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Contributions to Structural Modeling and Estimation

Gayle, Wayne-Roy (2007) Contributions to Structural Modeling and Estimation. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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<p>The first chapter of my thesis develops and estimates a dynamic<br />structural partial equilibrium model of schooling and work<br />decisions.  The estimated model explicitly accounts for the<br />simultaneous choice of enrolling in school and working.  It also<br />allows for endogenous leisure choices, intertemporal<br />nonseparabilities in preferences, aggregate skill specific<br />productivity shocks, aggregate consumption price effects, and<br />individual heterogeneity.  Times spent on schooling, working, and<br />leisure are treated as continuous choice variables.  The estimated<br />model is solved and two counterfactual simulation exercises are<br />performed.  The first is the case where a subsidy is given to<br />individuals who enroll in school and do not participate in the labor<br />market.  The second is the case where the demands of the school<br />curriculum are increased so that a young man enrolled in school<br />necessarily spends more time studying.   The conclusion is that the<br />latter policy is more effective in enhancing educational<br />achievements and future wages.</p><p>The second chapter of my thesis develops a semiparametric estimator<br />for a dynamic nonlinear single index panel data model.  Flexibility<br />of the model is achieved by assuming that the index function is<br />unknown.  Flexibility in individual heterogeneity is achieved by<br />assuming that the individual effect is an unknown function of some<br />observable random variable.  The paper proposes an algorithm that<br />estimates each of the finite and infinite dimensional parameters. In<br />particular, the full data generating process is estimated.  This is<br />important if the predicted outcomes are used as plug-in estimators,<br />as in the multistage estimation of dynamic structural models.</p><p>The final chapter of my thesis develops a powerful new algorithm to<br />solve single object first price auctions where bidders draw<br />independent private values from heterogeneous distributions.  The<br />algorithm allows for the scenario in which groups of symmetric and<br />asymmetric bidders may collude, and for the auctioneer to set a<br />reserve price.  The paper also provides operational univariate<br />quadratures to evaluate the probabilities of winning as well as the<br />expected revenues for the bidders and the auctioneer.  The expected<br />revenue function is used to the compute optimal reserve under<br />asymmetric environments.</p>


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairRichard, Jean Francoisfantin@pitt.eduFANTIN
Committee MemberSieg,
Committee MemberCaner, Mehmetcaner@pitt.eduCANER
Committee MemberMiller,
Committee MemberNamoro, Soiliousnamoro@pitt.eduSNAMORO
Date: 26 September 2007
Date Type: Completion
Defense Date: 27 November 2006
Approval Date: 26 September 2007
Submission Date: 7 March 2007
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
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: Asymmetric Auctions; Educational Attainment; Individual Heterogeneity; Labor Supply; Numerical Solutions; Panel Data; Seimiparametric
Other ID:, etd-03072007-104200
Date Deposited: 10 Nov 2011 19:32
Last Modified: 15 Nov 2016 13:36


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