I want to run the attached code, but the result is like below.
last estimates not found
r(301);
I think this error comes from [**4.2 run the state-depentent estimation ] part, but I can't know how I change.
code is from Corporate leverage and monetary policy effectiveness in the euro area - ScienceDirect
=======================
************************************************** *****************
* 27279 observations = 179*154-287
* time: 179 = 18y - 3y (lags/leads) - 1m (growth)
* cross: 154 = 22 (nace) * 7 (EZ countries)
* missing: 287 = 179 (C15DE) + 96 (4y C30PT-33PT) + 12 (1y C33ES)
************************************************** *****************
* 1 HOUSEKEEPING
clear all // clear memory
macro drop _all // drop all macros
cls // clear results window
set more off // do not display the "more" message
set graphics off // do (not) show graphics in STATA
set varabbrev off // do not use abbreviations
set type double
pause off // do (not) pause
adopath ++ PLUS
global path "/home/user/m397400/public/NFCfin_MP/ABC_EER/"
global exper "bas"
* 2 DATA and GLOBALS
capture log close
log using "${path}output/logs/${exper}.log", replace
use "${path}data/data_ABC.dta", clear
global maxhor=2*12
global lags=1*12
global stasample 2001m1
global endsample 2018m12
* 2.1 Time-dimension
gen sample = .
replace sample = 1 if month>=(tm(${stasample})+${lags}+1) & month<=(tm(${endsample})-${maxhor})
* 2.2 Cross-dimension
gen sampleC=1 if country=="AT" | ///
country=="BE" | ///
country=="DE" | ///
country=="ES" | ///
country=="FR" | ///
country=="IT" | ///
country=="PT"
gen sampleN=1 if nace=="C10" | ///
nace=="C11" | ///
nace=="C13" | ///
nace=="C14" | ///
nace=="C15" | ///
nace=="C16" | ///
nace=="C17" | ///
nace=="C18" | ///
nace=="C20" | ///
nace=="C21" | ///
nace=="C22" | ///
nace=="C23" | ///
nace=="C24" | ///
nace=="C25" | ///
nace=="C26" | ///
nace=="C27" | ///
nace=="C28" | ///
nace=="C29" | ///
nace=="C30" | ///
nace=="C31" | ///
nace=="C32" | ///
nace=="C33"
keep if sampleC==1 & sampleN==1 // keep only select countries and sectors
drop sampleC sampleN
* 2.3 Horizon
gen hor = _n-1
replace hor = . if hor>${maxhor} // define horizon (useful for stored results and graphs)
* 3 TRANSFORMATIONS
** 3.1 Shock
gen sho = -kj_shock_mp
sum sho if sample==1
replace sho = sho/r(sd)
** 3.2 LHS variables
tsset crossid month
* indexed log levels
gen yvar = 100*log(volume) // log-level
forvalues j=0/$maxhor {
gen yvarH`j' = F`j'.yvar - L1.yvar
}
* cumulative IRFs
qui gen cum_yvar_temp=0
forvalues j=0/$maxhor {
gen cum_yvarH`j'=yvarH`j'+cum_yvar_temp // cumulative
replace cum_yvar_temp=cum_yvarH`j'
}
drop cum_yvar_temp
** 3.3 RHS variables
* lagged controls
foreach var in yvarH0 sho {
forvalues p=1/$lags {
gen `var'L`p' = L`p'.`var'
}
}
* state-variables
gen stvar_pre = l_wm // leverage
by crossid: ipolate stvar_pre month, gen(stvar_ipo) // 1-year lagged - linear interporlation
gen stvar = L12.stvar_ipo
* intercept
gen ones = 1
* interactions
foreach sdvar of varlist ones sho shoL* yvarH0L* {
gen `sdvar'_0p = `sdvar'
gen `sdvar'_1p = `sdvar'*(stvar^1)
gen `sdvar'_2p = `sdvar'*(stvar^2)
}
* effective list of regressors
unab main: sho_*
unab ctrs: ones_* shoL*_* yvarH0L*_*
*
unab main_drop: sho_0p
unab ctrs_drop: ones_0p shoL*_0p
*
local main_eff: list main - main_drop
local ctrs_eff: list ctrs - ctrs_drop
* 4 REGRESSION
** 4.1 Pre-store beta coefficients
foreach v in beta betau68 betal68 betau90 betal90 {
foreach scen in 1p 2p t a b c d {
gen `v'_`scen' = .
