Arbeitspapier

Misclassification and the hidden silent rivalry

The interaction of economic agents is one of the most important elements in economic analyses. While most empirical studies investigate peer effects on objective final achievements, peer effects on subjective outcomes are inherently difficult to identify and estimate because these variables are prone to measurement errors. In particular, peer effects on students' attitudes towards learning are believed to have a significant impact on their achievements, while we found the presence of misclassification errors in students' self-reported attitudes. We develop a binary choice model with misclassification and social interactions and use a recently developed technique of measurement errormodels to correctmisreporting errors for estimating the peer effects on attitude. Our estimates suggest that a significant proportion of students overreport their attitudes towards learning and that peer effects are not only significant, but also much larger than estimates ignoring the misreporting errors. Our method may be generalized to the identification and estimation of peer effects with imperfect data information.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP12/18

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Econometrics of Games and Auctions
Computational Techniques; Simulation Modeling
Education and Research Institutions: General
Thema
Misclassification
Binary Choice
Peer Effects
Attitude Towards Learning
Silent Rivalry
Social Desirability

Ereignis
Geistige Schöpfung
(wer)
Hu, Yingyao
Lin, Zhongjian
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2018

DOI
doi:10.1920/wp.cem.2018.1218
Handle
Letzte Aktualisierung
10.03.2025, 11:41 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.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Hu, Yingyao
  • Lin, Zhongjian
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2018

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