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Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
A unified approach is proposed that makes it possible for researchers to preprocess data with matching and then to apply the best parametric techniques they would have used anyway and this procedure makes parametric models produce more accurate and considerably less model-dependent causal inferences.
MatchIt: Nonparametric Preprocessing for Parametric Causal Inference
MatchIt implements a wide range of sophisticated matching methods, making it possible to greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical modeling assumptions.
Estimating Causal Effects of Ballot Order from a Randomized Natural Experiment The California Alphabet Lottery, 1978–2002
Randomized natural experiments provide social scientists with rare opportunities to draw credible causal inferences in real-world settings. We capitalize on such a unique experiment to examine how…
The Supreme Court During Crisis: How War Affects Only Non-War Cases
Does the U.S. Supreme Court curtail rights and liberties when the nation's security is under threat? In hundreds of articles and books, and with renewed fervor since September 11, 2001, members of…
When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53,000+ legal holdings
- Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho
- Computer ScienceICAIL
- 18 April 2021
It is shown that domain pretraining may be warranted when the task exhibits sufficient similarity to the pretraining corpus: the level of performance increase in three legal tasks was directly tied to the domain specificity of the task.
Fudging the Nudge: Information Disclosure and Restaurant Grading
- Daniel E. Ho
- 1 December 2012
One of the most promising regulatory currents consists of “targeted” disclosure: mandating simplified information disclosure at the time of decisionmaking to “nudge” parties along. Its poster child…
Randomization Inference with Natural Experiments: An Analysis of Ballot Effects in the 2003 California Recall Election
Since the 2000 U.S. Presidential election, social scientists have rediscovered a long tradition of research that investigates the effects of ballot format on voting. Using a new dataset collected by…
Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies
Artificial intelligence (AI) promises to transform how government agencies do their work. Rapid developments in AI have the potential to reduce the cost of core governance functions, improve the…
Measuring Explicit Political Positions of Media
We amass a new, large-scale dataset of newspaper editorials that allows us to calculate fine-grained measures of the political positions of newspaper editorial pages. Collecting and classifying over…
Compliance and International Soft Law: Why Do Countries Implement the Basle Accord?
- Daniel E. Ho
- 1 August 2002
This article presents empirical research into why countries comply with international soft law. I examine economic and institutional determinants of implementation of the 1988 Basle Accord on capital…