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R E VIE W O F E C O N O M I C S T U D IE S

such central sociological concepts as norms and p eer influences to be spu rious phen om ena

explainable by processes operating entirely at the level of the individual. (See, for exam ple,

the Friedm an (1957) criticism of D uesenberry (1949).) Even am ong sociologists, on e still

does not find consensus on the nature of social effects. For example, there has been a

long-running debate about the existence and nature of neighbourhood effects. (See, for

example, Jencks and Mayer (1989).)

Why d o such different perspectives persist? Why d o the social sciences seem unab le

to converge to com mon conclusions abou t the channels through which society affects the

individual? I believe that a large part of the answer is the difficulty of the identification

problem. Empirical analysis of behaviour often cannot distinguish among competing

hypotheses about the nature of social effects.

Econo mists have lon g been c oncerned w ith the identification of end ogenou s effects

channelled through markets, especially with the conditions under which observations of

equilibrium prices and quantities reveal the demand behaviour of consumers and the

sup ply behaviour of firms. But the identification of oth er endogeno us effects has remained

relatively unexamined and poorly understoo d.

This pape r examines the "reflection" problem that arises whe n a researcher observing

the distribution of behaviour in a pop ulatio n tries to infer whether the average behaviour

in som e grou p influences the behaviour of the individuals that comprise the g roup. The

term reflection is appropriate because the problem is similar to that of interpreting the

almost simultaneous movements of a person and his reflection in a mirror. Does the

mirror image cause the person's movements or reflect them? An observer who does not

understand something of optics and hu man behaviour would not be able to tel l.

Although the reflection problem has several aspects, the series of simple findings

reported in this paper collectively develop a theme: Inference on endogenous effects is

not possible unless the researcher has prior information specifying the composition of

reference grou ps. If this information is available, the prospects for inference depe nd

critically on the pop ulatio n relationship between the variables defining reference gro ups

an d thos e directly affecting outc om es. Inferenc e is difficult to im pos sible if these variables

are functionally dependent or statistically independent. The prospects are better if the

variables defining reference grou ps an d those directly affecting outco me s are "moderately"

related in the popu lation.

Section 2 examines the reflection problem in the context of a linear model applied

in m any e mpirical studies of social effects. Section

3

analyzes non-linear models. Section

4 discusses dynam ic models. Section 5 relates conventional consumer dem and analysis

to the work of this paper. Section

concludes by stressing the need for richer data if

the analysis of social effects is to make more progress.

2. A L I N E A R M O D E L

Th e linear model analyze d here gives formal ex pression to three hypothe ses often advanced

to explain the com mon observation that individuals belonging to the sam e group tend to

behave similarly. These hypotheses are:

(a) endogenous effects, wherein the propensity of an individual to behave in some

way varies with the behaviour of the group;

(b ) exogenous (con textual) effects, wherein th e prop ensity of a n individual to behave

in some way varies with the exogenous characteristics of the group,' and

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MA NSKI THE REFLEC TION PROBLEM 533

(c) correlated efects, wherein ind ividu als in th e sam e gro up tend to behave similarly

because they have similar individual characteristics or face sim ilar institutional

environments.

An exam ple may help to clarify the distinction. Consider the high school achievement

of a teenage yo uth. Th ere is a n endog enous effect if, all else equal, individual achievement

tend s to vary with the average achievement of the students in the youth's school, ethnic

group, or other reference group. There is an exogenous effect if achievement tends to

vary w ith, say, the socio-econom ic com position of the reference g roup. There are correlated

effects if yo uths in th e s am e school tend t o achieve similarly because they have similar

family backgrounds or because they are taught by the same teachers.

The three hypo theses have differing policy implications. Consider, for examp le, a n

educational intervention providing tutoring to some of the students in a school but not

to the others. If individual achievement increases with the average achievement of the

students in the school, then an effective tutoring programme not only directly helps the

tutored stud ents but, as their achievement rises, indirectly helps all students in the sch ool,

with a feedba ck to fu rther achievement gains by the tutored students. Ex ogenou s effects

and correlated effects do not generate this "social multiplier".

Sec tion 2.1 specifies the m ode l. Sections 2.2 an d 2.3 analy se the identification

problem , first considering th e general mo del a nd th en a restricted version assuming that

neither exo genous no r correlated effects are present. Section 2.4 shows that, although

the linear mo del sometimes imposes restrictions o n observed beh aviour, the m odel holds

tautologically if the attributes defining reference groups and those directly affecting

outcom es are functionally dep end ent. Section 2.5 draws implications for the problem of

identifying reference groups. Section 2.6 discusses sample inference.

