Control function methods in applied econometrics
"This dissertation considers estimation and inference in three econometric models containing issues commonly encountered with observational data. Fundamental issues of self-selection, endogeneity, missing observations are pervasive in observational data. Moreover, often, the observations in a dataset are rarely statistically independent and have complex dependence structures. These issues can have a significant effect on the causal effect analysis and pose serious limitations on the popular methodologies that either maintain restrictive assumptions and/or require complicated and computationally tedious solutions.The dissertation aims to apply control function method as the primary tool to design estimation procedures under relaxed distributional and functional form assumptions. I describe computationally simple solutions to these issues to obtain more precise results. These estimation procedures are obtained under relaxed distributional and functional form assumptions allowing a researcher to incorporate more variability (or heterogeneity)."--from abstract.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- In Copyright
- Material Type
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Theses
- Authors
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Joshi, Riju
- Thesis Advisors
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Wooldridge, Jeffrey M.
- Committee Members
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Schmidt, Peter
Kim, Kyoo il
Liverpool-Tasie, Saweda
- Date Published
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2018
- Program of Study
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Economics - Doctor of Philosophy
- Degree Level
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Doctoral
- Language
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English
- Pages
- ix, 121 pages
- ISBN
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9780438294226
043829422X
- Permalink
- https://doi.org/doi:10.25335/h4vr-r826