Estimate a system object using seemingly unrelated regression (SUR).

Note that the EViews procedure is more general than textbook versions of SUR since the system of equations may contain cross-equation restrictions on parameters.

Syntax

system_name.sur(options)

Options

i | Iterate on the weighting matrix and coefficient vector simultaneously. |

s | Iterate on the weighting matrix and coefficient vector sequentially. |

o (default) | Iterate only on the coefficient vector with one step of the weighting matrix. |

c | One step iteration on the coefficient vector after one step of the weighting matrix. |

m=integer | Maximum number of iterations. |

c=number | Set convergence criterion.The criterion will be set to the nearest value between 1e-24 and 0.2. |

l=number | Set maximum number of iterations on the first-stage iteration to get one-step weighting matrix. |

numericderiv / ‑numericderiv | [Do / do not] use numeric derivatives only. If omitted, EViews will follow the global default. |

fastderiv / ‑fastderiv | [Do / do not] use fast derivative computation. If omitted, EViews will follow the global default. |

showopts / ‑showopts | [Do / do not] display the starting coefficient values and estimation options in the estimation output. |

prompt | Force the dialog to appear from within a program. |

p | Print estimation results. |

Examples

sys1.sur(i)

estimates SYS1 by SUR, iterating simultaneously on the weighting matrix and coefficient vector.

nlsys.sur(showopts,m=500)

estimates NLSYS by SUR with up to 500 iterations. The “showopts” option displays the starting values.

Cross-references