六步学会用MATLAB做空间计量回归详细步骤

1、I.excel 与 MATLAB链接:Excel :选项加载项COM加载项转到没有勾选项COM加载项可用力Lt顷;FoMtReader PDF 匚reator COM Add-inInquire港加(A). “Microsoft Power Wap for Excel Microsoft Power Pivot for Excel Microsoft Power View for Excel2. MATLAB安装目录中寻找 toolboxexlink点击，启y旦动求和S Wt *清除-排和瞒选童隊厳JOTLAB工宜用宏桥CK 口期K小Contents2013/13/28 3:14VATLAB

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7、E9呻屮巾 w m -nm c h b cAft(空间权重进行命名)4 口o Q fl Q Q QQ Q Q Q u- Q n Q fl Q Q Q d Q fl Q 1 fl- 1D n- D Q I 1 Q -D o u D D ODp-Accccn-cct bcccc-crvnp4-(3) 导入MATLAB中的两个矩阵变量就可以看见工作区double46x45 dc>uble主盂爲 1? 3国苣 新建打开肯 輕本 *乐打开变最讎工柞区=世Simuilink库* ill2IB .u>ir-?.uuKh <-i4.将elhorst和jpIv7两个程序文件夹复制到MATLAB

8、安装目录的toolbox 文件夹,_, el horsti如2017/1/M 15：0S文件矣5.设置路径:（?©出inkin Ff更改MATLAB用于壹找I'ik2017/1/15 0:46交件关« E) k MATLAB toolbox p7 Bn4去称B却,jplv7：/駡 12:19曲迅我栽i- local3 017/1/1 9 昭J* SStJ. hezoi7,aa 9z:常ap3M打'1沁止Q2；f. matlab2 CH打打丄i 9 24i. M;4lab prngrrtm3fW?J-?ni4?f>l 7/1/1'=障"

9、b箕机-J. mailabjd2017/114 923丈14央.& $ 地躍:C.)f. rnfcc?O17Z1/14 Q ?5114b帕pc2017/114 3 24U专业（C；）丄 nnft2OL7/bl4 9251 r 丽E：)t- opcZOL7/1/14 925a舸比）-OPT nr20L7/bl4 &25,臥？ m販如fiti* # 1rrr1 卜jplv6.输入程序，得出结果命令行窗口» T=30,N=15;W=noiHw -fWl);y=A(ij 3):x=A(: J 4, 6):xcorvE-t ant=on.es (K*rj 1);& no

10、bs E=size(y);1 r-LJc1 1T=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);results=ols(y,xc on sta nt x);vn ames=strvcat(logcit',' in terce pt','log p','logy');p rt_reg(results,v names,1);sige=results.sige*( nobs-K)/nobs);loglikols=-nobs/2*

11、log(2* pi*sige)-1/(2*sige)*results.resid'*results.resid % The (robust)LM tests develo ped by ElhorstLMsarsem_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=n ormw（w1）),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：xco

12、nstant ， （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: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静态面板空间计量经济学、OLS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);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'

13、,'logp' ,'logy');p rt_reg(results,v names,1);sige=results.sige*( nobs-K)/nobs);loglikols二-nobs/2*log(2* pi*sige)-1/(2*sige)*results.resid'*resu lts.resid % The (robust)LM tests develo ped by ElhorstLMsarsem_pa nel(results,W,y,xco nsta nt x); % (Robust) LM tests2、空间固定 OLS(spatial-

14、fixed effects)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=1;ywith,xwith,mea nny, mea nn x,mea nty,mea ntx二demea n( y,x,N,T,model);results=ols(ywith,xwith);vn ames二strvcat('logcit','log p','logy'); % should be cha nged if x is cha

15、nged p rt_reg(results,v names);sfe=mea nn y-mea nn x*results.beta; % in cludi ng the con sta nt term yme = y - mea n( y);et=on es(T,1);error二y-kro n(et,sfe)-x*results.beta;rsqrl = error'*error;rsqr2 = yme'*yme;FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared in cludi ng fixed effects sige=results.si

16、ge*( (n obs-K)/no bs);logliksfe=-nobs/2*log(2* pi*sige)-1/(2*sige)*results.resid'*resu lts.residLMsarsem_pa nel(results,W,ywith,xwith); % (Robust) LM tests3、时期固定 OLS (time-period fixed effects )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=2;ywith,xwit

17、h,mea nny, mea nn x,mea nty,mea ntx二demea n( y,x,N,model);results=ols(ywith,xwith);vn ames=strvcat('logcit','log p','logy'); % should be cha nged if x is cha nged p rt_reg(results,v names);tfe=mea nty-mea ntx*results.beta; % in cludi ng the con sta nt term yme = y - mea n( y)

