Stata：输出漂亮的LaTeX表格-T222

eststo  clear
eststo: areg empend_normsqi               after##c.frac lnpop lnpercap lnvc chHPI i.yq i.industry [weight=pa]  if ${SAMPLEIF} & age_buckets == 1, absorb(state) cluster(state)

eststo: areg empend_normsqi  lowsectorvc##after##c.frac lnpop lnpercap lnvc chHPI i.yq i.industry [weight=pa]  if ${SAMPLEIF} & age_buckets == 1, absorb(state) cluster(state)
test 1.after#c.frac + 1.lowsectorvc#1.after#c.frac = 0
estadd scalar sum_afterfrac_p = r(p)

eststo: areg empend_normsqi    empconc50##after##c.frac lnpop lnpercap lnvc chHPI i.yq i.industry [weight=pa]  if ${SAMPLEIF} & age_buckets == 1, absorb(state) cluster(state)
test 1.after#c.frac + 1.empconc50#1.after#c.frac = 0
estadd scalar sum_afterfrac_p = r(p)

eststo: areg empend_normsqi      highcap##after##c.frac lnpop lnpercap lnvc chHPI i.yq i.industry [weight=pa]  if ${SAMPLEIF} & age_buckets == 1, absorb(state) cluster(state)
test 1.after#c.frac + 1.highcap#1.after#c.frac = 0
estadd scalar sum_afterfrac_p = r(p)

*------------ 回归结果的输出 ---------------------*
esttab using "${OUTPATH}emp_entrants_industry", ///
nomtitles booktabs replace ///
order(1.after#c.frac ///
	1.lowsectorvc#1.after  1.lowsectorvc#c.f rac 1.lowsectorvc#1.after#c.frac ///
	1.empconc50#1.after  1.empconc50#c.frac 1.empconc50#1.after#c.frac ///
	1.highcap#1.after  1.highcap#c.frac 1.highcap#1.after#c.frac ///
	lnpop lnpercap lnvc chHPI) ///
drop(frac 1.after  1.empconc50 1.lowsectorvc 1.highcap) ///
indicate("Annual state-level controls = lnpop lnpercap lnvc chHPI"   "State FE = _cons" "Quarterly FE = *.yq" "Industry FE = *.industry", labels("\checkmark" "")) ///
stats(N sum_afterfrac_p, labels("Observations" "\$p\$-val: \$\beta_{\text{Aft}\times\text{Frac}} + \beta_{\text{\ldots industry}\times\text{Aft}\times\text{Frac}} = 0 \$")) ///
label nobaselevels interaction("\$\times\$") substitute("=1" "") nonotes se star(* 0.10 ** 0.05 *** 0.01)

* This file will estimate the returns to college education using the "college in the county" instrumental variable
* which instruments for college attendance with whether there is a 2 or 4 year college near the respondent of the NLS.
* You will first need to install estout (ssc install estout), and you will need to pull the card data from my Mixtape
* in the cloud.  

copy "https://file.lianxh.cn/data/card.dta" card.dta, replace
use "card", replace
*---------------- 回归分析 -------------------*
cap n tempvar tempsample
cap n local specname=`specname'+1
reg  lwage  educ  exper black south married   smsa
cap n estadd ysumm
cap n estimates store ols_`specname'

cap n local specname=`specname'+1
reg educ nearc4 exper black south married   smsa
cap n local biv = _b[nearc4]
cap n local seiv = _se[nearc4]
cap n unab ivs: nearc4
cap n local xlist: colnames e(b)
cap n local ivs: list ivs & xlist
cap n test `ivs'
cap n local F_iv=r(F)
cap n local specname=`specname'+1

cap n ivregress 2sls lwage (educ=nearc4) exper black south married   smsa, first
cap n estadd ysumm
cap n estadd scalar biv  = `biv'
cap n estadd scalar seiv = `seiv'
cap n estadd scalar F_iv = `F_iv'
cap n rivtest
n return list
cap n local ar_chi2=r(ar_chi2)
cap n local ar_p=r(ar_p)
cap n estadd scalar ar_chi2 = `ar_chi2'
cap n estadd scalar ar_p = `ar_p'
cap n estimates store tsls_`specname'

