Work

A Spatial Cliff-ord-type Model With Heteroskedastic Innovations: Small and Large Sample Results*

Year: 2009

Type: article

Abstract: ABSTRACT In this paper, we specify a linear Cliff-and-Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate multistep GMM/IV-type estimation procedures for the parameters of the model. We also give the limiting distributions for our suggested estimators and consistent estimators for their asymptotic variance-covariance matrices. We conduct a Monte Carlo study to show that the derived large-sample distribution provides a good approximation to the actual small-sample distribution of our estimators.

Source: Journal of Regional Science

DOI: 10.1111/j.1467-9787.2009.00618.x

Authors: Irani Arraiz, David M. Drukker, Harry H. Kelejian, Ingmar R. Prucha

Institutions: Inter-American Development Bank, University of Maryland, College Park

Language: English

Topic: Spatial and Panel Data Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W2166856702

FWCI: 64.39

Cites: 85

Cited by: 315

Related to: 10