simulation.threshold {hdthreshold}R Documentation

Monte Carlo simulation for existence of threshold effects under known threshold location

Description

Monte Carlo simulation to study the size and power properties of the uniform test for existence of threshold effects under known threshold locations. Provides the Monte Carlo distribution of the test statistic and empirical rejection probabilities at 10%, 5% and 1% level.

Usage

simulation.threshold(
  N,
  TL,
  p,
  M,
  epsilon = c("iid", "factor"),
  running = c("iid", "factor"),
  hetero = c(0, 1)
)

Arguments

N

cross-sectional dimension

TL

time series length

p

fraction of non-zero coefficients

M

number of Monte Carlo runs

epsilon

specification of error term. If "iid" is selected the error term is iid standard normal. If "factor" is selected, the error term follows a factor model with strong cross-sectional and weak temporal dependence.

running

specification of running variable. If "iid" is selected the running variable is iid uniformly distributed. If "factor" is selected, the running variable follows a factor model with strong cross-sectional and weak temporal dependence.

hetero

if hetero=1 the error term is heteroskedastic, if hetero=0 the error term is homoskedastic.

Value

A list containing the value of the test statistic for each Monte Carlo run and the empirical rejection rate for a 10%, 5% and 1% confidence level.

Examples

result_threshold = simulation.threshold(10, 200, 0, 10, epsilon = "iid",
                   running = "iid", hetero = 0)

[Package hdthreshold version 1.0.0 Index]