rank.select {tsDyn}

Selection of the cointegrating rank with Information criterion.

Description

Selection of the cointegrating rank and the lags with Information criterion (AIC, BIC).

Usage

rank.select(
  data,
  lag.max = 10,
  r.max = ncol(data) - 1,
  include = c("const", "trend", "none", "both"),
  fitMeasure = c("SSR", "LL"),
  sameSample = TRUE,
  returnModels = FALSE
)

## S3 method for class 'rank.select'
print(x, ...)

## S3 method for class 'rank.select'
as.data.frame(x, ...)

## S3 method for class 'rank.select'
summary(object, ...)

Arguments

data

multivariate time series.

lag.max

Maximum number of lags to investigate.

r.max

Maximum rank to investigate.

include

Type of deterministic regressors to include. See VECM or lineVar.

fitMeasure

Whether the AIC/BIC should be based on the full likelihood, or just the SSR. See explanations in logLik.VECM.

sameSample

Logical. Whether the data should be shortened so that the AIC/BIC are estimated on the same sample. Default to TRUE.

returnModels

Logical, default to FALSE. Whether the output should also contain the list of each model computed.

x

The output from rank.select for the print method.

...

Unused.

object

The output from rank.select for the summary method.

Details

This function estimates the AIC, BIC and Hannan-Quinn for each rank (up to lags.max) and lags (up to lags.max). This method has been shown to be useful to select simultaneously the rank and the lags, see references.

Value

An object of class ‘rank.select’, with ‘print’ and ‘summary methods’, containing among other the matrices of AIC/BIC/HQ, the Likelihood, and best ranks according to each criterion.

Author(s)

Matthieu Stigler

References

- Aznar A and Salvador M (2002). Selecting The Rank Of The Cointegration Space And The Form Of The Intercept Using An Information Criterion. Econometric Theory, *18*(04), pp. 926-947. <URL: http://ideas.repec.org/a/cup/etheor/v18y2002i04p926-947_18.html>.

-Cheng X and Phillips PCB (2009). Semiparametric cointegrating rank selection. Econometrics Journal , *12*(s1), pp. S83-S104. <URL: http://ideas.repec.org/a/ect/emjrnl/v12y2009is1ps83-s104.html>.

- Gonzalo J and Pitarakis J (1998). Specification via model selection in vector error correction models. Economics Letters, *60*(3), pp. 321 - 328. ISSN 0165-1765, <URL: http://dx.doi.org/DOI: 10.1016/S0165-1765(98)00129-3>.

- Kapetanios G (2004). The Asymptotic Distribution Of The Cointegration Rank Estimator Under The Akaike Information Criterion. Econometric Theory, *20*(04), pp. 735-742. <URL: http://ideas.repec.org/a/cup/etheor/v20y2004i04p735-742_20.html>.

- Wang Z and Bessler DA (2005). A Monte Carlo Study On The Selection Of Cointegrating Rank Using Information Criteria. Econometric Theory, *21*(03), pp. 593-620. <URL: http://ideas.repec.org/a/cup/etheor/v21y2005i03p593-620_05.html>.

See Also

VECM for estimating a VECM. rank.test (or ca.jo in package urca) for the classical Johansen cointegration test.

Examples

data(barry)

# 
rk_sel <- rank.select(barry)
rk_sel
summary(rk_sel)