Helmut Farbmacher

Personal Details

First Name:	Helmut
Middle Name:
Last Name:	Farbmacher
Suffix:
RePEc Short-ID:	pfa342
	[This author has chosen not to make the email address public]

Affiliation

Münchener Zentrum für Ökonomie und Demographischen Wandel
Max-Planck-Institut für Sozialrecht und Sozialpolitik
Max-Planck-Gesellschaft

München, Germany
http://mea.mpisoc.mpg.de/
RePEc:edi:memande (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)

1. Helmut Farbmacher, 2012. "GMM with many weak moment conditions: Replication and application of Newey and Windmeijer (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 343-346, March.

   Mentioned in:

   1. GMM with many weak moment conditions: Replication and application of Newey and Windmeijer (2009) (Journal of Applied Econometrics 2012) in ReplicationWiki ()

Working papers

1. Farbmacher, Helmut & Tauchmann, Harald, 2021. "Linear fixed-effects estimation with non-repeated outcomes," FAU Discussion Papers in Economics 03/2021, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2021.

   Cited by:

   1. Jaka Cepec & Peter Grajzl & Barbara Mörec, 2022. "Public cash and modes of firm exit," Journal of Evolutionary Economics, Springer, vol. 32(1), pages 247-298, January.
   2. Sam Desiere & Bart Cockx, 2021. "How effective are hiring subsidies to reduce long-term unemployment among prime-aged jobseekers? Evidence from Belgium," LIDAM Discussion Papers IRES 2021024, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
      • Desiere, Sam & Cockx, Bart, 2021. "How effective are hiring subsidies to reduce long-term unemployment among prime-aged jobseekers? Evidence from Belgium," ROA Research Memorandum 005, Maastricht University, Research Centre for Education and the Labour Market (ROA).
      • Desiere, Sam & Cockx, Bart, 2021. "How Effective Are Hiring Subsidies to Reduce Long-Term Unemployment among Prime-Aged Jobseekers? Evidence from Belgium," IZA Discussion Papers 14767, Institute of Labor Economics (IZA).
      • Sam Desiere & Bart Cockx, 2021. "How effective are hiring subsidies to reduce long-term unemployment among prime-aged jobseekers? Evidence from Belgium," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1025, Ghent University, Faculty of Economics and Business Administration.
      • Sam Desiere & Bart Cockx, 2021. "How Effective Are Hiring Subsidies to Reduce Long-Term Unemployment among Prime-Aged Jobseekers? Evidence from Belgium," CESifo Working Paper Series 9325, CESifo.

2. Bucher-Koenen, Tabea & Farbmacher, Helmut & Guber, Raphael & Vikström, Johan, 2020. "Double trouble: The burden of child rearing and working on maternal mortality," Working Paper Series 2020:7, IFAU - Institute for Evaluation of Labour Market and Education Policy.
   • Tabea Bucher-Koenen & Helmut Farbmacher & Raphael Guber & Johan Vikström, 2020. "Double Trouble: The Burden of Child-rearing and Working on Maternal Mortality," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 559-576, April.

   Cited by:

   1. Yan Xiong & Guojin Jiao & Jiaming Zheng & Jian Gao & Yaqing Xue & Buwei Tian & Jingmin Cheng, 2022. "Fertility Intention and Influencing Factors for Having a Second Child among Floating Women of Childbearing Age," IJERPH, MDPI, vol. 19(24), pages 1-12, December.
   2. Öberg, Stefan, 2018. "Instrumental variables based on twin births are by definition not valid (v.3.0)," SocArXiv zux9s, Center for Open Science.
   3. XIE Mingjia & YIN Ting & ZHANG Yi & OSHIO Takashi, 2022. "The Hidden Cost of Having More Children: The Impact of Fertility on the Elderly's Healthcare Utilization," Discussion papers 22033, Research Institute of Economy, Trade and Industry (RIETI).
   4. Gerrit Bauer & Martina Brandt & Thorsten Kneip, 2023. "The Role of Parenthood for Life Satisfaction of Older Women and Men in Europe," Journal of Happiness Studies, Springer, vol. 24(1), pages 275-307, January.
   5. Beatrice Baaba Tawiah, 2023. "The Effect of Children on Health," Working Papers Dissertations 103, Paderborn University, Faculty of Business Administration and Economics.

