Chapter 1 provides descriptive evidence of the large variation in spatial clustering across retail industries, and develops a game-theoretic structural model which can explain this phenomenon. The model is estimated and used to consider how zoning regulations affect retail industries differently. I find that zoning can be as much as twelve times more costly to consumers, in terms of additional travel costs, for industries in which there are low gains to search.
Chapter 2 investigates the estimation of models of dynamic discrete-choice games of incomplete information, formulating the maximum-likelihood estimation exercise as a constrained optimization problem which can be solved using state-of-the-art constrained optimization solvers. Monte Carlo experiments are conducted to investigate the numerical performance and finite-sample properties of the constrained optimization approach for computing the maximum-likelihood estimator, the two-step pseudo maximum-likelihood estimator and the nested pseudo-likelihood estimator.
Chapter 3 studies the manipulability of stable matching mechanisms and shows that manipulability comparisons are equivalent to preference comparisons: for any agent, a mechanism is more manipulable than another if and only if this agent prefers the latter to the former. It is also shown that generalized median stable matchings exist in many-to-many matching markets when contracts are strong substitutes and satisfy the law of aggregate demand. / Economics
| Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/33493532 |
| Date | 25 July 2017 |
| Creators | Egesdal, Michael Dannen |
| Contributors | Lewis, Greg, Pakes, Ariel, Lee, Robin |
| Publisher | Harvard University |
| Source Sets | Harvard University |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation, text |
| Format | application/pdf |
| Rights | open |
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