Nothing
#' Kapetanios, Shin and Snell(2006) nonlinear cointegration test function
#'
#' This function allows you to make Kapetanios, Shin and Snell(2006) nonlinear cointegration
#' test using residual based approach
#' @param y series name,
#' @param x series name
#' @param case if raw data 1 if demeaned data 2 if detrended data 3,
#' @param lags lag length
#' @param lsm lag selection methods if 1 AIC, if 2 BIC, if 3 t-stat significance
#' @return "Model" Estimated model
#' @return "Selected lag" the lag order
#' @return "Test Statistic" the value of the test statistic
#' @keywords STAR vector error correction model
#' @references
#' Kapetanios, G., Shin, Y., & Snell, A. (2006). Testing for cointegration in nonlinear smooth transition error correction models. Econometric Theory, 22(2), 279-303.
#'
#'
#' Burak Guris, R Uygulamalı Dogrusal Olmayan Zaman Serileri Analizi, DER Yayinevi, 2020.
#' @export
#' @importFrom stats AIC BIC lm residuals embed
#' @importFrom car linearHypothesis
#' @examples
#' x <- cumsum(rnorm(1000))
#' y <- cumsum(rnorm(1000))
#' KSS_2006_Cointegration(x, y, case = 1, lags = 6, lsm = 3)
#'
#'
#' KSS_2006_Cointegration(MarketPrices[,1],MarketPrices[,2], case = 1, lags = 2, lsm = 1)
#'
KSS_2006_Cointegration<-function(y, x, case, lags, lsm){
y = as.vector(y)
x = as.vector(x)
if(case==1){
res = residuals(lm(y~x-1))
u=res
}
if(case==2){
res = residuals(lm(I(y-mean(y))~I(x-mean(x))-1))
u=res
}
if(case==3){
trend<-seq(0,length(x)-1,1)
mod1=lm(y~trend)
y1=residuals(mod1)
mod2=lm(x~trend)
x1=residuals(mod2)
res = residuals(lm(y1~x1-1))
u=res
}
AICs = NULL
BICs = NULL
tstats = NULL
x = as.matrix(u)
for(i in 1:lags){
z=diff(x)
n=length(z)
z.diff=embed(z, i+1)[,1]
kup=x^3
z.lag.1=kup[(i+1):n]
k=i+1
z.diff.lag = embed(z, i+1)[, 2:k]
model<-lm(z.diff~z.lag.1+0+z.diff.lag )
son<-summary(lm(z.diff~z.lag.1+0+z.diff.lag ))$coefficients[1,3]
AICs[i+1] = AIC(model)
BICs[i+1] = BIC(model)
tstats[i+1] = summary(model)$coefficients[(i+1),4]
}
z=diff(x)
n=length(z)
z.diffzero=embed(z, 2)[,1]
kupzero=x^3
z.lag.zero.1=kupzero[2:n]
model0<-lm(z.diffzero~z.lag.zero.1+0)
sonzero<-summary(lm(z.diffzero~z.lag.zero.1+0))$coefficients[1,3]
AICs[1] = AIC(model0)
BICs[1] = BIC(model0)
tstats[1] = 0.0000
if(lsm == 1){
uygun_lag=which.min(AICs)-1
}
else if(lsm == 2){
uygun_lag=which.min(BICs)-1
}
else {
for (ti in (lags+1):1){
if (tstats[ti] <= 0.10){
uygun_lag = ti-1
break
}
}
}
z.diff=embed(z, uygun_lag+1)[,1]
kup=x^3
z.lag.1=kup[(uygun_lag+1):n]
k=uygun_lag+1
if(uygun_lag == 0){
model = lm(z.diff~z.lag.1+0)
son<-summary(lm(z.diff~z.lag.1+0 ))$coefficients[1,3]
} else {
z.diff.lag = embed(z, uygun_lag+1)[, 2:k]
model = lm(z.diff~z.lag.1+0+z.diff.lag)
son<-summary(lm(z.diff~z.lag.1+0+z.diff.lag ))$coefficients[1,3]
}
my_list <- list("Model"=summary(model),"Selected lag"=uygun_lag, "Test Statistic"=son)
return(my_list)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.