3. Helmut Farbmacher & Martin Huber & Luk'av{s} Laff'ers & Henrika Langen & Martin Spindler, 2020. "Causal mediation analysis with double machine learning," Papers 2002.12710, arXiv.org, revised Feb 2021.
   • Helmut Farbmacher & Martin Huber & Lukáš Lafférs & Henrika Langen & Martin Spindler, 2022. "Causal mediation analysis with double machine learning [Mediation analysis via potential outcomes models]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 277-300.
   • Farbmacher, Helmut & Huber, Martin & Langen, Henrika & Spindler, Martin, 2020. "Causal mediation analysis with double machine learning," FSES Working Papers 515, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

   Cited by:

   1. AmirEmad Ghassami & Andrew Ying & Ilya Shpitser & Eric Tchetgen Tchetgen, 2021. "Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference," Papers 2104.02929, arXiv.org, revised Mar 2022.
   2. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
   3. Hugo Bodory & Martin Huber & Lukáš Lafférs, 2022. "Evaluating (weighted) dynamic treatment effects by double machine learning [Identification of causal effects using instrumental variables]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 628-648.
      • Hugo Bodory & Martin Huber & Luk'av{s} Laff'ers, 2020. "Evaluating (weighted) dynamic treatment effects by double machine learning," Papers 2012.00370, arXiv.org, revised Jun 2021.
   4. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org.
   5. Nora Bearth & Michael Lechner, 2024. "Causal Machine Learning for Moderation Effects," Papers 2401.08290, arXiv.org, revised Apr 2024.
   6. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
   7. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
   8. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
      • Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2022. "Automatic Debiased Machine Learning of Causal and Structural Effects," Econometrica, Econometric Society, vol. 90(3), pages 967-1027, May.
   9. Xinyu Wei & Mingwang Cheng & Kaifeng Duan & Xiangxing Kong, 2024. "Effects of Big Data on PM 2.5 : A Study Based on Double Machine Learning," Land, MDPI, vol. 13(3), pages 1-21, March.
   10. Rahul Singh & Liyuan Xu & Arthur Gretton, 2021. "Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves," Papers 2111.03950, arXiv.org, revised Jul 2023.

4. Farbmacher, Helmut & Guber, Raphael & Vikström, Johan, 2016. "Increasing the credibility of the Twin birth instrument," Working Paper Series 2016:10, IFAU - Institute for Evaluation of Labour Market and Education Policy.
   • Helmut Farbmacher & Raphael Guber & Johan Vikström, 2018. "Increasing the credibility of the twin birth instrument," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 457-472, April.

   Cited by:

   1. Tabea Bucher-Koenen & Helmut Farbmacher & Raphael Guber & Johan Vikström, 2020. "Double Trouble: The Burden of Child-rearing and Working on Maternal Mortality," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 559-576, April.
      • Bucher-Koenen, Tabea & Farbmacher, Helmut & Guber, Raphael & Vikström, Johan, 2020. "Double trouble: The burden of child rearing and working on maternal mortality," Working Paper Series 2020:7, IFAU - Institute for Evaluation of Labour Market and Education Policy.
   2. Joseph Boniface Ajefu, 2019. "Does having children affect women’s entrepreneurship decision? Evidence from Nigeria," Review of Economics of the Household, Springer, vol. 17(3), pages 843-860, September.
   3. Boyan Zheng & Qiongshi Lu & Jason Fletcher, 2023. "Estimating Causal Effects of Fertility on Life Course Outcomes: Evidence Using A Dyadic Genetic Instrumental Variable Approach," NBER Working Papers 30955, National Bureau of Economic Research, Inc.
   4. Manuel Denzer, 2019. "Estimating Causal Effects in Binary Response Models with Binary Endogenous Explanatory Variables - A Comparison of Possible Estimators," Working Papers 1916, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
   5. Mark E. McGovern, 2018. "How Much Does Birth Weight Matter for Child Health in Developing Countries? Estimates from Siblings and Twins," CHaRMS Working Papers 18-04, Centre for HeAlth Research at the Management School (CHaRMS).
      • Mark E. McGovern, 2019. "How much does birth weight matter for child health in developing countries? Estimates from siblings and twins," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 3-22, January.
      • McGovern, Mark E., 2014. "How Much Does Birth Weight Matter for Child Health in Developing Countries? Estimates from Siblings and Twins," Working Paper 143921, Harvard University OpenScholar.
   6. Beatrice Baaba Tawiah, 2023. "The Effect of Children on Health," Working Papers Dissertations 103, Paderborn University, Faculty of Business Administration and Economics.
   7. Tumen, Semih & Turan, Belgi, 2020. "The Effect of Fertility on Female Labor Supply in a Labor Market with Extensive Informality," IZA Discussion Papers 13986, Institute of Labor Economics (IZA).
      • Semih Tumen & Belgi Turan, 2023. "The effect of fertility on female labor supply in a labor market with extensive informality," Empirical Economics, Springer, vol. 65(4), pages 1855-1894, October.
   8. Erika Raquel Badillo & Lina Cardona-Sosa & Carlos Medina & Leonardo Fabio Morales & Christian Posso, 2019. "Twin instrument, fertility and women’s labor force participation: evidence from Colombian low-income families," Borradores de Economia 1071, Banco de la Republica de Colombia.
   9. Cepaluni, Gabriel & Chewning, Taylor Kinsley & Driscoll, Amanda & Faganello, Marco Antonio, 2022. "Conditional cash transfers and child labor," World Development, Elsevier, vol. 152(C).

