CONSISTENCY AND EFFICIENCY OF LEAST SQUARES ESTIMATION FOR MIXED REGRESSIVE, SPATIAL AUTOREGRESSIVE MODELS

By Lung-fei Lee. Econometric Theory, 2002

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An efficient GMM estimator of spatial autoregressive models (2010, methodology): “This case has been studied in Lee (2002) for the OLS approach.”
Asymptotic theory for nonparametric regression with spatial data (2011, methodology): “…: Moreover, because Xn i;j=1 ij = 21 0 S 1S 1 0 1; where 1 = 1n is the n 1 vector of 10s, it follows that if S 1 has uniformly bounded column sums (for which a condition is given in Lemma 1 of Lee, 2002), thenXn i;j=1 ij = O(n); so "weak dependence" is implied, and part (i) of Theorem 4 applies.”
Testing Cross-Sectional Correlation in Large Panel Data Models with Serial Correlation (2016, result): “In some cases, it results in inconsistent estimation; see Lee [1] and Andrews [2].”
Efficient estimation of the semiparametric spatial autoregressive model (2006, methodology): “This is the case under (3.1) if ~ is OLS (see Lee, 2002).”
Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models (2010, methodology): “In case for which m0 ( .) is missing from the definition of Un (δ) , Lee (2002b, 2004) proposes maximizing the Gaussian quasi log likelihood logLn (θ) = −n 2 log (2π)− n 2 logσ2 + log |Tn (ρ)|− 1 2σ2 Un (δ) 0 Un (δ) , (2.3) where θ = ¡ β0, ρ, σ2 ¢0 .”
Correlation Testing in Time Series, Spatial and Cross-Sectional Data (2007, background): “2 =d`ndmn = op 0@n nX j=2 max k W 2jkmn=dmn 1A : (4.23) SupposeWjkmn = Op h 1m uniformly (cf. Lee, 2002).”