systemfit
A Package for Estimating Systems of Simultaneous Equations in R
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What is systemfit?
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systemfit is an extension package for the "language and environment for statistical computing and graphics" called R.
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systemfit provides functions for estimating systems of simultaneous equations, e.g. by Ordinary Least Squares (OLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), and Three-Stage Least Squares (3SLS).
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systemfit allows the user to specify either the same instrumental variables for all equations or different instrumental variables for each equation.
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systemfit allows the user to control many details of the estimation (in contrast to most other statistical and econometric software packages), e.g. the method to calculate the residual covariance and the method for the 3SLS estimation.
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systemfit provides statistical tests for parameter restrictions and consistency of the 3SLS estimation.
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systemfit has been tested on a variety of datasets and has produced satisfactory for a few years.
Who has written systemfit?
Where can I get systemfit?
- The released version is available on
CRAN
- The current development version is available on
R-Forge
Under which license is systemfit released?
Where can I ask questions, report bugs, or suggest new features?
FAQ
- Can the systemfit package estimate a system of non-linear
equations?
The systemfit package provides the function nlsystemfit,
which can estimate systems of non-linear equations.
However, while the code for estimating systems of linear equations
(function systemfit) has been very mature and reliable
for many years,
the estimation of systems of non-linear equations
(function nlsystemfit) is still under development
and often has convergence problems.
Therefore, we cannot recommend using function nlsystemfit
for serious applications.
- Can the systemfit package estimate panel data models?
Function systemfit can estimate a system of equations
with panel data if the same (single) equation is estimated for each individual.
However, it cannot (yet) estimate arbitrary systems of
multiple equations as panel data models (except for pooled regression).
Last Update: 7 April 2012