Liu, Quanquan
(2021)
Essays on Estimation of Microeconomic Models.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
This is the latest version of this item.
Abstract
This dissertation consists of three studies.
Hidden city ticketing occurs when an indirect flight from city A to city C through connection node city B is cheaper than the direct flight from city A to city B. In this paper, I build a structural model, collect empirical data, apply global optimization algorithms, and conduct counterfactual analysis to shed light on policy implications. I find that hidden city opportunity occurs only when airlines are applying a hub-and-spoke network structure. In the short run, hidden city ticketing does not necessarily decrease airlines' expected profits. Consumer welfare and total surplus always increase. In the long run, for some routes airlines have the incentive to switch from hub-and-spoke network to a fully-connected one when there are more passengers informed of hidden city ticketing. Firms always result in lower expected profits, consumers and the whole society are not necessarily better off.
Global optimization without access to gradient information is a central task to many econometric applications as the tool to obtain maximum likelihood estimators for very complicated likelihood functions. In this work, we study the problem of coordination between the multiple "threads" of estimating gradient descent in order to pause or terminate unpromising threads early. We test our proposed methodology on both synthetic data and real airline pricing data, and compare with competitive methods including the genetic algorithm and pattern search. The numerical results show the effectiveness and efficiency of our proposed approach.
In my third work, I exploit large changes in the H-1B visa program and examines the effect of changes in H-1B admission levels on the likelihood that US natives major in STEM fields. I find some evidence that H-1B population adversely affect natives' choices in STEM fields when they enter the college and graduate from it. Female, Male and White subgroups have been negatively affected, and the native Asian subgroup suffer from the most dramatic crowd-out effect. Given that the H-1B population share had been more than doubled during 1992 to 2017, the probability of native Asian graduates majoring in STEM fields would be 2.56 percentage points larger.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
20 January 2021 |
| Date Type: |
Publication |
| Defense Date: |
25 November 2020 |
| Approval Date: |
20 January 2021 |
| Submission Date: |
28 November 2020 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
118 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Dietrich School of Arts and Sciences > Economics |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
hidden city ticketing, network structure, second-degree price discrimination, maximum likelihood optimization, H-1B visa program, college major choices, crowd-out effect. |
| Date Deposited: |
20 Jan 2021 18:55 |
| Last Modified: |
20 Jan 2021 18:55 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/40055 |
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