TY - GEN
T1 - Automated local regression discontinuity design discovery
AU - Herlands, William
AU - Wilson, Andrew Gordon
AU - McFowland, Edward
AU - Neill, Daniel B.
N1 - Publisher Copyright:
© 2018 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery.
PY - 2018/7/19
Y1 - 2018/7/19
N2 - Inferring causal relationships in observational data is crucial for understanding scientific and social processes. We develop the first statistical machine learning approach for automatically discovering regression discontinuity designs (RDDs), a quasi-experimental setup often used in econometrics. Our method identifies interpretable, localized RDDs in arbitrary dimensional data and can seamlessly compute treatment effects without expert supervision. By applying the technique to a variety of synthetic and real datasets, we demonstrate robust performance under adverse conditions including unobserved variables, substantial noise, and model misspecification.
AB - Inferring causal relationships in observational data is crucial for understanding scientific and social processes. We develop the first statistical machine learning approach for automatically discovering regression discontinuity designs (RDDs), a quasi-experimental setup often used in econometrics. Our method identifies interpretable, localized RDDs in arbitrary dimensional data and can seamlessly compute treatment effects without expert supervision. By applying the technique to a variety of synthetic and real datasets, we demonstrate robust performance under adverse conditions including unobserved variables, substantial noise, and model misspecification.
KW - Natural experiments
KW - Pattern detection
KW - Regression discontinuity
UR - http://www.scopus.com/inward/record.url?scp=85051562408&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051562408&partnerID=8YFLogxK
U2 - 10.1145/3219819.3219982
DO - 10.1145/3219819.3219982
M3 - Conference contribution
AN - SCOPUS:85051562408
SN - 9781450355520
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 1512
EP - 1520
BT - KDD 2018 - Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
T2 - 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018
Y2 - 19 August 2018 through 23 August 2018
ER -