Method-of-moment view of linear simultaneous equation systems
AbstractIn this paper, we review the modern method-of-moment-based approaches to identification and estimation of linear simultaneous equation systems. First, we present the rank condition for the structural form (SF) parameter identification. The rank condition comes naturally and is much easier to understand than that in the conventional reduced-form-based indirect approach. Then, we show how to estimate all SF parameters jointly (in a single step) with method-of-moment estimators. As it turns out, using only unconditional moments, but not any conditional moments, greatly simplifies the identification and estimation issues, and makes light work of conveying the essential ideas involved.
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Bibliographic InfoArticle provided by Netherlands Society for Statistics and Operations Research in its journal Statistica Neerlandica.
Volume (Year): 62 (2008)
Issue (Month): 2 ()
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0039-0402
Other versions of this item:
- Myoung-jae Lee, 2007. "Method-of-Moment View of Linear Simultaneous Equation Systems," Discussion Paper Series 0719, Institute of Economic Research, Korea University.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Myoung-jae Lee & Pao-Li Chang, 2007. "Avoiding arbitrary exclusion restrictions using ratios of reduced-form estimates," Empirical Economics, Springer, vol. 33(2), pages 339-357, September.
- Myoung-Jae Lee & Ayal Kimhi, 2005. "Simultaneous equations in ordered discrete responses with regressor-dependent thresholds," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 176-196, 07.
- Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
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