5. Bach, P. & Farbmacher, H. & Spindler, M., 2016. "Semiparametric Count Data Modeling with an Application to Health Service Demand," Health, Econometrics and Data Group (HEDG) Working Papers 16/20, HEDG, c/o Department of Economics, University of York.
   • Bach, Philipp & Farbmacher, Helmut & Spindler, Martin, 2018. "Semiparametric count data modeling with an application to health service demand," Econometrics and Statistics, Elsevier, vol. 8(C), pages 125-140.
   • Bach, Philipp & Farbmacher, Helmut & Spindler, Martin, 2017. "Semiparametric count data modeling with an application to health service demand," hche Research Papers 15, University of Hamburg, Hamburg Center for Health Economics (hche).

   Cited by:

   1. Hofer, Florian & Birkner, Benjamin & Spindler, Martin, 2021. "Power of machine learning algorithms for predicting dropouts from a German telemonitoring program using standardized claims data," hche Research Papers 24, University of Hamburg, Hamburg Center for Health Economics (hche).
   2. Liu, Weiwei & Egan, Kevin J, 2019. "A Semiparametric Smooth Coefficient Estimator for Recreation Demand," MPRA Paper 95294, University Library of Munich, Germany.
      • Weiwei Liu & Kevin J. Egan, 2019. "A Semiparametric Smooth Coefficient Estimator for Recreation Demand," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 1163-1187, November.
   3. Corsini, Noemi & Viroli, Cinzia, 2022. "Dealing with overdispersion in multivariate count data," Computational Statistics & Data Analysis, Elsevier, vol. 170(C).

6. Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2016. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Bristol Economics Discussion Papers 16/674, School of Economics, University of Bristol, UK, revised 08 Aug 2017.
   • Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2019. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(527), pages 1339-1350, July.
   • Windmeijer, Frank & Farbmacher, Helmut & Davies, Neil & Smith, George Davey, 2017. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168196, Verein für Socialpolitik / German Economic Association.
   • Windmeijer, F.; Farbmacher, H.; Davies, N.; Davey Smith, G.;, 2017. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Health, Econometrics and Data Group (HEDG) Working Papers 17/22, HEDG, c/o Department of Economics, University of York.

   Cited by:

   1. Caner, Mehmet & Fan, Qingliang & Grennes, Thomas, 2021. "Partners in debt: An endogenous non-linear analysis of the effects of public and private debt on growth," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 694-711.
   2. Nicolas Apfel & Helmut Farbmacher & Rebecca Groh & Martin Huber & Henrika Langen, 2022. "Detecting Grouped Local Average Treatment Effects and Selecting True Instruments," Papers 2207.04481, arXiv.org, revised Oct 2023.
   3. Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Jul 2022.
   4. Martin, Stephen & Claxton, Karl & Lomas, James & Longo, Francesco, 2023. "The impact of different types of NHS expenditure on health: Marginal cost per QALY estimates for England for 2016/17," Health Policy, Elsevier, vol. 132(C).
   5. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
   6. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
   7. Frank Windmeijer & Xiaoran Liang & Fernando P Hartwig & Jack Bowden, 2019. "The Confidence Interval Method for Selecting Valid Instrumental Variables," Bristol Economics Discussion Papers 19/715, School of Economics, University of Bristol, UK.
      • Frank Windmeijer & Xiaoran Liang & Fernando P. Hartwig & Jack Bowden, 2021. "The confidence interval method for selecting valid instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 752-776, September.
   8. Marcus Munafò & Neil M. Davies & George Davey Smith, 2020. "Can genetics reveal the causes and consequences of educational attainment?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 681-688, February.
   9. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics and Public Policy Working Papers 2019-04, University of Adelaide, School of Economics and Public Policy.
   10. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
       • Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
       • Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
   11. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
   12. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised Mar 2023.
   13. Kumari, Meena & Bao, Yanchun & S. Clarke, Paul & Smart, Melissa, 2018. "A comparison of robust methods for Mendelian randomization using multiple genetic variants," ISER Working Paper Series 2018-08, Institute for Social and Economic Research.
   14. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
   15. Nicolas Apfel & Frank Windmeijer, 2022. "The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction," Papers 2212.04814, arXiv.org, revised Apr 2024.
   16. Hyunseung Kang & Youjin Lee & T. Tony Cai & Dylan S. Small, 2022. "Two robust tools for inference about causal effects with invalid instruments," Biometrics, The International Biometric Society, vol. 78(1), pages 24-34, March.
   17. Liang, X.; & Sanderson, E.; & Windmeijer, F.;, 2022. "Selecting Valid Instrumental Variables in Linear Models with Multiple Exposure Variables: Adaptive Lasso and the Median-of-Medians Estimator," Health, Econometrics and Data Group (HEDG) Working Papers 22/22, HEDG, c/o Department of Economics, University of York.
       • Xiaoran Liang & Eleanor Sanderson & Frank Windmeijer, 2022. "Selecting Valid Instrumental Variables in Linear Models with Multiple Exposure Variables: Adaptive Lasso and the Median-of-Medians Estimator," Papers 2208.05278, arXiv.org.
   18. Kogure, Katsuo & Kubo, Masahiro, 2022. "Cambodian Refugees," Discussion paper series HIAS-E-125, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
   19. Biewen, Martin & Fitzenberger, Bernd & Seckler, Matthias, 2020. "Counterfactual quantile decompositions with selection correction taking into account Huber/Melly (2015): An application to the German gender wage gap," Labour Economics, Elsevier, vol. 67(C).
   20. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
   21. Yiqi Lin & Frank Windmeijer & Xinyuan Song & Qingliang Fan, 2022. "On the instrumental variable estimation with many weak and invalid instruments," Papers 2207.03035, arXiv.org, revised Dec 2023.
   22. Ruoyu Wang & Qihua Wang & Wang Miao, 2023. "A robust fusion-extraction procedure with summary statistics in the presence of biased sources," Biometrika, Biometrika Trust, vol. 110(4), pages 1023-1040.
   23. Christian M. Dahl & Torben S. D. Johansen & Emil N. S{o}rensen & Christian E. Westermann & Simon F. Wittrock, 2021. "Applications of Machine Learning in Document Digitisation," Papers 2102.03239, arXiv.org.
   24. Christoph F. Kurz & Michael Laxy, 2020. "Application of Mendelian Randomization to Investigate the Association of Body Mass Index with Health Care Costs," Medical Decision Making, , vol. 40(2), pages 156-169, February.

7. Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie C. Wuppermann, 2013. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," CESifo Working Paper Series 4499, CESifo.
   • Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie Wuppermann, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Health Economics, John Wiley & Sons, Ltd., vol. 26(10), pages 1234-1248, October.
   • Farbmacher, Helmut & Ihle, Peter & Schubert, Ingrid & Winter, Joachim & Wuppermann, Amelie, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Munich Reprints in Economics 49875, University of Munich, Department of Economics.

   Cited by:

   1. Michael Gerfin & Boris Kaiser & Christian Schmid, 2014. "Health Care Demand in the Presence of Discrete Price Changes," Diskussionsschriften dp1403, Universitaet Bern, Departement Volkswirtschaft.
      • Michael Gerfin & Boris Kaiser & Christian Schmid, 2015. "Healthcare Demand in the Presence of Discrete Price Changes," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1164-1177, September.
      • Gerfin, M. & Kaiser, B. & Schmid, C., 2014. "Health Care Demand in the Presence of Discrete Price Changes," Health, Econometrics and Data Group (HEDG) Working Papers 14/22, HEDG, c/o Department of Economics, University of York.
   2. Klein, Tobias & Salm, Martin & Upadhyay, Suraj, 2020. "The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Disconti," CEPR Discussion Papers 14552, C.E.P.R. Discussion Papers.
   3. Stefanie Thönnes, 2019. "Ex-post moral hazard in the health insurance market: empirical evidence from German data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(9), pages 1317-1333, December.
   4. Giampiero Marra & Matteo Fasiolo & Rosalba Radice & Rainer Winkelmann, 2022. "A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health," ECON - Working Papers 413, Department of Economics - University of Zurich.
      • Giampiero Marra & Matteo Fasiolo & Rosalba Radice & Rainer Winkelmann, 2023. "A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1305-1322, June.
   5. Sá, Luís & Straume, Odd Rune, 2021. "Quality provision in hospital markets with demand inertia: The role of patient expectations," Journal of Health Economics, Elsevier, vol. 80(C).
      • Luís Sá & Odd Rune Straume, 2020. "Quality provision in hospital markets with demand inertia:The role of patient expectations," NIPE Working Papers 03/2020, NIPE - Universidade do Minho.
   6. Johansson, Naimi & de New, Sonja C. & Kunz, Johannes S. & Petrie, Dennis & Svensson, Mikael, 2023. "Reductions in out-of-pocket prices and forward-looking moral hazard in health care demand," Journal of Health Economics, Elsevier, vol. 87(C).
   7. Galina Besstremyannaya, 2012. "Heterogeneous effect of coinsurance rate on the demand for health care: a finite mixture approach," Working Papers w0163, New Economic School (NES).
   8. Klein, Tobias J. & Salm, Martin & Upadhyay, Suraj, 2020. "The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Discontinuities Design," IZA Discussion Papers 13108, Institute of Labor Economics (IZA).
      • Klein, Tobias J. & Salm, Martin & Upadhyay, Suraj, 2022. "The response to dynamic incentives in insurance contracts with a deductible: Evidence from a differences-in-regression-discontinuities design," Journal of Public Economics, Elsevier, vol. 210(C).
   9. Winkelmann, Rainer, 2015. "An empirical model of health care demand under non-linear pricing," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113027, Verein für Socialpolitik / German Economic Association.
      • Rainer Winkelmann, 2014. "An Empirical Model of Health Care Demand under Non-linear Pricing," SOEPpapers on Multidisciplinary Panel Data Research 688, DIW Berlin, The German Socio-Economic Panel (SOEP).
   10. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.
   11. Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie Wuppermann, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Health Economics, John Wiley & Sons, Ltd., vol. 26(10), pages 1234-1248, October.
       • Farbmacher, Helmut & Ihle, Peter & Schubert, Ingrid & Winter, Joachim & Wuppermann, Amelie, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Munich Reprints in Economics 49875, University of Munich, Department of Economics.
       • Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie C. Wuppermann, 2013. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," CESifo Working Paper Series 4499, CESifo.
   12. Johannes S. Kunz & Rainer Winkelmann, 2015. "An econometric model of health care demand with non-linear pricing," ECON - Working Papers 204, Department of Economics - University of Zurich.
       • Johannes S. Kunz & Rainer Winkelmann, 2017. "An Econometric Model of Healthcare Demand With Nonlinear Pricing," Health Economics, John Wiley & Sons, Ltd., vol. 26(6), pages 691-702, June.

