A Biparametric Approach to Spatial Autocorrelation
Bibliographic Data
| ID | 5115860 |
|---|---|
| Authors | A S Brandsma (Department of Econometrics, State University of Groningen, PO Box 800, 9700 AV, Groningen, The Netherlands), Andries Brandsma (University of Groningen), Ronald H Ketellapper (University of Groningen) |
| Year | 1979 |
| Volume | 11 |
| Issue | 1 |
| Pages | 51-58 |
| Publication date | 1979-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning A Economy and Space (JOURNAL) |
| Journal identifiers | ISSN: 0308-518X • E-ISSN: 1472-3409 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1068/a110051 |
| OpenAlex | W2015663416 |
| Language | EN |
| Citations received | 19 |
| References cited | 8 |
In spatial econometric models, autocorrelation among error terms is usually incorporated by means of the so-called contiguity matrix W, determining the interdependence between the spatial observations on the dependent variable. In this paper, the analysis is generalized by introducing two contiguity matrices, related to two autocorrelation parameters. This may be useful when dealing with variables representing flows between regions, where both the origin and the destination regions have a different impact on the autocorrelation scheme. It is shown analytically and illustrated empirically that the presence of such autocorrelation can be tested with the likelihood-ratio test, whereas the parameters can be estimated by the maximum-likelihood approach
Autocorrelation · Autocorrelation matrix · Autocorrelation technique · Contiguity · Econometrics · Mathematical analysis · Maximum likelihood · Physics · Spatial analysis · Statistical physics · Statistics · Computer Science · Housing Market and Economics · Mathematics · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis
Weight Matrices for Cultural Proximity
Spatial Weights
A spatial model incorporating dynamic, endogenous network interdependence
Contagion, Common Exposure, and Selection
Specification tests on the structure of interaction in spatial econometric models
Thirty years of spatial econometrics
Are commuting patterns a good indicator of urban spatial structure
The spatial structure debate in spatial interaction modeling
Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Micro-Level Data
Modeling social influence through network autocorrelation
Multivariate Modeling with Interdependent Network Data
A Note on Small Sample Properties of Estimators in a First-Order Spatial Autoregressive Model
Estimation of Autoregressive Models with Two Types of Weak Spatial Dependence by Means of the W-Based and the Latent Variables Approach
On Political Methodology
Bayesian Techniques in Spatial and Network Econometrics
Galton's Problem as network autocorrelation
Model Selection Procedures for Network Autocorrelated Disturbances Models
A Biparametric Approach to Network Autocorrelation
Maximum Likelihood Methods for Linear Models
| Unique citing works | 19 |
|---|---|
| Citations per year | 0,43 |
| Citation span | 1982 - 2020 (39) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 18 |