systemfit: A Package to Estimate Simultaneous Equation Systems in R

Henningsen, Arne and Hamann, Jeff (2006): systemfit: A Package to Estimate Simultaneous Equation Systems in R.

Abstract

Many 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.

• Item Type: MPRA Paper
• Institution: Department of Agricultural Economics, University of Kiel
• Language: English
• Keywords: simultaneous equations systems; seemingly unrelated regression; two-stage least squares; three-stage least squares; R
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C30 - General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General

References

Bates D (2004). “Least Squares Calculations in R.” R News, 4(1), 17–20. http://CRAN.R-project.org/doc/Rnews/.

Greene WH (2003). Econometric Analysis. Prentice Hall, 5th edition.

Greene WH (2006). “Information about SUR estimation in LIMDEP.” Personal email on 2006/02/16.

Grunfeld Y (1958). The Determinants of Corporate Investment. Ph.D. thesis, University of Chicago.

Hausman JA (1978). “Specification Test in Econometrics.” Econometrica, 46, 1251–1272.

Judge GG, Griffiths WE, Hill RC, Lütkepohl H, Lee TC (1985). The Theory and Practice of Econometrics. John Wiley and Sons, 2nd edition.

Klein L (1950). Economic Fluctuations in the United States, 1921–1941. John Wiley, New York.

Kmenta J (1986). Elements of econometrics. Macmillan, New York, 2 edition.

McElroy MB (1977). “Goodness of Fit for Seemingly Unrelated Regressions.” Journal of Econometrics, 6, 381–387.

Parks RW (1967). “Efficient estimation of a system of regression equations when disturbances are both serially and contemporaneously correlated.” Journal of the American Statistical Association, 62, 500–509.

R Development Core Team (2005). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org.

Schmidt P (1977). “Estimation of Seemingly Unrelated Regressions with Unequal Numbers of Observations.” Journal of Econometrics, 5, 365–377.

Schmidt P (1990). “Three-Stage Least Squares with Different Instruments for Different Equations.” Journal of Econometrics, 43, 389–394.

Theil H (1971). Principles of Econometrics. Wiley, New York.

Zellner A (1962). “An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias.” Journal of the American Statistical Association, 57, 348–368.

Zellner A, Huang DS (1962). “Further Properties of Efficient Estimators for Seemingly Unrelated Regression Equations.” International Economic Review, 3(3), 300–313.

Zellner A, Theil H (1962). “Three-Stage Least Squares: Simultaneous Estimation of Simultaneous Equations.” Econometrica, 30(1), 54–78.