MATLAB-空间计量模型详细步骤

I. excel 与 MATLAB 链接:

Excel :

选项一一加载项一一COM 加载项一一转到一一没有勾选项

2. MATLAB^装目录中寻找 toolbox —— exlink ——点击,启

用宏

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然后，ExceI 中就出现MATLAB 工具

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女量数扌臂权重数据

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3. 启动matlab

(1) 点击start MATLAB

(2) senddata to matlab ，并对变量矩阵变量进行命名(注意：选取变量为数值，不包括

各变量)

(data表中数据进行命名)

(空间权重进行命名)

(3) 导入MATLAB中的两个矩阵变量就可以看见El

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4. 将elhorst 和jplv7两个程序文件夹复制到 MATLAB 安装目录的toolbox 文件夹

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6.输入程序，得出结果

?1=30;

N=40;

W=no rjiiv (Wl):

y=A(：j 3)；

[4, 6]);

xcons-t ant=arLe E 1):

心[nobs E]=siz&(x);

T=30;

N=46;

W=n orm(W1);

y=A(:,3);

x=A(:,[4,6]);

xcon sta nt=on es(N*T,1);

[n obs K]=size(x);

results=ols(y,[xc on sta nt x]);

vn ames=strvcat(logcit',' in tercept','logp','logy');

prt_reg(results,v names,1);

sige=results.sige*(( nobs-K)/nobs);

loglikols二-nobs/2*log(2*pi*sige)-1/(2*sige)*results.resid'*results.resid % The (robust)LM tests developed by Elhorst

LMsarsem_pa nel(results,W,y,[xco nsta nt x]); % (Robust) LM

tests

解释

每一行分别表示：该面板数据的时期数为30 （T=30 ）, 该面板数据有30个地区（N=30 ）, 将空间权重矩阵标准化（W=normw（w1）），将名为A （以矩阵形式出现在MATLABA中）的变量的第3列数据定义为被解释变量

将名为A的变量的第4、5、6列数据定义为解释变量矩阵X,

定义一个有N*T行，1列的全1矩阵，该矩阵名为：xconstant，（ones即为全1矩阵）说明解释变量矩阵x的大小：有nobs行，K列。（size为描述矩阵的大小）。

附录：

静态面板空间计量经济学

一、O L S静态面板编程

1、普通面板编程

T=30;

N=46;

W=n ormw（W1）;

y=A(:,3);

x=A(:,[4,6]);

xconstant=ones(N*T,1);

[nobs K]=size(x);

results=ols(y,[xconstant x]);

vnames=strvcat( 'logcit' ,'intercept' ,'logp' ,'logy' );

prt_reg(results,vnames,1);

sige=results.sige*((nobs-K)/nobs); loglikols=-nobs/2*log(2*pi*sige)-

1/(2*sige)*results.resid'*results.resid % The (robust)LM tests developed by Elhorst LMsarsem_panel(results,W,y,[xconstant x]); % (Robust) LM tests

2、空间固定OLS (spatial-fixed effects )

T=30;

N=46;

W=normw(W1);

y=A(:,3);

x=A(:,[4,6]);

xconstant=ones(N*T,1);

[nobs K]=size(x);

model=1;

[ywith,xwith,meanny,meannx,meanty,meantx]=demean(y,x,N,T,model ); results=ols(ywith,xwith);

vnames=strvcat('logcit','logp','logy'); % should be changed if x is changed

prt_reg(results,vnames);

sfe=meanny-meannx*results.beta; % including the constant term yme = y - mean(y);

et=ones(T,1);

error=y-kron(et,sfe)-x*results.beta;

rsqr1 = error'*error;

rsqr2 = yme'*yme;

FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared including fixed effects

sige=results.sige*((nobs-K)/nobs);

logliksfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*results.resid'*results.resid LMsarsem_panel(results,W,ywith,xwith); % (Robust) LM tests

3、时期固定OLS( time-period fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,3);

x=A(:,[4,6]);

xconstant=ones(N*T,1);

