Library: | metrics |
See also: | glmest |
Quantlet: | tobit | |
Description: | 2-step estimation of a Tobit model |
Usage: | {b,s,cv} = tobit(x,y) | |
Input: | ||
x | n x d matrix , the observed explanatory variable | |
y | n x 1 matrix , the observed response variable | |
Output: | ||
b | d x 1 vector, contains the estimated coefficients of the components of x | |
s | scalar, contains the estimated standard deviation of the error term | |
cv | (d+1)x(d+1) matrix, estimated covariance matrix for [b,s] |
library("metrics") n = 500 k = 2 x = matrix(n)~aseq(1, n ,0.25) s = 8 u = s*normal(n) b = #(-9, 1) ystar = x*b+u y = ystar.*(ystar.>=0) tstep = tobit(x,y) tstep.b tstep.s tstep.cv dg = matrix(rows(tstep.cv),1) dig = diag(dg) stm = dig.*tstep.cv std = sqrt(sum(stm,2)) coef = tstep.b|tstep.s coef~(coef./std) ; t-ratios
2-step estimates of b and s