8. Farbmacher, Helmut, 2009. "Copayments for doctor visits in Germany and the probability of visiting a physician - Evidence from a natural experiment," Discussion Papers in Economics 10951, University of Munich, Department of Economics.

   Cited by:

   1. Schmitz, Hendrik, 2013. "Practice budgets and the patient mix of physicians – The effect of a remuneration system reform on health care utilisation," Journal of Health Economics, Elsevier, vol. 32(6), pages 1240-1249.
   2. Eibich, Peter & Ziebarth, Nicolas R., 2014. "Analyzing regional variation in health care utilization using (rich) household microdata," Health Policy, Elsevier, vol. 114(1), pages 41-53.
      • Eibich, Peter & Ziebarth, Nicolas R., 2014. "Analyzing Regional Variation in Health Care Utilization Using (Rich) Household Microdata," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 114(1), pages 41-53.
      • Peter Eibich & Nicolas R. Ziebarth, 2013. "Analyzing Regional Variation in Health Care Utilization Using (Rich) Household Microdata," SOEPpapers on Multidisciplinary Panel Data Research 551, DIW Berlin, The German Socio-Economic Panel (SOEP).
      • Eibich, P. & Ziebarth, N., 2013. "Analyzing Regional Variation in Health Care Utilization Using (Rich) Household Microdata," Health, Econometrics and Data Group (HEDG) Working Papers 13/12, HEDG, c/o Department of Economics, University of York.
      • Eibich, Peter & Ziebarth, Nicolas R., 2013. "Analyzing Regional Variation in Health Care Utilization Using (Rich) Household Microdata," IZA Discussion Papers 7409, Institute of Labor Economics (IZA).
   3. Mingming Xu & Benjamin Bittschi, 2022. "Does the abolition of copayment increase ambulatory care utilization?: a quasi-experimental study in Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(8), pages 1319-1328, November.
   4. Wuppermann, Amelie Catherine, 2011. "Empirical Essays in Health and Education Economics," Munich Dissertations in Economics 13187, University of Munich, Department of Economics.

Articles

1. Helmut Farbmacher & Raphael Guber & Sven Klaassen, 2022. "Instrument Validity Tests With Causal Forests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 605-614, April.

   Cited by:

   1. Thomas Carr & Toru Kitagawa, 2021. "Testing Instrument Validity with Covariates," Papers 2112.08092, arXiv.org, revised Sep 2023.
   2. Nadja van 't Hoff, 2023. "Identifying Causal Effects of Nonbinary, Ordered Treatments using Multiple Instrumental Variables," Papers 2311.17575, arXiv.org.
   3. Kugler, Philipp & Biewen, Martin, 2020. "Two-Stage Least Squares Random Forests with a Replication of Angrist and Evans (1998)," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224538, Verein für Socialpolitik / German Economic Association.
   4. Biewen, Martin & Kugler, Philipp, 2020. "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers 13613, Institute of Labor Economics (IZA).
      • Biewen, Martin & Kugler, Philipp, 2021. "Two-stage least squares random forests with an application to Angrist and Evans (1998)," Economics Letters, Elsevier, vol. 204(C).
   5. Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler & Sven Klaassen, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in R," Papers 2103.09603, arXiv.org, revised Feb 2024.