}
}
** 4.2 run the state-dependent estimation
forval i= 0/$maxhor {
local ord=`i'+1 // ord='i'+1 in ivreg2 is equivalent to ord='i' in xtscc (check "help ivreg2")
ivreghdfe cum_yvarH`i' `main_eff' `ctrs_eff' if sample==1, absorb(countryid naceid month) partial(`ctrs_eff') dkraay(`ord') small
capture gen esample = e(sample)
if _rc==0 {
latabstat cum_yvarH0 sho stvar if esample==1, statistics(n mean median sd p1 p99) columns(statistic) format(%9.2f)
}
local df = e(df_r)
di "OBS " e(N) " DF " e(df_r) " PARAMETERS " e(rankxx)+e(partial_ct)+(e(N_clust)-1) // shock + controls and day-FE + intraday-FE
pause
* UNDERLYING PARAMETERS
lincom sho_1p
qui replace beta_1p =r(estimate) if hor==`i'
qui replace betau68_1p =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_1p =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_1p =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_1p =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_2p
qui replace beta_2p =r(estimate) if hor==`i'
qui replace betau68_2p =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_2p =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_2p =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_2p =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
* PEAK EFFECTS
qui replace beta_t = -(1/2)*_b[sho_1p]/_b[sho_2p] if hor==`i'
qui replace beta_t = . if hor==`i' & (beta_t<0 | beta_t>100)
* EXCESS SENSITIVITIES
lincom sho_1p*(55-45)+sho_2p*(55*55-45*45)
qui replace beta_a =r(estimate) if hor==`i'
qui replace betau68_a =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_a =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_a =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_a =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_1p*(65-55)+sho_2p*(65*65-55*55)
qui replace beta_b =r(estimate) if hor==`i'
qui replace betau68_b =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_b =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_b =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_b =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_1p*(75-65)+sho_2p*(75*75-65*65)
qui replace beta_c =r(estimate) if hor==`i'
qui replace betau68_c =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_c =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_c =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_c =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_1p*(85-75)+sho_2p*(85*85-75*75)
qui replace beta_d =r(estimate) if hor==`i'
qui replace betau68_d =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_d =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_d =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_d =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
}
* 5 SAVE RESULTS
save "${path}output/dta/estres_${exper}",replace
log close
==========================================
last estimates not found
r(301);
I think this error comes from [**4.2 run the state-depentent estimation ] part, but I can't know how I change.
code is from Corporate leverage and monetary policy effectiveness in the euro area - ScienceDirect
=======================
************************************************** *****************
* 27279 observations = 179*154-287
* time: 179 = 18y - 3y (lags/leads) - 1m (growth)
* cross: 154 = 22 (nace) * 7 (EZ countries)
* missing: 287 = 179 (C15DE) + 96 (4y C30PT-33PT) + 12 (1y C33ES)
************************************************** *****************
* 1 HOUSEKEEPING
clear all // clear memory
macro drop _all // drop all macros
cls // clear results window
set more off // do not display the "more" message
set graphics off // do (not) show graphics in STATA
set varabbrev off // do not use abbreviations
set type double
pause off // do (not) pause
adopath ++ PLUS
global path "/home/user/m397400/public/NFCfin_MP/ABC_EER/"
global exper "bas"
* 2 DATA and GLOBALS
capture log close
log using "${path}output/logs/${exper}.log", replace
use "${path}data/data_ABC.dta", clear
global maxhor=2*12
global lags=1*12
global stasample 2001m1
global endsample 2018m12
* 2.1 Time-dimension
gen sample = .
