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A Spatial Durbin Model for Compositional Data

2021
A compositional linear model (regression of a scalar response on a set of compositions) for areal data is proposed, where observations are not independent and present spatial autocorrelation. Specifically, we borrow thoughts from the spatial Durbin model considering that it produces unbiased coefficient estimates compared to other spatial linear ...
Huang, Tingting   +2 more
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Identification of Spatial Durbin Panel Models

Journal of Applied Econometrics, 2015
SummaryThis paper considers identification of spatial Durbin dynamic panel models under 2SLS and ML estimations. We show that the parameters are generally identified via 2SLS moment relations or expected log‐likelihood or quasi‐likelihood functions. Monte Carlo experiments suggest that omitting relevant Durbin terms can result in significant biases in ...
Lung‐fei Lee, Jihai Yu
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Technology spillover and TFP growth: A spatial Durbin model

International Economics, 2016
Beginning with a model in which technological progress is reflected by product variety, we provide a structural approach to estimate technology spillovers allowing for spatial interdependencies. To this end, we first present a theoretical model of TFP growth by decomposing TFP into quality and variety components.
Legros, Diego   +2 more
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Bayesian estimation and model selection of threshold spatial Durbin model

Economics Letters, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhu, Yanli, Han, Xiaoyi, Chen, Ying
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Simultaneous outlier detection and variable selection for spatial Durbin model

Brazilian Journal of Probability and Statistics, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cheng, Yi, Song, Yunquan
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A deeper look at impacts in spatial Durbin model with sphet

Geographical Analysis, 2022
This article focuses on the estimation of the spatial Durbin model and associated relative impacts implemented in the R library sphet. Specifically, the current version of the library offers two ways of performing inference: one based on drawing samples from a multivariate normal distribution, and the other based on an analytical formula.
Piras G, Postiglione P
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