeneity by Sex

Robustness Checks

• State characteristics prior to adoption (i.e., pre-trends)

Similar in MKG and No-MKG states

• Migration across states between birth and KG

• We assume that children went to KG in their state of birth; potential mismatching

Moving between birth and age 5 not associated with MKG

• “Compliers” analysis

Hispanic families and HH with HS or less education more likely to enroll child as a result of the KG mandates

• Maternal labor market responses

No changes to employment status, some evidence worked more hours

Next steps

• Analyses in RDC (Census 2000; ACS 2005-2015)

• Heterogeneous effects

o By poverty and SES status, and urbanicity of city/county of birth using

Neighborhood Change Database (NCDB) Tract Data

• Falsification tests

o Estimate MKG effects on individuals too old to be subjected to policy

change

• Event study analyses for pre-trends

• Collect more state covariates

o 1960s & 70s limited data available

Summary and Conclusions

• Families responded to KG mandates• Hispanic families and those with HH lower educational attainment

• Suggestive positive main effects of MKG

• Long-run impacts most concentrated for Hispanic and Female adults

• States’ investments in universal early education pay off in the long run, and are equity enhancing

• Heterogeneity impacts similar to that of larger-scale interventions, e.g., Deming HS re-analysis, Dhuey K expansion grants

Thank you!

jvjenkin@uci.edu

Funding for this work generously provided by the Laura

and John Arnold Foundation through the UCI

Economic Self-Sufficiency Policy Research Institute

and by the Spencer Foundation

Table 2: State covariates and Kindergarten enrollment for MKG and non-MKG states

Never mandatory KG Ever mandatory KG

Mean SD Obs Mean SD Obs Mean Diff

State covariates in 1970

Gross State Product per capita 0.01 0.01 1,147 0.01683 0.01 179 0.002

Unemployment Rate 6.38% 2.03 1,147 6.16% 2.36 179 -0.219

Poverty Rate 13.36 4.20 733 16.50 4.65 134 3.133

AFDC recipients/pop 0.03 0.02 1,147 0.03 0.02 179 0.002

Snap expenditures per capita 0.04 0.03 1,132 0.06 0.04 177 0.018**

K-12 Expenditures per pupil 7,100.39 2,231.37 1,147 6,636.01 1,948.61 179 -464.382

K-12 Pupil-teacher ratio 18.77 2.82 1,147 17.49 2.31 179 -1.282

% state White 86.19% 0.15 1,147 82.05% 0.13 179 -0.041*

%state Black 9.83% 0.12 1,147 14.65% 0.14 179 0.048

% state Other race 3.98% 0.10 1,147 3.31% 0.03 179 -0.007

% of state house that is Democrat 59.60% 0.20 1,110 71.36% 0.17 174 0.118

State-year observations 1970-

1995

Kindergarten enrollment ratio 0.82 0.20 1,136 0.86 0.17 179 0.034**

First Stage Results

Data are from 1970-2000. K Enrollment rate = Statewide Kindergarten enrollment / State total #

children age 5

Kindergarten Enrollment Rate

(1) (2) (3)

State and

Year FE

State

Covariates 1+2

State has MKG policy 0.057 0.064** 0.085**

(0.058) (0.031) (0.037)

Observations 1,518 1,518 1,518

R-squared 0.497 0.182 0.618

Robust standard errors in parentheses clustered at the state level

Did k attendance increase as a result of the

mandates?

Examining Balance and Pre-trends

*Total SNAP recipients by state not available before 1980

(1) (2) (3) (4) (5) (6)

GSP per

capita

Unemployment

rate

% State AFDC

& TANF

recipients

SNAP

Benefits

per

capita*

K-12 exp.

per-pupil (ln)

% State

House

Democrat

State has

MKG Policy

0.001 -0.316 -0.001 0.005 -0.001 -0.020

(0.002) (0.436) (0.004) (0.005) (0.028) (0.035)

(7) (8) (9) (10) (11)

Pupil-

teacher

ratio

% State White % State Black % State

Other race

Pre-MKG

adoption K

enroll rate

State has

MKG Policy

-0.503 -0.005 0.008 -0.002 0.020

(0.351) (0.009) (0.007) (0.003) (0.048)

Maternal labor supply responses to MKG?• Current employment, hours per week, wages

• 𝐿𝑖𝑠𝑡 = 𝛼0 + 𝛽𝑀𝐾𝐺𝑠𝑡 + 𝑋𝑠𝑡𝛾 + 𝑆𝑠 + 𝑇𝑡 + 𝜀𝑠𝑡• i is a Mother of the 5 years old in survey year t.