[nobs K]=size(x);

model=2;

[ywith,xwith,meanny,meannx,meanty,meantx]=demean(y,x,N,T,model ); results=ols(ywith,xwith);

vnames=strvcat('logcit','logp','logy'); % should be changed if x is

changed

prt_reg(results,vnames);

tfe=meanty-meantx*results.beta; % including the constant term yme = y - mean(y);

en=ones(N,1);

error=y-kron(tfe,en)-x*results.beta;

rsqr1 = error'*error;

rsqr2 = yme'*yme;

FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared including fixed effects

sige=results.sige*((nobs-K)/nobs);

logliktfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*results.resid'*results.resid LMsarsem_panel(results,W,ywith,xwith); % (Robust) LM tests

4、空间与时间双固定模型

T=30;

N=46;

W=n ormw(W1);

y=A(:,3);

x=A(:,[4,6]);

xcon sta nt=on es(N*T,1);

[n obs K]=size(x);

model=3;

[ywith,xwith,mea nn y,mea nn x,mea nty,mea ntx]二demea

n( y,x,N,T,model

);

results=ols(ywith,xwith);

vnames二strvcat('logcit','logp','logy'); % should be changed if x is changed

prt_reg(results,v names)

en=on es(N,1);

et=on es(T,1);

in tercept=mea n(y)-mea n( x)*results.beta;

sfe=mea nn y-mea nn x*results.beta-kro n(en ,i ntercept);

tfe=mea nty-mea ntx*results.beta-kro n(et,i ntercept);

yme = y - mean( y);

en t=o nes(N*T,1);

error=y-kro n(tfe,e n)-kro n( et,sfe)-x*results.beta-kro n(e nt,i ntercept); rsqrl = error'*error;

rsqr2 = yme'*yme;

FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared including fixed effects

sige=results.sige*((nobs-K)/nobs);

loglikstfe=-nobs/2*log(2*pi*sige)- 1/(2*sige)*results.resid'*results.resid LMsarsem_panel(results,W,ywith,xwith); % (Robust) LM tests

、静态面板SAR 模型

1、无固定效应( No fixed effects )

T=30;

N=46;

W=normw(W1);

y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N;

wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0;

info.model=0;

info.fe=0;

results=sar_panel_FE(y,[xconstant x],W,T,info);

vnames=strvcat( 'logcit' , 'intercept' , 'logp' , 'logy' ); prt_spnew(results,vnames,1) % Print out effects estimates spat_model=0; direct_indirect_effects_estimates(results,W,spat_model);

panel_effects_sar(results,vnames,W);

2、空间固定效应( Spatial fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; info.model=1;

info.fe=0;

results=sar_panel_FE(y,x,W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' ); prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=0;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

3、时点固定效应( Time period fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end

xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=2;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sar_panel_FE(y,x,W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' ); prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=0;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

4、双固定效应( Spatial and time period fixed effects ) T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=3;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sar_panel_FE(y,x,W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' ); prt_spnew(results,vnames,1) % Print out effects estimates spat_model=0;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

三、静态面板SDM 模型

1、无固定效应( No fixed effects )

T=30;

N=46;

W=normw(W1);

y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N;

wx(t1:t2,:)=W*x(t1:t2,:);

end

xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0;

info.model=0;

info.fe=0; results=sar_panel_FE(y,[xconstant x wx],W,T,info);

vnames=strvcat( 'logcit' , 'intercept' , 'logp' , 'logy' , 'W*logp' prt_spnew(results,vnames,1)

, 'W*logy' ); % Print out effects estimates spat_model=1;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W);

2、空间固定效应( Spatial fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=1;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sar_panel_FE(y,[x wx],W,T,info);

vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , 'W*logy' ); prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=1;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W);

3、时点固定效应( Time period fixed effects )

T=30;

N=46;

W=norm(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=2;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

% New routines to calculate effects estimates results=sar_panel_FE(y,[x wx],W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , % Print out coefficient estimates prt_spnew(results,vnames,1) % Print out effects estimates

spat_model=1; direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W)

