myregress wpi L(1/4).wpi t, lagvar(wpi) nlags(4)

lincom   L.wpi+L2.wpi+L3.wpi+L4.wpi

note popsize: value label popsize defined for this variable

        local lab`v' : variable label `v'

twoway rarea lo hi end, color(gs12) title("Sum of moving lag coefficients, approx. 95% CI") ///
||  tsline sum, legend(off) scheme(s2mono)

label var beta_k "beta(lagged kstock)"

label def ind 1 Kappa 2 Lambda 3 Nu 4 Xi 5 Tau 6 Upsilon 7 Phi 8 Chi 9 Psi

label def ind 1 Kappa 2 Lambda 3 Nu 4 Xi 5 Tau 6 Upsilon 7 Phi 8 Chi 9 Psi

generate largepop = 0

drop smallpop largepop

drop smallpop largepop

label variable largepop "States with > 5 million pop, 1980"

describe pop smallpop largepop popsize urbanized

generate lat2 = .

scalar lb2 = 89

	tabulate anxiety if inrange(iq, lb`i', ub`i') 

histogram medagebrack, discrete frequency ///
lcolor(black) fcolor(gs15) addlabels ///
addlabopts(mlabposition(6)) xtitle(Upper limits of median age) ///
title(Northeast and North Central States: Median Age) 

qui rolling r(mean), window(3) saving(ldinvest, replace): summarize LD.linvest

qui rolling r(mean), window(3) saving(ldinvest, replace): summarize LD.linvest

char make[varname] "mod�le"

	display "Level `i' is `wd'"

mynormal, level(90)

   display "Anxiety level `count': `a'"

display "The defined levels of anxiety are: `anxlevel'"

display "There are `wds' anxiety levels:"

foreach v of varlist lexp gnppc safewater {

ml model lf meanvar (mu1: price = ) (mu2: price = ) /sigma1 /sigma2, ///
   constraints(1)

		regress lwage educ lhours black hisp if year == `y'

	regress lwage educ exper lhours if year == `y'

	avplot lhours, msize(small) nodraw scheme(s2mono) name(avplot`y', replace) 

sysuse lifeexp,clear

histogram medagebrack, discrete frequency ///
lcolor(black) fcolor(gs15) addlabels ///
addlabopts(mlabposition(6)) xtitle(Upper limits of median age) ///
title(Northeast and North Central States: Median Age) 

mvsumm LD.linvest, generate(invrate) stat(mean) window(3) end

label list cenreg

return list

matrix list e(b)

matrix list b 

matrix list Corr

matrix list cov2

	local allbut: list allcty - c

return list

return list

matrix list e(b)

return list

matrix list t2bb

return list

mat list grades, noheader

mat list grades, noheader

use litgov_estsample.dta, clear

estimates table model4 model1 model3 model2, stat(r2_a rmse ll) /// 
b(%7.3g) star label title("Models of sulphur dioxide concentration") 

matrix b0[1,1] = ln(-1*b0[1,1])

	generate double lngdp`c' = log(`c'gdp)

	summarize lngdp`c' 

	summarize lngdp`i' 

ml model d0 mynormal_lf_d0_c1 (a:) (mu: price = weight turn) /lnsigma, ///
maximize nolog diparm(lnsigma, exp label("sigma")) 

twoway rarea lo hi end, color(gs12) title("Sum of moving lag coefficients, approx. 95% CI") ///
||  tsline sum, legend(off) scheme(s2mono)

do loadcty.mata

do loadcty.mata

foreach c of local country {

foreach c of local ctycode {

	foreach y of local yrlist {

foreach c of local country {

foreach a of local anxlevel {

foreach c of local gdplist {

foreach p of local pct {

foreach v of local vars {

foreach c of local colist {

levelsof cty, local(gdplist)

levelsof company, local(colist)

levelsof company, local(colist)

qui levelsof hiord, local(indices)

file write `hh' "& Directors & Directors & & \multicolumn{2}{c}{in Location} \\" _newline