2.1. Model

speciJication

Let each m emb er of a po pula tion be characterized by a value fo r (y, x, z, u) R x R

R~

x R . Here y is a scalar outcom e (e.g. a youth's achievement in high school), are

attributes characterizing a n individual's reference g roup (e.g. a youth's school or ethnic

gr ou p), an d (z, u) are attributes that directly affect y (e.g. socioecono mic status an d

ability). A researcher observes a rand om samp le of realizations of (y, x, z). Realizations

of u are not observed.

Assume that

where ( a , p , y, S, is a parameter vector. It follows that the mean regression of y on

(x, z) h as the l inear form

If 0, the linear regression (2 ) expresses an endoge nous effect: a person's o utco m e y

varies with E(y x), the mean of y among those persons in the reference group defined

by x.' If y 0, the model expresses an exogenous effect: y varies with E ( z x) , the mean

of the exog enous variables z amon g those persons in the reference group. If 6

Z

0, the

mo del expresses correlated effects: persons in reference g roup x tend to behave similarly

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535A N S K I T H E R E F L E C T I O N P R OB L EM

The abil ity to detect some social effect breaks down if ~ z l) is a linear function

of [ I , x, z ]

Unfortuna tely, E z lx ) is a linear function of [ I , x, z] in various situations,

including those stated in the following corollary to Proposition 1.

Corollary In the linear model

2)

with

P

1,

the composite social-effects parameter

P 7 ) / 1 P )

is not ident~jied

f

any of these conditions hold almost everywhere.

a) z

is a function of

x.

b )

E

z x )

does not vary with

x.

c)

E

z x )

is a linear function of

x.

Th e corollary shows th at th e ability to infer the presenc e of social effects depe nds critically

on the ma nne r in which z varies with x. In the context of the linear mo del 2), inference

is possible only if E z x ) varies non-linearly with x an d Var z x )> 0.

2.3.

A pure endogenous-eflects model

Th e outloo k for identification improves if on e has inform ation o n som e parame ter values.

Em pirical studies of end oge nou s effects typically assume that =O; so neither

exogen ous nor correlated effects are present. In this case, 5) reduces to

Inspection of 6) show s the following:

Proposition

2

In the linear model

2)

with parameter restrictions

0

and

/3 1,

the composite parameters a / l - P ) , P q / 1 - P ) , and 7 are identijied if the regressors

[ I , E z x ) , z ] are linearly independent in the population.

The en dogenous-effectsparameter

/3

is not identijied

i 0

or if

E z x )

is a linear

function of

[ I , z].

In particular

/3

is not identijied if any of these conditions hold almost

everywhere:

a) z

is a function of

x.

b) E z x )

does not vary with

x.

d ) E z x ) is a linear function of x. x is a linear function of z.

Fo r exam ple, in a stu dy of scho ol achievem ent, /3 is identified if x is family incom e,

z is ability , ave rage ability ~ z l x )aries non-linearly with income, and achievement

varies with ability i.e. 0). But is not identified if x is ability, family incom e) an d

z is ability con dition a ) ; if x is family inco me , z is ability, an d average ability doe s not

vary with incom e con dition b ); or if x is family income, z is ability, family income ),

and average ability varies linea rly with income condition d ).

2.4. Tautological models

Even wh en its param eters are unid entified , a social-effects mod el may im pose restrictions

on observed behaviour and so have testable implications. There are, however,

specifications of x, z ) that make a mod el hold tautologically. In particular, this is the

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536 REVIEW O F ECON OM IC STUDIES

always consistent with the hypothesis that individual behav iour reflects m ean reference-

group behaviour. For example, if a researcher studying student achievement specifies x

to be (ability, family income) and z to be (ability), he will find that the da ta are consistent

with the hypothesis that reference groups are defined by (ability, family income), that

individual achievement reflects reference-group achievem ent, an d tha t ability has no direct

effect on achievement.

Conversely, specify x to be a function of z, say x x (z ). Then E [y x( z), z] E ( y Iz).

So the semi-linear model

holds w ith

3

y 0 and g (z ) E ( y 12); the only testable restriction of the l inear

model (2) is i ts assumption that g ( . ) is a l inear function. Continuing the school achieve-

ment example, a researcher who specifies x to be (family income) and z to be (ability,

family income) will find that th e da ta are consistent with the hypo thesis that social forces

d o no t affect achievement.

