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Title: Nonparametric structural analysis of discrete data : the quantile-based control function approach
Author: Lee, J.
ISNI:       0000 0004 2728 4701
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2010
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The first chapter is introduction and Chapter 2 proposes formal frameworks for identifiability and testability of structural features allowing for set identification. The results in Chapter 2 are used in other chapters. The second section of Chapter 3, Chapter 4 and Chapter 5 contain new results. Chapter 3 has two sections. The first section introduces the quantile-based control function approach (QCFA) proposed by Chesher (2003) to compare and contrast other results in Chapter 4 and 5. The second section contains new findings on the local endogeneity bias and testability of endogeneity. Chapter 4 assumes that the structural relations are differentiable and applies the QCFA to several models for discrete outcomes. Chapter 4 reports point identification results of partial derivatives with respect to a continuously varying endogenous variable. Chapter 5 relaxes differentiability assumptions and apply the QCFA with an ordered discrete endogeneous variable. The model in Chapter 5 set identifies partial differences of a nonseparable structural function.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available