| On the use of the lasso for instrumental variables estimation with some invalid instruments F Windmeijer, H Farbmacher, N Davies, G Davey Smith Journal of the American Statistical Association, 2018 | 161 | 2018 |
| The many weak instruments problem and Mendelian randomization NM Davies, S Hinke Kessler Scholder, H Farbmacher, S Burgess, ... Statistics in Medicine 34 (3), 454-468, 2015 | 155 | 2015 |
| Causal mediation analysis with double machine learning H Farbmacher, M Huber, L Lafférs, H Langen, M Spindler The Econometrics Journal 25 (2), 277-300, 2022 | 73 | 2022 |
| Increasing the credibility of the twin birth instrument H Farbmacher, R Guber, J Vikström Journal of Applied Econometrics 33 (3), 457-472, 2018 | 39 | 2018 |
| An explainable attention network for fraud detection in claims management H Farbmacher, L Löw, M Spindler Journal of Econometrics 228 (2), 244-258, 2022 | 38 | 2022 |
| Per‐Period Co‐Payments And The Demand For Health Care: Evidence From Survey And Claims Data H Farbmacher, J Winter Health Economics 22 (9), 1111-1123, 2013 | 35* | 2013 |
| Heterogeneous effects of poverty on attention H Farbmacher, H Kögel, M Spindler Labour Economics 71, 102028, 2021 | 26 | 2021 |
| Double trouble: The burden of child-rearing and working on maternal mortality T Bucher-Koenen, H Farbmacher, R Guber, J Vikström Demography 57 (2), 559-576, 2020 | 24 | 2020 |
| Instrument validity tests with causal forests H Farbmacher, R Guber, S Klaassen Journal of Business & Economic Statistics 40 (2), 605-614, 2022 | 17 | 2022 |
| Heterogeneous effects of a nonlinear price schedule for outpatient care H Farbmacher, P Ihle, I Schubert, J Winter, A Wuppermann Health Economics 26 (10), 1234-1248, 2017 | 16* | 2017 |
| Estimation of hurdle models for overdispersed count data H Farbmacher Stata Journal 11 (1), 82, 2011 | 13 | 2011 |
| Extensions of hurdle models for overdispersed count data H Farbmacher Health Economics 22 (11), 1398-1404, 2013 | 11 | 2013 |
| Testing under a special form of heteroscedasticity H Farbmacher, H Kögel Applied Economics Letters 24 (4), 264-268, 2017 | 10 | 2017 |
| Linear fixed-effects estimation with nonrepeated outcomes H Farbmacher, H Tauchmann Econometric Reviews 42 (8), 635-654, 2023 | 9 | 2023 |
| Semiparametric count data modeling with an application to health service demand P Bach, H Farbmacher, M Spindler Econometrics and statistics 8, 125-140, 2018 | 6 | 2018 |
| Finite sample properties of the GMM Anderson–Rubin test MJG Bun, H Farbmacher, RW Poldermans Econometric Reviews 39 (10), 1042-1056, 2020 | 5 | 2020 |
| Estimating grouped patterns of heterogeneity in repeated public goods experiments S Bordt, H Farbmacher, H Kögel Working paper, 2019 | 5 | 2019 |
| GMM with many weak moment conditions: Replication and application of Newey and Windmeijer (2009) H Farbmacher Journal of Applied Econometrics 27 (2), 343-346, 2012 | 4 | 2012 |
| SIVREG: Stata module to perform adaptive Lasso with some invalid instruments H Farbmacher Boston College Department of Economics, 2018 | 3 | 2018 |
| Detecting grouped local average treatment effects and selecting true instruments N Apfel, H Farbmacher, R Groh, M Huber, H Langen arXiv preprint arXiv:2207.04481, 2022 | 2 | 2022 |
Neil M DaviesUniversity College London, Division of Psychiatry, Department of Statistical ScienceVerified email at ucl.ac.uk
