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https://scholarbank.nus.edu.sg/handle/10635/192055
DC Field | Value | |
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dc.title | EXAMINING THE EARNINGS RETURNS TO DIFFERENT FIELDS OF STUDY | |
dc.contributor.author | ZHANG ANNINA | |
dc.date.accessioned | 2021-06-14T09:11:05Z | |
dc.date.available | 2021-06-14T09:11:05Z | |
dc.date.issued | 2021-04-05 | |
dc.identifier.citation | ZHANG ANNINA (2021-04-05). EXAMINING THE EARNINGS RETURNS TO DIFFERENT FIELDS OF STUDY. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/192055 | |
dc.description.abstract | This paper investigates how earnings returns differ between the various fields of study in NUS. It does so through a fuzzy regression discontinuity (RD) approach modelled after Kirkeboen, Leuven, and Mogstad (2014). The RD exploits the fact that entry into a specific field of study at NUS is governed by admission cut-offs, thus effectively randomising applicants near the cut-offs into different fields. I find that under RD, wage differences between fields of study appear much smaller in comparison to what an ordinary least squares (OLS) approach would suggest. I also find that returns to a field of study are heterogeneous; returns from a field appear to be dependent on individuals’ innate aptitudes and interests, which can be revealed from ranking preferences during application. This affirms the conclusion from Kirkeboen et al. (2014) that information on students’ next-best field of study is crucial when estimating returns to fields of study. | |
dc.subject | Labour, Earnings | |
dc.subject | Field of Study | |
dc.subject | Self-Selection | |
dc.subject | Regression Discontinuity | |
dc.subject | Singapore | |
dc.type | Thesis | |
dc.contributor.department | ECONOMICS | |
dc.contributor.supervisor | JESSICA PAN | |
dc.description.degree | Bachelor's | |
dc.description.degreeconferred | Bachelor of Social Sciences (Honours) | |
Appears in Collections: | Bachelor's Theses |
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File | Description | Size | Format | Access Settings | Version | |
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Zhang Annina AY2021 Sem 2.pdf | 1.94 MB | Adobe PDF | RESTRICTED | None | Log In |
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