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Applications of Generalized Method of Moments Estimation
Abstract
I describe how the method of moments approach to estimation, including the more recent generalized method of moments (GMM) theory, can be applied to problems using cross section, time series, and panel data. Method of moments estimators can be attractive because in many circumstances they are robust to failures of auxiliary distributional assumptions that are not needed to identify key parameters. I conclude that while sophisticated GMM estimators are indispensable for complicated estimation problems, it seems unlikely that GMM will provide convincing improvements over ordinary least squares and two-stage least squares--by far the most common method of moments estimators used in econometrics--in settings faced most often by empirical researchers.
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Cites
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1998) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00009-8 · Cited by 22,571
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. (1994) · doi:10.3386/t0151 · Cited by 5,302
Bound, J., Jaeger, D. A., & Baker, R. M. (1995) · Journal of the American Statistical Association · doi:10.2307/2291055 · Cited by 1,018
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The role of ageing in the growth of government and social welfare spending in the OECD
Sanz, I., & Velázquez, F. J. (2007) · European Journal of Political Economy · doi:10.1016/j.ejpoleco.2007.01.003 · Cited by 92
Performance Of The South African Banking Sector Since 1994
Ifeacho, C., & Ngalawa, H. (2014) · Journal of Applied Business Research (JABR) · doi:10.19030/jabr.v30i4.8663 · Cited by 42
Lin, W. L., Lee, C., & Law, S. H. (2021) · Business Strategy and the Environment · doi:10.1002/bse.2662 · Cited by 30
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Aranda, L., & Siyaranamual, M. D. (2014) · doi:10.2139/ssrn.2435818 · Cited by 5
Metadata
- Authors
- Wooldridge, J. M.
- Venue
- Journal of Economic Perspectives
- Publisher
- American Economic Association
- Published
- 2001-11-01
- Volume
- 15
- Issue
- 4
- Pages
- 87-100
- ISSN
- 0895-3309 (ISSN-L)
- OpenAlex
- W2155455221
- Cited by
- 541
- References
- 3
- FWCI
- 2.87
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
