fetch_401k: Data set on financial wealth and 401(k) plan participation.
In DoubleML: Double Machine Learning in R

fetch_401k

R Documentation

Data set on financial wealth and 401(k) plan participation.

Description

Preprocessed data set on financial wealth and 401(k) plan participation. The raw data files are preprocessed to reproduce the examples in Chernozhukov et al. (2020). An internet connection is required to sucessfully download the data set.

Usage

fetch_401k(
  return_type = "DoubleMLData",
  polynomial_features = FALSE,
  instrument = FALSE
)

Arguments

`return_type`	(`character(1)`) If `"DoubleMLData"`, returns a `DoubleMLData` object. If `"data.frame"` returns a `data.frame()`. If `"data.table"` returns a `data.table()`. Default is `"DoubleMLData"`.
`polynomial_features`	(`logical(1)`) If `TRUE` polynomial freatures are added (see replication file of Chernozhukov et al. (2018)).
`instrument`	(`logical(1)`) If `TRUE`, the returned data object contains the variables `e401` and `p401`. If `return_type = "DoubleMLData"`, the variable `e401` is used as an instrument for the endogenous treatment variable `p401`. If `FALSE`, `p401` is removed from the data set.

Details

Variable description, based on the supplementary material of Chernozhukov et al. (2020):

net_tfa: net total financial assets
e401: = 1 if employer offers 401(k)
p401: = 1 if individual participates in a 401(k) plan
age: age
inc: income
fsize: family size
educ: years of education
db: = 1 if individual has defined benefit pension
marr: = 1 if married
twoearn: = 1 if two-earner household
pira: = 1 if individual participates in IRA plan
hown: = 1 if home owner

The supplementary data of the study by Chernozhukov et al. (2018) is available at https://academic.oup.com/ectj/article/21/1/C1/5056401#supplementary-data.

Value

A data object according to the choice of return_type.

References

Abadie, A. (2003), Semiparametric instrumental variable estimation of treatment response models. Journal of Econometrics, 113(2): 231-263.

Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W. and Robins, J. (2018), Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21: C1-C68. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/ectj.12097")}.

DoubleML documentation built on June 22, 2024, 10:50 a.m.