Estimation of errors-in-variables models with no auxiliary data
Abstract/Contents
- Abstract
- This paper considers estimation in the context of regression models where some of the regressors are measured with errors. The regression model is identified under the assumption of strict exogeneity in the regression equation and classical errors. The structural model is equivalent to a certain infinite set of moment conditions, which allows me to construct a CGMM (continuous GMM) estimator for the parameters of the model. Alternatively, I also construct a finite-dimensional GMM by selecting a subset of moment conditions. Both frameworks are discussed in the paper, as they need to be augmented in order to allow for complex-valued moments. Monte-Carlo simulations show that my proposed estimation technique is several times better in terms of MSE than the alternatives proposed in the earlier literature.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2013 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Stetsenko, Pavlo |
|---|---|
| Associated with | Stanford University, Department of Economics. |
| Primary advisor | Hong, Han |
| Thesis advisor | Hong, Han |
| Thesis advisor | Romano, Joseph P, 1960- |
| Thesis advisor | Wolak, Frank A |
| Advisor | Romano, Joseph P, 1960- |
| Advisor | Wolak, Frank A |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Pasha Stetsenko. |
|---|---|
| Note | Submitted to the Department of Economics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2013. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Pavlo Stetsenko
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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