18、;en=on es(N,1);error二y-kro n(tfe,e n)-x*results.beta;rsqrl = error'*error;rsqr2 = yme'*yme;FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared in cludi ng fixed effects sige=results.sige*( (n obs-K)/no bs);logliktfe=-no bs/2*log(2* pi*sige)-1/(2*sige)*results.resid'*resu lts.residLMsarsem_pa nel(re

19、sults,W,ywith,xwith); % (Robust) LM tests4、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 nny, mea nn x,mea nty,mea ntx二demea n( y,x,N,T,model);results=ols(ywith,xwith);vn ames=strvcat('logcit','log p','logy&#

20、39;); % should be cha nged if x is cha nged p rt_reg(results,v names) en=on es(N,1);et=on es(T,1);in terce pt二mea n(y)-mea n( x)*results.beta;sfe=mea nn y-mea nn x*results.beta-kro n(en ,i nterce pt);tfe=mea nty-mea ntx*results.beta-kro n(et,i nterce pt);yme = y - mea n( y);en t=o nes(N*T,1);error二y

21、-kro n( tfe,e n)-kro n( et,sfe)-x*results.beta-kro n(en t,i ntercep t);rsqrl = error'*error;rsqr2 = yme'*yme;FE_rsqr2 = 1.0 - rsqr1/rsqr2 % r-squared in cludi ng fixed effectssige=results.sige*( nobs-K)/nobs);loglikstfe=-nobs/2*log(2* pi*sige)-1/(2*sige)*results.resid'*results.residLMsar

22、sem_pa nel(results,W,ywith,xwith); % (Robust) LM tests二、静态面板SAR模型1、无固定效应（No fixed effectsT=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1);nobs K=size(x);in fo.lflag=0;info. model=0;in fo.fe=0;,'logp' , 'logy

23、9;);results=sar_ pan el_FE(y,xc on sta nt x,W,T,i nfo); vnames=strvcat( 'logcit' , 'intercept' prt_spn ew(results,v names,1)% Print out effects estimates sp at_model=0; direct_i ndirect_effects_estimates(results,W,s pat_model); pan el_effects_sar(results,v names,W);2、空间固定效应（Spatial f

24、ixed effectsT=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1); nobs K=size(x);in fo.lflag=0;info. model=1;in fo.fe=0;results=sar_ pan el_FE(y,x,W,T,i nfo);）；vnames=strvcat( 'logcit' , 'logp' , 'logy'

25、prt_spn ew(results,v names,1)% Print out effects estimates sp at_model=0;direct_i ndirect_effects_estimates(results,W,s pat_model);pan el_effects_sar(results,v names,W);3、时点固定效应(Time period fixed effectsT=30;N=46;W=n ormw(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,:);

26、end xcon sta nt=on es(N*T,1); nobs K=size(x);% required for exact resultsin fo.lflag=0;info. model=2;info.fe=0; % Do not print in terce pt and fixed effects; use info. fe=1 to turn on results=sar_ pan el_FE(y,x,W,T,i nfo);vn ames=strvcat('logcit'prt_spn ew(results,v names,1),'logp' ,

27、 'logy');% Print out effects estimatessp at_model=0;direct_i ndirect_effects_estimates(results,W,s pat_model);pan el_effects_sar(results,v names,W);4、双固定效应(Spatial and time period fixed effectsT=30;N=46;W=n ormw(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,:);e

28、ndxcon sta nt=on es(N*T,1);nobs K=size(x);in fo.lflag=0; info. model=3;% required for exact resultsin fo.fe=0;% Do not print in terce pt and fixed effects; use info. fe=1 toturn onresults=sar_ pan el_FE(y,x,W,T,i nfo);vnames=strvcat( 'logcit' , 'logp', 'logy' );prt_spn ew(res

29、ults,v names,1)% Print out effects estimatessp at_model=0;direct_ in direct_effects_estimates(results,W,s pat_model);pan el_effects_sar(results,v names,W);三、静态面板SDM模型1、无固定效应（No fixed effectsT=30;N=46;W=n ormw(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,:);endxcon sta

30、nt=on es(N*T,1); nobs K=size(x);in fo.lflag=0;info. model=0;in fo.fe=0;results=sar_ pan el_FE(y,xc on sta nt x wx,W,T,i nfo);vn ames=strvcat('logcit'prt_spn ew(results,v names,1),'intercept','logp', 'logy' , 'W*logp', 'W*logy');% Print out effects esti

31、matessp at_model=1;direct_i ndirect_effects_estimates(results,W,s pat_model);pan el_effects_sdm(results,v names,W);2、空间固定效应（Spatial fixed effectsT=30;N=46;W=n ormw(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,:);endxcon sta nt=on es(N*T,1); nobs K=size(x);in fo.lflag=0;