*---------------- 输出回归表格 -------------------*
#delimit ;
	cap n estout * using card.tex,
		style(tex) label notype
		cells((b(star fmt(%9.3f))) (se(fmt(%9.3f)par))) 		
		stats(biv seiv F_iv ar_p N ymean ysd, star(biv)
		labels("College in the county" "Robust standard error " "F statistic for IV in first stage" "Anderson-Rubin test" "N" "Mean Dependent Variable" "Std. Dev. Dependent Variable")
			fmt(3 3 3 2 %9.0fc 3 3))
		keep(educ exper black south married smsa) replace noabbrev starlevels(* 0.10 ** 0.05 *** 0.01)
		title(OLS and 2SLS regressions of Log Earnings on Schooling)   
		collabels(none) eqlabels(none) mlabels(none) mgroups(none)
		prehead("\begin{table}[htbp]\centering" "\scriptsize" "\caption{@title}" "\label{2sls_1}" "\begin{center}" "\begin{threeparttable}" "\begin{tabular}{l*{@E}{c}}"
"\toprule"
"\multicolumn{1}{l}{\textbf{Dependent variable}}&"
"\multicolumn{2}{c}{\textbf{Log wage}}\\"
"\multicolumn{1}{c}{}&"
"\multicolumn{1}{c}{OLS}&"
"\multicolumn{1}{c}{2SLS}\\")
		posthead("\midrule")
		prefoot("\\" "\midrule" "\multicolumn{1}{c}{First Stage Instrument}\\")  
		postfoot("\bottomrule" "\end{tabular}" "\begin{tablenotes}" "\tiny" "\item Standard errors in parenthesis. * p$<$0.10, ** p$<$0.05, *** p$<$0.01" "\end{tablenotes}" \end{threeparttable} \end{center} \end{table});
#delimit cr

gen t_entry_norm1 = entry_norm1 * 100
label var t_entry_norm1	"Firm entry rate (\%)"

gen t_frac = frac * 100
label var t_frac	"Frac (\%)"

gen t_chHPI = chHPI * 100
label var t_chHPI	"House price index change (\%)"

eststo clear
eststo: quietly estpost summarize	t_entry_norm1 ///
									t_frac lnpop lnpercap lnvc t_chHPI ///
								if ${SAMPLEIF} & (age_buckets == 1) & (pa > 0), detail

esttab using "${OUTPATH}summstat_bds_sy.tex", replace ///
	cells("mean(fmt(2)) sd(fmt(2)) p50(fmt(2)) p25(fmt(2)) p75(fmt(2))") label booktab nonumber nomtitles
eststo clear

label var responses		"Responses"
label var scams			"Scams"
label var nonscams		"Non-scams"
label var offers		"Offers"


estpost tabstat anyresponse anyscam anynonscam anyoffer [aw = stateweight], statistics(mean) columns(statistics)
matrix anys = e(mean)
matrix colnames anys = responses scams nonscams offers	// Get column in same rows as responses scams nonscams offers
matrix rownames anys = anys

eststo clear
estpost tabstat responses scams nonscams offers [aw = stateweight], statistics(mean sd p25 p50 p75 p95 max count) columns(statistics)

estadd matrix anys

esttab using "${OUTPATH}numberresponsesw.tex", ///
	cells("mean(fmt(a2) label(Mean)) sd(fmt(a2) label(Std.\ Dev.)) p25(fmt(a2) label(25\%)) p50(fmt(a2) label(50\%)) p75(fmt(a2) label(75\%))  p95(fmt(a2) label(95\%)) max(fmt(a2) label(Max.)) anys(fmt(a2) label(Frac.\ $>0$))") ///
	nostar nonumbers nomtitle label booktabs width(38em) replace

global ADCHARS			"highquality price"
label var highquality "Ad.\ quality"

tabout ${ADCHARS} type using ${OUTPATH}adchars.tex, c(freq col) f(0 1) ///
	cl1(2-11) cl2(2-3 4-5 6-7 8-9 10-11) topstr(Advertisement Characteristics\label{tab:adchars}|\textwidth) ///
	replace style(tex) bt font(bold) topf(top.tex) botf(bot.tex)

