Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances
TLDR
In this paper, a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations is developed.About:
This article is published in Journal of Econometrics.The article was published on 2010-07-01 and is currently open access. It has received 749 citations till now. The article focuses on the topics: Estimator & Autoregressive model.read more
Citations
More filters
Journal ArticleDOI
Comparing Implementations of Estimation Methods for Spatial Econometrics
Roger Bivand,Gianfranco Piras +1 more
TL;DR: This review constitutes an up-to-date comparison of generalized method of moments and maximum likelihood implementations now available, using the cross-sectional US county data set provided by Drukker, Prucha, and Raciborski (2013d).
Journal ArticleDOI
Thirty years of spatial econometrics
TL;DR: It is argued that the field of spatial econometric methodology has moved from the margins to the mainstream of applied econometrics and social science methodology during the past 30 years.
Journal ArticleDOI
Large Panels with Common Factors and Spatial Correlation
M. Hashem Pesaran,Elisa Tosetti +1 more
TL;DR: In this paper, the authors consider the statistical analysis of large panel data sets where even after condi- tioning on common observed eects the cross section units might remain dependently distrib- uted.
Journal ArticleDOI
Matlab Software for Spatial Panels
TL;DR: This article extends Matlab routines to include the bias correction procedure proposed by Lee and Yu if the spatial panel data model contains spatial and/or time-period fixed effects, the direct and indirect effects estimates of the explanatory variables proposed by LeSage and Pace, and a selection framework to determine which spatialpanel data model best describes the data.
Journal ArticleDOI
The SLX model
TL;DR: In this paper, the authors provide a comprehensive overview of the strengths and weaknesses of different spatial econometric model specifications in terms of spillover effects and advocate taking the SLX model as point of departure in case a well-founded theory indicating which model is most appropriate is lacking.
References
More filters
Book
Matrix Analysis
Roger A. Horn,Charles R. Johnson +1 more
TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Book
Spatial Econometrics: Methods and Models
TL;DR: In this article, a typology of Spatial Econometric Models is presented, and the maximum likelihood approach to estimate and test Spatial Process Models is proposed, as well as alternative approaches to Inference in Spatial process models.
Book
Introduction to Statistical Time Series
TL;DR: In this paper, Fourier analysis is used to estimate the mean and autocorrelations of the Fourier spectral properties of a Fourier wavelet and the estimated spectrum of the wavelet.
Journal ArticleDOI
Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data
John C. Driscoll,Aart Kraay +1 more
TL;DR: The authors presented conditions under which a simple extension of common nonparametric covariance matrix estimation techniques yields standard error estimates that are robust to very general forms of spatial and temporal dependence as the time dimension becomes large.
Posted Content
R&D Spillovers and the Geography of Innovation and Production
TL;DR: In this article, the spatial distribution of innovation activity and the geographic concentration of production are examined, using three sources of economic knowledge: industry R&D, skilled labor, and the size of the pool of basic science for a specific industry.