Peer Effects in Networks: A Survey
1
AMSE -
Aix-Marseille Sciences Economiques
2 IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics
3 Department of Economics, Université Laval
4 CRREP - Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques
5 CIRANO - Centre interuniversitaire de recherche en analyse des organisations
2 IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics
3 Department of Economics, Université Laval
4 CRREP - Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques
5 CIRANO - Centre interuniversitaire de recherche en analyse des organisations
Yann Bramoullé
- Fonction : Auteur
- PersonId : 17456
- IdHAL : yann-bramoulle
- IdRef : 195570707
Bernard Fortin
- Fonction : Auteur
Résumé
We survey the recent, fast-growing literature on peer effects in networks. An important recurring theme is that the causal identification of peer effects depends on the structure of the network itself. In the absence of correlated effects, the reflection problem is generally solved by network interactions even in nonlinear, heterogeneous models. By contrast, microfoundations are generally not identified. We discuss and assess the various approaches developed by economists to account for correlated effects and network endogeneity in particular. We classify these approaches in four broad categories: random peers, random shocks, structural endogeneity, and panel data. We review an emerging literature relaxing the assumption that the network is perfectly known. Throughout, we provide a critical reading of the existing literature and identify important gaps and directions for future research.
Domaines
Economies et financesFormat du dépôt | Notice |
---|---|
Type de dépôt | Article dans une revue |
Titre |
en
Peer Effects in Networks: A Survey
|
Résumé |
en
We survey the recent, fast-growing literature on peer effects in networks. An important recurring theme is that the causal identification of peer effects depends on the structure of the network itself. In the absence of correlated effects, the reflection problem is generally solved by network interactions even in nonlinear, heterogeneous models. By contrast, microfoundations are generally not identified. We discuss and assess the various approaches developed by economists to account for correlated effects and network endogeneity in particular. We classify these approaches in four broad categories: random peers, random shocks, structural endogeneity, and panel data. We review an emerging literature relaxing the assumption that the network is perfectly known. Throughout, we provide a critical reading of the existing literature and identify important gaps and directions for future research.
|
Auteur(s) |
Yann Bramoullé
1
, Habiba Djebbari
1, 2
, Bernard Fortin
2, 3, 4, 5
1
AMSE -
Aix-Marseille Sciences Economiques
( 526949 )
- 5-9 Boulevard Bourdet
CS 50498
13205 Marseille Cedex 1
- France
2
IZA -
Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics
( 237214 )
- Schaumburg-Lippe-Str. 5-9 D-53113 Bonn Germany
- Allemagne
3
Department of Economics, Université Laval
( 215413 )
- Canada
4
CRREP -
Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques
( 487361 )
- Pavillon J.-A.-DeSève
1025, avenue des Sciences-Humaines, bureau DES-2186
Université Laval
Québec (Québec) G1V 0A6
CANADA
- Canada
5
CIRANO -
Centre interuniversitaire de recherche en analyse des organisations
( 37218 )
- 2020, rue University, 25e étage Montréal, Québec, H3A 2A5
- Canada
|
Langue du document |
Anglais
|
Nom de la revue |
|
Vulgarisation |
Non
|
Comité de lecture |
Oui
|
Audience |
Internationale
|
Date de publication |
2020-08-02
|
Date de publication électronique |
2020-05-05
|
Volume |
12
|
Numéro |
1
|
Page/Identifiant |
603-629
|
URL éditeur |
https://www.annualreviews.org/doi/10.1146/annurev-economics-020320-033926
|
Domaine(s) |
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Projet(s) ANR |
|
Mots-clés |
en
social networks, peer effects, identification, causal effects, randomization, measurement errors
|
DOI | 10.1146/annurev-economics-020320-033926 |
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