EFFICIENT GMM ESTIMATION OF HIGH ORDER SPATIAL AUTOREGRESSIVE MODELS WITH AUTOREGRESSIVE DISTURBANCES

By Lung-fei Lee, Xiaodong Liu. Econometric Theory, 2009

205 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/67c88ccb225a9816ab4e10fe58e65950cb89617b

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In Economics and Econometrics

Citations in the corpus

Inference on Higher-Order Spatial Autoregressive Models with Increasingly Many Parameters (2015, unknown): “…it is computationally simpler than procedures which may have better statistical properties, such as generalized method of moments (Kelejian and Prucha (1999) and Lee and Liu (2010)), optimal IV (Lee (2003)), Gaussian pseudo maximum likelihood (Lee (2004)), and adaptive estimation (Robinson (2010)).”
Heterogeneous peer effects in education (2014, unknown): “…)]′ /n + √ nσ2 [ (φ̃L − φL)tr ( PKG LM̃GLM ) , 0 ]′ /n + √ nσ2 [ (φ̃S − φS)tr ( PKG LM̃GSM ) , (φ̃L − φL)tr ( PKG SM̃GLM )]′ /n + √ nσ2 [ 0, (φ̃S − φS)tr ( PKG SM̃GSM )]′ /n = Op( √ K/n) = op(1) because M̃−M =M̃[(φ̃L − φL)GLM+(φ̃S − φS)GSM], as a special case of Lemma C.11 in Lee and Liu (2010).”
GMM estimation of social interaction models with centrality (2010, methodology): “We pay special attention to the role of centrality of members in a network on the identication and estimation of interaction e¤ects on outcomes. The network structure in a group is captured by a sociomatrix W . For the case that W is not row-normalized and the indegrees of its nodes are not all equ”
On model specification and parameter space definitions in higher order spatial econometric models (2012, background): “…(1979), Sherrell (1990), Hepple (1995), Bell and Bocksteal (2000), Bordignon et al. (2003), Lacombe (2004), Allers and Elhorst (2005), McMillen et al. (2007), Ward and Gleditsch (2008), Dall'Erba et al. (2008), Elhorst and Fréret (2009), Lee and Liu (2010), and Badinger and Egger (2011).”
On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors (2013, background): “…Das et al. (2003), Kelejian and Prucha (1998, 1999, 2001, 2004, 2007, 2010), Kapoor et al. (2007), Lee (2002, 2003, 2004), LeSage (1997, 2000), Lee and Liu (2010), Lin and Lee (2010), Liu and Lee (2011), Pace and Barry (1997), Pinkse and Slade (1998), Pinkse et al. (2002), and Rey and Boarnet…”
Large sample properties of the matrix exponential spatial specification with an application to FDI (2015, background): “Even though LeSage and Pace (2007) present the maximum likelihood and Bayesian estimators of the MESS, no asymptotic theory has been derived for this specification.”
Estimating a spatial autoregressive model with an endogenous spatial weight matrix (2015, methodology): “…literature: the maximum likelihood estimation (MLE) of Ord (1975) and Lee (2004); the instrumental variable (IV) methods of Anselin (1980) and Kelejian and Prucha (1998, 1999), and the generalized method of moments (GMM) of Lee (2007), Lee and Liu (2010), Lin and Lee (2010), and Liu et al. (2010).”
Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity (2018, background): “An inspection of the quantities K1 and K2 shows that strengthening the assumptions to 7See, e.g., Kelejian and Prucha (1998,1999), Lee and Liu (2010) and Lee and Yu (2014). vecD(At) = vecD(Bt) = 0 for all t and using orthogonally transformed disturbances ensures that K1 = K2 = 0, and thus…”
Linear Spatial Dependence Models for Cross-Section Data (2014, background): “This expression shows that the parameter space in the first quadrant is independent of W1 and W2 and thus identical to both the time-series form and the definition given by Lee and Liu (2010) and Badinger and Egger (2011).”
R&D Networks: Theory, Empirics, and Policy Implications (2019, background): “The best-response quantity in equation (25) then corresponds to a higher-order spatial autoregressive (SAR) model with two spatial lags, At qt and Bqt (Lee & Liu, 2010).”