2.5. Identifying reference groups

So far, I have presumed that researchers know how individuals form reference groups

an d that individuals correctly perceive the mean outcom es experienced by their sup pos ed

reference group s. There is substantial reason to question these assum ptions. Researchers

studying social effects rarely offer empirical evidence to support their reference-group

specifications. Th e prevailing practice is simply to assum e that ind ividua ls are influenced

by E ( y x ) a nd E ( z Ix) , for some specif ied x . ~ ne of the few s tudies that does a t tempt

to justify its specification of reference g roup s is Woittiez an d K aptey n (1991). They use

individuals' responses to questions abo ut their social environments as evidence o n their

reference grou ps.

If researchers do not know how individuals form reference groups and perceive

reference-group outcom es, then it is reasonable to ask whether observed behavior can be

used to infer these unknow ns. The findings reported in S ection 2.4 imply that this is not

possible. Any specification of a functionally depen den t pair (x, z) is consistent with

observed behaviou r. The con clusion to be d raw n is that info rmed specification of reference

groups is a necessary prelude to analysis of social effects.

2.6. Sample inference

Although our primary concern is with identification, a discussion of sample inference is

warranted.

Em pirical studies of social effects have generally assum ed that there are no correlated

effects and only one of the two types of social effects. Studies of exogenous effects have

typically a pplie d a two-stage m ethod to estimate (y, 7 ). In the first stage, one uses the

sample data on (z,

x

to estimate E ( z x ) non-parame trically; typically x is discrete and

the estimate of

E

(z lx) is a cell-average. In the second stage, one estimates (y, 7 ) by

f inding the leas t squares fit of y to [ I , ~ , ( z l x ) , ], where ~ , ( z l x ) s the f irs t-stage

estim ate of ~ ( z l x ) . ee, for example, Coleman et al. (1966), Sewell and Armer (1966),

Hauser (1970), Crane (1991) or Mayer (1991).

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537ANSKI THE REFLECTION PROBLEM

Studies of endogenous effects have also applied a two-stage method to estimate

(p, q ) , but in the guise of a spatial correlation model

Here Y

=

(y,,

i

=

1 ,

N )

is the

N

1 vector of sample realizations of y and WiN is a

specified 1x N weighting vector; the components of WiN are non-negative and sum to

one. The disturbances

u

are usually assumed to be normally distributed, independent of

x, and the model is estimated by maximum likelihood. See, for example, Cliff and Ord

(1981), Doreian (1981), or Case (1991).

Equation (7) states that the behaviour of each person in the sample varies with a

weighted average of the behaviours of the other sample members. Thus, the spatial

correlation model assumes that an endogenous effect is present within the researcher's

sample rather than within the population from which the sample was drawn. This makes

sense in studies of small-group interactions, where the sample is composed of clusters

of friends, co-workers, or household members; see, for example, Duncan, Haller, and

Portes (1968) or Erbring and Young (1979). But it does not make sense in studies of

neighbourhood and other large-group social effects, where the sample members are

randomly chosen individuals. Taken at face value, equation (7) implies that the sample

members know who each other are and choose their outcomes only after having been

selected into the sample.

The spatial correlation model does make sense in studies of large-group interactions

if interpreted as a two-stage method for estimating a pure endogenous-effects model. In

the first stage, one uses the sample data on (y, x ) to estimate E (y Ix) non-parametrically,

and in the second stage, one estimates (p , q ) by finding the least-squares fit of y to

[I , x) , z ] where

x ) is the first-stage estimate of E (y x). Many non-

parametric estimates of E(y x i) are weighted averages of the form EN(y xi )= W.NY,

with WiN determining the specific estimate; see Hardle (1990). Hence, estimates of (P, q )

reported in the spatial correlation literature can be interpreted as estimates of pure

endogenous-effects models.

Note that point estimates can be obtained for unidentified models. If condition a, b,

or d of Proposition

holds, then E (y lx) is a linear function of [ I , z]. But the estimate

EN(y x) typically is linearly independent of [I, z ] . So the two-stage procedure typically

produces an estimate for

p even when this parameter is unidentified.'

