/*Following is the code used for the analysis in "Campaign Effects and the Dyanmics of Turnout Intention in Election 2000"*/
/*Contact Sunshine Hillygus at sunshine_hillygus@harvard.edu with any questions or comments*/


use jopturnout.dta

#delimit ;
logit  vote559 vote1 age female black hispanic partisan interest contact ads persany2  
xv1age xv1fml xv1blk xv1hsp xv1part xv1intst xv1con xv1ads2 xv1pers2  [iweight=weightn];
predict prob;
matrix V = e(V);
#delimit cr

/* Calculate standard errors*/
#delimit cr
lincom vote1 + _cons      /* lag variable               */
lincom age + xv1age 	   /* age 			 */
/*lincom agesqr + xv1age2 	   age-square 			 */
lincom female + xv1fml	   /* female 			 */
lincom black + xv1blk  	   /* black 			 */
lincom hispanic + xv1hsp   /* hispanic 			 */
lincom partisan + xv1part   /* strength of partisanship 	 */
/* lincom attn2 + xv1atn2     attention to campaign 	 */
lincom interest + xv1intst /* interest in politics 	 */
lincom contact + xv1con  /* contacted to participate 	 */
lincom ads + xv1ads2   /* saw any ads 		 */
lincom persany2 + xv1pers2 /* someone talked to	 */


/****************** Calculated Probabilities ************/
/* age mean= 45   */
/* partisan mean= .50  */
/* ads mean= .67*/
/* intrst mean= .57*/
/*contact mean=.215*/
/*persany2 mean =.282*/


/* Test 1: ALL ACTIVITIES, vote1 = 0 */
#delimit ;
scalar zhat1 = _b[_cons]  + _b[age]*45 + 
   	      _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
            _b[partisan]*.50 + 
	      _b[interest]*.57 +
 	      _b[contact]*0 +
	      _b[persany2]*0 +
	      _b[ads]*0;

display zhat1;
	  
scalar zhat2 = _b[_cons]  + _b[age]*45 + 
	       _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
	       _b[partisan]*.50 +
	       _b[interest]*.57 +
 	       _b[contact]*1 +
	       _b[persany2]*1 +
	       _b[ads]*1;	

display zhat2;	
scalar phat1 = exp(zhat1)/(1+exp(zhat1));
scalar phat2 = exp(zhat2)/(1+exp(zhat2));
scalar phatdiff = phat2*(1-phat2) - phat1*(1-phat1); /*C matrix in the delta method*/
display phat1;
display phat2;
display phatdiff;
display phat2-phat1;
matrix C = (0,0,0,0,0,0,0,phatdiff,phatdiff,phatdiff,0,0,0,0,0,0,0,0,0,0);
matrix varcov = C*V*C';
matrix phatse = sqrt(det(varcov));
matrix list phatse;
matrix zstat = (phat2-phat1)*syminv(phatse);
matrix list zstat;


/* Test 2: ALL ACTIVITIES (min-max), vote1 = 1 */
#delimit ;
scalar zhat1 = _b[_cons]  + _b[age]*45 + 
	      _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
            _b[partisan]*.50 + 
	      _b[interest]*.57 +
 	      _b[contact]*0 +
	      _b[persany2]*0 +
	      _b[ads]*0 +
	      _b[vote1] + _b[xv1age]*45 +
	      _b[xv1hsp]*0 + _b[xv1blk]*0 + _b[xv1fml]*0 +
	      _b[xv1part]*.50 +
	      _b[xv1intst]*.57 +
 	      _b[xv1con]*0 +
	      _b[xv1pers2]*0 +
	      _b[xv1ads2]*0;		 		

display zhat1;
	  
scalar zhat2 = _b[_cons]  + _b[age]*45 + 
	       _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
	       _b[partisan]*.50 +
	       _b[interest]*.57 +
 	       _b[contact]*1 +
	       _b[persany2]*1 +
	       _b[ads]*1 +
	       _b[vote1] + _b[xv1age]*45 + 
	       _b[xv1hsp]*0 + _b[xv1blk]*0 + _b[xv1fml]*0 +
	       _b[xv1part]*.50 +
	       _b[xv1intst]*.57 +
 	       _b[xv1con]*1 + 
	       _b[xv1pers2]*1 +
	       _b[xv1ads2]*1;
display zhat2;	
scalar phat1 = exp(zhat1)/(1+exp(zhat1));
scalar phat2 = exp(zhat2)/(1+exp(zhat2));
scalar phatdiff = phat2*(1-phat2) - phat1*(1-phat1); /*C matrix in the delta method*/
display phat1;
display phat2;
display phatdiff;
display phat2-phat1;
matrix C = (0,0,0,0,0,0,0,phatdiff,phatdiff,phatdiff,0,0,0,0,0,0,0,phatdiff,phatdiff,phatdiff);
matrix varcov = C*V*C';
matrix phatse = sqrt(det(varcov));
matrix list phatse;
matrix zstat = (phat2-phat1)*syminv(phatse);
matrix list zstat;