2. Farbmacher, Helmut & Kögel, Heinrich & Spindler, Martin, 2021. "Heterogeneous effects of poverty on attention," Labour Economics, Elsevier, vol. 71(C).

   Cited by:

   1. Bernard, René, 2022. "Mental Accounting and the Marginal Propensity to Consume," VfS Annual Conference 2022 (Basel): Big Data in Economics 264186, Verein für Socialpolitik / German Economic Association.
   2. Timothée Demont & Daniela Horta Sáenz & Eva Raiber, 2023. "Turning worries into cognitive performance: Results from an online experiment during Covid," AMSE Working Papers 2302, Aix-Marseille School of Economics, France.
      • Timothée Demont & Daniela Horta Sáenz & Eva Raiber, 2023. "Turning worries into cognitive performance: Results from an online experiment during Covid," Working Papers hal-03953178, HAL.
   3. Bernard, René, 2023. "Mental accounting and the marginal propensity to consume," Discussion Papers 13/2023, Deutsche Bundesbank.
   4. Sharafi, Zahra, 2023. "Poverty and perseverance: The detrimental effect of poverty on effort provision," Journal of Development Economics, Elsevier, vol. 162(C).
   5. Eva Raiber & Daniela Horta Saenz & Timothée Demont, 2023. "Turning worries into performance: Results from an online experiment during COVID," French Stata Users' Group Meetings 2023 08, Stata Users Group.
   6. Strittmatter, Anthony, 2023. "What is the value added by using causal machine learning methods in a welfare experiment evaluation?," Labour Economics, Elsevier, vol. 84(C).

3. Maurice J. G. Bun & Helmut Farbmacher & Rutger W. Poldermans, 2020. "Finite sample properties of the GMM Anderson–Rubin test," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1042-1056, November.

   Cited by:

   1. Crudu, Federico & Mellace, Giovanni & Sándor, Zsolt, 2021. "Inference In Instrumental Variable Models With Heteroskedasticity And Many Instruments," Econometric Theory, Cambridge University Press, vol. 37(2), pages 281-310, April.
      • Federico Crudu & Giovanni Mellace & Zsolt Sandor, 2017. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 761, Department of Economics, University of Siena.
      • Federico Crudu & Giovanni Mellace & Zsolt Sándor, 2020. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 821, Department of Economics, University of Siena.

4. Tabea Bucher-Koenen & Helmut Farbmacher & Raphael Guber & Johan Vikström, 2020. "Double Trouble: The Burden of Child-rearing and Working on Maternal Mortality," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 559-576, April.
   • Bucher-Koenen, Tabea & Farbmacher, Helmut & Guber, Raphael & Vikström, Johan, 2020. "Double trouble: The burden of child rearing and working on maternal mortality," Working Paper Series 2020:7, IFAU - Institute for Evaluation of Labour Market and Education Policy.
   See citations under working paper version above.
5. Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2019. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(527), pages 1339-1350, July.
   • Windmeijer, Frank & Farbmacher, Helmut & Davies, Neil & Smith, George Davey, 2017. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168196, Verein für Socialpolitik / German Economic Association.
   • Windmeijer, F.; Farbmacher, H.; Davies, N.; Davey Smith, G.;, 2017. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Health, Econometrics and Data Group (HEDG) Working Papers 17/22, HEDG, c/o Department of Economics, University of York.
   • Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2016. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Bristol Economics Discussion Papers 16/674, School of Economics, University of Bristol, UK, revised 08 Aug 2017.
   See citations under working paper version above.
6. Helmut Farbmacher & Raphael Guber & Johan Vikström, 2018. "Increasing the credibility of the twin birth instrument," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 457-472, April.
   • Farbmacher, Helmut & Guber, Raphael & Vikström, Johan, 2016. "Increasing the credibility of the Twin birth instrument," Working Paper Series 2016:10, IFAU - Institute for Evaluation of Labour Market and Education Policy.
   See citations under working paper version above.
7. Bach, Philipp & Farbmacher, Helmut & Spindler, Martin, 2018. "Semiparametric count data modeling with an application to health service demand," Econometrics and Statistics, Elsevier, vol. 8(C), pages 125-140.
   • Bach, Philipp & Farbmacher, Helmut & Spindler, Martin, 2017. "Semiparametric count data modeling with an application to health service demand," hche Research Papers 15, University of Hamburg, Hamburg Center for Health Economics (hche).
   • Bach, P. & Farbmacher, H. & Spindler, M., 2016. "Semiparametric Count Data Modeling with an Application to Health Service Demand," Health, Econometrics and Data Group (HEDG) Working Papers 16/20, HEDG, c/o Department of Economics, University of York.
   See citations under working paper version above.
8. Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie Wuppermann, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Health Economics, John Wiley & Sons, Ltd., vol. 26(10), pages 1234-1248, October.
   • Farbmacher, Helmut & Ihle, Peter & Schubert, Ingrid & Winter, Joachim & Wuppermann, Amelie, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Munich Reprints in Economics 49875, University of Munich, Department of Economics.
   • Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie C. Wuppermann, 2013. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," CESifo Working Paper Series 4499, CESifo.
   See citations under working paper version above.
9. Helmut Farbmacher & Heinrich Kögel, 2017. "Testing under a special form of heteroscedasticity," Applied Economics Letters, Taylor & Francis Journals, vol. 24(4), pages 264-268, February.

