o_delta_boot: Bootstrapped deltas*

In robomit: Robustness Checks for Omitted Variable Bias

Description

Estimates bootstrapped deltas*, i.e. the degree of selection on unobservables relative to observables that would be necessary to explain away the result, following Oster (2019).

Usage

o_delta_boot(y, x, con, id = "none", time = "none", beta = 0, R2max, sim, obs,
rep, type, useed = NA, data)

Arguments

y	Name of the dependent variable (as string).
x	Name of the independent variable of interest (treatment variable; as string).
con	Name of the other control variables. Provided as string in the format: "w + z +...".
id	Name of the individual id variable (e.g. firm or farm; as string). Only applicable for fixed effect models.
time	Name of the time variable (e.g. year or month; as string). Only applicable for fixed effect models.
beta	Beta for which delta* should be estimated (default is beta = 0).
R2max	Max R-square for which beta* should be estimated.
sim	Number of simulations.
obs	Number of draws per simulation.
rep	Bootstrapping either with (= TRUE) or without (= FALSE) replacement.
type	Model type (either lm or plm; as string).
useed	Seed number defined by user.
data	Data.

Details

Estimates bootstrapped deltas*, i.e. the degree of selection on unobservables relative to observables that would be necessary to explain away the result, following Oster (2019). Bootstrapping can either be done with or without replacement. The function supports linear cross sectional (see lm objects in R) and panel fixed effect (see plm objects in R) models.

Value

Returns tibble object. Including bootstrapped deltas*.

References

Oster, E. (2019). Unobservable selection and coefficient stability: Theory and evidence. Journal of Business & Economic Statistics, 37, 187-204.

Examples

# load data, e.g. the in-build mtcars dataset
data("mtcars")
data_oster <- mtcars

# preview of data
head(data_oster)

# load robomit
require(robomit)

# estimate bootstrapped deltas*
o_delta_boot(y = "mpg",              # define the dependent variable name
                 x = "wt",           # define the main independent variable name
                 con = "hp + qsec",  # other control variables
                 beta = 0,           # define beta. This is usually set to 0
                 R2max = 0.9,        # define the max R-square.
                 sim = 100,          # define number of simulations
                 obs = 30,           # define number of drawn observations per simulation
                 rep = FALSE,        # define if bootstrapping is with or without replacement
                 type = "lm",        # define model type
                 useed = 123,        # define seed
                 data = data_oster)  # define dataset

robomit documentation built on Sept. 15, 2020, 5:07 p.m.