32、 info. model=1;% required for exact resultsin fo.fe=0;% Do not print in terce pt and fixed effects; use info. fe=1 toturn onresults=sar_ pan el_FE(y,x wx,W,T,i nfo);vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , 'W*logy' );prt_spn ew(results,v names,1

33、)% Print out effects estimatessp at_model=1;direct_i ndirect_effects_estimates(results,W,s pat_model); pan el_effects_sdm(results,v names,W);3、时点固定效应(Time period fixed effectsT=30;N=46;W=n ormw(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,:);endxcon sta nt=on es(N*T,1);

34、nobs K=size(x);in fo.lflag=0;% required for exact resultsinfo. model=2;in fo.fe=0;% Do not print in terce pt and fixed effects; use info. fe=1 toturn on% New rout ines to calculate effects estimatesresults=sar_ pan el_FE(y,x wx,W,T,i nfo);vnames=strvcat( 'logcit' , 'logp', 'logy&

35、#39; , 'W*logp'，W*logy'% Print out coefficie nt estimates);prt_spn ew(results,v names,1)% Print out effects estimatessp at_model=1;direct_ in direct_effects_estimates(results,W,s pat_model); pan el_effects_sdm(results,v names,W)4、双固定效应(Spatial and time period fixed effectsT=30;N=46;W=n o

36、rmw(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,:);endxcon sta nt=on es(N*T,1);nobs K=size(x);in fo.bc=0;in fo.lflag=0;info. model=3;info.fe=0; % Do not print in terce pt and fixed effects; use info. fe=1 to% required for exact resultsturn onresults=sar_ pan el_FE(y,x

37、wx,W,T,i nfo);vnames=strvcat( 'logcit' , 'logp' , 'logy' , 'W*logp' , 'W*logy');prt_spn ew(results,v names,1)% Print out effects estimatessp at_model=1;direct_ in direct_effects_estimates(results,W,s pat_model);pan el_effects_sdm(results,v names,W)wald test sp

38、 atial lag% Wald test for sp atial Durbin model aga inst sp atial lag model bte mp=results .p arm;varcov=results.cov;Rafg=zeros(K,2*K+2);for k=1:KRafg(k,K+k)=1; end% R(1,3)=0 and R(2,4)=0;Wald_s patial_lag=(Rafg*bte mp )'* in v(Rafg*varcov*Rafg')*Rafg*bte mp pr ob_s patial_lag=1-chis_cdf (Wa

39、ld_s patial_lag, K)wald test sp atial error% Wald test sp atial Durbin model aga inst sp atial error model R=zeros(K,1);for k=1:K% k cha nged in 1, 7/12/2010R(k)=bte mp (2*K+1)*btem p(k)+btem p( K+k);% R(1)=btem p( 5)*btem p(1)+bte mp (3);% R(2)=bte mp (5)*btem p( 2)+bte mp (4); endRafg=zeros(K,2*K+

40、2);for k=1:KRafg(k,k) =bte mp (2*K+1);Rafg(k,K+k) =1;Rafg(k,2*K+1)=btem p(k);% k changed in 1,7/12/2010% Rafg(1,1)=btem p( 5);Rafg(1,3)=1;Rafg(1,5)=btem p(1);% Rafg(2,2)=btem p( 5);Rafg(2,4)=1;Rafg(2,5)=btem p(2); endWald_s patial_error=R'* in v(Rafg*varcov*Rafg')*R p rob_s patial_error=1-ch

41、is_cdf (Wald_s patial_error,K)LR test sp atial lagresultssar=sar_ pan el_FE(y,x,W,T,i nfo);LR_s patial_lag=-2*(resultssar.lik-results.lik) pr ob_s patial_lag=1-chis_cdf (LR_s patial_lag,K)LR test sp atial errorresultssem=sem _pan el_FE(y,x,W,T,i nfo);LR_s patial_error=-2*(resultssem.lik-results.lik)

42、p rob_s patial_error=1-chis_cdf (LR_s patial_error,K)5、空间随机效应与时点固定效应模型T=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1);nobs K=size(x);ywith,xwith,mea nn y,mea nn x,mea nty,mea ntx=demea n(y,x wx,N,T,2);2=time dummies info.

