Select the best lag for threshold cointegration regression by AIC and BIC
ciTarLag(y, x, model = c("tar", "mtar"), maxlag = 4,
thresh = 0, adjust = TRUE)
dependent or left-side variable for the long-run regression.
independent or right-side variable for the long-run regression.
a choice of two models, either tar or mtar.
maximum number of lags allowed in the search process.
a threshold value.
logical value (default of TRUE) of whether to adjust the window widths so all regressions by lag have the same number of observations
Return a list object of class "ciTarLag" with the following components:
a data frame of model criterion values by lag, including lag
for the current lag, totObs
for total observations in the raw data, coinObs
for observations used in the cointegration regression, sse
for the sum of squared errors, aic
for AIC value, bic
for BIC value, LB4
for the p-value of Ljung_Box Q statistic with 4 autocorrelation coefficients, LB8
with 8 coefficients, LB12
for Q statistic with 12 coefficients
a data frame of the final model selection, including the values of model, maximum lag, threshold value, best lag by AIC, best lag by BIC
Two methods are defined as follows:
print
:This shows the out
component in the returned list.
plot
:This demonstrates the trend of AIC and BIC changes of threshold cointegration regressions by lag. It facilitates the selection of the best lag for a threshold cointegration model.
Estimate the threshold cointegration regressions by lag and then select the best regression by AIC or BIC value. The longer the lag, the smaller the number of observations availabe for estimation. If the windows of regressions by lag are not ajusted, the maximum lag is usually the best lag by AIC or BIC. Theorectially, AIC and BIC from different models should be compared on the basis of the same observation numbers (Ender 2004). adjust
shows the effect of this adjustment on the estimation window. By default, the value of adjust
should be TRUE.
Enders, W. 2004. Applied Econometric Time Series. John Wiley & Sons, Inc., New York. 480 P.
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.
# NOT RUN {
# see example at daVich
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