reverse-shooting

Matlab scripts for reverse shooting
Log | Files | Refs | README

panelreg3.m (4430B)

      1 % panelreg.m  function [u,NN,K,stdest,beta,vcv]=
      2 %               panelreg(y,x,Method,yname,xnames,nnames);
      3 %     This is the FUNCTION for the panel regressions.
      4 %     Run the panel regressions in levels including fixed effects: 
      5 %
      6 %     y = a_i +b_i*t + Xbeta + epsilon
      7 %
      8 %     and then we can do some hypothesis testing.
      9 %
     10 %     Method is a 2x1 vector    Method=[FE Time]
     11 %          FE=0   ==> No Fixed Effects
     12 %          FE=1   ==> Fixed Effects
     13 %          FE=2   ==> F.E. and All of the X coefficients vary.
     14 %          FE=3   ==> Between Estimator
     15 %          FE=4   ==> Random Effects--GLS (Theta differenced)
     16 %          Time=0 ==> No time trends
     17 %          Time=1 ==> Single time trend
     18 %          Time=2 ==> Country Specific Time trends (automatically FE)
     19 %
     20 %     Note:  If Method is scalar, Time=0 is assumed.  Also, the between
     21 %     (FE=3) and the GLS (FE=4) assume no time trends...
     22 
     23 
     24 function [u,NN,K,stdest,beta,vcv]=...
     25       panelreg(y,x,Method,yname,xnames,nnames);
     26 
     27 if length(Method)==1; 
     28    Time=0; 
     29 else; 
     30    Time=Method(2); 
     31 end;
     32 FE=Method(1);
     33 
     34 % So now we've got our data and the years, feed this into panlag.
     35 % Take out means (mean0=1) so that we are running the fixed effects
     36 % regression.  Then we have to adjust the degrees of freedom.
     37 %    Notice:  PanShape returns the Balanced Panel only.
     38 
     39 [T0,N0]=size(y); 			% Years x Countries
     40 [Tx,NX]=size(x); 			% Years x Countries*Variables
     41 numv=NX/N0; 				% Number of Variables
     42 X=[];
     43 
     44 % Random Effects:  Greene, p. 490
     45 %     Run the Within and Between regressions and use the output to construct
     46 %     estimates of theta.  Then call Panshape with Theta to
     47 %     theta-difference the data and then run the regression.
     48 
     49 if FE==4; 				% Random Effects/GLS
     50    
     51    % Pooled;
     52    Meth=0; [uP,NP,KP,sigP,bP,vcvP]=panelreg(y,x,Meth,yname,xnames,nnames);
     53    
     54    % Within;
     55    Meth=1; [uW,NW,KW,sigW,bW,vcvW]=panelreg(y,x,Meth,yname,xnames,nnames);
     56    Ftest(uP,uW,KW-KP,NW-KW,'Test H0:  Fixed Effects are not different');
     57       
     58    % Between;
     59    Meth=3; [uB,NB,KB,sigB,bB,vcvB]=panelreg(y,x,Meth,yname,xnames,nnames);
     60 
     61    T=NW/NB;
     62    sig2e=sigW^2;
     63    sig2u=sigB^2-sig2e/T;
     64    fprintf('Estimated Sig2u: %7.4f\n',sig2u);
     65    theta=1-sigW/sqrt(T*sig2u+sig2e);
     66    fprintf('Estimated Theta: %7.4f\n',theta);
     67    fetime=4;
     68 else;
     69    fetime=(FE>0)+(Time==2); 		% Param for panshape 1=demean 2=detrend
     70    theta=[];
     71 end;
     72    
     73 if FE==3; fetime=3; end; 		% Panshape =3 ==> between.
     74 [y keeps]=panshape(y,fetime,theta);
     75 for i=1:numv;
     76    [xx Nx]=panshape(x(:,(i-1)*N0+(1:N0)),fetime,theta);
     77    X=[X xx];
     78    keeps=keeps.*Nx;
     79 end;
     80 NN=sum(keeps);
     81 prevest=0;
     82 
     83 data=packr([y X]);
     84 y=data(:,1);
     85 data(:,1)=[];
     86 NT=length(y);
     87 
     88 disp ' ';
     89 fprintf('Observations Kept in the Sample: %5.0f\n',sum(keeps));
     90 say(nnames(keeps,:));
     91 disp ' ';
     92 fprintf('Eliminated for NaN Reasons:      %5.0f\n',sum(~keeps));
     93 say(nnames(~keeps,:));
     94 disp ' ';
     95 
     96 if FE==0 & Time==0;
     97    rhs=[ones(NT,1) data];
     98    indv=['Constant'; xnames];
     99    tle='Panel Estimation--Pooled Regression';   
    100 elseif FE==3;
    101    rhs=[ones(NT,1) data];
    102    indv=['Constant'; xnames];
    103    tle='Panel Estimation--Between Estimate';   
    104 elseif FE==1 & Time==0;
    105    rhs=data;
    106    indv=xnames;
    107    tle='Panel Estimation--Fixed Effects';   
    108    prevest=NN;
    109 elseif FE==4;
    110    rhs=[ones(NT,1)*(1-theta) data]; 	% Difference the Constant!
    111 %   rhs=[ones(NT,1) data]; 	% Difference the Constant!
    112    y=y/sigW; 		
    113    rhs=rhs/sigW; 			% Corrects VCV
    114    indv=['Constant'; xnames];
    115    tle='Panel Estimation--Random Effects GLS';   
    116    prevest=NN-1;
    117 elseif FE==0 & Time==1;
    118    commont=kron(ones(NN,1),(1:(NT/NN))');
    119    rhs=[ones(NT,1) commont data];
    120    indv=['Constant'; 'Time    '; xnames];
    121    tle='Panel Estimation--No F.E.';
    122 elseif FE==1 & Time==1;
    123    commont=kron(ones(NN,1),(1:(NT/NN))');
    124    rhs=[commont data];
    125    indv=['Time    '; xnames];
    126    tle='Panel Estimation -- F.E./CommonTrend';
    127    prevest=NN;
    128 elseif FE==1 & Time==2;
    129    rhs=data;
    130    indv=xnames;
    131    tle='Panel Estimation -- F.E./CountryTrends';
    132    prevest=2*NN;
    133 else;
    134    disp 'Not Yet Implemented!!!'; break;
    135 end;
    136 if exist('yname')==1; depv=yname; else; depv='Y       '; end;
    137 [u,NN,K,stdest,beta,vcv] =ols(y,rhs,tle,depv,indv,prevest);
    138 if FE==4; 				% Hausman Test, p 495 Greene
    139 %   vcvW
    140 %   vcv
    141    Kp=K-prevest;
    142    Sigma=vcvW-vcv(2:Kp,2:Kp);
    143    bdiff=bW-beta(2:Kp);
    144    W=bdiff'*inv(Sigma)*bdiff; 	
    145    pval=1-chicdf(W,Kp-1);
    146    fprintf('Hausman Test of E(e|X)=0:  W=%6.2f  P-Value=%4.2f\n',[W pval]);
    147    disp ' ';
    148 end;
    149