pdR (version 1.9.3)

SMPLSplit_est: Estimation of sub-sampled data

Description

A function for estimating the subsampled data.

Usage

SMPLSplit_est(data,dep,indep,th,plot,h=1,nonpar=2)

Value

threshold

values of threshold estimates.

est0

coefficient estimates of global data.

est.low

coefficient estimates of low regime.

est.high

coefficient estimates of high regime.

est0.info

additional information of global data.

est.joint.info

additional information of joint threshods.

est.low.info

additional information of est.low.

est.high.info

additional information of est.high.

Arguments

data

the data in either data.frame or matrix.

dep

the name of dependent variable.

indep

the name(s) of independent variable(s).

th

the name of threshold variable.

plot

=1, plot; =0, do not plot.

h

h=1, heteroskedasticity-consistent covariance; h=0, homoskedastic case.

nonpar

Indicator for non-parametric method used to estimate nuisance scale in the presence of heteroskedasticity (only relevant if h=1).Set nonpar=1 to estimate regressions using a quadratic.Set nonpar=2 to estimate regressions using an Epanechnikov kernel with automatic bandwidth.

Details

This code estimates the parameters of sub-sampled data. It generalizes the simple code of Dr. Hansen, allowing White Corrected Heteroskedastic Errors.

References

Hanse B. E. (2000) Sample Splitting and Threshold Estimation. Econometrica, 68, 575-603.

Examples

## Not run, becasue of bootstrap replicaiton takes time. Users may unmark # and run. 
data("dur_john")
rep <- 500
trim_per <- 0.15
dep <- "gdpGrowth"
indep <- colnames(dur_john)[c(2,3,4,5)]

SMPLSplit_est(data=dur_john,dep,indep,th="GDP60",plot=0,h=1,nonpar=2)