/* Test 3: see ads (min to max, vote1=0) */
#delimit ;
scalar zhat1 = _b[_cons]  + _b[age]*45 + 
             _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
            _b[partisan]*.50 + 
	      _b[interest]*.57 +
 	      _b[contact]*.22 +
	      _b[persany2]*.28 +
	      _b[ads]*0;	
display zhat1;
	  
scalar zhat2 = _b[_cons]  + _b[age]*45 + 
	       _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
	       _b[partisan]*.50 +
	       _b[interest]*.57 +
 	       _b[contact]*.22 +
	       _b[persany2]*.28 +
	       _b[ads]*1;

display zhat2;	
scalar phat1 = exp(zhat1)/(1+exp(zhat1));
scalar phat2 = exp(zhat2)/(1+exp(zhat2));
scalar phatdiff = phat2*(1-phat2) - phat1*(1-phat1); /*C matrix in the delta method*/
display phat1;
display phat2;
display phatdiff;
display phat2-phat1;
matrix C = (0,0,0,0,0,0,0,0,0,phatdiff,0,0,0,0,0,0,0,0,0,0);
matrix varcov = C*V*C';
matrix phatse = sqrt(det(varcov));
matrix list phatse;
matrix zstat = (phat2-phat1)*syminv(phatse);
matrix list zstat;

/* Test 4: Personal Persuasion (min to max, vote1=0) */
#delimit ;
scalar zhat1 = _b[_cons]  + _b[age]*45 + 
             _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
            _b[partisan]*.50 + 
	      _b[interest]*.57 +
 	      _b[contact]*.22 +
	      _b[persany2]*0 +
	      _b[ads]*.67;	
display zhat1;
	  
scalar zhat2 = _b[_cons]  + _b[age]*45 + 
	       _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
	       _b[partisan]*.50 +
	       _b[interest]*.57 +
 	       _b[contact]*.22 +
	       _b[persany2]*1 +
	       _b[ads]*.67;

display zhat2;	
scalar phat1 = exp(zhat1)/(1+exp(zhat1));
scalar phat2 = exp(zhat2)/(1+exp(zhat2));
scalar phatdiff = phat2*(1-phat2) - phat1*(1-phat1); /*C matrix in the delta method*/
display phat1;
display phat2;
display phatdiff;
display phat2-phat1;
matrix C = (0,0,0,0,0,0,0,0,phatdiff,0,0,0,0,0,0,0,0,0,0,0);
matrix varcov = C*V*C';
matrix phatse = sqrt(det(varcov));
matrix list phatse;
matrix zstat = (phat2-phat1)*syminv(phatse);
matrix list zstat;

		 		
/* Test 5: Party Contact (min-max), vote1 = 1 */
#delimit ;
scalar zhat1 = _b[_cons]  + _b[age]*45 + 
	      _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
            _b[partisan]*.50 + 
	      _b[interest]*.57 +
 	      _b[contact]*0 +
	      _b[persany2]*.28 +
	      _b[ads]*.67 +
	      _b[vote1] + _b[xv1age]*45 +
	      _b[xv1hsp]*0 + _b[xv1blk]*0 + _b[xv1fml]*0 +
	      _b[xv1part]*.50 +
	      _b[xv1intst]*.57 +
 	      _b[xv1con]*0 +
	      _b[xv1pers2]*.28 +
	      _b[xv1ads2]*.67;		 		

display zhat1;
	  
scalar zhat2 = _b[_cons]  + _b[age]*45 +
	       _b[hispanic]*0 + _b[black]*0 + _b[female]*0 +
	       _b[partisan]*.50 +
	       _b[interest]*.57 +
 	       _b[contact]*1 +
	       _b[persany2]*.28 +
	       _b[ads]*.67 +
	       _b[vote1] + _b[xv1age]*45 +
	       _b[xv1hsp]*0 + _b[xv1blk]*0 + _b[xv1fml]*0 +
	       _b[xv1part]*.50 +
	       _b[xv1intst]*.57 +
 	       _b[xv1con]*1 + 
	       _b[xv1pers2]*.28 +
	       _b[xv1ads2]*.67;
display zhat2;	
scalar phat1 = exp(zhat1)/(1+exp(zhat1));
scalar phat2 = exp(zhat2)/(1+exp(zhat2));
scalar phatdiff = phat2*(1-phat2) - phat1*(1-phat1); /*C matrix in the delta method*/
display phat1;
display phat2;
display phatdiff;
display phat2-phat1;
matrix C = (0,0,0,0,0,0,0,phatdiff,0,0,0,0,0,0,0,0,0,phatdiff,0,0);
matrix varcov = C*V*C';
matrix phatse = sqrt(det(varcov));
matrix list phatse;
matrix zstat = (phat2-phat1)*syminv(phatse);
matrix list zstat;

/******************** Predicted Values ******************/
#delimit cr
gen yhatT = .
replace yhatT = 1 if prob > 0.5 & prob <= 1
replace yhatT = 0 if prob <= 0.5 
tabulate vote559 yhatT, row