* Simulates univariate OLS regression ;


#delimit ;            			* set end of line marker to a semicolor;


capture program drop ols1 ;         * if ols1 exists, drop it ;
program define ols1, rclass ;       * create a new command called ols1 ;
   
	drop _all ;                   * clear memory ;
	set obs 100 ;                 * set observations to n=100 ;
 
	gen x = uniform() ;           * draw the regressor from U[0,1] ;
	gen u = invnorm(uniform()) ;  * draw the error from N(0,1) ;
	gen y = 1 + 2*x + u ;         * the DGP ;

	reg y x ;                     * regress y on x ;
	test x=1 ;
	
	return scalar b1  = _b[x];  	* store est. slope in variable "b1" ;
	return scalar b0  = _b[_cons];* store constant in "b0" ;
	return scalar seb1= _se[x] ;  * store std. err. of slope in "seb1" ;
      return scalar p  = r(p) ;   * return model R2 in "r2" ;

   end ;