| 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 | 85 | 2015 |
| 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 | 77 | 2018 |
| 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 | 25* | 2013 |
| Increasing the credibility of the twin birth instrument H Farbmacher, R Guber, J Vikström Journal of Applied Econometrics 33 (3), 457-472, 2018 | 19 | 2018 |
| 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 | 8* | 2017 |
| An explainable attention network for fraud detection in claims management H Farbmacher, L Löw, M Spindler Journal of Econometrics, 2020 | 7 | 2020 |
| 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 | 7 | 2020 |
| Extensions of hurdle models for overdispersed count data H Farbmacher Health Economics 22 (11), 1398-1404, 2013 | 7 | 2013 |
| Causal mediation analysis with double machine learning H Farbmacher, M Huber, L Lafférs, H Langen, M Spindler arXiv preprint arXiv:2002.12710, 2020 | 6 | 2020 |
| Estimation of hurdle models for overdispersed count data H Farbmacher Stata Journal 11 (1), 82, 2011 | 6 | 2011 |
| Testing under a special form of heteroscedasticity H Farbmacher, H Kögel Applied Economics Letters 24 (4), 264-268, 2017 | 5* | 2017 |
| Instrument validity tests with causal forests H Farbmacher, R Guber, S Klaassen Journal of Business & Economic Statistics, 1-10, 2020 | 4 | 2020 |
| 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 |
| Semiparametric count data modeling with an application to health service demand P Bach, H Farbmacher, M Spindler Econometrics and statistics 8, 125-140, 2018 | 3 | 2018 |
| Heterogeneous Effects of Poverty on Cognition H Farbmacher, H Kögel, M Spindler MEA Discussion Paper, 2019 | 2 | 2019 |
| Estimating grouped patterns of heterogeneity in repeated public goods experiments S Bordt, H Farbmacher, H Kögel Working paper, 2019 | 2 | 2019 |
| SIVREG: Stata module to perform adaptive Lasso with some invalid instruments H Farbmacher Boston College Department of Economics, 2018 | 2 | 2018 |
| Heterogeneous Effects of Poverty on Attention H Farbmacher, H Kögel, M Spindler Labour Economics, 102028, 2021 | | 2021 |
| Linear fixed-effects estimation with non-repeated outcomes H Farbmacher, H Tauchmann FAU Discussion Papers in Economics, 2021 | | 2021 |
| Finite sample properties of the GMM Anderson–Rubin test MJG Bun, H Farbmacher, RW Poldermans Econometric Reviews 39 (10), 1042-1056, 2020 | | 2020 |
Neil M DaviesMRC Integrative Epidemiology Unit (IEU) at the University of BristolBestätigte E-Mail-Adresse bei bristol.ac.uk
