systemfit: A Package for Estimating Systems of Simultaneous Equations in R
Many statistical analyses (e.g., in econometrics, biostatistics and experimental design) are based on models containing systems of structurally related equations. The systemfit package provides the capability to estimate systems of linear equations within the R programming environment. For instance, this package can be used for "ordinary least squares" (OLS), "seemingly unrelated regression" (SUR), and the instrumental variable (IV) methods "two-stage least squares" (2SLS) and "three-stage least squares" (3SLS), where SUR and 3SLS estimations can optionally be iterated. Furthermore, the systemfit package provides tools for several statistical tests. It has been tested on a variety of datasets and its reliability is demonstrated.
References listed on IDEAS
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- Hausman, Jerry, 2015.
"Specification tests in econometrics,"
Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
- John Freebairn & Bill Griffiths, 2006. "Introduction," The Economic Record, The Economic Society of Australia, vol. 82(s1), pages S1-S1, 09.
- 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.
- 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.
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