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This paper studies the spatial autoregressive (SAR) model for cross sectional data when the true spatial e¤ect parameter is near unity. We decompose the data generating process into an unstable compon...
We describe the spreg command, which implements a maximum likelihood estimator and a generalized spatial two-stage least-squares estimator for the parameters of a linear cross-sectional spatial-auto...
Consider an autoregressive model with measurement error: we observe Zi = Xi+εi, where Xi is a stationary solution of the equation Xi = f0(Xi−1)+ξi. The regression function f0 is known up to ...
Spatial autoregressive model $X_{k,\ell}=\alpha X_{k-1,\ell}+\beta X_{k,\ell-1}+\gamma X_{k-1,\ell-1}+\epsilon_{k,\ell}$ is investigated in the unit root case, that is when the parameters are on the b...
Spatial autoregressive model $X_{k,\ell}=\alpha X_{k-1,\ell}+\beta X_{k,\ell-1}+\gamma X_{k-1,\ell-1}+\epsilon_{k,\ell}$ is investigated in the unit root case, that is when the parameters are on the b...

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