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LSunit add-in
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FAVAR add-in
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Add factors
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Generate series by sort
Ok, thank you startz..
Then, if I would like to generate lagged series in every household, what command that should I use?
like: if a household has 5 members, and their age is 1; 2; 3; 4; 5, I would like to make series that contain age(-1), that is NA;1;2;3;4. The household id is an alphanumeric (text) data and i want to do this for more than 15000 household. please help
Then, if I would like to generate lagged series in every household, what command that should I use?
like: if a household has 5 members, and their age is 1; 2; 3; 4; 5, I would like to make series that contain age(-1), that is NA;1;2;3;4. The household id is an alphanumeric (text) data and i want to do this for more than 15000 household. please help
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Converting some stata code to eviews code
Hi,
I'm using IFLS 5 data and want to merging some data. My friend give me these codes to perform it in stata, but i want to perform it in eviews.
Can anyone help me to convert this stata code to eviews programming language?
I'm using IFLS 5 data and want to merging some data. My friend give me these codes to perform it in stata, but i want to perform it in eviews.
Code:
global ifls5 "/Users/GHBS/Documents/IFLS/IFLS 5/household"
global kompilasi "/Users/GHBS/Documents/Work/Asisten Semester 9/Ekonometrika MEP/grup kiri"
**[i]MAIN[/i]
use "$ifls5/bk_ar1.dta", clear
keep hhid14 pid14 ar09 ar10 ar11
rename ar09 age
rename ar10 id_father
rename ar11 id_mother
save "$kompilasi/data_anak.dta", replace
** [i]father's id file[/i]
use "$ifls5/bk_ar1.dta", clear
keep hhid14 pid14 ar09
rename ar09 age_father
rename pid id_father
save "$kompilasi/data_father.dta", replace
** [i]mother's id file[/i]
use "$ifls5/bk_ar1.dta", clear
keep hhid14 pid14 ar09
rename ar09 age_mother
rename pid id_mother
save "$kompilasi/data_mother.dta", replace
** MERGE
use "$kompilasi/data_anak.dta", clear
merge m:1 hhid id_father using "$kompilasi/data_father.dta"
keep if _merge==3
drop _merge
merge m:1 hhid id_mother using "$kompilasi/data_mother.dta"
keep if _merge==3
drop _merge
save "$kompilasi/data_anak_lengkap.dta", replace
Can anyone help me to convert this stata code to eviews programming language?
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scenario command - desc option
Hi
I am having trouble with understanding the DESC option in the SCENARIO command. Running the code:
works fine. However, If you replace the last line with
I get the error message:
How should one use the desc option? When I do this manually in the model object (i.e., change the description of a scenrio) I get the following code in the CAPTURE window:
But this code does not work if I include it in the program.....?
Can you please take a look at it?
Thomas
I am having trouble with understanding the DESC option in the SCENARIO command. Running the code:
Code:
wfcreate u 100
genr x=50+0.03*@trend+2*nrnd
genr log(y)=3*log(x)+nrnd
model _m
_m.append 0*x+log(y)=3*log(x)
_m.scenario(n,a="_1") "scenario 2"
works fine. However, If you replace the last line with
Code:
_m.scenario(n,a="_1",desc="test") "scenario 2"
I get the error message:
How should one use the desc option? When I do this manually in the model object (i.e., change the description of a scenrio) I get the following code in the CAPTURE window:
Code:
_m.scenario(desc="test", usedesc) "scenario 1"
But this code does not work if I include it in the program.....?
Can you please take a look at it?
Thomas
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Generate series by sort
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makegraph - option r
↧
scenario command - desc option
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Kalman filter and NAIRU
Hello!
I am new in using EViews, so I need some help.
I would like to model NAIRU in the European Union countries with unemployment rate. I have quarterly rates from the beginning of 2000 until 2017Q3 for all the 28 EU countries.
I have already modelled NAIRUs with Hodrick-Prescott filter but now I would like to do it with Kalman filter as well.
I have read different posts and EViews user's guide as well but I still think I need some help.
From where should I start and is it enough if I use only unemployment rate? What is the logic behind state and signal equations? How should I write them down in EViews in order to model NAIRU with unemployment rate?
Also, one option for writing signal equation for modelling NAIRU would be that NAIRU is dependent on the previous value. But I have no clue how to make this state-space model with quarterly unemployment rate and if this information is enough for NAIRU.
I hope You can help me at least a little bit![:)]( "Smile")
I am new in using EViews, so I need some help.
I would like to model NAIRU in the European Union countries with unemployment rate. I have quarterly rates from the beginning of 2000 until 2017Q3 for all the 28 EU countries.
I have already modelled NAIRUs with Hodrick-Prescott filter but now I would like to do it with Kalman filter as well.
I have read different posts and EViews user's guide as well but I still think I need some help.
From where should I start and is it enough if I use only unemployment rate? What is the logic behind state and signal equations? How should I write them down in EViews in order to model NAIRU with unemployment rate?
