function prt_spreg(results,vnames,fid) % PURPOSE: Prints output using spatial regression results structures %--------------------------------------------------- % USAGE: prt_sp(results,vnames,fid) % Where: results = a structure returned by a spatial panel regression % vnames = an optional vector of variable names % fid = optional file-id for printing results to a file % (defaults to the MATLAB command window) %--------------------------------------------------- % NOTES: e.g. vnames = strvcat('y','const','x1','x2'); % e.g. fid = fopen('ols.out','wr'); % use prt_sp(results,[],fid) to print to a file with no vnames % -------------------------------------------------- % RETURNS: nothing, just prints the spatial panel regression results % -------------------------------------------------- if ~isstruct(results) error('prt_sp requires structure argument'); elseif nargin == 1 nflag = 0; fid = 1; elseif nargin == 2 fid = 1; nflag = 1; elseif nargin == 3 nflag = 0; [vsize junk] = size(vnames); % user may supply a blank argument if vsize > 0 nflag = 1; end; else error('Wrong # of arguments to prt_sp'); end; nvar = results.nvar; nobs = results.nobs; % handling of vnames Vname = 'Variable'; for i=1:nvar tmp = ['variable ',num2str(i)]; Vname = strvcat(Vname,tmp); end; if (nflag == 1) % the user supplied variable names [tst_n nsize] = size(vnames); if tst_n ~= nvar+1 fprintf(fid,'Wrong # of variable names in prt_sp -- check vnames argument \n'); fprintf(fid,'will use generic variable names \n'); nflag = 0; else, Vname = 'Variable'; for i=1:nvar Vname = strvcat(Vname,vnames(i+1,:)); end; end; % end of if-else end; % end of nflag issue fprintf(fid,'\n'); switch results.meth case {'semreg'} fprintf(fid,'Pooled model with spatial error autocorrelation and two regimes, no fixed effects \n'); case {'semregsfe'} fprintf(fid,'Pooled model with spatial error autocorrelation, spatial fixed effects and two regimes\n'); case {'semregtfe'} fprintf(fid,'Pooled model with spatial error autocorrelation, time period fixed effects and two regimes \n'); case {'semregstfe'} fprintf(fid,'Pooled model with spatial error autocorrelation, spatial and time period fixed effects, and two regimes \n'); case {'sarreg'} fprintf(fid,'Pooled model with spatially lagged dependent variable and two regimes, no fixed effects \n'); case {'sarregsfe'} fprintf(fid,'Pooled model with spatially lagged dependent variable, spatial fixed effects and two regimes\n'); case {'sarregtfe'} fprintf(fid,'Pooled model with spatially lagged dependent variable, time period fixed effects and two regimes\n'); case {'sarregstfe'} fprintf(fid,'Pooled model with spatially lagged dependent variable, spatial and time period fixed effects, and two regimes \n'); otherwise error('results structure not known by prt_sp function'); end % switch statement switch results.meth case {'semreg','semregsfe','semregtfe','semregstfe'} % <=================== spatial panel error models % add spatial rho parameter name Vname = strvcat(Vname,'regime 1','regime 2'); if (nflag == 1) fprintf(fid,'Dependent Variable = %16s \n',vnames(1,:)); end; fprintf(fid,'R-squared = %9.4f \n',results.rsqr); fprintf(fid,'Rbar-squared = %9.4f \n',results.rbar); fprintf(fid,'sigma^2 = %9.4f \n',results.sige); fprintf(fid,'log-likelihood = %16.8g \n',results.lik); fprintf(fid,'Nobs,Nvar,TNvar = %6d,%6d,%6d \n',results.nobs,results.nvar,results.tnvar); fprintf(fid,'# iterations = %6d \n',results.iter); fprintf(fid,'min and max rho = %9.4f,%9.4f \n',results.rmin,results.rmax); % print timing information fprintf(fid,'total time in secs = %9.4f \n',results.time); fprintf(fid,'***************************************************************\n'); bout = [results.beta results.rho]; % <=================== end of sem case case {'sarreg','sarregsfe','sarregtfe','sarregstfe'} % <=================== spatial panel autoregressive models % add spatial rho parameter name Vname = strvcat(Vname,'regime 1','regime 2'); if (nflag == 1) fprintf(fid,'Dependent Variable = %16s \n',vnames(1,:)); end; fprintf(fid,'R-squared = %9.4f \n',results.rsqr); fprintf(fid,'Rbar-squared = %9.4f \n',results.rbar); fprintf(fid,'sigma^2 = %9.4f \n',results.sige); fprintf(fid,'Nobs,Nvar,TNvar = %6d,%6d,%6d \n',results.nobs,results.nvar,results.tnvar); fprintf(fid,'log-likelihood = %16.8g \n',results.lik); fprintf(fid,'# of iterations = %6d \n',results.iter); fprintf(fid,'min and max rho = %9.4f,%9.4f \n',results.rmin,results.rmax); % print timing information fprintf(fid,'total time in secs = %9.4f \n',results.time); fprintf(fid,'***************************************************************\n'); bout = [results.beta results.rho]; % <=================== end of sar case otherwise error('results structure not known by prt_sp function'); end; % now print coefficient estimates, t-statistics and probabilities tout = norm_prb(results.tstat); % find asymptotic z (normal) probabilities, function of LeSage tmp = [bout results.tstat tout]; % matrix to be printed % column labels for printing results bstring = 'Coefficient'; tstring = 'Asymptot t-stat'; pstring = 'z-probability'; cnames = strvcat(bstring,tstring,pstring); in.cnames = cnames; in.rnames = Vname; in.fmt = '%16.6f'; in.fid = fid; mprint(tmp,in); %function of LeSage fprintf(fid,'Difference rho1-rho2 and T-value = %9.4f,%9.4f \n',results.dif,results.tdif);