1.excel与MATLAB链接：Excel：选项加载项COM加载项转到没有勾选项 2. MATLAB安装目录中寻找toolboxexlink点击,启用宏 E:MATLABtoolboxexlink然后，Excel中就浮现MATLAB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（注意：选用变量为数值，不涉及各变量）(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4.将elhorst和jplv7两个程序文献夹复制到MATLAB安装目录的toolbox文献夹5.设立途径：6.输入程序，得出成果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=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 ElhorstLMsarsem_panel(results,W,y,xconstant x); % (Robust) LM tests解释每一行分别表达：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），将空间权重矩阵原则化（W=normw(w1)），将名为A（以矩阵形式出目前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，定义一种有N*T行，1列的全1矩阵，该矩阵名为：xconstant，（ones即为全1矩阵）阐明解释变量矩阵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、OLS静态面板编程1、一般面板编程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=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 ElhorstLMsarsem_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(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*results.beta; % including the constant termyme = 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 effectssige=results.sige*(nobs-K)/nobs);logliksfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*results.resid*results.residLMsarsem_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,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 changedprt_reg(results,vnames);tfe=meanty-meantx*results.beta; % including the constant termyme = 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 effectssige=results.sige*(nobs-K)/nobs);logliktfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*results.resid*results.residLMsarsem_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,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 changedprt_reg(results,vnames)en=ones(N,1);et=ones(T,1);intercept=mean(y)-mean(x)*results.beta; sfe=meanny-meannx*results.beta-kron(en,intercept);tfe=meanty-meantx*results.beta-kron(et,intercept);yme = y - mean(y);ent=ones(N*T,1);error=y-kron(tfe,en)-kron(et,sfe)-x*results.beta-kron(ent,intercept);rsqr1 = error*error;rsqr2 = yme*yme;FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared including fixed effectssige=results.sige*(nobs-K)/nobs);loglikstfe=-nobs/2*log(2*pi*sige)-1/(2*sige)*results.resid*results.residLMsarsem_panel(results,W,ywith,xwith); % (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:T t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);endxconstant=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 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:T t1=(t-1)*N+1;t2=t*N; wx(t1:t2,:)=W*x(t1:t2,:);endxconstant=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 estimatesspat_model=0;direct_indirect_effects_estimates(results,W,spat_model);panel_effects_