mortgages

The <code>mortgages</code> data contains data from Fetter (2015) on home ownership rates by men, focusing on whether they were born at the right time to be eligible for mortgage subsidies based on their military service.

datasets

Example data sets to run the example
problems from causal inference textbooks. Currently, contains data
sets for Huntington-Klein, Nick (2021) "The Effect" <https://theeffectbook.net>,
Cunningham, Scott (2021, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape",
and Hern<c3><a1>n, Miguel and James Robins (2020) "Causal Inference: What If"
<https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.

Nick Huntington-Klein

causaldata

Example Data Sets for Causal Inference Textbooks

Malcolm Barrett

mortgages function

A data frame with 214144 rows and 6 variables<dl class="dl-horizontal">
 <dt>bpl</dt><dd>Birth State</dd>
 <dt>qob</dt><dd>Quarter of birth</dd>
 <dt>nonwhite</dt><dd>White/nonwhite race indicator. 1 = Nonwhite</dd>
 <dt>vet_wwko</dt><dd>Veteran of either the Korean war or World War II</dd>
 <dt>home_ownership</dt><dd>Owns a home</dd>
 <dt>qob_minus_kw</dt><dd>Quarter of birth centered on eligibility for mortgage subsidy (0+ = eligible)</dd>
</dl>

Format

Data from "How do Mortgage Subsidies Affect Home Ownership? Evidence from the Mid-Century GI Bills" — mortgages

A data frame with 214144 rows and 6 variables<dl class='dl-horizontal'>
 <dt>bpl</dt><dd>Birth State</dd>
 <dt>qob</dt><dd>Quarter of birth</dd>
 <dt>nonwhite</dt><dd>White/nonwhite race indicator. 1 = Nonwhite</dd>
 <dt>vet_wwko</dt><dd>Veteran of either the Korean war or World War II</dd>
 <dt>home_ownership</dt><dd>Owns a home</dd>
 <dt>qob_minus_kw</dt><dd>Quarter of birth centered on eligibility for mortgage subsidy (0+ = eligible)</dd>
</dl>

mortgages: Data from "How do Mortgage Subsidies Affect Home Ownership? Evidence from the Mid-Century GI Bills"

Description

Usage

Arguments

Format

Details

References