Two-Step Estimation of Incomplete Information Social Interaction Models With Sample Selection
Bibliographic Data
| ID | 19419075 |
|---|---|
| Authors | Tadao Hoshino (0000-0001-9484-2943, Tokyo University of Science, corresponding author) |
| Year | 2019 |
| Volume | 37 |
| Issue | 4 |
| Pages | 598-612 |
| Publication date | 2019-10-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2017.1394861 |
| OpenAlex | W2766113232 |
| Language | EN |
| Citations received | 3 |
| References cited | 39 |
This article considers linear social interaction models under incomplete information that allow for missing outcome data due to sample selection. For model estimation, assuming that each individual forms his/her belief about the other members’ outcomes based on rational expectations, we propose a two-step series nonlinear least squares estimator. Both the consistency and asymptotic normality of the estimator are established. As an empirical illustration, we apply the proposed model and method to National Longitudinal Study of Adolescent Health (Add Health) data to examine the impacts of friendship interactions on adolescents’ academic achievements. We provide empirical evidence that the interaction effects are important determinants of grade point average and that controlling for sample selection bias has certain impacts on the estimation results.
Asymptotic distribution · Econometrics · Economics · Estimation · Estimator · Machine learning · Missing data · Model selection · Point estimation · Selection bias · Statistics · Computer Science · Mathematics · Media Influence and Politics · School Choice and Performance · Urban, Neighborhood, and Segregation Studies · Artificial Intelligence
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| Citations per year | 0.75 |
|---|---|
| Citation span | 2022 - 2026 (5) |
| Highly cited | No |