"Students who are exposed to unusually low achieving
cohorts tend to score lower themselves."
How can advanced economies get the biggest increase in
human capital for their education dollar? That is, how
productive are their investments in education? In answering
these questions, one tricky problem is "peer effects":
students are "good" peers if they produce positive learning
spillovers, so that students exposed to them gain more for
each dollar spent on their education, or "bad" peers if they
have the reverse effect.
It is hard to know whether such peer effects exist, but if
they do, they are crucial to current debates on which policies
maximize the productivity of a country's education spending.
The United States is debating
school choice; European
countries are discussing whether to eliminate ability tracks
from their education systems; Latin American countries are
debating whether to devolve control and funding of education
to localities. Many arguments against school choice,
decentralized funding, and ability tracking rest on the belief
that peer effects are important and have a particular
asymmetry: that is, bad peers gain more by being exposed to
good peers than good peers lose by being exposed to bad peers.
If this asymmetry is strong, then investments in human capital
are maximized when students are forced to attend
schools with a broad array of abilities and backgrounds. Such
coercion is obviously impossible with ability tracking and can
be hard to achieve with choice or local funding.
In Peer Effects in the Classroom: Learning From
Gender and Race Variation (NBER Working Paper
No.7867), NBER Research Associate Caroline
Hoxby tries to determine whether peer effects exist
and, if they do, what form they take (for instance, are they
asymmetric?) She begins by noting that true peer effects are
hard to measure. Parents who provide home environments that
are good for learning tend to select the same schools. Even
within a school, interested parents lobby to have their
children assigned to particular teachers. Thus, if high
achievers tend to be clumped in some classrooms and low
achievers in other classrooms, we should not assume that the
achievement differences are caused by peer effects. Most of
the achievement differences probably are due to parents, who
would influence their children a lot even if they could not
get them in classrooms with particular groups of peers.
It is not just parents' activities that make peer effects
hard to measure, though; it is also schools' activities.
Students with similar abilities may be assigned to the same
classroom in order to make it easier to teach. Teachers with a
knack for handling the unruly students may have classes full
of them. Thus, classroom achievement could differ because the
initial student composition differs, not because peers
influence one another.
To identify true peer effects, Hoxby compares groups within
a given school that differ randomly in peer composition. To
illustrate: suppose that a family shows up for kindergarten
with their older son and finds that, simply because of random
variation in local births, that son's cohort is 80 percent
female. The next year, they show up with their younger son and
find that, also because of random variation, that son's cohort
is 30 percent female. Their two sons now will go through
elementary school consistently experiencing classrooms that
have different peer composition on average. Their older son
will be exposed to more female students (who tend to be higher
achievers and less disruptive in elementary school). Their
younger son will be exposed to more male students. Because the
two boys have the same parents and the same school, the main
difference in their experience will be peers. If it turns out
that male students systemically do better (or worse) when
exposed to more female students, then that systematic
difference must be attributable to peer effects.
Hoxby also compares school cohorts that differ in racial
composition or initial achievement, rather than in gender
composition. She uses data from the entire population of
elementary students in Texas from 1990 to 1999 (the Texas
Schools Microdata Sample). Her measure of achievement is a
student's score on the Texas Assessment of Academic Skills,
which is administered in all Texas public schools.
Hoxby finds that peer effects do exist. For instance, her
results suggest that having a more female peer group raises
both male and female scores in reading and math. She points
out that only some of the "good" peer effect of females can be
direct learning spillovers because females do not know math
better than males on average, although they are better
readers. The fact that females raise math scores,
therefore, must be due to phenomena more general than direct
learning spillovers -- for instance, females' lower tendency
to disrupt.
In Texas, black and Hispanic students tend to enter school
with lower initial achievement. Does this matter? Hoxby finds
that it does. Students who are exposed to unusually low
achieving cohorts tend to score lower themselves. Interestingly enough, black students appear to be particularly
affected by the achievement of other black students. Hispanic
students appear to be particularly affected by the achievement
of other Hispanic students. In fact, Hispanic students do
better when in majority Hispanic cohorts, even though the
additional Hispanic students tend to have lower initial
achievement. It may be that in classes with more Hispanics, a
student who is learning English is more likely to find a
bilingual student who helps him out.
Hoxby finds little evidence of a
general
asymmetry, though, such as low achievers gaining more by being
with high achievers and that high achievers lose by being with
low achievers. After taking steps to eliminate changes in
achievement that could be caused by general time trends or
unusual events -- such as the appearance of an especially good
teacher in one school -- Hoxby concludes that, on average,
a
student's own test score rises by 0.10 to 0.55 points when he
or she is surrounded by peers who score one point higher.