3. NON-LINEAR ENDOGENOUS-EFFECTS MODELS

How do the findings reported in Section fare when the social-effects model is not

necessarily linear? This section examines two situations. Section 3.1 assumes that one

7 . It is necessary to point out that empirical studies reporting two-stage estimates of social-effects models

have routinely misreported the sampling distribution of their estimates. The practice in two-stage estimation

of exogenous-effects models has been to treat the first-stage estimate E , z l x ) as if it were E z x ) rather than

an estimate thereof. The literature on spatial correlation models has presumed that equation 7 ) holds as stated

and has not specified how the weights

W

should change with

N.

Two-stage estimation of social-effects models is similar to other semi-parametric two-stage estimation

problems whose asymptotic properties have been studied recently. Ahn and Manski

1 9 9 3 ) ,

Ichimura and Lee

1 9 9 1 ) , and others have analyzed the asymptotic behaviour of various estimators whose first stage is non-

parametric regression and whose second stage is parametric estimation conditional on the first-stage estimate.

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538 REVIEW O F ECONOMIC STUDIES

doesnotknowtheformoftheregressionandsoanalysessocialeffectsnon-parametrically.

Section3.2 assumesthat the regression isamemberofaspecified non-linear familyof

functions.Tokeeptheanalysisrelativelysimple,Irestrictattentiontopureendogenous-

effectsmodels.

3.1. Non-parametricanalysis

Assumethat,forsomeunknownfunction R1

x

R K R1,

This non-parametric endogenous-effects model, with the implied social equilibrium

equation

dropsthelinearityassumptionimposedinSection2.3.

Inthisnon-parametricsetting,onemeasuresendogenouseffectsdirectlyratherthan

throughaparameter. Thatis,onefixeszandaskshow E(y

) ,z]varieswithE ( ~ ).

Let6E R~ and(e,, el)E R2.Thenthecontrast

measurestheeffectat6ofexogenouslychangingmeanreference-groupbehaviour from

e, toel . Intheabsenceoffunctionalformassumptions,

, ) isidentifiedonthesupport

of [ E ( ~ x),z]. The contrast T(e l,e,, 5)isidentifiedif andonly if (e l, 6)and (e,, 5)

arebothonthesupportof [E(yIx),z].

To say more requires that one z].haracterize the support of [ ~ ( ~ l x ) , Useful

conditionsensuringthatcontrastsareidentifiedseemhardtoobtain. Ontheotherhand,

I canshowthat contrastsaregenerically notidentifiedifxandzareeitherfunctionally

dependentorstatisticallyindependent.

Proposition

3 In thenon-parametric endogenous-efects model (8), no contrasts of

theform (10) areidentijed

i

anyof theseconditionshold,almost everywhere:

(e) zisafunction of xandthesocialequilibriumequation (9)hasauniquesolution.

(f) z is statistically independentof x and thesocialequilibrium equation (9) hasa

uniquesolution.

(g) x isafunction of z.

ProoJ: IfE (y

x)isafunctionofz,( el , 6)and(e,, 6)cannotbothbeonthesupport

of (x,z). Sono contrasts areidentified. Conditions e,J andg all implythat E (y lx)

isa functionof z.

(e) Let6

E

RK.Thedistributionofxconditionalontheevent[z

=

51

isconcentrated

onthesetX(6)= [x:z(x)= 61; hence, the distributionof E(y x)conditional

ontheevent[z= 61isconcentratedon[ E (y x),x

E

X([)]. Forx

E

X(6),P(z x)

has all itsmass at thepoint

5

Hence, forX E X ( ~ ) , quation (9)reduces to

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MANSKI THE REFLECTION PROBLEM 539

(f) Statistical independence means that

~ ( z l x ) = P ( z ) .

Hence

( 9 )

reduces to

E ( y

x ) = f

E

( y

x ) , z ] d P ( z ) . So

E ( y

x ) solves the same equation for each

value of x. The uniqueness assumption then implies that E ( y x ) is constant for

all values of x.

(g) Let

x

=

x ( z ) .

Then

E C y x ( z ) ]

is a function of

z .

A useful way to think about the proposition is to imagine that f ( . ,

.

is really linear

with p

#

but, not knowing this, one proceeds non-parametrically. The linear model has

a unique social equilibrium so conditions e, f, and g all apply. Taken together, the

conditions say that non-parametric identification of endogenous effects is precluded if

the attributes defining reference groups and those directly affecting outcomes are func-

tionally dependent or statistically independent. Non-parametric study of social effects

remains conceivable only if x and z are "moderately related" random variables.

