Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data Article Swipe
Yang Ning
,
Sida Peng
,
Jing Tao
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2009.03151
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2009.03151
This paper proposes a doubly robust two-stage semiparametric difference-in-difference estimator for estimating heterogeneous treatment effects with high-dimensional data. Our new estimator is robust to model miss-specifications and allows for, but does not require, many more regressors than observations. The first stage allows a general set of machine learning methods to be used to estimate the propensity score. In the second stage, we derive the rates of convergence for both the parametric parameter and the unknown function under a partially linear specification for the outcome equation. We also provide bias correction procedures to allow for valid inference for the heterogeneous treatment effects. We evaluate the finite sample performance with extensive simulation studies. Additionally, a real data analysis on the effect of Fair Minimum Wage Act on the unemployment rate is performed as an illustration of our method. An R package for implementing the proposed method is available on Github.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2009.03151
- https://arxiv.org/pdf/2009.03151
- OA Status
- green
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3083037704
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3083037704Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2009.03151Digital Object Identifier
- Title
-
Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional DataWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-07Full publication date if available
- Authors
-
Yang Ning, Sida Peng, Jing TaoList of authors in order
- Landing page
-
https://arxiv.org/abs/2009.03151Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2009.03151Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2009.03151Direct OA link when available
- Concepts
-
Estimator, Semiparametric model, Parametric statistics, Computer science, Inference, Semiparametric regression, Data set, Robust statistics, Average treatment effect, Rate of convergence, Econometrics, Mathematical optimization, Mathematics, Statistics, Artificial intelligence, Key (lock), Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.score. | 56 |
| abstract_inverted_index.second | 59 |
| abstract_inverted_index.stage, | 60 |
| abstract_inverted_index.Github. | 147 |
| abstract_inverted_index.Minimum | 121 |
| abstract_inverted_index.effects | 14 |
| abstract_inverted_index.general | 43 |
| abstract_inverted_index.machine | 46 |
| abstract_inverted_index.method. | 135 |
| abstract_inverted_index.methods | 48 |
| abstract_inverted_index.outcome | 83 |
| abstract_inverted_index.package | 138 |
| abstract_inverted_index.provide | 87 |
| abstract_inverted_index.unknown | 74 |
| abstract_inverted_index.analysis | 115 |
| abstract_inverted_index.effects. | 100 |
| abstract_inverted_index.estimate | 53 |
| abstract_inverted_index.evaluate | 102 |
| abstract_inverted_index.function | 75 |
| abstract_inverted_index.learning | 47 |
| abstract_inverted_index.proposed | 142 |
| abstract_inverted_index.proposes | 2 |
| abstract_inverted_index.require, | 32 |
| abstract_inverted_index.studies. | 110 |
| abstract_inverted_index.available | 145 |
| abstract_inverted_index.equation. | 84 |
| abstract_inverted_index.estimator | 9, 20 |
| abstract_inverted_index.extensive | 108 |
| abstract_inverted_index.inference | 95 |
| abstract_inverted_index.parameter | 71 |
| abstract_inverted_index.partially | 78 |
| abstract_inverted_index.performed | 129 |
| abstract_inverted_index.treatment | 13, 99 |
| abstract_inverted_index.two-stage | 6 |
| abstract_inverted_index.correction | 89 |
| abstract_inverted_index.estimating | 11 |
| abstract_inverted_index.parametric | 70 |
| abstract_inverted_index.procedures | 90 |
| abstract_inverted_index.propensity | 55 |
| abstract_inverted_index.regressors | 35 |
| abstract_inverted_index.simulation | 109 |
| abstract_inverted_index.convergence | 66 |
| abstract_inverted_index.performance | 106 |
| abstract_inverted_index.illustration | 132 |
| abstract_inverted_index.implementing | 140 |
| abstract_inverted_index.unemployment | 126 |
| abstract_inverted_index.Additionally, | 111 |
| abstract_inverted_index.heterogeneous | 12, 98 |
| abstract_inverted_index.observations. | 37 |
| abstract_inverted_index.specification | 80 |
| abstract_inverted_index.semiparametric | 7 |
| abstract_inverted_index.high-dimensional | 16 |
| abstract_inverted_index.miss-specifications | 25 |
| abstract_inverted_index.difference-in-difference | 8 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/8 |
| sustainable_development_goals[0].score | 0.7400000095367432 |
| sustainable_development_goals[0].display_name | Decent work and economic growth |
| citation_normalized_percentile |