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Spatial Econometric Analysis Using GAUSS 4 Kuan-Pin Lin Portland State University

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Spatial Econometric Analysis Using GAUSS. 4 Kuan-Pin Lin Portland State University. Spatial Econometric Models. Spatial Exogenous Model Spatial Lag Model Spatial Mixed Model Spatial Error Model Spatial AR(1) Spatial MA(1) Spatial ARMA(1,1) Spatial Error Components Model. - PowerPoint PPT Presentation

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Page 1: Spatial Econometric Analysis Using GAUSS

Spatial Econometric Analysis Using GAUSS

4

Kuan-Pin LinPortland State University

Page 2: Spatial Econometric Analysis Using GAUSS

Spatial Econometric Models

Spatial Exogenous Model Spatial Lag Model Spatial Mixed Model Spatial Error Model

Spatial AR(1) Spatial MA(1) Spatial ARMA(1,1)

Spatial Error Components Model

Page 3: Spatial Econometric Analysis Using GAUSS

Spatial Exogenous ModelLagged Explanatory Variables

The Model

'

1

1,2,...,

n

ij jjw

Wi n

xX

W y Xβ Xγ ε

2

( | , ) 0

( | , ) ( ')

E W

Var W E

ε X

Iε X εε

Page 4: Spatial Econometric Analysis Using GAUSS

Spatial Lag ModelLagged Dependent Variable

The ModelW y y Xβ ε

1

1,2,...,

n

ij jjw y

Wi n

y

2

( | , ) 0

( | , ) ( ')

E W

Var W E

ε X

Iε X εε

1 1

2 1

2 1

( )

( ) ( )

( ) [( ) '( )]

( , ) ( ) 0

W

W W

Var W W

Cov W W W

I y Xβ ε

y I Xβ I ε

y I I

y ε I

Page 5: Spatial Econometric Analysis Using GAUSS

Spatial Mixed Model

The Model

2

( | , ) 0, ( | , ) ( ')

W W

E W Var W E

y y Xβ Xγ ε

Iε X ε X εε

1 1

2 1

2 1

( )

( ) ( ) ( )

( ) [( ) '( )]

( , ) ( ) 0

W W

W W W

Var W W

Cov W W W

I y Xβ Xγ ε

y I Xβ Xγ I ε

y I I

y ε I

Page 6: Spatial Econometric Analysis Using GAUSS

Spatial Error Models

Spatial AR(1) Spatial MA(1) Spatial ARMA(1,1)

W ε ε υ

W ε υ υW W ε ε υ υ

2

( | , ) 0

( | , ) ( ')

E W

Var W E

υ X

υ X υυ I

Page 7: Spatial Econometric Analysis Using GAUSS

Spatial Error Components Model

The Model

W ε ψ υ

2 2

( ) ( ) 0, ( , )

( ') , ( ')

E E Cov

E E

ψ υ ψ υ 0

ψψ I υυ I

2 2

( ) 0

( ) '

E

Var WW

ε

ε I

Page 8: Spatial Econometric Analysis Using GAUSS

Spatial Econometric Models

The General Model

W W y y Xβ Xγ ε

W W ε ε υ υ

2

( | , ) 0

( | , ) ( ')

E W

Var W E

υ X

υ X υυ I

Page 9: Spatial Econometric Analysis Using GAUSS

Spatial Model Specification Tests

Moran Test Moran’s I Test Statistic Asymptotic Theory Bootstrap Method

LM Test and Robust LM Test Spatial Error Model Spatial Lag Model

Page 10: Spatial Econometric Analysis Using GAUSS

Hypothesis Testing

The Basic Model

W or

W

y Xβ ε

ε ε υ

ε υ υ

2

( | , ) 0

( | , )

E

Var

υ X W

υ X W I

0

1 0

: 0 0

: ( )

H or

H not H

2~ (0, )normal iid υ I

Page 11: Spatial Econometric Analysis Using GAUSS

Moran-Based Test Statistics

Moran’s I Index

Can not distinguish between spatial lag or spatial error

2

ˆ ˆ ˆ ˆ' '~ ( ( ), ( ))