   Cited by:

   1. Tomasz Chrulski & Mariusz Łaciak, 2021. "Analysis of Natural Gas Consumption Interdependence for Polish Industrial Consumers on the Basis of an Econometric Model," Energies, MDPI, vol. 14(22), pages 1-26, November.

10. Helmut Farbmacher & Joachim Winter, 2013. "Per‐Period Co‐Payments And The Demand For Health Care: Evidence From Survey And Claims Data," Health Economics, John Wiley & Sons, Ltd., vol. 22(9), pages 1111-1123, September.

    Cited by:

    1. Stefanie Thönnes, 2019. "Ex-post moral hazard in the health insurance market: empirical evidence from German data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(9), pages 1317-1333, December.
    2. Schmitz, Hendrik, 2013. "Practice budgets and the patient mix of physicians – The effect of a remuneration system reform on health care utilisation," Journal of Health Economics, Elsevier, vol. 32(6), pages 1240-1249.
    3. Gregori Baetschmann & Rainer Winkelmann, 2014. "A Dynamic Hurdle Model for Zero-Inflated Count Data: With an Application to Health Care Utilization," SOEPpapers on Multidisciplinary Panel Data Research 648, DIW Berlin, The German Socio-Economic Panel (SOEP).
       • Gregori Baetschmann & Rainer Winkelmann, 2014. "A dynamic hurdle model for zero-inflated count data: with an application to health care utilization," ECON - Working Papers 151, Department of Economics - University of Zurich.
    4. Johansson, Naimi & de New, Sonja C. & Kunz, Johannes S. & Petrie, Dennis & Svensson, Mikael, 2023. "Reductions in out-of-pocket prices and forward-looking moral hazard in health care demand," Journal of Health Economics, Elsevier, vol. 87(C).
    5. Kuhn, Michael & Ochsen, Carsten, 2019. "Population change and the regional distribution of physicians," The Journal of the Economics of Ageing, Elsevier, vol. 14(C).
    6. Winkelmann, Rainer, 2015. "An empirical model of health care demand under non-linear pricing," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113027, Verein für Socialpolitik / German Economic Association.
       • Rainer Winkelmann, 2014. "An Empirical Model of Health Care Demand under Non-linear Pricing," SOEPpapers on Multidisciplinary Panel Data Research 688, DIW Berlin, The German Socio-Economic Panel (SOEP).
    7. Kim Dalziel & Jinhu Li & Anthony Scott & Philip Clarke, 2018. "Accuracy of patient recall for self‐reported doctor visits: Is shorter recall better?," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1684-1698, November.
    8. Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie Wuppermann, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Health Economics, John Wiley & Sons, Ltd., vol. 26(10), pages 1234-1248, October.
       • Farbmacher, Helmut & Ihle, Peter & Schubert, Ingrid & Winter, Joachim & Wuppermann, Amelie, 2017. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," Munich Reprints in Economics 49875, University of Munich, Department of Economics.
       • Helmut Farbmacher & Peter Ihle & Ingrid Schubert & Joachim Winter & Amelie C. Wuppermann, 2013. "Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care," CESifo Working Paper Series 4499, CESifo.
    9. Johannes S. Kunz & Rainer Winkelmann, 2015. "An econometric model of health care demand with non-linear pricing," ECON - Working Papers 204, Department of Economics - University of Zurich.
       • Johannes S. Kunz & Rainer Winkelmann, 2017. "An Econometric Model of Healthcare Demand With Nonlinear Pricing," Health Economics, John Wiley & Sons, Ltd., vol. 26(6), pages 691-702, June.
    10. Raúl Del Pozo-Rubio & Isabel Pardo-García & Francisco Escribano-Sotos, 2020. "Financial Catastrophism Inherent with Out-of-Pocket Payments in Long Term Care for Households: A Latent Impoverishment," IJERPH, MDPI, vol. 17(1), pages 1-19, January.
    11. Himmel, Konrad & Schneider, Udo, 2017. "Ambulatory care at the end of a billing period," hche Research Papers 14, University of Hamburg, Hamburg Center for Health Economics (hche).
    12. Andree Ehlert & Eva García‐Morán, 2022. "Workers' self‐selection into public sector employment: A tale of absenteeism," Kyklos, Wiley Blackwell, vol. 75(3), pages 394-409, August.

