*	scalar N_clust =	e(N_clust)
	scalar `N' =           	e(N) 

local mc_reps = r(N)

local maxrank = r(N)     

local N_fe = e(N)

local mc_reps = r(N)

local maxrank = r(N)     

local N_re = e(N)

local N_ar1 = e(N)

		ereturn scalar N_clus`c' =  `Gclusvar`c''

local G_fe = e(N_clust)

local N_fe = e(N)

local bs_misreps = e(N_misreps)

local N_ols = e(N) 						

qui log using table2_out.csv , text replace name(t2out)

qui log using table1_out.csv , text replace name(t1out)

quantile p_`type'_res if numstates == `gg' , 
		title(`type' G=`gg') name(g_`type'_`gg' , replace)

graph twoway (scatter p_rad_res p_webb_res if numstates == `gg') 
		(line p_webb_res p_webb_res if numstates == `gg') ,
		title(G=`gg') name(g_sc_`gg' , replace)

graph twoway (line Rademacher t_stat if t_stat >= `lower' & t_stat <= `upper') (line Webb t_stat if t_stat >= `lower' & t_stat <= `upper') , xline(`main_t') ti("CDFs of Bootstrapped t-distributions") 
	note("Note: 6 Clusters.  999 bootstrap replications.  Vertical line at main t-statistic.  Zoomed in near main t-staistic.")

		confirm new var `generate'

	local eigenfix "no"

xtreg `lhs' `rhs'  , pa corr(ar1) vce(conventional) noconstant

xtreg `lhs' `rhs'  , pa corr(ar1) vce(conventional) noconstant

/* Row 2, White robust */
reg `reglhs' `regrhs' , vce(robust) noconstant

/* 
Bonus estimation (not in Table 3): two-way clustering on state and year.
Implemented using ivreg2.  This can be downladed (as of 2014-07-06) from:
http://ideas.repec.org/c/boc/bocode/s425401.html
*/
cgmreg `reglhs' `regrhs' , cluster(statefip) noconstant

/* row 1, default standard error */
reg `reglhs' `regrhs' , noconstant

/* Rows 4 and 5 */
CR23_IK_CSS , betavec(`betavec') lhs(`reglhs') rhs(`regrhs') key_rhs(`regrhs') 
	noconstant(1) main_data("`main_data'")

local command = "reg `reglhs' `regrhs' , vce(ols) noconstant "

	list `by' `generate' if `generate'!=., noobs nodisplay

/* calls program "table3_np_boot", which is defined in t34_programs.do.  That program re-does the "deviations from means" and then 
re-runs the regression, to get the betas and (clustered) standard errors. */
qui bootstrap b=r(mybeta) se=r(myse) , reps(`bsreps') nodots cluster(statefip) idcluster(pseudo_cluster_2) 
	seed(10101) saving(`pairs_bs_out' , double)
	: table3_np_boot , lhs(`lhs') rhs(`rhs') keyrhs(`keyrhs') clusterid(pseudo_cluster_2) `yearonly'

	syntax anything [if] [in] [aweight fweight iweight pweight /], /*
		*/ Cluster(string) [NOEIGenfix *] 

				di "          Because you used the -noeigenfix- option, -cgmreg- must end."

merge 1:m statefip using `maindata' , assert(match) keep(match) nogenerate

merge m:1 statefip subid using `to_be_sampled' , assert(match) keep(match) nogenerate

merge 1:1 _n using `pairs_bs_out' , nogenerate

merge 1:m statefip using "`sourcedata'" , assert(match using) keep(match) nogenerate

merge 1:m pseudo_cluster using `main_data' , assert(match) keep(match) nogenerate

qui merge 1:1 _n using `pairs_bs_out' , nogenerate

noi di " `mc' " _continue

noi di " `mc' " _continue

		    di " -> NOTE: Raw estimated variance matrix was non-positive semi-definite."

	list `by' `generate' if `generate'!=., noobs nodisplay

		    di " -> NOTE: Raw estimated variance matrix was non-positive semi-definite."

graph twoway (line Rademacher t_stat if t_stat >= `lower' & t_stat <= `upper') (line Webb t_stat if t_stat >= `lower' & t_stat <= `upper') , xline(`main_t') ti("CDFs of Bootstrapped t-distributions") 
	note("Note: 6 Clusters.  999 bootstrap replications.  Vertical line at main t-statistic.  Zoomed in near main t-staistic.")

graph twoway (line Rademacher t_stat) (line Webb t_stat) , xline(`main_t') ti("CDFs of Bootstrapped t-distributions") 
	note("Note: 6 Clusters.  999 bootstrap replications.  Vertical line at main t-statistic.")

foreach ns in `num_states_list' {

foreach ns in `num_states_list' {

	di _column(50) "Num clusvars      =    `numcvars'"

di "Num Clusters," _column(25) %6s "`ss'"

di "Num clusters,"			_column(20) %8.0f `G_ar1'

di "Num clusters,"			_column(20) %8.0f `G_fe'

di "Num obs,"		%8.0f `N_ols'

di "Num obs,"		%8.0f `N_re'

local num_bs_reps = 399

local num_mc_reps = 100

local num_mc_reps = `mc_reps_smallG'

local num_mc_reps = `mc_reps_bigG'

gen num_miss = t_pairs_bs == .

*local num_states_list = "6 " ;
local num_states_list = "6 10 20 30 50"

	di _column(50) "Number of obs     =    `n'"

di in gr "Number of records is  "in ye "`N'"

di "Number BS replications," _column(25) %6.0f `bs_reps'

di "Number MC replications," _column(35) %6.0f `mc_reps'

di "Number missed pairs BS - beta," _column(35) %6.0f `bs_missed_b'

di "Table 4 loop.  MC Reps = `mcreps', BS Reps = `bsreps', Number of states sampled = `numstates'"

	local numcols = colsof(`running_sum')

do_the_monte_carlo , sourcedata("`mysourcedata'") savedata("`mcout_`ns''")
		mcreps(`num_mc_reps') bsreps(`num_bs_reps') numstates(`ns')

syntax  , [mcreps(integer 3) bsreps(integer 4) numstates(integer 6) sourcedata(string) savedata(string)]

display_results , results_data(t2_mcout_all) 
	numstates_list("`num_states_list'") sourcedata("`mysourcedata'")

syntax  , [results_data(string) numstates_list(string) sourcedata(string)]

	local numsubs = 2^`numcvars' - 1