On the asymptotic distribution of the Moran I test statistic with applications

By Harry H. Kelejian, Ingmar R. Prucha. 2001

649 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d0ac9c51c80dec0bfd1c5fd0c0c89ef35a7cfe61

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In Economics and Econometrics

Citations in the corpus

Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models (2004, background): “For the case {hn} being a bounded sequence, the central limit theorem for linear-quadratic forms in Kelejian and Prucha (2001) is applicable (see, also, Giraitis and Taqqu (1998)).”
Specification and Estimation of Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances (2010, methodology): “Therefore this assumption automatically implies the assumption maintained in Theorem 1 of Kelejian and Prucha (2001) w.r.t. the variance of a linear quadratic form for each of the linear quadratic formsQr,n.”
2SLS and OLS in a spatial autoregressive model with equal spatial weights (2002, background): “A selection of more recent studies which relate to certain theoretical and empirical issues are Case (1991), Boarnet (1994), Anselin et al. (1996), Bollinger and Ihlanfeldt (1997), Pace and Barry (1977), Conley (1999), Lee (1999a,b,c), and Kelejian and Prucha (1998, 1999, 2001).”
A general method for third-order bias and variance corrections on a nonlinear estimator (2015, background): “, Case, 1991), and in this case, Lee (2004a) showed that the QML estimators of λ and β may not be √ n-consistent, but rather √ n/hn-consistent.”
ESTIMATION OF UNIT ROOT SPATIAL DYNAMIC PANEL DATA MODELS (2010, background): “Assumption 7 is originated by Kelejian and Prucha (1998, 2001) and also used in Lee (2004, 2007).”
Instrumental Variable Quantile Estimation of Spatial Autoregressive Models (2007, background): “One is the maximum likelihood (ML) or quasi maximum likelihood (QML) estimator; see, among the others, Ord (1975), Anselin (1988), Smirnov and Anselin (2001), and Lee (2002b, 2004).”
An efficient GMM estimator of spatial autoregressive models (2010, methodology): “The assumption that ϵni have existing moments higher than the fourth is needed in order to apply a central limit theorem due to Kelejian and Prucha (2001).”
Testing Panel Data Regression Models with Spatial Error Correlation (2002, background): “…sample distribution of the LM test statistics derived in this paper are not formally established, but are likely to hold under similar sets of low level assumptions developed in Kelejian and Prucha (2001) for the Moran I test statistic and its close cousins the LM tests for spatial correlation.”
Estimation of simultaneous systems of spatially interrelated cross sectional equations (2004, background): “Kelejian and Prucha (2001a) give general results concerning the distribution of the Moran I test statistic.”