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Spatial Econometric Analysis Using GAUSS
7
Kuan-Pin LinPortland State Univerisity
Spatial Autoregressive Model with Autoregressive Disturbances
SARAR(1,1) = SPLAG(1)+SPAR(1)
W y y Xβ ε
W ε ε υ
2
( | , ) 0
( | , ) ( ')
E W
Var W E
υ X
υ X υυ I
min max: 1/ , 1/ 1Stability
Spatial Autoregressive Model with Moving Average Disturbances
SARMA(1,1) = SPLAG(1)+SPMA(1)
W y y Xβ ε
W ε υ υ
2
( | , ) 0
( | , ) ( ')
E W
Var W E
υ X
υ X υυ I
min max: 1/ , 1/ 1Stability
Spatial Autoregressive Model with ARMA Disturbances
SARARMA(1,1,1)= SPLAG(1)+SPAR(1)+SPMA(1)
W y y Xβ εW W ε ε υ υ
2
( | , ) 0
( | , ) ( ')
E W
Var W E
υ X
υ X υυ I
min max: 1/ , , 1/ 1Stability
Model EstimationMaximum Likelihood Estimation
Log-Likelihood Function
22
' '( ; , , ) ln(2 ) ln( )
2 2 2ln ln , ( )
n n J JL W
I W J I W
ε εy X
ε y Xβ
SPLAG(1) + … J
SPAR(1) (I-W)
SPMA(1) (I+W)-1
SPARMA(1,1) (I+W)-1(I-W)
Model EstimationMaximum Likelihood Estimation
Quasi Maximum Likelihood (QML) Estimator
1 12 2
ˆ max arg ( ; , , )
ˆ ˆ ˆ ˆ( ) ( ) ( ) ( )ˆˆ ( )' ' '
L W
L L L LVar
y X
Model EstimationSARAR(1,1)
1( )
, ' '
W W
W W
y y Xβ ε y Zδ I υ
ε ε υ Z y X δ β
2
12
2 1 1
2 1
( | , ) 0
( | , )
( | , ) ( ) '( )
( , ) ( ) ( ) 0
( , ) ( ) 0
E W
Var W
Var W W W
Cov W W W W
Cov W W W
υ X
υ X I
ε X I I
y ε I I
ε υ I
Model EstimationSARAR(1,1): Generalized Method of Moments
Moment Functions (Kelejian and Prucha, 1998, 2009)
ˆˆ ˆˆ
ˆ
ˆ ˆ
W IV estimator
W
W
ε y y Xββ
υ ε ε
υ υ' 2
' ' ' 2
' ' 2
( )
( ) [ ( )] '
( ) [ ( )]
E
E W E W WW
E W E W
υυ I
υυ υυ
υυ υυ
Model EstimationSARAR(1,1): Generalized Method of Moments
Sample moment functions are the same two equations of one parameter as in the spatial error AR(1) model.
The efficient GMM estimator follows exactly the same as the spatial error AR(1) model with the IV estimator of the spatial lag model.
Model EstimationSARAR(1,1)
The Model
Estimate , and simultaneously: QML Estimate , and iteratively: IV/GMM/GLS
IV or 2SLS GMM GLS
( )[( ) ]W I W I W
W
y y Xβ ε y Xβ υ
ε ε υ
ˆ ˆ,
ˆ
ˆ ˆ,
β
β
Crime EquationAnselin (1988) [anselin.10, anselin.11]
SARAR(1) Model(Crime Rate) = + (Family Income) + (Housing Value) + + W (Crime rate) + , = W +
GMM vs. QML Estimator
GMM Parameter
GMMs.e
QML Parameter
QMLs.e
0.45602 0.17491 0.36806 0.14947
-0.1221 0.13571 0.16669 0.17286
-1.0438 0.37611 -1.0259 0.44610
-0.2537 0.08706 -0.28165 0.18534
43.916 10.738 47.784 6.9048
Q/L 2.6706 -182.23
Applications
Geographically Weighted Regression (GWR) Spatial Heterogeneity Spatial Autocorrelation
Limited Dependent Variables Spatial Probit and Spatial Tobit Models Spatial Inference
Spatial Prediction Best Predictors Spatial Model Comparison
References K.P. Bell, N.E. Bockstael, 2000, Applying the Generalized-Moments
Estimation to Spatial Problems Involving Microlevel Daqta, Review of Economic s and Statistics, 82, 72-82.
H. Kelejian, and I. R. Prucha, 2009. Specification and Estimation of Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances. Journal of Econometrics, forthcoming.
Das, D., H. Kelejian, and I.R. Prucha, 2003. Small Sample Properties of Estimators of Spatial Autoregressive Models with Autoregressive Disturbances. Papers in Regional Science, 82, 1-26.
L.F. Lee, 2007. GMM and 2SLS Estimation of Mixed Regressive Spatial Autoregressive Models. Journal of Econometrics, 137, 489-514.