The prospects for identification may improve iff( is non-linear in a manner that

generates multiple social equilibria. In this case, condition

g

remains in effect but

e

and

do not apply. When there are multiple equilibria,

E ( y x )

may fluctuate from one

equilibrium value to another and so may not be a function of

z.

3.2. Binary response models

Perhaps the most familiar non-linear parametric models with endogenous effects are

binary response models. Let y be a binary random variable and assume that

where H ( . ) is a specified continuous, strictly increasing distribution function.

For

example, if

H ( . )

is the logistic distribution, we have a logit model with social effects.

Models of form

1 1 )

have been estimated by two-stage methods. The usual approach

is to estimate P ( y = 1 Ix ) non-parametrically and then estimate

p ,

y by maximizing the

quasi-likelihood in which P N ( y=

1

l x ) takes the place of P ( y = 1 l x ) . Examples include

Case and Katz ( 1 9 9 1 ) and Gamoran and Mare ( 1 9 8 9 ) . multinomial response model

estimated in this manner appears in Manski and Wise (1983 , Chapter 6 ) .

The literature has not addressed the coherency and identification of model

1 1 )

but

I can settle the coherency question here. The model is coherent if there is a solution to

the social equilibrium equation

P ( y = l I x ) = H [ a + P P ( y = l I ~ ) + z ~ ] d ~ ( z \ x ) .

( 1 2 )

If

p =

0,

E ( y Ix) =

so there is a unique solution to

( 1 2 ) .

If

p <

0,

H ( a ~ ~ ) d ~ ( z l x )

the right-hand side of

( 1 2 ) decreases strictly and continuously from H ( a

~ ~ ) d ~ ( z l

to H ( a

/3 z t V ) d ~ ( z) as E ( y x ) rises from 0 to 1. Meanwhile, the left-hand side

increases strictly and continuously from 0 to

1 .

Hence the left- and right-hand sides cross

at a unique value of

E ( y x ) .

Finally, let

P

>

0. In this case, a solution exists because the right-hand side of

( 1 2 )

increases strictly and continuously from

H ( a

z 1 7 7 ) d p ( z x )

to

H ( a P z t 7 ) d P ( z x )

as E ( y x ) rises from 0 to

1 .

Meanwhile, the left-hand side traverses the larger interval

[O,

1 1 .

Hence, the left-hand side must cross the right-hand side from below at some value

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540 REVIEW OF ECONOMIC STUDIES

not appear possible to determine the number of equilibria without imposing additional

structure. The conditions under which the parameters a ,

P 7

are identified have not

been established.

4 .

DYNAMIC MODELS

The models posed thus far assume contemporaneous effects. It may well be more realistic

to assume some lag in the transmission of these effects. Some authors, including Alessie

and Kapteyn ( 1 9 9 1 ) and Borjas ( 1 9 9 1 ) ,have estimated the following dynamic version of

the linear model 2):

E,(Y

x,

2

a

+

PEr-1 (y x ) E , - I ( z X ) ' Y x r f 6 ~ ~ ' 7 ,

( 1 3 )

where E, and E , - , denote expectations taken at periods t and t - 1 . The idea is that

non-social forces act contemporaneously but social forces act on the individual with a lag.

If

{ ~ ( z l x ) ,

< p

<

1,

the dynamic process

( 1 3 )

has a

, z )

are time-invariant and

- 1

unique stable temporal equilibrium of the form ( 3 ) . If one observes the process in temporal

equilibrium, the identification analysis of Section 2 holds without modification. On the

other hand, if one observes the process out of equilibrium, the recursive structure of ( 1 3 )

opens new possibilities for identification.

One should not, however, conclude that dynamic models solve the problem of

identifying social effects. To exploit the recursive structure of ( 1 3 ) , a researcher must

maintain the hypothesis that the transmission of social effects really follows the assumed

temporal pattern. But empirical studies typically provide no evidence for any particular

timing. Some authors assume that individuals are influenced by the behaviour of their

contemporaries, some assume a time lag of a few years, while others assume that social

effects operate across generations.

5.

DEMAND ANALYSIS

In Section 1, I noted that mainstream economic demand models embody an endogenous

social effect: individual demand for a product varies with price, which is partly determined

by aggregate demand in the relevant market. This section elaborates.