43、 model=1;results=sar_ pan el_RE(ywith,xwith,W,T,i nfo); prt_spn ew(results,v names,1) sp at_model=1;direct_i ndirect_effects_estimates(results,W,s pat_model); pan el_effects_sdm(results,v names,W)wald test sp atial lagbte mp=results. parm(1:2*K+2);varcov=results.cov(1:2*K+2,1:2*K+2);Rafg=zeros(K,2*K

44、+2);for k=1:KRafg(k,K+k)=1; end% R(1,3)=0 and R(2,4)=0;Wald_s patial_lag=(Rafg*bte mp )'* in v(Rafg*varcov*Rafg')*Rafg*bte mp pr ob_s patial_lag= 1-chis_cdf (Wald_s patial_lag, K)wald test sp atial errorR=zeros(K,1);for k=1:K% k Cha nged in 1, 7/12/2010R(k)=bte mp (2*K+1)*btem p(k)+btem p( K

45、+k); % R(1)=btem p( 5)*btem p(1)+bte mp (3); % R(2)=bte mp (5)*btem p( 2)+bte mp (4);endRafg=zeros(K,2*K+2);for k=1:K% k changed in 1,7/12/2010Rafg(k,k) =bte mp (2*K+1);Rafg(k,K+k) =1;Rafg(k,2*K+1)=btem p( k);% Rafg(1,1)=btem p( 5);Rafg(1,3)=1;Rafg(1,5)=bte mp (1);% Rafg(2,2)=btem p( 5);Rafg(2,4)=1;

46、Rafg(2,5)=bte mp (2); endWald_s patial_error=R'* in v(Rafg*varcov*Rafg')*R pr ob_s patial_error= 1-chis_cdf (Wald_s patial_error,K)LR test sp atial lagresultssar=sar_ pan el_RE(ywith,xwith(:,1:K),W,T,i nfo);LR_s patial_lag=-2*(resultssar.lik-results.lik)pr ob_s patial_lag=1-chis_cdf (LR_s pa

47、tial_lag,K)LR test sp atial errorresultssem=sem _pan el_RE(ywith,xwith(:,1:K),W,T,i nfo);LR_s patial_error=-2*(resultssem.lik-results.lik)pr ob_s patial_error=1-chis_cdf (LR_s patial_error,K)四、静态面板SEM模型1、无固定效应（ No fixed effectsT=30;N=46;W=n ormw(W1); y=A(:,3);x=A(:,4,6);for t=1:Tt1=(t-1)*N+1;t2=t*N;

48、wx(t1:t2,:)=W*x(t1:t2,:);end xcon sta nt=on es(N*T,1); nobs K=size(x);in fo.lflag=0;info. model=0;in fo.fe=0;results=sem_ pan el_FE(y,xc on sta nt x,W,T,i nfo);,'logy');vnames=strvcat( 'logcit' , 'intercept', 'logp' prt_spn ew(results,v names,1)% Print out effects est

49、imates sp at_model=0;direct_i ndirect_effects_estimates(results,W,s pat_model); pan el_effects_sar(results,v names,W);2、空间固定效应（Spatial fixed effectsT=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1); nobs K=size(x);in fo.lfl

50、ag=0;info. model=1;in fo.fe=0;results=sem_ pan el_FE(y,x,W,T,i nfo);）；vnames=strvcat('logcit' , 'logp', 'logy' prt_spn ew(results,v names,1)% Print out effects estimates sp at_model=0;directndirect_effects_estimates(results,W,s pat_model); pan el_effects_sar(results,v names,W

51、);3、时点固定效应(Time period fixed effectsT=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1);nobs K=size(x);in fo.lflag=0;% required for exact results info. model=2;in fo.fe=0;% Do not print in terce pt and fixed effects; use info.

52、 fe=1 to turn on results=sem_ pan el_FE(y,x,W,T,i nfo);vnames=strvcat('logcit' , 'logp' , 'logy' );prt_spn ew(results,v names,1)% Print out effects estimates sp at_model=0;direct_i ndirect_effects_estimates(results,W,s pat_model); pan el_effects_sar(results,v names,W);4、双固定效应

53、(Spatial and time period fixed effectsT=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1);nobs K=size(x);in fo.lflag=0;% required for exact resultsinfo. model=3;in fo.fe=0;turn on% Do not print in terce pt and fixed effects;

54、use info. fe=1 to results=sem _pan el_FE(y,x,W,T,i nfo);vnames=strvcat('logcit' , 'logp', 'logy' );prt_spn ew(results,v names,1)% Print out effects estimates sp at_model=0;direct_ in direct_effects_estimates(results,W,s pat_model); pan el_effects_sar(results,v names,W);五、静态面板SDEM模型1、无固定效应（No fixed effectsT=30;N=46;W=n ormw(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 xcon sta nt=on es(N*T,1); nobs K=size(x);in fo.lflag=0;info. model=0;in fo.fe=0;results=sem_ pan el_FE(y,xc on sta nt x