2026-09-19T07:44:23Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1474172023-01-20T03:21:43Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Pathak, Parag
Agarwal, Nikhil
Shayani, Joseph N.
Massachusetts Institute of Technology. Department of Economics
2023-01-19T19:48:50Z
2023-01-19T19:48:50Z
2022-09
2022-09-16T16:22:27.383Z
https://hdl.handle.net/1721.1/147417
0000-0002-9344-0341
This thesis contains three essays on the topic of quantifying the impact of interviews in a matching market. The first two essays are empirical and use novel preference and matching data from the Canadian Residency Matching Service (CaRMS), and the third essay presents a formal identification result. In the first essay, I measure the impact of interviews on employers' preferences, and in the second essay, I measure the impact of reducing interviews on match outcomes. Both essays require me to quantify employers' pre-interview information about their post-interview preferences, but employers observe information unobservable to the econometrician. To address this econometric challenge, I estimate a joint structural model of interview offers and post-interview ranks in which unobservables may be correlated across the two periods, and thereby I use the information contained in post-interview preferences to correct for employers' additional pre-interview information. The third essay presents a non-parametric identification result that formalizes the possibility of using selection (e.g., interview-offer) data and binary outcome (e.g., job-offer) data jointly to correct for the role of unobservable factors in selection.
Ph.D.
Massachusetts Institute of Technology
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https://rightsstatements.org/page/InC-EDU/1.0/
Essays on Interviews and Matching
Thesis
application/pdf
Doctoral
Doctor of Philosophy
Publication
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unknown
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<Abstract>This thesis contains three essays on the topic of quantifying the impact of interviews in a matching market. The first two essays are empirical and use novel preference and matching data from the Canadian Residency Matching Service (CaRMS), and the third essay presents a formal identification result. In the first essay, I measure the impact of interviews on employers' preferences, and in the second essay, I measure the impact of reducing interviews on match outcomes. Both essays require me to quantify employers' pre-interview information about their post-interview preferences, but employers observe information unobservable to the econometrician. To address this econometric challenge, I estimate a joint structural model of interview offers and post-interview ranks in which unobservables may be correlated across the two periods, and thereby I use the information contained in post-interview preferences to correct for employers' additional pre-interview information. The third essay presents a non-parametric identification result that formalizes the possibility of using selection (e.g., interview-offer) data and binary outcome (e.g., job-offer) data jointly to correct for the role of unobservable factors in selection.</Abstract>
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