Measuring the Effects of Segregation in the Presence of Social Spillovers: A Nonparametric Approach

Working Paper: NBER ID: w16499

Authors: Bryan S. Graham; Guido W. Imbens; Geert Ridder

Abstract: In this paper we nonparametrically analyze the effects of reallocating individuals across social groups in the presence of social spillovers. Individuals are either 'high' or 'low' types. Own outcomes may vary with the fraction of high types in one's social group. We characterize the average outcome and inequality effects of small increases in segregation by type. We also provide a measure of average spillover strength. We generalize the setup used by Benabou (1996) and others to study sorting in the presence of social spillovers by incorporating unobserved individual- and group-level heterogeneity. We relate our reallocation estimands to this theory. For each estimand we provide conditions for nonparametric identification, propose estimators, and characterize their large sample properties. We also consider the social planner's problem. We illustrate our approach by studying the effects of sex segregation in classrooms on mathematics achievement.

Keywords: Segregation; Social Spillovers; Nonparametric Methods

JEL Codes: C14; C31; D62; I21


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Reallocating individuals across groups (C92)Changes in average outcomes (I14)
Reallocating individuals across groups (C92)Changes in inequality (D31)
Local segregation outcome effect (LSOE) (R23)Average outcomes (C29)
Small increases in segregation (J79)Changes in average outcomes (I14)
Fraction of high-type individuals in a group (C92)Overall group outcomes (C92)
Segregation-increasing reallocation (R23)Outcome gap between high and low-type individuals (D29)
Average outcome effects of small increases in segregation (J79)Relative magnitudes of local average complementarity and curvature (D50)

Back to index