• X=race, marital status, age and age sq, education (with our without).

• Mother going to school?

• Fertility?

(1) (2)

Employment Num. hours worked^

Exposed to

MKG Policy

0.010 1.528**

(0.034) (0.408)

N 38625 22067

Married Unmarried Married Unmarried

Exposed to

MKG Policy

0.014 0.021 0.831 1.603

(0.030) (0.044) (0.855) (1.059)

N 31981 6644 19315 2752

Public Use Second Stage ResultsHeterogeneity

^ Income below 100% federal poverty level

(1) (2) (3) (4) (5) (6)

High School Some

College

Assoc. or BA

degree

Poverty^ Wage

Income (ln)

Total

Income (ln)

Exposed to

MKG

Policy

0.00 -0.00 -0.00 0.00 -0.01 -0.01

(0.01) (0.01) (0.01) (0.00) (0.01) (0.01)

Black-0.06** -0.13** -0.17** 0.17** -0.33** -0.32**

(0.00) (0.01) (0.01) (0.01) (0.01) (0.01)

Hispanic-0.09** -0.15** -0.15** 0.05** -0.17** -0.18**

(0.01) (0.01) (0.00) (0.01) (0.02) (0.02)

MKG*Black-0.01 -0.01 0.03* -0.02 0.03+ 0.02*

(0.01) (0.01) (0.01) (0.01) (0.01) (0.01)

MKG* Hispanic0.05** 0.12** 0.13** -0.04** 0.18** 0.18**

(0.01) (0.03) (0.03) (0.02) (0.04) (0.04)

Y mean 0.93 0.66 0.40 0.15 10.10 10.03

Observations 6422499 6422499 6422499 5520227 4351094 4351094

Public Use Second Stage ResultsHeterogeneity

^ Income below 100% federal poverty level

(1) (2) (3) (4) (5) (6)

High School Some

College

Assoc. or BA

degree

Poverty^ Wage

Income (ln)

Total

Income (ln)

Exposed to

MKG

Policy

-0.00 -0.00 0.01* -0.01+ -0.02 -0.02

(0.01) (0.01) (0.01) (0.00) (0.02) (0.02)

Female0.03** 0.10** 0.09** 0.02** -0.34** -0.33**

(0.00) (0.00) (0.00) (0.00) (0.01) (0.01)

MKG*Female0.01** 0.02** 0.00 0.01 0.06* 0.06*

(0.00) (0.00) (0.00) (0.01) (0.03) (0.03)

Observations 6422499 6422499 6422499 5520227 4351094 4351094

Understanding “compliers”

○ Households with 5 year-olds in 1977^-1995 CPS October supplement

○ Info from HH and 5 yo

𝐸𝑖𝑠𝑡 = 𝛼0 + 𝛽𝑀𝐾𝐺𝑠𝑡 + 𝑋𝑖𝛾 +𝑀𝐾𝐺𝑠𝑡 ∗𝑋𝑖Γ + 𝑆𝑠 + 𝑇𝑡 + 𝜀𝑠𝑡

○ Outcome: Enrollment in primary school

○ Predictors: MKG, HH and child covariates, MKG*covariates

○ State and year FE

^ State ID not available prior to 1977

K enrollment

MKG*Poverty & near poor -0.006

(0.012)

MKG*Male 0.007

(0.009)

MKG*Black -0.019

(0.018)

MKG*Hispanic 0.047+

(0.024)

MKG*Other 0.077

(0.056)

MKG*HH male 0.012

(0.019)

MKG*Married 0.001

(0.017)

MKG*Employed 0.013

(0.033)

MKG*Not in labor force 0.043

(0.027)

MKG*HH HS or less 0.027+

(0.016)

MKG*HH Some College 0.014

(0.014)

N 39212