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DISPLAY '*******************************************************'
DISPLAY "Asymmetric ERPT in EA"
DISPLAY '*******************************************************'
CALENDAR 1975 1 4
ALLOCATE 2010:4
OPEN DATA
DATA(FORMAT=XLS,ORG=COLS)
PRINT /
*******************************************************'
SET lipc_1 = log(ipc_1)
SET ltc_1 = log(tc_1)
SET lwpx = log(wpx)
SET lpib = log(pib)
*log transformation
*
set dlipc_1 = log(ipc_1) - log(ipc_1 {1})
set dltc_1 = log(tc_1) - log(tc_1 {1})
set dlwpx = log(wpx) - log(wpx {1})
set dlpib = log(pib) - log(pib {1})
*First difference
*
***********************************************
*Unit root tests:
*********************************************
*
@URADF(maxlag=8,sclags=18,det=constant,signif=.05) dlipc_1
@Zivot(maxlag=8,signif=.05,CRIT=AIC,BREAK=intercept) dlipc_1
@LPUnit(maxlag=8,signif=.05,Method=AIC,break=trend) dlipc_1
@URADF(maxlag=8,sclags=18,det=constant,signif=.05) dltc_1
@Zivot(maxlag=8,signif=.05,CRIT=AIC,BREAK=intercept) dltc_1
@LPUnit(maxlag=8,signif=.05,Method=AIC,break=intercept) dltc_1
@URADF(maxlag=8,sclags=18,det=constant,signif=.05) dlwpx
@Zivot(maxlag=8,signif=.05,CRIT=AIC,BREAK=intercept) dlwpx
@LPUnit(maxlag=8,signif=.05,Method=AIC,break=intercept) dlwpx
@URADF(maxlag=8,sclags=18,det=constant,signif=.05) dlpib
@Zivot(maxlag=8,signif=.05,CRIT=AIC,BREAK=intercept) dlpib
@LPUnit(maxlag=8,signif=.05,Method=AIC,break=intercept) dlpib
*
******************************************************
*Cointeration test:
******************************************************
*
LINREG lipc_1 / res
# constant ltc_1 lwpx lpib
*OLS estimation
*
@LAGSELECT(MAXLAG=8,SCLAGS=18,DET=constant,SIGNIF=.05) res
*procedure lagselect on residuals
*
@egtestresids(lags=2) res
*Engle-Granger test
******************
*Gregory-hansen test (level shift):
*****************
*
@GregoryHansen(model=CONSTANT,LAGMETHOD=AIC,MAXLAGS=12,nograph) lipc_1
# constant ltc_1 lwpx lpib
*
******************
*Gregory-hansen test (level and slope shift):
*****************
*
@GregoryHansen(model=REGIMETREND,LAGMETHOD=AIC,MAXLAGS=12,nograph) lipc_1
# constant ltc_1 lwpx lpib
*
****************
*ARDL Model:
*************************
*
LINREG dlipc_1
# constant dlipc_1{1 to 4} dltc_1{0 to 4} dlwpx{0 to 4} dlpib{0 to 4} seasons{-2 to 0}
*OLS estimation
*
*standard equation is trimmed :
*
LINREG(lwindow=neweywest) dlipc_1
# constant dlipc_1{1 4} dltc_1{0 4} dlwpx{0 2 4} dlpib{1 3 4} seasons{-2 to 0}
*
summarize (%beta(5)+%beta(6)+%beta(7))/(1-(%beta(2)+%beta(3)+%beta(4)))
*
**************
*Tests:
***************
*
stat %resids
*
@RegCorrs(number=4,QSTATS,nograph,report) %resids
*
display "AIC" %aic
*
@mcleodli(number=4) %resids
*
@ARCHTest(lags=4) %resids
*
******
*RESET Tests:
********
*
set resids = %resids
@regreset(h=4) resids
*
*************************************************************************************************
*STR Model
*******************
*
set vtc = log(tc_1) - log(tc_1 {1})
*
stat dltc_1
*
display *.####### %variance
*
display *.####### 1.0/sqrt(%variance)
*
**************************************************************************
*LSTR model:
**************************
nlpar(exactlinesearch)
compute scalef=1.0/sqrt(%variance)
nonlin(parmset=starparms) gamma c
frml glstar = logistic = %logistic(20.46*gamma*(dltc_1{4}-c),1.0)
compute c=%mean,gamma=2.0
*
equation standard dlipc_1
# constant dlipc_1{1 to 4} dltc_1{0 to 4} dlwpx{0 to 4} dlpib{0 to 4} seasons{-2 to 0}
*
equation transit dlipc_1
# constant dlipc_1{1 to 4} dltc_1{0 to 4} dlwpx{0 to 4} dlpib{0 to 4} seasons{-2 to 0}
*
frml(equation=standard,vector=phi1) phi1f
frml(equation=transit ,vector=phi2) phi2f
frml star dlipc_1 = g=glstar,phi1f+g*phi2f
*
nonlin(parmset=regparms) phi1 phi2
nonlin(parmset=starparms) gamma c
*
*
nlls(parmset=regparms,frml=star) dlipc_1
*
* ***********
* Based upon the initial results, the standard equation is trimmed. This is now estimated with
* all the parameters.
