Helmut Farbmacher
Helmut Farbmacher
Munich Center for the Economics of Aging (MEA), Max Planck Society
Bestätigte E-Mail-Adresse bei mea.mpisoc.mpg.de - Startseite
Zitiert von
Zitiert von
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
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
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
Increasing the credibility of the twin birth instrument
H Farbmacher, R Guber, J Vikström
Journal of Applied Econometrics 33 (3), 457-472, 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
Extensions of hurdle models for overdispersed count data
H Farbmacher
Health Economics 22 (11), 1398-1404, 2013
Estimation of hurdle models for overdispersed count data
H Farbmacher
Stata Journal 11 (1), 82, 2011
Testing under a special form of heteroscedasticity
H Farbmacher, H Kögel
Applied Economics Letters 24 (4), 264-268, 2017
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
Double Trouble: The Burden of Child-rearing and Working on Maternal Mortality
T Bucher-Koenen, H Farbmacher, R Guber, J Vikström
Demography, 1-18, 2020
An explainable attention network for fraud detection in claims management
H Farbmacher, L Löw, M Spindler
Journal of Econometrics, 2020
Instrument Validity Tests with Causal Forests
H Farbmacher, R Guber, S Klaassen
MEA Discussion Paper, 2020
Semiparametric count data modeling with an application to health service demand
P Bach, H Farbmacher, M Spindler
Econometrics and statistics 8, 125-140, 2018
SIVREG: Stata module to perform adaptive Lasso with some invalid instruments
H Farbmacher
Boston College Department of Economics, 2018
Causal mediation analysis with double machine learning
H Farbmacher, M Huber, H Langen, M Spindler
arXiv preprint arXiv:2002.12710, 2020
Heterogeneous Effects of Poverty on Cognition
H Farbmacher, H Kögel, M Spindler
MEA Discussion Paper, 2019
Estimating Grouped Patterns of Heterogeneity in Repeated Public Goods Experiments
S Bordt, H Farbmacher, H Kögel
Working paper, 2019
Finite sample properties of the GMM Anderson–Rubin test
MJG Bun, H Farbmacher, RW Poldermans
Econometric Reviews, 1-15, 2020
On the Effect of Imputation on the 2SLS Variance
H Farbmacher, A Kann
arXiv preprint arXiv:1903.11004, 2019
NWIND: Stata module to compute Newey-Windmeijer VCE after ivreg2 GMM-CUE estimation
H Farbmacher
Boston College Department of Economics, 2014
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