ˆ ˆ ˆ'

W WI normal iid E I V I

n ε ε ε ε

ε ε

1( )( ) , ( ' )

trace MWE I where M

n K

I X X X X

' 2 22( ) [( ) ] [ ( )]

( ) ( )( )( 2)

trace MWMW trace MW trace MWV I E I

n K n K

ˆˆ

ˆ ( ' ) '

ε y Xβ

β X X X y

Page 12: Spatial Econometric Analysis Using GAUSS

LM-Based Test Statistics

LM Test Statistic for Spatial Error

Can not distinguish between spatial AR or spatial MA

2'

22

2 '

ˆ ˆˆ

~ (1)

ˆˆ ˆ ˆ ˆ, /

( ' )

W

LM ErrorT

n

T trace WW W W

ε ε

y Xβ ε ε

Page 13: Spatial Econometric Analysis Using GAUSS

LM-Based Test Statistics

LM Test Statistic for Spatial Lag2'

22

' 22

ˆˆ

~ (1)

1ˆ ˆ ˆ( ) ( )

ˆ

W

LM LagnJ

J Wy M Wy Tn

ε y

Page 14: Spatial Econometric Analysis Using GAUSS

LM-Based Test Statistics

Robust LM Test Statistic for Spatial Error

Robust LM Test Statistic for Spatial Lag

2' '

2 2* 2

ˆ ˆ ˆˆ ˆ

~ (1)1

W T WnJ

LM ErrorT

TnJ

ε ε ε y

2' '

2 2* 2

ˆ ˆ ˆˆ ˆ

~ (1)

W W

LM LagnJ T

ε y ε ε

Page 15: Spatial Econometric Analysis Using GAUSS

Hypothesis TestingExample

Crime Equation (anselin.3) (Crime Rate) = + (Family Income) + (Housing Value) +

(numbers in parentheses are p-values of the tests)

Moran-I LM-err LM-lagRobust LM-err

RobustLM-lag Hetero.

Crime Rate

5.6753(0.000)

26.902(0.000)

26.902(0.000)

Family Income

4.6624(0.000)

17.841(0.000)

17.841(0.000)

Housing Value

2.1529(0.031)

3.3727(0.066)

3.3727(0.066)

2.954(0.003)

5.723(0.017)

9.363(0.002)

0.0795(0.778)

3.72(0.054)

1.058(0.589)

Page 16: Spatial Econometric Analysis Using GAUSS

Hypothesis TestingExample

China Output 2006 (china.6) ln(GDP) = + ln(L) + ln(K) +

(numbers in parentheses are p-values of the tests)

Moran-I LM-err LM-lagRobust LM-err

RobustLM-lag Hetero.

ln(GDP) 1.949(0.052)

2.359(0.125)

2.359(0.125)

ln(L) 1.946(0.052)

2.351(0.125)

2.351(0.125)

ln(K) 2.387(0.017)

3.7658(0.052)

3.7658(0.052)

1.534(0.125)

0.972(0.324)

0.005(0.942)

1.094(0.296)

0.127(0.721)

1.719(0.423)

Page 17: Spatial Econometric Analysis Using GAUSS

References L. Anselin, and A. K. Bera, R. J.G.M. Florax, and M. Yoon (1996),

“Simple Diagnostic Tests for Spatial Dependence,” Regional Science and Urban Economics, 26, 77-104.

L. Anselin, and H. Kelejian (1997), “Testing for Spatial Autocorrelation in the Presence of Endogenous Regressors,” International Regional Science Review, 20, 153–182.

L. Anselin, and S. Rey (1991), “Properties of Tests for Spatial Dependence in Linear Regression Models,” Geographical Analysis, 23, 112-131.

H. Kelejian, and I.R. Prucha (2001)., “On the Asymptotic Distribution of Moran I Test Statistic with Applications,” Journal Econometrics, 104, 219-257.