Let y denote a consumer's demand for a given product. Let x denote the market in

which the consumer operates; different values of

x

may, for example, refer to different

geographic areas or to different time periods. Let p ( x ) be the market equilibrium price

in market x. Then a conventional model of consumer demand assumes that, conditioning

on consumer attributes, the market in which a consumer operates affects demand only

through the price prevailing in that market. A common empirical formulation is

E ( Y Ix, z ) D [ p ( x ) , l7

( 1 4 )

where z are consumer attributes observed by the researcher and where D ( . , . is mean

demand conditional on ( x , z .

Market equilibrium models assume that the price p ( x ) is determined by aggregate

demand in market

x

and by supply conditions in this market. Let the population of

consumers living in market x have size m ( x ) . Then ~ ( ~ l x )s per capita demand in

market x and ~ ( y I x ) m ( x )s aggregate demand. Let s ( x ) denote the relevant supply

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MANSKI THE REFLECTION PROBLEM

Equations (14) and (15) imply that

This is an endogenous effects model of a type distinct from (8). Conditional on z, y

varies with x only through ~ ( y lx)m(x), s(x)]x) in (8) but varies with x through [ ~ ( y

in (16). Equation (16) reduces to (8) if m ( . ) and s ( . ) do not vary with x; that is, if the

population of consumers has the same size in all markets and if supply conditions are

homogeneous across markets. In this case, the variation of price across markets derives

entirely from variation in the distribution p(z x) of consumer attributes. The findings of

Sections 2 and then apply to the problem of identifying the consumer demand function.

6. CONCLUSION

This paper has analyzed the problem of identifying endogenous social effects from

observations of the distribution of behaviour in a population. We have found that there

may be realistic prospects for inference on endogenous effects if the attributes defining

reference groups and those directly affecting outcomes are moderately related. On the

other hand, the prospects are poor to nil if these attributes are either functionally dependent

or are statistically independent. Moreover, observations of behaviour cannot be used to

identify individuals reference groups.

The only ways to improve the prospects for identification are to develop tighter

theory or to collect richer data.

I have no thoughts to offer on tighter theory but I see

much that we can do to collect richer data. The analysis of this paper has presumed that

inferences are based only on observed behaviour. Empirical evidence may also be obtained

from controlled experiments and from subjective data, the statements people make about

why they behave as they do. (Jones (1984) surveys some experiments conducted by social

psychologists.) Given that identification based on observed behaviour alone is so tenuous,

experimental and subjective data will have to play an important role in future efforts to

learn about social effects.

Acknowledgement: This research is supported by National Science Foundation Grant SES-8808276 and

by National Institute of Child Health and Human Development grant lROl HD25842 HLB. I have benefitted

from discussions with numerous colleagues and from the comments of the reviewers.

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You have printed the following article:

Identification of Endogenous Social Effects: The Reflection Problem

Charles F. Manski

The Review of Economic Studies, Vol. 60, No. 3. (Jul., 1993), pp. 531-542.

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http://links.jstor.org/sici?sici=0034-6527%28199307%2960%3A3%3C531%3AIOESET%3E2.0.CO%3B2-U

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[Footnotes]

1 Neighborhood Context and College Plans

William H. Sewell; J. Michael Armer

American Sociological Review, Vol. 31, No. 2. (Apr., 1966), pp. 159-168.

Stable URL:http://links.jstor.org/sici?sici=0003-1224%28196604%2931%3A2%3C159%3ANCACP%3E2.0.CO%3B2-C

1The Epidemic Theory of Ghettos and Neighborhood Effects on Dropping Out and Teenage

Childbearing

Jonathan Crane

The American Journal of Sociology, Vol. 96, No. 5. (Mar., 1991), pp. 1226-1259.

Stable URL:

http://links.jstor.org/sici?sici=0002-9602%28199103%2996%3A5%3C1226%3ATETOGA%3E2.0.CO%3B2-5

2 Effects of Peer, Faculty, and Parental Influences on Students' Persistence

Barbara J. Bank; Ricky L. Slavings; Bruce J. Biddle

Sociology of Education, Vol. 63, No. 3. (Jul., 1990), pp. 208-225.

Stable URL:

http://links.jstor.org/sici?sici=0038-0407%28199007%2963%3A3%3C208%3AEOPFAP%3E2.0.CO%3B2-S

http://www.jstor.org

LINKED CITATIONS- Page 1 of 4 -

NOTE: The reference numbering from the original has been maintained in this citation list.