11. Helmut Farbmacher, 2013. "Extensions Of Hurdle Models For Overdispersed Count Data," Health Economics, John Wiley & Sons, Ltd., vol. 22(11), pages 1398-1404, November.

    Cited by:

    1. White-Means, Shelley I. & Osmani, Ahmad Reshad, 2018. "Affordable Care Act and Disparities in Health Services Utilization among Ethnic Minoritiy Breast Cancer Survivors: Evidence from Longitudinal Medical Expenditure Panel Surveys 2008-2015," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(9), pages 1-26.
       • Shelley I. White-Means & Ahmad Reshad Osmani, 2018. "Affordable Care Act and Disparities in Health Services Utilization among Ethnic Minority Breast Cancer Survivors: Evidence from Longitudinal Medical Expenditure Panel Surveys 2008–2015," IJERPH, MDPI, vol. 15(9), pages 1-26, August.
    2. Koppenberg, Maximilian & Mishra, Ashok K. & Hirsch, Stefan, 2023. "Food Aid and Violent Conflict: A Review of Literature," IZA Discussion Papers 16574, Institute of Labor Economics (IZA).

12. Helmut Farbmacher, 2012. "GMM with many weak moment conditions: Replication and application of Newey and Windmeijer (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 343-346, March.

    Cited by:

    1. Simplice A. Asongu & Mushfiqur Rahman & Joseph Nnanna & Mohamed Haffar, 2020. "Enhancing Information Technology for Value Added Across Economic Sectors in Sub-Saharan Africa," Working Papers 20/064, European Xtramile Centre of African Studies (EXCAS).
       • Simplice A. Asongu & Mushfiqur Rahman & Joseph Nnanna & Mohamed Haffar, 2020. "Enhancing Information Technology for Value Added Across Economic Sectors in Sub-Saharan Africa," Working Papers of the African Governance and Development Institute. 20/064, African Governance and Development Institute..
       • Asongu, Simplice & Rahman, Mushfiqur & Nnanna, Joseph & Haffar, Mohamed, 2020. "Enhancing Information Technology for Value Added Across Economic Sectors in Sub-Saharan Africa," MPRA Paper 107238, University Library of Munich, Germany.
       • Simplice A. Asongu & Mushfiqur Rahman & Joseph Nnanna & Mohamed Haffar, 2020. "Enhancing Information Technology for Value Added Across Economic Sectors in Sub-Saharan Africa," Research Africa Network Working Papers 20/064, Research Africa Network (RAN).
    2. Andrew Berg & Jonathan D. Ostry & Charalambos G. Tsangarides & Yorbol Yakhshilikov, 2018. "Redistribution, inequality, and growth: new evidence," Journal of Economic Growth, Springer, vol. 23(3), pages 259-305, September.
    3. Asongu, Simplice A. & Rahman, Mushfiqur & Nnanna, Joseph & Haffar, Mohamed, 2020. "Enhancing information technology for value added across economic sectors in Sub-Saharan Africa✰," Technological Forecasting and Social Change, Elsevier, vol. 161(C).

Software components

1. Helmut Farbmacher, 2017. "SIVREG: Stata module to perform adaptive Lasso with some invalid instruments," Statistical Software Components S458394, Boston College Department of Economics, revised 31 Jul 2018.

   Cited by:

   1. Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Jul 2022.

Chapters

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 14 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-HEA: Health Economics (7) 2009-07-28 2012-09-30 2016-08-21 2017-10-08 2020-03-16 2020-05-25 2020-06-08. Author is listed
2. NEP-ECM: Econometrics (6) 2015-06-13 2016-06-25 2016-08-21 2019-04-01 2020-03-16 2021-05-24. Author is listed
3. NEP-BIG: Big Data (4) 2017-08-27 2017-10-15 2020-03-16 2020-05-25
4. NEP-CMP: Computational Economics (2) 2020-03-16 2020-05-25
5. NEP-DEM: Demographic Economics (2) 2016-08-14 2020-06-08
6. NEP-AGE: Economics of Ageing (1) 2020-06-08
7. NEP-COM: Industrial Competition (1) 2012-09-30
8. NEP-DCM: Discrete Choice Models (1) 2021-05-24
9. NEP-EUR: Microeconomic European Issues (1) 2020-06-08
10. NEP-IAS: Insurance Economics (1) 2012-09-30
11. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2016-08-14
12. NEP-NET: Network Economics (1) 2016-06-25
13. NEP-ORE: Operations Research (1) 2017-10-08

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