*
equation standard dlipc_1
# constant dlipc_1{4} dltc_1{0 2 3} dlwpx{0 1 2} dlpib{0} seasons{-2 to 0}
*
equation transit dlipc_1
# constant dlipc_1{4} dltc_1{0 2 3} dlwpx{0 1 2} dlpib{0} seasons{-2 to 0}
*
frml(equation=standard,vector=phi1) phi1f
frml(equation=transit ,vector=phi2) phi2f
compute c=%mean,gamma=2.0
*
* We have to re-estimate this since we changed the specification.
*
nlls(parmset=regparms+starparms,frml=star,trace) dlipc_1
*
**************
*Tests:
***************
*
stat %resids
*
*Test d'absence d'autocorrelation residuelles :
*
@RegCorrs(number=4,QSTATS,nograph,report) %resids
*
display "AIC" %aic
*
*Tests d'absence d'effets ARCH :
*
@mcleodli(number=4) %resids
*
@ARCHTest(lags=4) %resids
*
*************************************************************************
*Fonction de transition :
*************************************************************************
*
set cc = %beta(26)
set Seuil = cc(t)
set F_Transition = glstar(t)
set V_Transition = dltc_1{4}
scatter
# V_Transition F_Transition / 10
*
nonlin coef1 coef2 coef3 coef4 coef5 coef6 coef7
compute coef1 = %beta(2)
compute coef2 = %beta(3)
compute coef3 = %beta(4)
compute coef4 = %beta(5)
compute coef5 = %beta(15)
compute coef6 = %beta(16)
compute coef7 = %beta(17)
*
**********************
*ERPT when G=0 :
**********************
*
compte SR = coef2
compte LR = (coef2+coef3+coef4)/(1-(coef1))
*
Display SR LR
*
summarize (%beta(3)+%beta(4)+%beta(5))/(1-(%beta(2)))
*
**********************
*ERPT when G=1 :
**********************
*
compte SR_g = (coef2+coef5)
compte LRg = (coef5+coef6+coef7)/(1-(coef1))
compte LR_g = (coef2+coef3+coef4+coef5+coef6+coef7)/(1-(coef1))
*
display SR_g LRg LR_g
*
summarize (%beta(3)+%beta(4)+%beta(5)+%beta(15)+%beta(16)+%beta(17))/(1-(%beta(2)))
summarize %beta(3)+%beta(15)
*
*
frml pt_sr = coef2+F_Transition*coef5
*
set ERPT_SR = pt_sr
*
frml pt_lr = LR+F_Transition*LRg
*
set ERPT_LR = pt_lr
*
*print / F_Transition ERPT
*
SCATTER(STYLE=DOTS,OVERLAY=DOTS,OVCOUNT=2,pattern,key=below,nokbox) 2
# V_TRANSITION F_TRANSITION
# V_TRANSITION ERPT_SR
*
SCATTER(STYLE=DOTS,OVERLAY=DOTS,OVCOUNT=2,pattern,key=below,nokbox) 2
# V_TRANSITION F_TRANSITION
# V_TRANSITION ERPT_LR
*
GRAPH(STYLE=LINE,OVERLAY=LINE,scale=both,OVCOUNT=1,$
klabel=||"Past Depreciation (Left scale)","Threshold","Short-run ERPT (Right scale)"||,key=below,nokbox,pattern) 3
# V_TRANSITION / 8
# Seuil / 3
# ERPT_SR / 1
*
GRAPH(STYLE=LINE,OVERLAY=LINE,scale=both,OVCOUNT=1,$
klabel=||"Past Depreciation (Left scale)","Threshold","Long-run ERPT (Right scale)"||,key=below,nokbox,pattern) 3
# V_TRANSITION / 8
# Seuil / 3
# ERPT_LR / 1
*
*
*****************************************************************************************************
*ESTR model :
**************************
*
nlpar(exactlinesearch)
compute scalef=1.0/sqrt(%variance)
nonlin(parmset=starparms) gamma c
frml glstar = exponential = 1-exp(-20.46^2*gamma*(dltc_1{4}-c)^2)
compute c=%mean,gamma=2.0
*
equation standard dlipc_1
# constant dlipc_1{1 to 4} dltc_1{0 to 4} dlwpx{0 to 4} dlpib{0 to 4} seasons{-2 to 0}
*
equation transit dlipc_1
# constant dlipc_1{1 to 4} dltc_1{0 to 4} dlwpx{0 to 4} dlpib{0 to 4} seasons{-2 to 0}
*
frml(equation=standard,vector=phi1) phi1f
frml(equation=transit ,vector=phi2) phi2f
frml star dlipc_1 = g=glstar,phi1f+g*phi2f
*
nonlin(parmset=regparms) phi1 phi2
nonlin(parmset=starparms) gamma c
*
*
nlls(parmset=regparms,frml=star) dlipc_1
*
* ***********
* Based upon the initial results, the standard equation is trimmed. This is now estimated with
* all the parameters.
