Empirical Likelihood Estimators Of The Linear Simultaneous Equations Model
AbstractInformation theoretic estimators are specified for a system of linear simultaneous equations, including maximum empirical likelihood, maximum empirical exponential likelihood, and maximum log Euclidean likelihood. Monte Carlo experiments are used to compare finite sample performance of these estimators to traditional generalized method of moments.
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Bibliographic InfoPaper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2001 Annual meeting, August 5-8, Chicago, IL with number 20752.
Date of creation: 2001
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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.:
- Guido W. Imbens & Richard H. Spady & Phillip Johnson, 1998.
"Information Theoretic Approaches to Inference in Moment Condition Models,"
Econometric Society, vol. 66(2), pages 333-358, March.
- Guido W Imbens, Phillip Johnson & Richard H Spady, . "Information theoretic approaches to inference in moment condition model," Economics Papers W12., Economics Group, Nuffield College, University of Oxford.
- Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," NBER Technical Working Papers 0186, National Bureau of Economic Research, Inc.
- Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," Harvard Institute of Economic Research Working Papers 1736, Harvard - Institute of Economic Research.
- Imbens, G.W. & Johnson, P. & Spady, R.H., 1995. "Information Theoretic Approaches to Inference in Movement Condition Models," Economics Papers 99, Economics Group, Nuffield College, University of Oxford.
- Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-80, July.
- Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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