cointReg: Estimation and Inference for cointegrating regressions

Description Usage Arguments Value References See Also Examples

View source: R/cointReg.R

Description

Computes either the Phillips and Hansen (1990) Fully Modified OLS estimator, or the Saikkonen (1990) Dynamic OLS estimator, or the Vogelsang and Wagner (2014) Integrated Modified OLS estimator.

Usage

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cointReg(method = c("FM", "D", "IM"), x, y, ...)

Arguments

method

[character(1)]
Select the method for the estimation of your cointegration model:

  • "FM": FM-OLS (default), see details at cointRegFM

  • "D": D-OLS, see details at cointRegD

  • "IM": IM-OLS, see details at cointRegIM

x

[numeric | matrix | data.frame]
RHS variables on which to apply the model estimation.

y

[numeric | matrix | data.frame]
LHS variable(s) on which to apply the model estimation. Usually one-dimensional, but a matrix or data.frame with more than one column is also possible (only for FM-OLS).

...

[any]
Arguments passed to the corresponding cointReg function, like:

  • x, y, deter: data to include in the model

  • kernel, bandwidth: parameters for calculating the long-run variance

  • n.lead, n.lag, kmax, info.crit: D-OLS specific arguments.

  • selector, t.test: IM-OLS specific arguments.

  • check: Wheather to check (and if necessary convert) the arguments. See checkVars for further information.

Value

[cointReg] object.

References

See Also

Other cointReg: cointRegD, cointRegFM, cointRegIM, plot.cointReg, print.cointReg

Examples

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set.seed(1909)
x1 = cumsum(rnorm(100, mean = 0.05, sd = 0.1))
x2 = cumsum(rnorm(100, sd = 0.1)) + 1
x3 = cumsum(rnorm(100, sd = 0.2)) + 2
x = cbind(x1, x2, x3)
y = x1 + x2 + x3 + rnorm(100, sd = 0.2) + 1
deter = cbind(level = 1, trend = 1:100)
cointReg("FM", x = x, y = y, deter = deter, kernel = "ba",
         bandwidth = "and")

# Compare the results of all three models:
res = sapply(c("FM", "D", "IM"), cointReg, x = x, y = y, deter = deter)
do.call(cbind, lapply(res, "[[", "theta"))

cointReg documentation built on May 2, 2019, 3:45 a.m.