systemfit: A Package to Estimate Simultaneous Equation Systems in R
AbstractMany statistical analyses are based on models containing systems of structurally related equations. In cases where cross-equation disturbances are correlated, full information methods are required (Zellner, 1962). If exogenous variables are stochastically dependent on the disturbances in the system, then instrumental variable estimation methods should be used (Zellner and Theil, 1962) The package systemﬁt provides the capability to estimate systems of linear equations within the R programming environment.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 1421.
Date of creation: 15 Mar 2006
Date of revision:
simultaneous equations systems; seemingly unrelated regression; two-stage least squares; three-stage least squares; R;
Find related papers by JEL classification:
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-01-14 (All new papers)
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.:
- Hausman, Jerry A, 1978.
"Specification Tests in Econometrics,"
Econometric Society, vol. 46(6), pages 1251-71, November.
- Schmidt, Peter, 1977. "Estimation of seemingly unrelated regressions with unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 5(3), pages 365-377, May.
- Schmidt, Peter, 1990. "Three-stage least squares with different instruments for different equations," Journal of Econometrics, Elsevier, vol. 43(3), pages 389-394, March.
- McElroy, Marjorie B., 1977. "Goodness of fit for seemingly unrelated regressions : Glahn's R2y.x and Hooper's r2," Journal of Econometrics, Elsevier, vol. 6(3), pages 381-387, November.
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