| cointRegD {cointReg} | R Documentation |
Dynamic OLS
Description
Computes the Saikkonen (1990) Dynamic OLS estimator.
Usage
cointRegD(x, y, deter, kernel = c("ba", "pa", "qs", "tr"),
bandwidth = c("and", "nw"), n.lead = NULL, n.lag = NULL,
kmax = c("k4", "k12"), info.crit = c("AIC", "BIC"), demeaning = FALSE,
check = TRUE, ...)
Arguments
x |
[ |
y |
[ |
deter |
[ |
kernel |
[ |
bandwidth |
[ |
n.lead, n.lag |
[ |
kmax |
[ |
info.crit |
[ |
demeaning |
[ |
check |
[ |
... |
Arguments passed to |
Details
The equation for which the FM-OLS estimator is calculated:
y = \delta \cdot D + \beta \cdot x + u
with D as the deterministics matrix.
Then \theta = (\delta', \beta')' is the full parameter vector.
Information about the D-OLS specific arguments:
n.lag,n.leadA positive number to set the number of lags and leads. If at least one of them is equal to
NULL(default), the functiongetLeadLagwill be used to calculate them automatically (see Choi and Kurozumi (2012) for details). In that case, the following two arguments are needed.kmaxMaximal value for lags and leads, when they are calculated automatically. If "k4", then the maximum is equal to
floor(4 * (x.T/100)^(1/4)), else it'sfloor(12 * (x.T/100)^(1/4))withx.Tis equal to the data's length. One of"k4"or"k12". Default is"k4".info.critInformation criterion to use for the automatical calculation of lags and leads. One of
"AIC"or"BIC". Default is"AIC".
Value
[cointReg]. List with components:
beta[numeric]-
coefficients of the regressors
delta[numeric]-
coefficients of the deterministics
theta[numeric]-
combined coefficients of
betaanddelta sd.theta[numeric]-
standard errors for
theta t.theta[numeric]-
t-values for
theta p.theta[numeric]-
p-values for
theta theta.all[numeric]-
combined coefficients of
beta,deltaand the auxiliary leads-and-lags regressors residuals[numeric]-
D-OLS residuals (length depends on leads and lags)
omega.u.v[numeric]-
conditional long-run variance based on OLS residuals
varmat[matrix]-
variance-covariance matrix
Omega[list]-
the whole long-run variance matrix and parts of it
bandwidth[list]-
number and name of the calculated bandwidth
kernel[character]-
abbr. name of kernel type
lead.lag[list]-
leads-and-lags parameters
References
Phillips, P.C.B. and M. Loretan (1991): "Estimating Long Run Economic Equilibria," Review of Economic Studies, 58, 407–436, DOI:10.2307/2298004.
Saikkonen, P. (1991): "Asymptotically Efficient Estimation of Cointegrating Regressions," Econometric Theory, 7, 1–21, DOI:10.1017/S0266466600004217.
Stock, J.H. and M.W. Watson (1993): "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems," Econometrica, 61, 783–820, DOI:10.2307/2951763.
See Also
Other cointReg: cointRegFM,
cointRegIM, cointReg,
plot.cointReg, print.cointReg
Other D-OLS: getLeadLag,
getModD, makeLeadLagMatrix
Examples
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)
test <- cointRegD(x, y, deter, n.lead = 2, n.lag = 2,
kernel = "ba", bandwidth = "and")
print(test)
test2 <- cointRegD(x, y, deter, kmax = "k4", info.crit = "BIC",
kernel = "ba", bandwidth = "and")
print(test2)