rkt: Estimation for regression kink with a time-varying threshold In RegKink: Regression Kink with a Time-Varying Threshold

Description

This is a function estimating regression kink with a time-varying threshold.

Usage

 `1` ```rkt(y,x,z,q,r01,r02,r11,r12,stp1,stp2) ```

Arguments

 `y` A vector of response. `x` A vector of regressor `z` A data matrix of control variables `q` A vector of variable affecting threshold `r01` Lower bounder of parameter space for r0 `r02` Upper bounder of parameter space for r0 `r11` Lower bounder of parameter space for r1 `r12` Upper bounder of parameter space for r1 `stp1` Step used in grid search of r0 `stp2` Step used in grid search of r1

Value

A list with the elements

 `bols` The OLS estimates when a kink effect is ignored. `bt` The regression coefficients when a kink effect is included in the model. `gammahat0` The estimated threshold of the constant one in threshold parameters. `gammahat1` The estimated threshold of the slop in threshold parameters. `sig` The sum of squred errors of the kink model.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25``` ```sta <- proc.time() ##Simulated data set.seed(12345) n=200 x = rnorm(n) q = rnorm(n) rt = 0.2 - 0.5*q z = rnorm(n) x1 = cbind(neg.part(x-rt),pos.part(x-rt),z) b0 =c(1,2,1) y = b0[1]*x1[,1]+b0[2]*x1[,2]+b0[3]*x1[,3]+ rnorm(n) # set grid search paramaters r01 = 0 r02 = 2 stp1 = 0.1 r11 = -10 r12 = 5 stp2 = 0.1 # estimate the model with a state-dependent threshold est1 <- rkt(y,x,z,q,r01,r02,r11,r12,stp1,stp2) proc.time() - sta ```

RegKink documentation built on April 15, 2021, 9:10 a.m.