Essays in microeconomic theory
Abstract/Contents
- Abstract
- This dissertation consists of three essays in microeconomic theory. They all concern strategic decisions or interactions under incomplete information. The first chapter, Armed Conflict Bargaining, is coauthored with James Fearon. In armed conflict bargaining, states (or governments and rebel groups) may exchange offers while they are fighting, and conflict can end either with a negotiated deal or a military victory. If fighting is driven by private information about military capabilities or costs relative to benefits, why doesn't the possibility of frequent offers lead to rapid learning and convergence on a settlement, as tends to occur in standard buyer-seller bargaining models? We show that when private information concerns military capability, equilibrium war durations can be quite long for reasonable parameter values, and the conditional probability of negotiated settlement is U-shaped. Armed conflict bargaining with private information about capabilities is an interdependent values (aka ``lemons") problem, but one that differs from buyer-seller contexts in that some fighting can directly reveal information about the value of more fighting. We also show that if, as makes sense for this setting, the sides can't contract to implement deals implying ``ex post regret, " then in equilibrium there can be long stretches of pure fighting with no exchange of serious offers. This is typically the case for both interstate and civil wars. The second chapter, Optimal Ordering in Sequential Auctions, is coauthored with Fanqi Shi and Yiqing Xing. It studies the optimal ordering of first-price and second-price (sealed-bid) sequential auctions. In the case of positive one-dimensional signal, we show sellers always want to order items in decreasing spread when such ordering exists. Moreover, the seller can achieve either fully efficient outcome or optimal revenue. Our analysis provides a (partial) explanation for the prevalence of sequential auctions. The third chapter, Robust Contracts with One-Sided Dynamic Impact, studies a repeated moral hazard setting in which the principal has nonquantifiable uncertainty and evaluates contracts by worse-case performances. In each period a distinct agent appears, and the principal knows only that the agent's action set contains a known base action set, but does not know the full action set. In addition, we assume the contracts cannot be legally enforced, and thus have to be self-enforcing, meaning that the principal will not renege on the previously agreed payment and this incentive must entirely come from that the potential benefits from the future contractual relationships outweigh the short-run payoffs from taking away the payment. In this case, a simple linear or affine contract does not work due to the lack of self-enforcement. We show that an also relatively simple form of contracts, ``capped-linear'' contracts, will satisfy the self-enforcement requirement and is optimal.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Jin, Xin |
|---|---|
| Degree supervisor | Carroll, Gabriel |
| Thesis advisor | Carroll, Gabriel |
| Thesis advisor | Fearon, James D |
| Thesis advisor | Kojima, Fuhito |
| Degree committee member | Fearon, James D |
| Degree committee member | Kojima, Fuhito |
| Associated with | Stanford University, Department of Economics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Xin Jin. |
|---|---|
| Note | Submitted to the Department of Economics. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Xin Jin
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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