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tsDyn (version 0.7-60)

TVECM: Treshold Vector Error Correction model (VECM)

Description

Estimate a Treshold Vector Error Correction model (VECM)

Usage

TVECM(data,lag=1,nthresh=1, trim=0.05, ngridBeta=50, ngridTh=50, plot=TRUE,  th1=list(exact=NULL, int=c("from","to"), around="val"), th2=list(exact=NULL, int=c("from","to"), around="val"), beta=list(exact=NULL, int=c("from","to"), around=c("val","by")), restr=c("none", "equal", "signOp"), common=c("All", "only_ECT"), include = c( "const", "trend","none", "both"),dummyToBothRegimes=TRUE,beta0=0,methodMapply=FALSE, trace=TRUE )

Arguments

data
time series
lag
Number of lags to include in each regime
nthresh
number of threshold (see details)
trim
trimming parameter indicating the minimal percentage of observations in each regime
ngridBeta
number of elements to search for the cointegrating value
ngridTh
number of elements to search for the threshold value
plot
Whether a grid with the SSR of each threshold should be printed
th1
different possibilities to pre-specify an exact value, an interval or a central point for the search of gamma1
th2
different possibilities to pre-specify an exact value or a central point for the search of gamma2
beta
different possibilities to pre-specify an exact value, an interval or a central point for the search of the cointegrating value
restr
Currently not avalaible
common
Whether the regime-specific dynamics are only for the ECT or for the ECT and the lags
include
Type of deterministic regressors to include
dummyToBothRegimes
Whether the dummy in the one threshold model is applied to each regime or not.
beta0
Additional regressors to include in the cointegrating relation
methodMapply
only for programming. Is to make the choice between a for loop or mapply implementation
trace
should additional infos be printed? (logical)

Value

  • Fitted model data

Details

For fixed threshold and cointegrating vector, the model is linear, so estimation can be done directly by CLS (Conditional Least Squares). The search of the parameters values which minimize the residual sum of squares (SSR) is made upon a grid of potential values. The search on the threshold values is made upon existing ones, whereas the search for the cointegrating value is made by default based on a confidence interval around the estimate form linear model.

nthresh=1: estimation of one threshold model (two regimes) upon a grid of ngridTh values (default to ALL) possible thresholds and delays values.

nthresh=2: estimation of two thresholds model (three regimes) Conditional on the threshold found in model where nthresh=1, the second threshold is searched. When both are found, a second grid search is made with 30 values around each threshold.

The model can be either with a threshold effect on all variables ("All") or only on the error correction term (ECT) (argument "only ECT"). In the second case, the value for the middle threshold is taken a null, as in Balke and Fomby (1997).

References

Hansen, B. and Seo, B. (2002), Testing for two-regime threshold cointegration in vector error-correction models, Journal of Econometrics, 110, pages 293 - 318

Seo, M. H. (2009) Estimation of non linear error-correction models, Working paper

See Also

VECM for the linear VECM, TVAR for the threshold VAR, TVECM.SeoTest to test for TVECM, TVECM.sim to simulate/bootstrap a TVECM.

Examples

Run this code
data(zeroyld)
data<-zeroyld

##Estimate a TVECM (we use here minimal grid, it should be usually much bigger!)

tv<-TVECM(data, nthresh=2,lag=1, ngridBeta=20, ngridTh=30, plot=TRUE,trim=0.05, common="All")

print(tv)
summary(tv)

#Obtain diverse infos:
AIC(tv)
BIC(tv)

res.tv<-residuals(tv)

#export the equations as Latex:
toLatex(tv)

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