Full Citation

Title: Three Essays on Nonlinear Panel Data Models and Quantile Regression Analysis

Citation Type: Dissertation/Thesis

Publication Year: 2005

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Abstract: This dissertation is a collection of three independent essays in theoretical and applied econometrics,organized in the form of three chapters. In the first two chapters, I investigate the propertiesof parametric and semiparametric fixed effects estimators for nonlinear panel data models. Thefirst chapter focuses on fixed effects maximum likelihood estimators for binary choice models,such as probit, logit, and linear probability model. These models are widely used in economicsto analyze decisions such as labor force participation, union membership, migration, purchaseof durable goods, marital status, or fertility. The second chapter looks at generalized methodof moments estimation in panel data models with individual-specific parameters. An importantexample of these models is a random coefficients linear model with endogenous regressors. Thethird chapter (co-authored with Joshua Angrist and Victor Chernozhukov) studies the interpretationof quantile regression estimators when the linear model for the underlying conditionalquantile function is possibly misspecified.

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Authors: Fernandez-Val, Ivan

Institution: Massachusetts Institute of Technology

Department: Economics

Advisor: Joshua Angrist

Degree: Doctor of Philosophy

Publisher Location: Cambridge, MA

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Data Collections: IPUMS USA

Topics: Methodology and Data Collection

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