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8/18/2019 Manski 1993


2 Habit Formation, Interdependent Preferences and Demographic Effects in the Almost IdealDemand System

Rob Alessie; Arie Kapteyn

The Economic Journal, Vol. 101, No. 406. (May, 1991), pp. 404-419.

Stable URL:

http://links.jstor.org/sici?sici=0013-0133%28199105%29101%3A406%3C404%3AHFIPAD%3E2.0.CO%3B2-0

References

A Theory of Social Custom, of Which Unemployment May be One Consequence

George A. Akerlof

The Quarterly Journal of Economics, Vol. 94, No. 4. (Jun., 1980), pp. 749-775.

Stable URL:

http://links.jstor.org/sici?sici=0033-5533%28198006%2994%3A4%3C749%3AATOSCO%3E2.0.CO%3B2-N

Habit Formation, Interdependent Preferences and Demographic Effects in the Almost IdealDemand System

Rob Alessie; Arie Kapteyn

The Economic Journal, Vol. 101, No. 406. (May, 1991), pp. 404-419.

Stable URL:

http://links.jstor.org/sici?sici=0013-0133%28199105%29101%3A406%3C404%3AHFIPAD%3E2.0.CO%3B2-0

Effects of Peer, Faculty, and Parental Influences on Students' Persistence

Barbara J. Bank; Ricky L. Slavings; Bruce J. Biddle

Sociology of Education, Vol. 63, No. 3. (Jul., 1990), pp. 208-225.

Stable URL:

http://links.jstor.org/sici?sici=0038-0407%28199007%2963%3A3%3C208%3AEOPFAP%3E2.0.CO%3B2-S

Spatial Patterns in Household Demand

Anne C. Case

Econometrica, Vol. 59, No. 4. (Jul., 1991), pp. 953-965.

Stable URL:

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http://links.jstor.org/sici?sici=0013-0133%28199105%29101%3A406%3C404%3AHFIPAD%3E2.0.CO%3B2-0&origin=JSTOR-pdf

http://links.jstor.org/sici?sici=0033-5533%28198006%2994%3A4%3C749%3AATOSCO%3E2.0.CO%3B2-N&origin=JSTOR-pdf



http://links.jstor.org/sici?sici=0012-9682%28199107%2959%3A4%3C953%3ASPIHD%3E2.0.CO%3B2-Z&origin=JSTOR-pdf

http://links.jstor.org/sici?sici=0012-9682%28199107%2959%3A4%3C953%3ASPIHD%3E2.0.CO%3B2-Z&origin=JSTOR-pdf



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8/18/2019 Manski 1993


The Epidemic Theory of Ghettos and Neighborhood Effects on Dropping Out and TeenageChildbearing

Jonathan Crane


Stable URL:

http://links.jstor.org/sici?sici=0002-9602%28199103%2996%3A5%3C1226%3ATETOGA%3E2.0.CO%3B2-5

Peer Influences on Aspirations: A ReinterpretationOtis Dudley Duncan; Archibald O. Haller; Alejandro Portes

The American Journal of Sociology, Vol. 74, No. 2. (Sep., 1968), pp. 119-137.

Stable URL:

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Secondary School Tracking and Educational Inequality: Compensation, Reinforcement, orNeutrality?

Adam Gamoran; Robert D. Mare


Stable URL:

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Context and Consex: A Cautionary Tale

Robert M. Hauser

The American Journal of Sociology, Vol. 75, No. 4, Part 2: Status and Achievement in the U.S.:1969. (Jan., 1970), pp. 645-664.

Stable URL:

http://links.jstor.org/sici?sici=0002-9602%28197001%2975%3A4%3C645%3ACACACT%3E2.0.CO%3B2-A

Tied Transfers and Paternalistic Preferences

Robert A. Pollak The American Economic Review, Vol. 78, No. 2, Papers and Proceedings of the One-HundredthAnnual Meeting of the American Economic Association. (May, 1988), pp. 240-244.

Stable URL:

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http://links.jstor.org/sici?sici=0002-9602%28196809%2974%3A2%3C119%3APIOAAR%3E2.0.CO%3B2-9&origin=JSTOR-pdf

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8/18/2019 Manski 1993


Neighborhood Context and College Plans

William H. Sewell; J. Michael Armer

American Sociological Review, Vol. 31, No. 2. (Apr., 1966), pp. 159-168.

Stable URL:

http://links.jstor.org/sici?sici=0003-1224%28196604%2931%3A2%3C159%3ANCACP%3E2.0.CO%3B2-C






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Manski 1993

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