hurdle.IV: Hurdle IV regression

Description Usage Arguments Value

View source: R/wrapperFunc.R

Description

Run a hurdle IV regression, either lognormal IV or cragg IV. You should specify the model you want to fit. Currently this does not have a nice summary function for the output.

Usage

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hurdle.IV(formula, inst, endog, exog, data, endog_reg = list(),
  start_val = list(), type = "lognormal", options = list(cholesky = T,
  maxit = 5000, trace = 0, method = "BFGS"))

Arguments

formula

the second stage regression: y~exogenous + endogenous

inst

a vector of your instrument(s): c(inst1,inst2)

endog

a vector of your endogenous variable(s): c(end1,end2)

exog

a vector of your exogenous variable(s): c(ex1,ex2)

data

the dataframe

endog_reg

a list of endogenous regression formulae. By default will estimate endogenous ~ all exogenous variables + all instruments

start_val

an optional list of start values. By default the function will find start values using simple linear/probit regressions of the specified formulae

type

either "lognormal" or "cragg"

options:

cholesky true or false; maxit = maximal number of iterations; trace = 0; method = "BFGS". Options are similar to those for optim, see optim documentation for more details

Value

Returns estimated parameters as well as a the hessian and standard deviations


jackiemauro/hurdleIV documentation built on April 2, 2018, 8:28 p.m.