ordered |

Estimation of ordered dependent variable models.

Syntax

equation name.ordered(options) y x1 [x2 x3 ...]

equation name.ordered(options) specification

The ordered command estimates the model and saves the results as an equation object with the given name.

Options

d=arg (default=“n”) | Specify likelihood: normal likelihood function, ordered probit (“n”), logistic likelihood function, ordered logit (“l”), Type I extreme value likelihood function, ordered Gompit (“x”). |

optmethod = arg | Optimization method: “bfgs” (BFGS); “newton” (Newton-Raphson), “opg” or “bhhh” (OPG or BHHH), “legacy” (EViews legacy). Newton-Raphson is the default method. |

optstep = arg | Step method: “marquardt” (Marquardt); “dogleg” (Dogleg); “linesearch” (Line search). Marquardt is the default method. |

cov=arg | Covariance method: “ordinary” (default method based on inverse of the estimated information matrix), “huber” or “white” (Huber-White sandwich method)., “glm” (GLM method), “cr” (cluster robust). |

covinfo = arg | Information matrix method: “opg” (OPG); “hessian” (observed Hessian). (Applicable when non-legacy “optmethod=”.) |

df | Degree-of-freedom correct the coefficient covariance estimate.(For non-cluster robust methods estimated using non-legacy estimation). |

h | Huber-White quasi-maximum likelihood (QML) standard errors and covariances. (Legacy option Applicable when “optmethod=legacy”). |

crtype=arg (default “cr1”) | Cluster robust weighting method: “cr0” (no finite sample correction), “cr1” (finite sample correction), when “cov=cr”. |

crname=arg | Cluster robust series name, when “cov=cr”. |

m=integer | Set maximum number of iterations. |

c=scalar | 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. |

s | Use the current coefficient values in “C” as starting values (see also
param). |

s=number | Specify a number between zero and one to determine starting values as a fraction of preliminary EViews default values (out of range values are set to “s=1”). |

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 results. |

If you choose to employ user specified starting values, the parameters corresponding to the limit points must be in ascending order.

Examples

ordered(d=l,cov=huber) y c wage edu kids

estimates an ordered logit model of Y on a constant, WAGE, EDU, and KIDS with QML standard errors. This command uses the default quadratic hill climbing algorithm.

param c(1) .1 c(2) .2 c(3) .3 c(4) .4 c(5).5

equation eq1.binary(s) y c x z

coef betahat = eq1.@coefs

eq1.makelimit gamma

estimates an ordered probit model of Y on a constant, X, and Z from the specified starting values. The estimated coefficients are then stored in the coefficient vector BETAHAT, and the estimated limit points are stored in the vector GAMMA.

Cross-references

See
“Ordered Dependent Variable Models” for additional discussion.

See
Equation::binary for the estimation of binary dependent variable models. See also
Equation::makelimits.