liml |

Limited Information Maximum Likelihood and K-class Estimation.

Syntax

eq_name.liml(options) y c x1 [x2 x3 ...] @ z1 [z2 z3 ...]

eq_name.liml(options) specification @ z1 [z2 z3 ...]

To use the liml command, list the dependent variable first, followed by the regressors, then any AR or MA error specifications, then an “@”-sign, and finally, a list of exogenous instruments.

You may estimate nonlinear equations or equations specified with formulas by first providing a specification, then listing the instrumental variables after an “@”-sign. There must be at least as many instrumental variables as there are independent variables. All exogenous variables included in the regressor list should also be included in the instrument list. A constant is included in the list of instrumental variables, unless the noconst option is specified.

Options

noconst | Do not include a constant in the instrumental list. Without this option, a constant will always be included as an instrument, even if not specified explicitly. |

w=arg | Weight series or expression. |

wtype=arg (default=“istdev”) | Weight specification type: inverse standard deviation (“istdev”), inverse variance (“ivar”), standard deviation (“stdev”), variance (“var”). |

wscale=arg | Weight scaling: EViews default (“eviews”), average (“avg”), none (“none”). The default setting depends upon the weight type: “eviews” if “wtype=istdev”, “avg” for all others. |

kclass=number | Set the value of in the K‑class estimator. If omitted, LIML is performed, and is calculated as part of the estimation procedure. |

se = arg (default=“iv”) | Set the standard-error calculation type: IV based (“se=iv”), K-Class based (“se=kclass”), Bekker (“se=bekk”), or Hansen, Hausman, and Newey (“se=hhn”). |

m=integer | Set maximum number of iterations. |

c=number | Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled coefficients. The criterion will be set to the nearest value between 1e-24 and 0.2. |

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. Available only for legacy estimation (“optmeth=legacy”). |

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

coef=arg | Specify the name of the coefficient vector (if specified by list); the default behavior is to use the “C” coefficient vector. |

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

p | Print estimation results. |

Examples

equation eq1.liml gdp c cpi inc @ lw lw(-1)

creates equation EQ1 and calculates a LIML estimation of GDP on a constant, CPI, and INC, using a constant, LW, and LW(-1) as instruments.

e1.liml(kclass=2)

estimates the same equation, but this time via K-Class estimation, with K=2.

Cross-references

See also
“Limited Information Maximum Likelihood and K-Class Estimation” for discussion.