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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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
y,
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' );
'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' );。