replace sample = 1 if month>=(tm(${stasample})+${lags}+1) & month<=(tm(${endsample})-${maxhor})
* 2.2 Cross-dimension
gen sampleC=1 if country=="AT" | ///
country=="BE" | ///
country=="DE" | ///
country=="ES" | ///
country=="FR" | ///
country=="IT" | ///
country=="PT"
gen sampleN=1 if nace=="C10" | ///
nace=="C11" | ///
nace=="C13" | ///
nace=="C14" | ///
nace=="C15" | ///
nace=="C16" | ///
nace=="C17" | ///
nace=="C18" | ///
nace=="C20" | ///
nace=="C21" | ///
nace=="C22" | ///
nace=="C23" | ///
nace=="C24" | ///
nace=="C25" | ///
nace=="C26" | ///
nace=="C27" | ///
nace=="C28" | ///
nace=="C29" | ///
nace=="C30" | ///
nace=="C31" | ///
nace=="C32" | ///
nace=="C33"
keep if sampleC==1 & sampleN==1 // keep only select countries and sectors
drop sampleC sampleN
* 2.3 Horizon
gen hor = _n-1
replace hor = . if hor>${maxhor} // define horizon (useful for stored results and graphs)
* 3 TRANSFORMATIONS
** 3.1 Shock
gen sho = -kj_shock_mp
sum sho if sample==1
replace sho = sho/r(sd)
** 3.2 LHS variables
tsset crossid month
* indexed log levels
gen yvar = 100*log(volume) // log-level
forvalues j=0/$maxhor {
gen yvarH`j' = F`j'.yvar - L1.yvar
}
* cumulative IRFs
qui gen cum_yvar_temp=0
forvalues j=0/$maxhor {
gen cum_yvarH`j'=yvarH`j'+cum_yvar_temp // cumulative
replace cum_yvar_temp=cum_yvarH`j'
}
drop cum_yvar_temp
** 3.3 RHS variables
* lagged controls
foreach var in yvarH0 sho {
forvalues p=1/$lags {
gen `var'L`p' = L`p'.`var'
}
}
* state-variables
gen stvar_pre = l_wm // leverage
by crossid: ipolate stvar_pre month, gen(stvar_ipo) // 1-year lagged - linear interporlation
gen stvar = L12.stvar_ipo
* intercept
gen ones = 1
* interactions
foreach sdvar of varlist ones sho shoL* yvarH0L* {
gen `sdvar'_0p = `sdvar'
gen `sdvar'_1p = `sdvar'*(stvar^1)
gen `sdvar'_2p = `sdvar'*(stvar^2)
}
* effective list of regressors
unab main: sho_*
unab ctrs: ones_* shoL*_* yvarH0L*_*
*
unab main_drop: sho_0p
unab ctrs_drop: ones_0p shoL*_0p
*
local main_eff: list main - main_drop
local ctrs_eff: list ctrs - ctrs_drop
* 4 REGRESSION
** 4.1 Pre-store beta coefficients
foreach v in beta betau68 betal68 betau90 betal90 {
foreach scen in 1p 2p t a b c d {
gen `v'_`scen' = .
}
}
** 4.2 run the state-dependent estimation
forval i= 0/$maxhor {
local ord=`i'+1 // ord='i'+1 in ivreg2 is equivalent to ord='i' in xtscc (check "help ivreg2")
ivreghdfe cum_yvarH`i' `main_eff' `ctrs_eff' if sample==1, absorb(countryid naceid month) partial(`ctrs_eff') dkraay(`ord') small
capture gen esample = e(sample)
if _rc==0 {
latabstat cum_yvarH0 sho stvar if esample==1, statistics(n mean median sd p1 p99) columns(statistic) format(%9.2f)
}
local df = e(df_r)
di "OBS " e(N) " DF " e(df_r) " PARAMETERS " e(rankxx)+e(partial_ct)+(e(N_clust)-1) // shock + controls and day-FE + intraday-FE
pause
* UNDERLYING PARAMETERS
lincom sho_1p
qui replace beta_1p =r(estimate) if hor==`i'
qui replace betau68_1p =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_1p =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_1p =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_1p =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_2p
qui replace beta_2p =r(estimate) if hor==`i'
qui replace betau68_2p =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_2p =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_2p =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_2p =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
* PEAK EFFECTS
qui replace beta_t = -(1/2)*_b[sho_1p]/_b[sho_2p] if hor==`i'
qui replace beta_t = . if hor==`i' & (beta_t<0 | beta_t>100)
* EXCESS SENSITIVITIES
lincom sho_1p*(55-45)+sho_2p*(55*55-45*45)
qui replace beta_a =r(estimate) if hor==`i'
qui replace betau68_a =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_a =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_a =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_a =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_1p*(65-55)+sho_2p*(65*65-55*55)
qui replace beta_b =r(estimate) if hor==`i'
qui replace betau68_b =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_b =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_b =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_b =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_1p*(75-65)+sho_2p*(75*75-65*65)
qui replace beta_c =r(estimate) if hor==`i'
qui replace betau68_c =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_c =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_c =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_c =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
*
lincom sho_1p*(85-75)+sho_2p*(85*85-75*75)
qui replace beta_d =r(estimate) if hor==`i'
qui replace betau68_d =r(estimate)+invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betal68_d =r(estimate)-invt(`df',(100+68)/2/100)*r(se) if hor==`i'
qui replace betau90_d =r(estimate)+invt(`df',(100+90)/2/100)*r(se) if hor==`i'
qui replace betal90_d =r(estimate)-invt(`df',(100+90)/2/100)*r(se) if hor==`i'
}
* 5 SAVE RESULTS
save "${path}output/dta/estres_${exper}",replace
log close
==========================================