/**********************************************************************************************
* 主题：使用texdoc输出LaTeX表格的实例
* 创建者：M: M. Bennett
* 创建于：04/02/19
* 目的：dofile生成模拟数据，展示如何使用 texdoc 输出不同的 LaTex 表格
**********************************************************************************************/

*------- 生成模拟数据 -------------*
* Start with an empty dataset
clear

* Set a seed so results are replicable (I'm using Stata 15, just in case)
set seed 123

* Set number of obs
set obs 1000

* Generate an error term u normally distributed
gen u=rnormal(0,100)

* Generate a random treatment variable:
gen treat = runiform(0,1)>0.5
label var treat "Treatment"

* Generate a binary covariate (50% of the population)
gen x1=runiform(0,1)>0.7
label var x1 "High income"

* Generate a continuous covariate
gen x2=rnormal(400,110)
label var x2 "Test score in 4th grade"

* Generate an outcome:
gen y= 100 + 50*x1 + 1*x2 + 20*treat + u
label var y "Test score in 8th grade"

* Generate a simple covariate table (there are different ways to run this, but here's one):
foreach var of varlist x1 x2{
	* Run a regression (using , robust to account for heteroskedasticity)
	reg `var' treat, robust

	* Store whatever you want (in this case, we are going to save the means for each group and the difference)
	global m`var'_0: di %6.3fc _b[_cons]
	global m`var'_1: di %6.3fc _b[_cons] + _b[treat]
	global dif_`var': di %6.3fc _b[treat]

	* Store the label of the variable, because it's easier then to put it in the tables:
	global lbe_`var' : var label `var'

	* Because I also want to know if the difference is significant, I'm going to store the p-value (and the star level)
	qui test treat=0
	global p_`var': di %12.3fc r(p)
	glo star_`var'=cond(${p_`var'}<.01,"***",cond(${p_`var'}<.05,"**",cond(${p_`var'}<.1,"*","")))
}

*----------- 输出描述性统计分析表格 ---------------*
* Now, lets generate our balance table! (heads up, if you haven't set a current directory (cd), it's going to store this table wherever is the default).
* PS: It's not necessary to do this with a loop, but if you have a lot of covariates, might be useful.

texdoc init balance_table.tex, replace force
tex \begin{tabular}{lccc} \toprule \toprule
tex Variable			& 	Control	& Treatment & Difference \\
tex \addlinespace \hline \\
foreach var of varlist x1 x2{
tex ${lbe_`var'} & ${m`var'_0} & ${m`var'_1} & ${dif_`var'}${star_`var'}\\
}
tex \hline \hline
tex \end{tabular}

texdoc close

*------------- 回归分析-------------*
* Let's run a regression now! (with and without controls)

global covs0 "treat"
global covs1 "treat x*"

global lbe_y : var label y
global lbe_treat : var label treat

forvalues spec=0(1)1{

	*Run the regression
	reg y ${covs`spec'}, robust
	*Save some outputs
	scalar N=e(N)
	scalar r2=e(r2)
	global N_`spec'=N
	global r2_`spec': di %6.3fc r2

	*Store the variable of interest
	global b_`spec': di %6.3fc _b[treat]
	global se_`spec': di %6.3fc _se[treat]

	qui test treat=0
	global p_`spec': di %12.3fc r(p)
	glo star_`spec'=cond(${p_`spec'}<.01,"***",cond(${p_`spec'}<.05,"**",cond(${p_`spec'}<.1,"*","")))
}

*----------- 输出回归表格 ---------------*
texdoc init treatment_effect.tex, replace force
tex \begin{tabular}{lcc} \toprule \toprule
tex Variable			& 	${lbe_y}	& ${lbe_y} \\
tex \addlinespace \hline \\
tex ${lbe_treat} & ${b_0}${star_0} & ${b_1}${star_1}\\
tex 			& (${se_0}) & (${se_1})\\ \addlinespace
tex Controls & No & Yes \\
tex Observations & $N_0 & $N_1 \\
tex R-square & $r2_0 & $r2_1 \\
tex \hline \hline
tex \end{tabular}

texdoc close