Essays in econometrics and random matrix theory
Name
180190294-MIT.pdf
Description
Full printable version
Size
2.07 MB
Format
Adobe PDF
Checksum (MD5)
8cc7c7213f7d01eda823325770d0cfd3
Author(s)
Harding, Matthew C
Advisor(s)
Jerry Hausman, Victor Chernozhukov and Whitney Newey.
Date Issued
2007
Publisher
Massachusetts Institute of Technology
Abstract
This dissertation develops new econometric procedures for the analysis of high-dimensional datasets commonly encountered in finance, macroeconomics or industrial organization. First, I show that traditional approaches to the estimation of latent factors in financial data underestimate the number of risk factors. They are also biased towards a single market factor, the importance of which is overestimated in samples. In Chapter 3, I derive a new consistent procedure for the estimation of the number of latent factors by examining the effect of the idiosyncratic noise in a factor model. Furthermore, I show that the estimation of factor loadings by Principal Components Analysis is inconsistent for weak factors and suggest alternative Instrumental Variables procedures. Chapter 4 uses the theoretical results of the earlier chapters to estimate the stochastic dimension of the US economy and shows that global risk factors may obfuscate the relationship between inflation and unemployment. Chapter 5 (co-authored with Jerry Hausman) suggests a new procedure for the estimation of discrete choice models with random coe±cients and shows that ignoring individual taste heterogeneity can lead to misleading policy counterfactuals.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references.
Subjects
Economics.
MIT Department
Massachusetts Institute of Technology. Department of Economics
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