Semiparametric GMM estimation of spatial autoregressive models

By Liangjun Su. 2012

143 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e5229e749dedc32fde79eaae714486b9172e9574

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In Economics and Econometrics

Citations in the corpus

Functional-coefficient spatial autoregressive models with nonparametric spatial weights (2016, methodology): “AssumptionA1(iii) restricts on spatial weights; see, e.g., Lee (2004) and Su (2012), where supz2Sz jg (z)j < 1 is a necessary condition for (Gn) < 1.”
Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models (2017, methodology): “In the spatial autoregression literature, Su (2012) and Zhang (2013) both focus on the case when ρ (zi) = ρ0 over its domain, however, with varying assumptions about x′iβ (zi) (in our notation).”
A general method for third-order bias and variance corrections on a nonlinear estimator (2015, unknown): “…et al. (1993), Besley and Case (1995), Brueckner (1998), Anselin and Bera (1998), Kelejian and Prucha (1998, 1999, 2001), Bell and Bockstael (2000), Bertrand, et al. (2000), Topa (2001), Lee (2002, 2003, 2004a, 2007a,b), Mynbaev and Ullah (2008), Robinson (2010), Su and Jin (2010), Su (2012), etc..”
Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling (2013, background): “Recently, Das (2005), Cai et al. (2006, CDXW hereafter), Lewbel (2007), Cai and Li (2008), Tran and Tsionas (2010), and Su (2012), among others, had considered the semiparametric models with endogenous variables and they suggested a nonparametric/semiparametric generalized method of moments (GMM)…”
A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers (2015, background): “tial lags of the dependent variable and the error term (e.g. Kelejian and Prucha, 2010; Su, 2012; Baltagi and Breeson, 2011), and also the spatial Durbin model (Anselin, 1988; Anselin and Bera, 1998).”