KConfid {gmmExtra}R Documentation

Confidence interval using the K statistics of Kleibergen

Description

The confidence is either an interval or an ellipse.

Usage

KConfid(obj, which, type = c("K", "KJ"), alpha = 0.05, alphaJ = 0.01,
        n = 4, mc.cores=1)

Arguments

obj

Object of class "gmm" returned by gmm (not restricted)

type

Should we base the confidence interval on the K or K-J statistics.

which

A 2x1 vector or a scalar. The interval is computed for coef(obj)[which].

alpha, alphaJ

The overall size and the size for the J-test when type is "KS".

n

The number of points to compute the confidence region is 4(n-1). It must be greater than2.

mc.cores

The number of cores to use in mclapply

Value

Interval for lenght(which)=1 or a series of points if lenght(which)>1.

References

Kleibergen, F. (2005), Testing Parameters in GMM without assuming that they are identified. Econometrica, 73, 1103-1123,

Examples


data(Finance)
r <- Finance[1:300, 1]
rf <- Finance[1:300, "rf"]
z <- as.matrix(r-rf)
zm <-  Finance[1:300, "rm"]-rf
f1 <- zm
f2 <- Finance[1:300, "hml"] - rf
f3 <- Finance[1:300, "smb"] - rf
## Kconfid fails with prewhite=1
res <- gmm(z ~ f1 + f2 + f3, ~ f1 + f2 + f3, prewhite=0)

## To avoid errors especially with windows OS
## Not run: KConfid(res,2, mc.cores=4)
sol <- KConfid(res,c(2,3), mc.cores=4)
plot(sol, main="Confidence Region")
polygon(sol,col="grey")
points(res$coef[2],res$coef[3],pch=21,bg=1)
text(res$coef[2],res$coef[3],expression(hat(theta)),pos=3)
## End(Not run)


[Package gmmExtra version 0.0-3 Index]