4、双固定效应( Spatial and time period fixed effects

T=30; N=46;

W=normw(W1); y=A(:,[3]); x=A(:,[4,6]); for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:); end

xconstant=ones(N*T,1); [nobs K]=size(x); info.bc=0; info.lflag=0; % required for exact results

info.model=3; info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sar_panel_FE(y,[x wx],W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , prt_spnew(results,vnames,1) % Print out effects estimates

spat_model=1; direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W)

wald test spatial lag

% Wald test for spatial Durbin model against spatial lag model btemp=results.parm; varcov=results.cov; Rafg=zeros(K,2*K+2); for k=1:K Rafg(k,K+k)=1; % R(1,3)=0 and R(2,4)=0;

end Wald_spatial_lag=(Rafg*btemp)'*inv(Rafg*varcov*Rafg')*Rafg*btemp prob_spatial_lag=1-chis_cdf

(Wald_spatial_lag, K)

'W*logy' );

wald test spatial error

% Wald test spatial Durbin model against spatial error model R=zeros(K,1);

for k=1:K

R(k)=btemp(2*K+1)*btemp(k)+btemp(K+k); % k changed in 1,

7/12/2010

% R(1)=btemp(5)*btemp(1)+btemp(3);

% R(2)=btemp(5)*btemp(2)+btemp(4);

end Rafg=zeros(K,2*K+2);

for k=1:K

Rafg(k,k) =btemp(2*K+1); % k changed in 1, 7/12/2010

Rafg(k,K+k) =1;

Rafg(k,2*K+1)=btemp(k);

% Rafg(1,1)=btemp(5);Rafg(1,3)=1;Rafg(1,5)=btemp(1);

% Rafg(2,2)=btemp(5);Rafg(2,4)=1;Rafg(2,5)=btemp(2); end

Wald_spatial_error=R'*inv(Rafg*varcov*Rafg')*R prob_spatial_error=1-chis_cdf (Wald_spatial_error,K)

LR test spatial lag

resultssar=sar_panel_FE(y,x,W,T,info);

LR_spatial_lag=-2*(resultssar.lik-results.lik) prob_spatial_lag=1-chis_cdf (LR_spatial_lag,K)

LR test spatial error

resultssem=sem_panel_FE(y,x,W,T,info);

LR_spatial_error=-2*(resultssem.lik-results.lik) prob_spatial_error=1-chis_cdf (LR_spatial_error,K) 5、空间随机效应与时点固定效应模型

T=30;

N=46;

W=normw(W1);

y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N;

wx(t1:t2,:)=W*x(t1:t2,:);

end

xconstant=ones(N*T,1);

[nobs K]=size(x);

[ywith,xwith,meanny,meannx,meanty,meantx]=demean(y,[x wx],N,T,2); %

2=time dummies

info.model=1;

results=sar_panel_RE(ywith,xwith,W,T,info);

prt_spnew(results,vnames,1)

spat_model=1; direct_indirect_effects_estimates(results,W,spat_model);

panel_effects_sdm(results,vnames,W)

wald test spatial lag

btemp=results.parm(1:2*K+2); varcov=results.cov(1:2*K+2,1:2*K+2);

Rafg=zeros(K,2*K+2);

for k=1:K

Rafg(k,K+k)=1; % R(1,3)=0 and R(2,4)=0; end

Wald_spatial_lag=(Rafg*btemp)'*inv(Rafg*varcov*Rafg')*Rafg*btemp prob_spatial_lag= 1-chis_cdf (Wald_spatial_lag, K)

wald test spatial error

R=zeros(K,1);

for k=1:K

R(k)=btemp(2*K+1)*btemp(k)+btemp(K+k);

% k changed in 1,

7/12/2010

% R(1)=btemp(5)*btemp(1)+btemp(3);

