Package: bndovb 1.2

bndovb: Bounding Omitted Variable Bias Using Auxiliary Data

Functions to implement a Hwang(2021) <doi:10.2139/ssrn.3866876> estimator, which bounds an omitted variable bias using auxiliary data.

Authors:Yujung Hwang [aut, cre]

# Install 'bndovb' in R:

install.packages('bndovb', repos = c('https://yujunghwang.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

auxdat_mecont - A simulated auxiliary data to show how to use 'bndovbme' function with continuous proxy variables
auxdat_medisc - A simulated auxiliary data to show how to use 'bndovbme' function with discrete proxy variables
auxdat_nome - A simulated auxiliary data to show how to use 'bndovb' function
maindat_mecont - A simulated main data to show how to use 'bndovbme' function with continuous proxy variables
maindat_medisc - A simulated main data to show how to use 'bndovbme' function with discrete proxy variables
maindat_nome - A simulated main data to show how to use 'bndovb' function

On CRAN:

Last updated 3 years agofrom:dc4479bacc. Checks:OK: 1 NOTE: 6. Indexed: yes.

Yujung Hwang

Last update: 2021-07-27
Started: 2021-03-17

Help page	Topics
A simulated auxiliary data to show how to use 'bndovbme' function with continuous proxy variables	auxdat_mecont
A simulated auxiliary data to show how to use 'bndovbme' function with discrete proxy variables	auxdat_medisc
A simulated auxiliary data to show how to use 'bndovb' function	auxdat_nome
bndovb	bndovb
bndovb_tuning	bndovb_tuning
bndovbme	bndovbme
bndovbme_tuning	bndovbme_tuning
A simulated main data to show how to use 'bndovbme' function with continuous proxy variables	maindat_mecont
A simulated main data to show how to use 'bndovbme' function with discrete proxy variables	maindat_medisc
A simulated main data to show how to use 'bndovb' function	maindat_nome