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Helmut Farbmacher

Personal Details

First Name:Helmut
Middle Name:
Last Name:Farbmacher
Suffix:
RePEc Short-ID:pfa342

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)

Research output

as
Jump to: Working papers Articles Software Chapters

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.
  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.
  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.
  4. Helmut Farbmacher & Alexander Kann, 2019. "On the Effect of Imputation on the 2SLS Variance," Papers 1903.11004, arXiv.org.
  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.
  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.
  7. 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.
  8. Farbmacher, Helmut & Kögel, Heinrich, 2015. "Inference Problems under a Special Form of Heteroskedasticity," MEA discussion paper series 201503, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  9. 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.
  10. Helmut Farbmacher; & Joachim Winter, 2012. "Non-linear price schedules, demand for health care and response behavior," Health, Econometrics and Data Group (HEDG) Working Papers 12/15, HEDG, c/o Department of Economics, University of York.
  11. 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.

Articles

  1. Helmut Farbmacher & Maximilian Hartmann & Heinrich Kögel, 2022. "Economic Hardship, Sleep, and Self-Rated Health," American Journal of Health Economics, University of Chicago Press, vol. 8(2), pages 216-251.
  2. 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.
  3. Farbmacher, Helmut & Kögel, Heinrich & Spindler, Martin, 2021. "Heterogeneous effects of poverty on attention," Labour Economics, Elsevier, vol. 71(C).
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  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.
  12. 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.
  13. 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.
  14. Helmut Farbmacher, 2011. "Estimation of hurdle models for overdispersed count data," Stata Journal, StataCorp LP, vol. 11(1), pages 82-94, March.

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.
  2. Helmut Farbmacher, 2014. "NWIND: Stata module to compute Newey-Windmeijer VCE after ivreg2 GMM-CUE estimation," Statistical Software Components S457780, Boston College Department of Economics.
  3. Helmut Farbmacher, 2012. "ZTNBP: Stata module to estimate zero-truncated NegBin-P regression," Statistical Software Components S457558, Boston College Department of Economics, revised 05 Jul 2013.
  4. Helmut Farbmacher, 2012. "ZTPFLEX: Stata module to estimate zero-truncated Poisson mixture regression," Statistical Software Components S457557, Boston College Department of Economics.

Chapters

  1. Farbmacher, Helmut & Ihle, Peter & Schubert, Ingrid & Winter, Joachim & Wuppermann, Amelie C., . "Heterogeneous effects of the 2004 health care reform," Chapters in Economics,, University of Munich, Department of Economics.

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.

    Cited by:

    1. 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).
    2. 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. 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.

    Cited by:

    1. Öberg, Stefan, 2018. "Instrumental variables based on twin births are by definition not valid (v.3.0)," SocArXiv zux9s, Center for Open Science.

  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.

    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. 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.
    3. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Generalized Kernel Ridge Regression for Nonparametric Structural Functions and Semiparametric Treatment Effects," Papers 2010.04855, arXiv.org, revised Dec 2021.
    4. Rahul Singh & Liyuan Xu & Arthur Gretton, 2021. "Kernel Methods for Multistage Causal Inference: Mediation Analysis and Dynamic Treatment Effects," Papers 2111.03950, arXiv.org.

  4. 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.

    Cited by:

    1. Liu, Weiwei & Egan, Kevin J, 2019. "A Semiparametric Smooth Coefficient Estimator for Recreation Demand," MPRA Paper 95294, University Library of Munich, Germany.

  5. 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.

    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.
    5. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    6. 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.
    7. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    8. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    9. 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.
    10. 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.
    11. Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Nov 2020.
    12. 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.
    13. 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.
    14. 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.
    15. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics Working Papers 2019-04, University of Adelaide, School of Economics.

  6. 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.

    Cited by:

    1. 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. 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.
    4. 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).
    5. 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.
    6. 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.

  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.

    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.
    2. 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).
    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. 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).
    5. Klein, Tobias & Salm, Martin & Upadhyay, Suraj, 2020. "The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Discontinuities Design," CEPR Discussion Papers 14552, C.E.P.R. Discussion Papers.
    6. 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.
    7. 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.
    8. 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.
    9. 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. 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. Wuppermann, Amelie Catherine, 2011. "Empirical Essays in Health and Education Economics," Munich Dissertations in Economics 13187, University of Munich, Department of Economics.
    2. 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).

Articles

  1. 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.

  2. 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.
    See citations under working paper version above.
  3. 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.
    See citations under working paper version above.
  4. 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.
    See citations under working paper version above.
  5. 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.
    See citations under working paper version above.
  6. 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.
    See citations under working paper version above.
  7. 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, pages 1-26.

  8. 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. 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).
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Himmel, Konrad & Schneider, Udo, 2017. "Ambulatory care at the end of a billing period," hche Research Papers 2017/14, University of Hamburg, Hamburg Center for Health Economics (hche).
    8. Kuhn, Michael & Ochsen, Carsten, 2019. "Population change and the regional distribution of physicians," The Journal of the Economics of Ageing, Elsevier, vol. 14(C).
    9. 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.

  9. 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. 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.
    2. 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..
    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 Nov 2020.

Chapters

    Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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, & 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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