% R(2)=btemp(5)*btemp(2)+btemp(4); end

Rafg=zeros(K,2*K+2);

for k=1:K

Rafg(k,k) =btemp(2*K+1); % k changed in 1, 7/12/2010

Rafg(k,K+k) =1;

Rafg(k,2*K+1)=btemp(k);

% Rafg(1,1)=btemp(5);Rafg(1,3)=1;Rafg(1,5)=btemp(1);

% Rafg(2,2)=btemp(5);Rafg(2,4)=1;Rafg(2,5)=btemp(2); end

Wald_spatial_error=R'*inv(Rafg*varcov*Rafg')*R prob_spatial_error= 1-chis_cdf (Wald_spatial_error,K)

LR test spatial lag

resultssar=sar_panel_RE(ywith,xwith(:,1:K),W,T,info);

LR_spatial_lag=-2*(resultssar.lik-results.lik)

prob_spatial_lag=1-chis_cdf (LR_spatial_lag,K)

LR test spatial error

resultssem=sem_panel_RE(ywith,xwith(:,1:K),W,T,info);

LR_spatial_error=-2*(resultssem.lik-results.lik) prob_spatial_error=1-chis_cdf (LR_spatial_error,K)

四、静态面板SEM 模型

1、无固定效应( No fixed effects )

T=30;

N=46;

W=normw(W1);

y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N;

wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0;

info.model=0;

info.fe=0; results=sem_panel_FE(y,[xconstant x],W,T,info);

vnames=strvcat( 'logcit' , 'intercept' , 'logp' , 'logy' ); prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=0; direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

2、空间固定效应( Spatial fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x); info.lflag=0;

info.model=1;

info.fe=0; results=sem_panel_FE(y,x,W,T,info);

vnames=strvcat( 'logcit' , 'logp' , 'logy' ); prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=0; direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

3、时点固定效应( Time period fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=2;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sem_panel_FE(y,x,W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' ); prt_spnew(results,vnames,1) % Print out effects estimates spat_model=0;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

4、双固定效应( Spatial and time period fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end

xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=3;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sem_panel_FE(y,x,W,T,info); vnames=strvcat( 'logcit' , 'logp' , 'logy' ); prt_spnew(results,vnames,1) % Print out effects estimates spat_model=0;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sar(results,vnames,W);

五、静态面板SDEM 模型

1、无固定效应( No fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x); info.lflag=0;

info.model=0;

info.fe=0; results=sem_panel_FE(y,[xconstant x wx],W,T,info);

vnames=strvcat( 'logcit' , 'intercept' , 'logp' , 'logy' , 'W*logp' prt_spnew(results,vnames,1)

, 'W*logy' ); % Print out effects estimates spat_model=1;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W);

2、空间固定效应( Spatial fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=1;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sem_panel_FE(y,[x wx],W,T,info);

vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , 'W*logy' ); prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=1;

direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W);

3、时点固定效应( Time period fixed effects )

T=30;

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.lflag=0; % required for exact results

info.model=2;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

% New routines to calculate effects estimates results=sem_panel_FE(y,[x wx],W,T,info);

vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , % Print out coefficient estimates

prt_spnew(results,vnames,1)

% Print out effects estimates spat_model=1; direct_indirect_effects_estimates(results,W,spat_model); panel_effects_sdm(results,vnames,W)

4、双固定效应( Spatial and time period fixed effects T=30;

'W*logy' );

N=46;

W=normw(W1); y=A(:,[3]);

x=A(:,[4,6]);

for t=1:T

t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);

end xconstant=ones(N*T,1);

[nobs K]=size(x);

info.bc=0;

info.lflag=0; % required for exact results

info.model=3;

info.fe=0; % Do not print intercept and fixed effects; use info.fe=1

to turn on

results=sem_panel_FE(y,[x wx],W,T,info);

vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' ,

prt_spnew(results,vnames,1)

% Print out effects estimates

spat_model=1;

direct_indirect_effects_estimates(results,W,spat_model);

panel_effects_sdm(results,vnames,W)

'W*logy' );