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Alternative GMM estimators for spatial regression models

Breitung, Jörg; Wigger, Christoph - In: Spatial economic analysis : the journal of the Regional … 13 (2018) 2, pp. 148-170

Persistent link: https://www.econbiz.de/10011870482

A Robust Lagrange-Multiplier Test for Spatial Autoregression Versus (Unobserved) Spatially Correlated Shocks

Franzese, Robert J.; Hays, Jude C. - 2013

One of the central challenges to inference in the context of potentially interdependent observations, known as Galton's Problem, is the difficulty distinguishing spatially correlated observations due to observed units exposure to spatially correlated shocks from spatial correlation in outcomes...

Persistent link: https://www.econbiz.de/10014160453

Employment Densities, Spatial Autocorrelation, and Subcenters in Large Metropolitan Areas

McMillen, Daniel P. - 2004

. Lagrange Multiplier (LM) tests imply significant spatial autocorrelation under highly restrictive ordinary least squares (OLS … methods. The results serve as a warning that functional form misspecification causes spatial autocorrelation …

Persistent link: https://www.econbiz.de/10014071024

Estimation of Spatial Autoregressive Models for Origin-Destination Flows : A Partial Likelihood Approach

JEONG, HANBAT; Lee, Lung-Fei; Lin, Yanli - 2022

We extend LeSage and Pace's (2008) spatial autoregressive model for origin-destination flows by accommodating two-way fixed effects. Those fixed effects represent unobserved characteristics of origin and destination units. A partial likelihood approach is used to remove fixed effects in the...

Persistent link: https://www.econbiz.de/10013294293

Estimation of spatial autoregressive models for origin-destination flows : a partial likelihood approach

Jeong, Hanbat; Lin, Yanli; Lee, Lung-fei - In: Economics letters 229 (2023), pp. 1-4

Persistent link: https://www.econbiz.de/10014456221

Estimating spatial autoregressions under heteroskedasticity without searching for instruments

Bao, Yong - In: Regional science and urban economics 106 (2024), pp. 1-16

Persistent link: https://www.econbiz.de/10015070916

Measurement errors in a spatial context

Le Gallo, Julie; Fingleton, Bernard - In: Regional science & urban economics 42 (2012) 1/2, pp. 114-125

Persistent link: https://www.econbiz.de/10009621220

Estimating spatial autocorrelation with sampled network data

Zhou, Jing; Tu, Yundong; Chen, Yuxin; Wang, Hansheng - In: Journal of business & economic statistics : JBES ; a … 35 (2017) 1, pp. 130-138

Persistent link: https://www.econbiz.de/10011704139

Spatial simultaneous autoregressive models for compositional data : application to land use

Thomas-Agnan, Christine; Laurent, Thibault; Ruiz-Gazen, Anne - 2020

Persistent link: https://www.econbiz.de/10012216052

Estimating Spatial Autocorrelation with Sampled Network Data

Zhou, Jing - 2016

Spatial autocorrelation is a parameter of importance for network data analysis. To estimate spatial autocorrelation … to rely on sampled network data to infer about spatial autocorrelation. By doing so, network relationships (i.e., edges …) involving unsampled nodes are overlooked. This leads to distorted network structure and underestimated spatial autocorrelation …

Persistent link: https://www.econbiz.de/10012998126