Seminario Applied

Grant Hillier

University of Southampton


Seminar 3 – 14:30


The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spatial autoregressive model cannot in general be written explicitly in terms of the data. The only known properties of the estimator have hitherto been its first-order asymptotic properties (Lee, 2004, Econometrica), derived under specific assumptions on the evolution of the spatial weights matrix involved. In this paper we show that the exact cumulative distribution function of the estimator can, under mild assumptions, be written in terms of that of a particular quadratic form. A number of immediate consequences of this result are discussed, and some examples of theoretical and practical interest are analyzed in detail. The examples are of interest in their own right, but also serve to illustrate some unexpected features of the distribution of the MLE. In particular, we show that the distribution of the MLE may not be supported on the entire parameter space, and may be nonanalytic at some points in its support.

Bajar pdf
Deja un comentario

Tu dirección de correo electrónico no será publicada. Los campos requeridos están marcados *

Puedes usar las siguientes HTML etiquetas y atributos: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

borrar formularioEnviar

Este sitio usa Akismet para reducir el spam. Aprende cómo se procesan los datos de tus comentarios.