Also, one option for writing signal equation for modelling NAIRU would be that NAIRU is dependent on the previous value. But I have no clue how to make this state-space model with quarterly unemployment rate and if this information is enough for NAIRU.
I hope You can help me at least a little bit
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Clustered Standard Errors
Thank you for the reply.
That is indeed what I want, but when I attempted the estimation I noticed there are no options for it in panel data (dated panel, more specifically; if i use unstructured data, the options are there).
Is there any reason why the options aren't available for panel data when even the example the manual uses is based on it? Is there any difference/problem in using unstructured/undated data in my analysis so I can perform said clustering?
Thank you again!
P.S.: Attached go the estimation options I get for dated panel.
That is indeed what I want, but when I attempted the estimation I noticed there are no options for it in panel data (dated panel, more specifically; if i use unstructured data, the options are there).
Is there any reason why the options aren't available for panel data when even the example the manual uses is based on it? Is there any difference/problem in using unstructured/undated data in my analysis so I can perform said clustering?
Thank you again!
P.S.: Attached go the estimation options I get for dated panel.
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Clustered Standard Errors
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Loop for find a minimun
Hi, I have something like this. I want to create the series hdebt and ldebt outside program, but instead the value is fixed in 60 I want to vary from 10 to 100 and I want the program to find which number between 10 and 100 could minimize the SSR done by :
scalar ssrt_debt=sum_ssr_ldebt+sum_ssr_hdebt
I was trying to do it like this but it doesn't work, I do not know how make the program to give results to hdebt_10 and ldebt_10, hdebt_20 and ldebt_20, etc:
'for !x=10 to 100
'smpl if debt>!x
'series hdebt_!x=1
'smpl if debt 'series ldebt_!x=1
'next
****THIS IS A PART OF THE PROGRAM (NOT COMPLETED)****
smpl if debt>60
series hdebt=1
smpl if debt<60
series ldebt=1
.
.
.
string grps = "h dev fixed flex open closed hdebt ldebt"
.
for %grp {grps} ' country/observation groupings
.
'running VAR and impulse responses
%%%%%%%%%%%%%%%%%%%%%%%%%%
smpl @first 2007q4 if {%grp}=1 and {%grp}(-!lags)=1
'Choosing lag length optimally
%%%%%%%%%%%%%%
if %lag_crit = "wald" then
var var_{%grp}.ls(noconst) 1 !maxlags {varlist}
var_{%grp}.testlags(name=waldlags_{%grp})
!flag=1
!count = !maxlags+1
while !flag
!count = !count-1
if @chisq(waldlags_{%grp}(!count,!vars+1),!vars^2) < 0.05 or !count=2 then
!lags = !count
!flag=0
endif
wend
delete waldlags_{%grp}
endif
if %lag_crit<>"none" and %lag_crit<>"wald" then
var var_{%grp}.ls(noconst) 1 !maxlags {varlist}
var_{%grp}.laglen(!maxlags, vname=lagtests_{%grp})
if %lag_crit = "lr" then
!lags = lagtests_{%grp}(1)
endif
if %lag_crit = "aic" then
!lags = lagtests_{%grp}(3)
endif
if %lag_crit = "sc" then
!lags = lagtests_{%grp}(4)
endif
if %lag_crit = "hq" then
!lags = lagtests_{%grp}(5)
endif
delete lagtests_{%grp}
endif
scalar lags_{%grp}_{%type}_{%lagcrit} = !lags
var var_{%grp}.ls(noconst) 1 !lags {varlist}
var_{%grp}.impulse(!imp_len, m, se=a, imp=chol, matbys=imp_{%grp}) {varlist} @ {gvar}
var_{%grp}.impulse(!imp_len, m, a, se=a, imp=chol, matbys=imp_{%grp}_a) {varlist} @ {gvar}
var_{%grp}.makeresids {residlist}
sym resid_cov_actual = var_{%grp}.@residcov
matrix resid_cov_act = var_{%grp}.@residcov
for %c {%grp}
for !j = 1 to var_{%c}.@neqn
vector(!j) ssr_{%c}(!j)= var_{%c}.@ssr(!j)
vector sum_ssr_{%c}=@sum(ssr_{%c})
next
next
close var_{%grp}
scalar ssrt_debt=sum_ssr_ldebt+sum_ssr_hdebt
Thank you very much!
scalar ssrt_debt=sum_ssr_ldebt+sum_ssr_hdebt
I was trying to do it like this but it doesn't work, I do not know how make the program to give results to hdebt_10 and ldebt_10, hdebt_20 and ldebt_20, etc:
'for !x=10 to 100
'smpl if debt>!x
'series hdebt_!x=1
'smpl if debt 'series ldebt_!x=1
'next
****THIS IS A PART OF THE PROGRAM (NOT COMPLETED)****
smpl if debt>60
series hdebt=1
smpl if debt<60
series ldebt=1
.
.
.
string grps = "h dev fixed flex open closed hdebt ldebt"
.
for %grp {grps} ' country/observation groupings
.
