ltz: Local-to-Zero Test

In apoorvalal/ivDiag: Estimation and Diagnostic Tools for Instrumental Variables Designs

Local-to-Zero Test

Description

Estimates Local-to-Zero IV coefficients and SEs for a single instrument.

Usage

ltz(data, Y, D, Z, controls, FE = NULL, cl = NULL, weights = NULL, prior, prec = 4)

Arguments

data	name of a dataframe.
Y	a string indicating the outcome variable.
D	a string indicating the treatment variable.
Z	a vector of strings indicating the instrumental variables.
controls	a vector of strings indicating the control variables.
FE	a vector of strings indicating the fixed effects variables.
cl	a string indicating the clustering variable.
weights	a string indicating the variable that stores weights.
prior	prior mean and standard deviation of the direct effect of instrument on outcome.
prec	precision of results (4 by default).

Value

iv	results from a 2SLS regression.
ltz	results after local-to-zerio adjustment.
prior	prior mean and standard deviation

References

Conley, Timothy G, Christian B Hansen, and Peter E Rossi. 2012. "Plausibly Exogenous." Review of Economics and Statistics 94 (1): 260–72.

See Also

plot_coef

Examples

data(ivDiag)
controls <- c('altitudine', 'escursione', 'costal', 'nearsea', 'population', 
    'pop2', 'gini_land', 'gini_income')
ltz_out <- ltz(data = gsz, Y = "totassoc_p", D = "libero_comune_allnord", 
    Z = "bishopcity", controls = controls, weights = "population", 
    prior = c(0.178, 0.137))
plot_ltz(ltz_out)    
    
library(testthat)    
test_that("Check local-to-zero adjustment", {
  expect_equal(as.numeric(ltz_out$ltz[1]), 3.6088)
})

apoorvalal/ivDiag documentation built on July 12, 2024, 12:53 p.m.