Artikel
Specification and estimation of network formation and network interaction models with the exponential probability distribution
We model network formation and interactions under a unified framework by considering that individuals anticipate the effect of network structure on the utility of network interactions when choosing links. There are two advantages of this modeling approach: first, we can evaluate whether network interactions drive friendship formation or not. Second, we can control for the friendship selection bias on estimated interaction effects. We provide microfoundations of this statistical model based on the subgame perfect equilibrium of a two-stage game and propose a Bayesian MCMC approach for estimating the model. We apply the model to study American high school students' friendship networks using the Add Health dataset. From two interaction variables, GPA and smoking frequency, we find that the utility of interactions in academic learning is important for friendship formation, whereas the utility of interactions in smoking is not. However, both GPA and smoking frequency are subject to significant peer effects.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 11 ; Year: 2020 ; Issue: 4 ; Pages: 1349-1390 ; New Haven, CT: The Econometric Society
- Klassifikation
-
Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Analysis of Education
Fertility; Family Planning; Child Care; Children; Youth
- Thema
-
Social networks
social interactions
selectivity
spatial autoregressive model
Bayesian estimation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hsieh, Chih-Sheng
Lee, Lung-fei
Boucher, Vincent
- Ereignis
-
Veröffentlichung
- (wer)
-
The Econometric Society
- (wo)
-
New Haven, CT
- (wann)
-
2020
- DOI
-
doi:10.3982/QE944
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Hsieh, Chih-Sheng
- Lee, Lung-fei
- Boucher, Vincent
- The Econometric Society
Entstanden
- 2020
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