*
equation standard dlipc_1
# constant dlipc_1{4} dltc_1{0 2 3} dlwpx{0 1 2} dlpib{0} seasons{-2 to 0}
*
equation transit dlipc_1
# constant dlipc_1{4} dltc_1{0 2 3} dlwpx{0 1 2} dlpib{0} seasons{-2 to 0}
*
frml(equation=standard,vector=phi1) phi1f
frml(equation=transit ,vector=phi2) phi2f
compute c=%mean,gamma=2.0
*
* We have to re-estimate this since we changed the specification.
*
nlls(parmset=regparms+starparms,frml=star,trace) dlipc_1
*
**************
*Tests:
***************
*
stat %resids
*
*Test d'absence d'autocorrelation residuelles :
*
@RegCorrs(number=4,QSTATS,nograph,report) %resids
*
display "AIC" %aic
*
*Tests d'absence d'effets ARCH :
*
@mcleodli(number=4) %resids
*
@ARCHTest(lags=4) %resids
*
*************************************************************************
*Fonction de transition :
*************************************************************************
*
set cc = %beta(26)
set Seuil = cc(t)
set F_Transition = glstar(t)
set V_Transition = dltc_1{4}
scatter
# V_Transition F_Transition / 10
*
nonlin coef1 coef2 coef3 coef4 coef5 coef6 coef7
compute coef1 = %beta(2)
compute coef2 = %beta(3)
compute coef3 = %beta(4)
compute coef4 = %beta(5)
compute coef5 = %beta(15)
compute coef6 = %beta(16)
compute coef7 = %beta(17)
*
**********************
*ERPT when G=0 :
**********************
*
compte SR = coef2
compte LR = (coef2+coef3+coef4)/(1-(coef1))
*
Display SR LR
*
summarize (%beta(3)+%beta(4)+%beta(5))/(1-(%beta(2)))
*
**********************
*ERPT when G=1 :
**********************
*
compte SR_g = (coef2+coef5)
compte LRg = (coef5+coef6+coef7)/(1-(coef1))
compte LR_g = (coef2+coef3+coef4+coef5+coef6+coef7)/(1-(coef1))
*
display SR_g LRg LR_g
*
summarize (%beta(3)+%beta(4)+%beta(5)+%beta(15)+%beta(16)+%beta(17))/(1-(%beta(2)))
summarize %beta(3)+%beta(15)
*
*
frml pt_sr = coef2+F_Transition*coef5
*
set ERPT_SR = pt_sr
*
frml pt_lr = LR+F_Transition*LRg
*
set ERPT_LR = pt_lr
*
*print / F_Transition ERPT
*
SCATTER(STYLE=DOTS,OVERLAY=DOTS,OVCOUNT=2,pattern,key=below,nokbox) 2
# V_TRANSITION F_TRANSITION
# V_TRANSITION ERPT_SR
*
SCATTER(STYLE=DOTS,OVERLAY=DOTS,OVCOUNT=2,pattern,key=below,nokbox) 2
# V_TRANSITION F_TRANSITION
# V_TRANSITION ERPT_LR
*
GRAPH(STYLE=LINE,OVERLAY=LINE,scale=both,OVCOUNT=1,$
klabel=||"Past Depreciation (Left scale)","Threshold","Short-run ERPT (Right scale)"||,key=below,nokbox,pattern) 3
# V_TRANSITION / 8
# Seuil / 3
# ERPT_SR / 1
*
GRAPH(STYLE=LINE,OVERLAY=LINE,scale=both,OVCOUNT=1,$
klabel=||"Past Depreciation (Left scale)","Threshold","Long-run ERPT (Right scale)"||,key=below,nokbox,pattern) 3
# V_TRANSITION / 8
# Seuil / 3
# ERPT_LR / 1
*Thanks a lot for your help. After adding SEASONAL SEASONS in the codes, the program now runs smoothly up to the part with McLeodiLi and ARCH tests. However, I get errors when I get to the estimation of the transition funcitions. Although I am able to plot the transition function, I got an error in the summary of function of coefficients and the latter charts are no longer produced since I got NAs in the summary of function of coefficients.TomDoan wrote:It looks like it needs
SEASONAL SEASONS
at some point before the LINREG's start.
Thanks a million, Tom. Perfect!TomDoan wrote:Comment out the @ARCHTEST procedure calls. They're overwriting the regression information.
I'm pretty sure that Table A1 is just a list of results from univariate @STARTEST's. The entire paper is about univariate STAR models.mightydell37 wrote:Dear Tom,
May I know how linearity tests against STR model was implemented? Table A1, p.23 of paper on Asymmetric Exchange Rate Pass-Through by Ben Cheikh presents these linearity tests but the codes were not included in the attached RATS code. The examples in the RATS Workbook using @STARTEST use only a univariate nonlinear models.
You would have to ask the author. You can see his questions and answers (his handle is nbcheikh) about this at:mightydell37 wrote: The attached RATS codes also do not include the LM test of parameter constancy and the LM test of no remaining nonlinearity which appear in Table 1, p.15 of the paper.