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1、链接点击 , 启用宏注意：选取变量MATLAB安装目录的与 M A T L A BExcel ：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 安装目录中寻找 toolbox exlink E:MATLABtoolboxexlink然后，Excel中就出现MATLA工具（注意 Excel 中的数据：）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 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的两个矩阵变量就可以看见4. 将 elhors
2、t 和 jplv7 两个程序文件夹复制到toolbox 文件夹5. 设置路径：6. 输入程序，得出结果T=30;N=46;W=normw(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=*(nobs-K)/nobs); loglikols=-nobs/2*log(2*pi*sige)-1/(2*sige)
3、*LMtests% The (robust)LM tests developed by Elhorst LMsarsem_panel(results,W,y,xconstant x); %(Robust) 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
4、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、OLS静态面板编程1、普通面板编程T=30;N=46;W=no rmw(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);vnames=strvcat( logcit , intercept , logp , logy ); prt_reg(results,vnames,1);sige=*(nobs-K)/nobs); loglikols=-nobs/2
5、*log(2*pi*sige)-1/(2*sige)* % The (robust)LM tests developed by Elhorst LMsarsem_panel(results,W,y,xconstant x); % (Robust) LM tests2、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
6、(y,x,N,T,model); results=ols(ywith,xwith);vnames=strvcat(logcit,logp,logy); % should be changed if x is changedprt_reg(results,vnames);sfe=meanny-meannx*; % including the constant termyme = y - mean(y);et=ones(T,1);error=y-kron(et,sfe)-x*;rsqr1 = error*error;rsqr2 = yme*yme;FE_rsqr2 = - rsqr1/rsqr2
7、% r-squared including fixed effects sige=*(nobs-K)/nobs);logliksfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*LMsarsem_panel(results,W,ywith,xwith); % (Robust) LM tests3、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,mean
8、ny,meannx,meanty,meantx=demean(y,x,N,T,model); results=ols(ywith,xwith);vnames=strvcat(logcit,logp,logy); % should be changed if x ischangedprt_reg(results,vnames);tfe=meanty-meantx*; % including the constant termyme = y - mean(y);en=ones(N,1);error=y-kron(tfe,en)-x*;rsqr1 = error*error;rsqr2 = yme*
9、yme;FE_rsqr2 = - rsqr1/rsqr2 % r-squared including fixed effects sige=*(nobs-K)/nobs);logliktfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*LMsarsem_panel(results,W,ywith,xwith); % (Robust) LM tests4、空间与时间双固定模型T=30;N=46;W=normw(W1);y=A(:,3);x=A(:,4,6);xconstant=ones(N*T,1);nobs K=size(x);model=3;ywith,xwith,m
10、eanny,meannx,meanty,meantx=demean(y,x,N,T,model); results=ols(ywith,xwith);vnames=strvcat(logcit,logp,logy); % should be changed if x ischangedprt_reg(results,vnames)en=on es(N,1);et=on es(T,1);in tercept二mea n(y)-mea n(x)*;sfe=mea nn y-mea nn x*(e n,i ntercept);tfe=mea nty-mea ntx*(et,i ntercept);y
11、me = y - mean( y);en t=o nes(N*T,1);error二y-kro n( tfe,e n)-kro n(et,sfe)-x*(e nt,i ntercept);rsqrl = error*error;rsqr2 = yme*yme;FE_rsqr2 = - rsqr1/rsqr2 % r-squared in cludi ng fixed effects sige=*( (n obs-K)/no bs);loglikstfe二-nobs/2*log(2*pi*sige)-1/(2*sige)*LMsarsem_pa nel(results,W,ywith,xwith
12、); % (Robust) LM tests二、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:Tt1=(t-1)*N+1;t2=t*N;wx(t1:t2,:)=W*x(t1:t2,:);endxconstant=ones(N*T,1);nobs K=size(x);=0;=0;=0;results=sar_panel_FE(y,xconstant x,W,T,info);vnames=strvcat( logcit , intercept , logp , logy );
13、 prt_spnew(results,vnames,1)% Print out effects estimatesspat_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:Tt1=(t-1)*N+1;t2=t*N;wx(t1:t2,:)=W*x(t1:t2,:);endxconst
14、ant=ones(N*T,1);nobs K=size(x);=0;=1;=0;results=sar_panel_FE(y,x,W,T,info);vnames=strvcat( logcit , logp , logy ); prt_spnew(results,vnames,1)% Print out effects estimatesspat_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
15、fixed effects)T=30;N=46;W=normw(W1);y=A(:,3);x=A(:,4,6);for t=1:Tt1=(t-1)*N+1;t2=t*N;wx(t1:t2,:)=W*x(t1:t2,:);end xconstant=ones(N*T,1);nobs K=size(x);=0; % required for exact results=2;=0; % Do not print intercept and fixed effects; use =1 to turn on results=sar_panel_FE(y,x,W,T,info);vnames=strvcat( l
