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Essays on Network and Panel Modeling
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Essays on Network and Panel Modeling. |
| 개인저자 | Gao, Wayne Yuan. |
| 단체저자명 | Yale University. Economics. |
| 발행사항 | [S.l.]: Yale University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 482 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-03A. Dissertation Abstract International |
| ISBN | 9781085777032 |
| 학위논문주기 | Thesis (Ph.D.)--Yale University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: A.
Advisor: Phillips, Peter C.B. |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | This dissertation studies a range of inter-related topics on social networks and panel data in economics. Recognizing the prevalence of heterogeneity and its importance in economic modeling and empirical research, this dissertation examines various forms of heterogeneity in network and panel models, developing new methods to tackle heterogeneity in ways that seek to better integrate economic theory, econometric method and empirical data.Chapters 1 and 2 study microeconomic models of local information in informal risk-sharing networks in the context of village economies in developing countries, providing theoretical and empirical analysis of the economic implications of informational network heterogeneity. Chapters 3 and 4 study econometric models of dyadic network formation that incorporates unobserved individual degree heterogeneity, semi/non-parametric homophily effects, flexible (nonparametric) specifications of error distributions and nontransferable utilities in link surplus distribution. Chapter 5 considers a seemingly different but underlyingly related semiparametric model of panel multinomial choices, proposing an econometric methodology that is robust against rich forms of unobserved heterogeneity. Chapter 1, coauthored with Eunyong Moon and reprinted from the B.E. Journal of Theoretical Economics, studies the strategic formation of risk-sharing networks under a local equal sharing rule, motivated by information heterogeneity across individuals in the networks. We find that any pairwise stable network features low average degree and almost two-regular structures, even under individual risk heterogeneity. This suggests that, in real-world networks with average degrees often much larger than two, risk-sharing considerations tend to generate negative incentives for network linkage. Moreover, we find that pairwise stable networks are likely to exhibit positive assortativity in terms of risk variances.Chapter 2, coauthored with Attila Ambrus and Pau Milan considers the effect of contracting limitations in risk-sharing networks that arise, for example, from local information constraints. We derive necessary and sufficient conditions for Pareto efficiency under these constraints in a general setting and provide an explicit characterization of the optimal risk-sharing arrangements under CARA utilities and normally distributed endowments. In our model, individuals with higher centralities become quasi-insurance providers to more peripheral individuals. We show that network centrality is (asymptotically) positively correlated with consumption volatility in dense and moderately sparse random graphs, and empirically corroborate this prediction using consumption and network data on rural villages in Thailand.Chapter 3 focuses on the identification of an index model of dyadic link formation with nonparametric homophily effects and unobserved degree heterogeneity. The paper derives sharp nonparametric identification results for these unknown elements. The key to the identification strategy is a novel form of scale normalization that controls an arbitrary inter-quantile range of the error distribution and provides a convenient linkage between observable conditional choice probabilities and the unknown index values. Under this normalization we deploy a new recursive in-fill and out-expansion algorithm to establish the main identification results. As a byproduct of the analysis a notion of modeling equivalence is proposed, the relevance of which in econometric modeling is illustrated in a formal discussion about normalization, identification and their interplay with counterfactual analysis.Chapter 4, coauthored with Ming Li and Sheng Xu, considers a semiparametric model of dyadic network formation under nontransferable utilities. Such dyadic links arise frequently in real-world social interactions that require bilateral consent but by their nature induce additive nonseparability. We show how two-way fixed effects (corresponding to unobserved individual heterogeneity in sociability) can be canceled out without requiring additivity, using a new method we call logical differencing. The key idea is to construct an observable event involving the intersection of two mutually exclusive restrictions on the fixed effects, while these restrictions are obtained by taking the logical contraposition of multivariate monotonicity. Based on this identification strategy we provide consistent estimates of the network formation model.Chapter 5, coauthored with Ming Li, develops a simple and robust method for semiparametric identification and estimation in a panel multinomial choice model, where we allow for infinite- dimensional fixed effects that enter into consumer utilities in an additively nonseparable way, thus incorporating rich forms of unobserved heterogeneity. Our identification strategy exploits multivariate monotonicity in an index vector of observable characteristics, and uses the logical contraposition of an intertemporal inequality on choice probabilities to obtain identifying restrictions on the indexes. We provide consistent estimators based on our identification strategy, together with a computational procedure that exploits a combination of theoretical and practical advantages under a spherical-coordinate reparameterization. A simulation study and an empirical illustration with the Nielsen data are conducted to analyze the finite-sample performance of our estimation method and demonstrate the adequacy of our computational procedure for practical implementation. |
| 일반주제명 | Economics. |
| 언어 | 영어 |
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