Estimate an asymmetric error correction model (ECM) for two time series.
ecmAsyFit(y, x, lag =1, split =TRUE, model = c("linear","tar","mtar"), thresh =0)
Arguments
y: dependent or left-side variable for the long-run regression.
x: independent or right-side variable for the long-run regression.
lag: number of lags for variables on the right side.
split: a logical value (default of TRUE) of whether the right-hand variables should be split into positive and negative parts.
model: a choice of three models: linear, tar , or mtar cointegration.
thresh: a threshold value; this is only required when the model is specified as 'tar' or 'mtar.'
Details
There are two specficiations of an asymmetric ECM. The first one is how to calculate the error correction terms. One way is through linear two-step Engle Granger approach, as specificied by model="linear". The other two ways are threshold cointegration by either 'tar' or 'mtar' with a threshold value. The second specification is related to the possible asymmetric price transmission in the lagged price variables, as specified in split = TRUE. Note that the linear cointegration specification is a special case of the threshold cointegration. A model with model="linear" is the same as a model with model="tar", thresh = 0.
Returns
Return a list object of class "ecm" and "ecmAsyFit" with the following components: - y: dependend variable
x: independent variable
lag: number of lags
split: logical value of whether the right-hand variables are split
model: model choice
IndVar: data frame of the right-hand variables used in the ECM
name.x: name of the independent variable
name.y: name of the dependent variable
ecm.y: ECM regression for the dependent variable
ecm.x: ECM regression for the independent variable
data: all the data combined for the ECM
thresh: thresh value for TAR and MTAR model
Methods
Two methods are defined as follows:
print:: showing the key outputs.
summary:: summarizing thekey outputs.
References
Enders, W., and C.W.J. Granger. 1998. Unit-root tests and asymmetric adjustment with an example using the term structure of interest rates. Journal of Business & Economic Statistics 16(3):304-311.