School Choice and Information

Rómulo A. ChumaceroDaniel Gómez

Ricardo D. Paredes

Motivation

• The Chilean educational voucher system was introduced in 1981

• Pillar of the system: – Parent’s right to choose would foster competition and

improve quality– Rejection of low quality schools would lead to declining

number of students, and eventually eliminate them from the market

• This line of reasoning was questioned by surveys:– Most important factor for choosing school: distance– Parents value quality but do not know results of

standardized tests

Contributions

• Role of information on school choice– Fills gaps and helps make better choice– Information used correlated with quality (“as if”)– Don’t know, don’t care

• Natural experiment– Score results were not always public

• Contrast what is said with what is doneHow do parents really act(declared versus reveled preferences)

Structure of the Paper

• The data• The model• The results• Concluding remarks

The Data(measuring distance)

• SIMCE: Test scores, characteristics of schools and households, location of school, but not of household

• CASEN: Characteristics of household, school chosen, and block of household

• School directory: address of schools– Digital maps (Mapcity and Dictuc)– Estimate Euclidian distance from centroid of the

block (home and school)– 2003: 2,310 out of 2,312 schools in the 34

counties in the Santiago area

Natural experiment

• Results of 1995 test were made public in April 1996

• Parents had already enrolled children• CASEN survey conducted in 1996• How were choices made prior to making

results public?• Compare 1996 and 2003

– How to consider that Santiago has grown?– Blocks are not directly comparable– Role of information

• Quasi-matching

How things really are(Distance)

0

0.5

1

1.5

2

2.5

3

1996 2003

Nearest Chosen

How things really are(Distance and age)

1

2

3

4

5

6

7

6 8 10 12 14 16 18

Age

1996 2003

How things really are(Attending the nearest school)

0

5

10

15

20

1996 2003

Elite voucher schools(where they are)

Elite voucher schools(where the students live)

How things really are(Quality)

235

240

245

250

255

260

265

270

1996 2003

Nearest Chosen

How things really are(Competition: Schools in 2 kms radius)

0

5

10

15

20

25

1996 2003

Municipal Subsidized Total

The Empirical Model

• Parents consider several factors– Child specific and common to schools (age, gender,

income, education of parents, x)– School specific (type, quality, cost, other factors, y)– Child and school specific (distance, z)

( ), , ,, , ,i j i j i j i ju u x y z e= +

• Agent i chooses school h if ui,j≤ui,h for all j– Problem: In 2003 there were 2310 schools and

7479 students. Compute and model more than 17 million distances and possible choices

The Empirical Model

• Define ni as “nearest school to household i”

1 if .

0 if i i

i i

m n

im n

u uv

u u

ì =ïïï= íï >ïïî

[ ] ( )Pr 1 ,ii iv w F wb¢= =

• QML estimator

Determinants (w)• Individual or household characteristics: Gender,

age, parents’ education, and (log) per capita income.

• Nearest school: Quality of the school (average result in standardized tests), distance of the nearest school from the household, price.

• Chosen school: Quality of the school (average result in standardized tests), type of school (municipal, subsidized, private), price.

• “Competition”: Number of schools in a 2 kilometers radius from the household.

Main results

• The probability of chosing the nearest school increases:– Women– Younger– Poorer– Less educated parents– Quality of the nearest school– Fewer schools in the area– Cheaper (2003)

• Trade-offs (Distance – quality)• Consistent in sub-samples (“as if”)

Probability of choosing nearest school

.04

.08

.12

.16

.20

.24

6 7 8 9 10 11 12 13 14 15 16 17 18 19

Age

.05

.10

.15

.20

.25

.30

.35

.40

0 2 4 6 8 10 12 14 16 18

Years of Schooling (Mother)

.05

.10

.15

.20

.25

.30

.35

.40

200 210 220 230 240 250 260 270 280 290 300 310 320 330 340

Quality of the Nearest School

.00

.05

.10

.15

.20

.25

0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 3.6 4.0 4.4 4.8

1996 2003 (full) 2003 (matched)

Distance of the Nearest School

Concluding remarks

• Policy prescriptions should not be guided by anecdotal evidence

• As they should, families have always valued quality (among other factors) and have behaved “as if” they knew it

• Additional information has helped to take more informed decisions

• Extreme caution when tampering with incentives

School Choice and Information

Rómulo A. ChumaceroDaniel Gómez

Ricardo D. Paredes