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Jann Spiess
Title
Cited by
Cited by
Year
Machine learning: an applied econometric approach
S Mullainathan, J Spiess
Journal of Economic Perspectives 31 (2), 87-106, 2017
22392017
Revisiting event-study designs: robust and efficient estimation
K Borusyak, X Jaravel, J Spiess
Review of Economic Studies, rdae007, 2024
14942024
Big data and discrimination
TB Gillis, JL Spiess
The University of Chicago Law Review 86 (2), 459-488, 2019
1902019
Robust post-matching inference
A Abadie, J Spiess
Journal of the American Statistical Association 117 (538), 983-995, 2022
1812022
Megastudies improve the impact of applied behavioural science
KL Milkman, D Gromet, H Ho, JS Kay, TW Lee, P Pandiloski, Y Park, A Rai, ...
Nature 600 (7889), 478-483, 2021
1752021
A 680,000-person megastudy of nudges to encourage vaccination in pharmacies
KL Milkman, L Gandhi, MS Patel, HN Graci, DM Gromet, H Ho, JS Kay, ...
Proceedings of the National Academy of Sciences 119 (6), e2115126119, 2022
1152022
Blueprint for a cyclical shock insurance in the euro area
H Enderlein, J Spiess, L Guttenberg, A Vitorino
Notre Europe, 2013
1032013
Machine-learning tests for effects on multiple outcomes
J Ludwig, S Mullainathan, J Spiess
arXiv preprint arXiv:1707.01473, 2017
332017
Making One Size Fit All: Designing at Cyclical Adjustment Insurance Fund for the Eurozone
H Enderlein, L Guttenberg, J Spiess
Jacques Delors Institut, 2013
332013
Optimal estimation when researcher and social preferences are misaligned
J Spiess
Unpublished Manuscript, 2018
292018
A design-based perspective on synthetic control methods
L Bottmer, GW Imbens, J Spiess, M Warnick
Journal of Business & Economic Statistics 42 (2), 762-773, 2024
202024
Augmenting pre-analysis plans with machine learning
J Ludwig, S Mullainathan, J Spiess
Aea papers and proceedings 109, 71-76, 2019
182019
Synthetic design: An optimization approach to experimental design with synthetic controls
N Doudchenko, K Khosravi, J Pouget-Abadie, S Lahaie, M Lubin, ...
Advances in Neural Information Processing Systems 34, 8691-8701, 2021
152021
On the fairness of machine-assisted human decisions
T Gillis, B McLaughlin, J Spiess
arXiv preprint arXiv:2110.15310, 2021
152021
Unpacking the black box: Regulating algorithmic decisions
L Blattner, S Nelson, J Spiess
arXiv preprint arXiv:2110.03443, 2021
152021
Improving inference from simple instruments through compliance estimation
S Coussens, J Spiess
arXiv preprint arXiv:2108.03726, 2021
122021
Algorithmic assistance with recommendation-dependent preferences
B McLaughlin, J Spiess
arXiv preprint arXiv:2208.07626, 2022
92022
Machine Learning Explainability and Fairness: Insights from Consumer Lending
L Blattner, J Spiess
FinRegLab Empirical White Paper, 2022
7*2022
Double and single descent in causal inference with an application to high-dimensional synthetic control
J Spiess, G Imbens, A Venugopal
Advances in Neural Information Processing Systems 36, 2024
52024
Machine learning who to nudge: causal vs predictive targeting in a field experiment on student financial aid renewal
S Athey, N Keleher, J Spiess
arXiv preprint arXiv:2310.08672, 2023
52023
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