simulation.hetero: Monte Carlo simulation for heterogeneity of threshold effects...

In hdthreshold: Inference on Many Jumps in Nonparametric Panel Regression Models

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

Description

Monte Carlo simulation to study the size and power properties of the uniform test for heterogeneity 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.hetero(
  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_hetero = simulation.hetero(10, 200, 0, 10, epsilon = "iid",
                running = "iid", hetero = 0)

hdthreshold documentation built on April 11, 2025, 5:54 p.m.