IDEAS home Printed from https://ideas.repec.org/e/psp125.html
   My authors  Follow this author

Martin Spindler

Personal Details

First Name:Martin
Middle Name:
Last Name:Spindler
Suffix:
RePEc Short-ID:psp125
[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/

: +49 89 38602-442
+49 89 38602-490
Amalienstraße 33, 80799 München
RePEc:edi:memande (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Vijay Aseervatham & Christoph Lex & Spindler, Martin, 2014. "How do unisex rating regulations affect gender differences in insurance premiums?," MEA discussion paper series 201416, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.

Articles

  1. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
  2. Spindler, Martin, 2015. "Asymmetric information in (private) accident insurance," Economics Letters, Elsevier, vol. 130(C), pages 85-88.
  3. Martin Spindler, 2014. "Econometric Methods for Testing for Asymmetric Information: A Comparison of Parametric and Nonparametric Methods with an Application to Hospital Daily Benefits*," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 39(2), pages 254-266, September.
  4. Liangjun Su & Martin Spindler, 2013. "Nonparametric Testing for Asymmetric Information," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 208-225, April.

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.

Working papers

  1. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
    2. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
    3. Giuseppe de Luca & Jan Magnus & Franco Peracchi, 2017. "Weighted-Average Least Squares Estimation of Generalized Linear Models," Tinbergen Institute Discussion Papers 17-029/III, Tinbergen Institute.
    4. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Dec 2017.
    5. Alexandre Belloni & Victor Chernozhukov & Ivan Fern'andez-Val & Christian Hansen, 2013. "Program Evaluation and Causal Inference with High-Dimensional Data," Papers 1311.2645, arXiv.org, revised Jan 2018.
    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, Department of Economics, University of Bristol, UK, revised 08 Aug 2017.
    7. Ruf, Daniel, 2017. "Agglomeration Effects and Liquidity Gradients in Local Rental Housing Markets," Working Papers on Finance 1702, University of St. Gallen, School of Finance.
    8. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers CWP33/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  2. Vijay Aseervatham & Christoph Lex & Spindler, Martin, 2014. "How do unisex rating regulations affect gender differences in insurance premiums?," MEA discussion paper series 201416, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.

    Cited by:

    1. Javier Pla-Porcel & Manuel Ventura-Marco & Carlos Vidal-Meliá, 2017. "How do unisex life care annuities embedded in a pay-as-you-go retirement system affect gender redistribution?," Documentos de Trabajo del ICAE 2017-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Mercedes Ayuso & Montserrat Guillen & Ana María Pérez-Marín, 2016. "Telematics and Gender Discrimination: Some Usage-Based Evidence on Whether Men’s Risk of Accidents Differs from Women’s," Risks, MDPI, Open Access Journal, vol. 4(2), pages 1-10, April.

Articles

  1. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
    See citations under working paper version above.
  2. Spindler, Martin, 2015. "Asymmetric information in (private) accident insurance," Economics Letters, Elsevier, vol. 130(C), pages 85-88.

    Cited by:

    1. Sebastian Soika, 2018. "Moral Hazard and Advantageous Selection in Private Disability Insurance," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 43(1), pages 97-125, January.
    2. Choi Yun Jeong & Chen Joe & Sawada Yasuyuki, 2015. "Life Insurance and Suicide: Asymmetric Information Revisited," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(3), pages 1127-1149, July.

  3. Liangjun Su & Martin Spindler, 2013. "Nonparametric Testing for Asymmetric Information," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 208-225, April.

    Cited by:

    1. Spindler, Martin, 2013. "“They do know what they are doing... at least most of them.†Asymmetric Information in the (private) Disability Insurance," MEA discussion paper series 201209, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    2. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    3. Arnold Polanski & Evarist Stoja, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
    4. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    5. Karl Ove Aarbu, 2017. "Asymmetric Information in the Home Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(1), pages 35-72, March.
    6. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    7. Georges Dionnne & Pierre-Carl Michaud & Jean Pinquet, 2012. "A Review of Recent Theoretical and Empirical Analyses of Asymmetric Information in Road Safety and Automobile Insurance," Cahiers de recherche 1204, CIRPEE.
    8. Spindler, M., 2014. "“They do know what they are doing ... at least most of them.†Asymmetric Information in the (private) Disability Insurance," Health, Econometrics and Data Group (HEDG) Working Papers 14/16, HEDG, c/o Department of Economics, University of York.
    9. Feng Gao & Michael R. Powers & Jun Wang, 2017. "Decomposing Asymmetric Information in China's Automobile Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1269-1293, December.
    10. Spindler, Martin & Winter, Joachim & Hagmayer, Steffen, 2012. "Asymmetric Information in the Market for Automobile Insurance: Evidence from Germany," MEA discussion paper series 201208, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    11. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    12. David Rowell & Son Nghiem & Luke B Connelly, 2017. "Two Tests for Ex Ante Moral Hazard in a Market for Automobile Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1103-1126, December.
    13. Georges Dionne, 2012. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data," Cahiers de recherche 1233, CIRPEE.
    14. Choi Yun Jeong & Chen Joe & Sawada Yasuyuki, 2015. "Life Insurance and Suicide: Asymmetric Information Revisited," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(3), pages 1127-1149, July.

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 1 paper 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-IAS: Insurance Economics (1) 2015-06-13. Author is listed

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Martin Spindler should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.