Matching Items (2)
Description
In this paper, I study many-to-one matching markets in a dynamic framework with the
following features: Matching is irreversible, participants exogenously join the market
over time, each agent is restricted by a quota, and agents are perfectly patient. A
form of strategic behavior in such markets emerges: The side with many slots can
manipulate the subsequent matching market in their favor via earlier matchings. In
such a setting, a natural question arises: Is it possible to analyze a dynamic many-to-one
matching market as if it were either a static many-to-one or a dynamic one-to-one
market? First, I provide sufficient conditions under which the answer is yes. Second,
I show that if these conditions are not met, then the early matchings are "inferior"
to the subsequent matchings. Lastly, I extend the model to allow agents on one side
to endogenously decide when to join the market. Using this extension, I provide
a rationale for the small amount of unraveling observed in the United States (US)
medical residency matching market compared to the US college-admissions system.
Micro Finance Institutions (MFIs) are designed to improve the welfare of the poor.
Group lending with joint liability is the standard contract used by these institutions.
Such a contract performs two roles: it affects the composition of the groups that form,
and determines the properties of risk-sharing among their members. Even though the
literature suggests that groups consist of members with similar characteristics, there
is evidence also of groups with heterogeneous agents. The underlying reason is that
the literature lacked the risk-sharing behavior of the agents within a group. This
paper develops a model of group lending where agents form groups, obtain capital
from the MFI, and share risks among themselves. First, I show that joint liability
introduces inefficiency for risk-averse agents. Moreover, the composition of the groups
is not always homogeneous once risk-sharing is on the table.
following features: Matching is irreversible, participants exogenously join the market
over time, each agent is restricted by a quota, and agents are perfectly patient. A
form of strategic behavior in such markets emerges: The side with many slots can
manipulate the subsequent matching market in their favor via earlier matchings. In
such a setting, a natural question arises: Is it possible to analyze a dynamic many-to-one
matching market as if it were either a static many-to-one or a dynamic one-to-one
market? First, I provide sufficient conditions under which the answer is yes. Second,
I show that if these conditions are not met, then the early matchings are "inferior"
to the subsequent matchings. Lastly, I extend the model to allow agents on one side
to endogenously decide when to join the market. Using this extension, I provide
a rationale for the small amount of unraveling observed in the United States (US)
medical residency matching market compared to the US college-admissions system.
Micro Finance Institutions (MFIs) are designed to improve the welfare of the poor.
Group lending with joint liability is the standard contract used by these institutions.
Such a contract performs two roles: it affects the composition of the groups that form,
and determines the properties of risk-sharing among their members. Even though the
literature suggests that groups consist of members with similar characteristics, there
is evidence also of groups with heterogeneous agents. The underlying reason is that
the literature lacked the risk-sharing behavior of the agents within a group. This
paper develops a model of group lending where agents form groups, obtain capital
from the MFI, and share risks among themselves. First, I show that joint liability
introduces inefficiency for risk-averse agents. Moreover, the composition of the groups
is not always homogeneous once risk-sharing is on the table.
ContributorsAltinok, Ahmet (Author) / Chade, Hector (Thesis advisor) / Manelli, Alejandro (Committee member) / Friedenberg, Amanda (Committee member) / Kovrijnykh, Natalia (Committee member) / Arizona State University (Publisher)
Created2020
Description
The aim of this project was to provide college applicants with the ability to apply using a video instead of an essay. These videos are analyzed automatically and their scripts are taken and submitted with the application. This was implemented through the use of Amazon Web Services (AWS) and their S3 buckets along with their speech to text transcription service. This type of application process can give admissions teams the opportunity to get to know who will potentially be attending their university and allows the applicants to express themselves to admissions teams in a new and unique way.
ContributorsStephan, Meagan (Co-author) / Pratt, Devan (Co-author) / Chen, Yinong (Thesis director) / Balasooriya, Janaka (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12