'running VAR and impulse responses
%%%%%%%%%%%%%%%%%%%%%%%%%%
smpl @first 2007q4 if {%grp}=1 and {%grp}(-!lags)=1
'Choosing lag length optimally
%%%%%%%%%%%%%%
if %lag_crit = "wald" then
var var_{%grp}.ls(noconst) 1 !maxlags {varlist}
var_{%grp}.testlags(name=waldlags_{%grp})
!flag=1
!count = !maxlags+1
while !flag
!count = !count-1
if @chisq(waldlags_{%grp}(!count,!vars+1),!vars^2) < 0.05 or !count=2 then
!lags = !count
!flag=0
endif
wend
delete waldlags_{%grp}
endif
if %lag_crit<>"none" and %lag_crit<>"wald" then
var var_{%grp}.ls(noconst) 1 !maxlags {varlist}
var_{%grp}.laglen(!maxlags, vname=lagtests_{%grp})
if %lag_crit = "lr" then
!lags = lagtests_{%grp}(1)
endif
if %lag_crit = "aic" then
!lags = lagtests_{%grp}(3)
endif
if %lag_crit = "sc" then
!lags = lagtests_{%grp}(4)
endif
if %lag_crit = "hq" then
!lags = lagtests_{%grp}(5)
endif
delete lagtests_{%grp}
endif
scalar lags_{%grp}_{%type}_{%lagcrit} = !lags
var var_{%grp}.ls(noconst) 1 !lags {varlist}
var_{%grp}.impulse(!imp_len, m, se=a, imp=chol, matbys=imp_{%grp}) {varlist} @ {gvar}
var_{%grp}.impulse(!imp_len, m, a, se=a, imp=chol, matbys=imp_{%grp}_a) {varlist} @ {gvar}
var_{%grp}.makeresids {residlist}
sym resid_cov_actual = var_{%grp}.@residcov
matrix resid_cov_act = var_{%grp}.@residcov
for %c {%grp}
for !j = 1 to var_{%c}.@neqn
vector(!j) ssr_{%c}(!j)= var_{%c}.@ssr(!j)
vector sum_ssr_{%c}=@sum(ssr_{%c})
next
next
close var_{%grp}
scalar ssrt_debt=sum_ssr_ldebt+sum_ssr_hdebt
Thank you very much!
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Clustered Standard Errors
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Clustered Standard Errors
The panel estimators have built-in tools which allow for clustering by cross-section or by period, but not by both. So you can cluster by firm, and you can cluster by year, but not by firm-year.
The non-panel estimators were recently updated to allow for arbitrary clustering.
I am pretty sure that there is a way to compute what you want, but I'm not entirely clear at to the structure of your data. Are there multiple observations for each firm-year combination? If you can tell me a bit more about your data, I can offer some suggestions on how to proceed.
The non-panel estimators were recently updated to allow for arbitrary clustering.
I am pretty sure that there is a way to compute what you want, but I'm not entirely clear at to the structure of your data. Are there multiple observations for each firm-year combination? If you can tell me a bit more about your data, I can offer some suggestions on how to proceed.
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Loop for find a minimun
↧
Loop for find a minimun
But how I can report for example the vector sum_ssr_hdebt_10, sum_ssr_hdebt_20? I can't see them. Where I have to use !x? when I define the group string grps= "h dev fixed felx open closed hdebt_!x ldebt_!x"
like this?
for !x = 10 to 100 step 10
series hdebt_!x = debt > !x
series ldebt_!x = debt < !x
next
string grps = "h dev fixed flex open closed hdebt_!x ldebt!x"
for %grp {grps} ' country/observation groupings
for %c {%grp}
for !j = 1 to var_{%c}.@neqn
vector(!j) ssr_{%c}(!j)= var_{%c}.@ssr(!j)
vector sum_ssr_{%c}=@sum(ssr_{%c})
next
next
like this?
for !x = 10 to 100 step 10
series hdebt_!x = debt > !x
series ldebt_!x = debt < !x
next
string grps = "h dev fixed flex open closed hdebt_!x ldebt!x"
for %grp {grps} ' country/observation groupings
for %c {%grp}
for !j = 1 to var_{%c}.@neqn
vector(!j) ssr_{%c}(!j)= var_{%c}.@ssr(!j)
vector sum_ssr_{%c}=@sum(ssr_{%c})
next
next
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ARDL Modeling in Eviews
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GARCH(1,1) Forecast Series
Hello everyone! I am currently trying to make an out of sample forecast using 10 years of daily data. I have divided my entire sample in two sub-samples the first ranging from the 27th of march 2008 and ending on the 29th of December 2017 and the second one from the 29th of december 2017 to the 27th of March 2018. The latter sample is the one that I am trying to forecast to then compare to the actual forecasted values. I have fitted and AR(1) EGARCH (1,1,1) model in my first sample. However, when I hit the forecast button and I click on my forecasted period for the mean, I get the same value for the entire forecasted period. That doesn't seem right to me. Moreover, when I try to manually calculate the way those numbers have been produced in eviews I get a completely different result. Any ideas regarding what I might be doing wrong?
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GARCH(1,1) Forecast Series
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