Stephan Stahlschmidt

Personal Details

First Name:	Stephan
Middle Name:
Last Name:	Stahlschmidt
Suffix:
RePEc Short-ID:	pst632
	[This author has chosen not to make the email address public]
Terminal Degree:	2015 Center for Applied Statistics and Econometrics (CASE); Humboldt-Universität Berlin (from RePEc Genealogy)

Affiliation

(25%) Institut für Statistik und Ökonometrie (ISÖ)
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

Berlin, Germany
http://ise.wiwi.hu-berlin.de/
RePEc:edi:ishubde (more details at EDIRC)

(50%) Centrum für Soziale Investitionen und Innovationen (CSI)
Ruprecht-Karls-Universität Heidelberg

Heidelberg, Germany
http://www.csi.uni-heidelberg.de/
RePEc:edi:csheide (more details at EDIRC)

(25%) Center for Applied Statistics and Econometrics (CASE)
Humboldt-Universität Berlin

Berlin, Germany
http://www.case.hu-berlin.de/
RePEc:edi:cahubde (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.

Working papers

1. Stahlschmidt, Stephan & Eckardt, Matthias & Härdle, Wolfgang Karl, 2014. "Expectile treatment effects: An efficient alternative to compute the distribution of treatment effects," SFB 649 Discussion Papers 2014-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

   Cited by:

   1. Marina Bonaccolto-Töpfer & Giovanni Bonaccolto, 2023. "Gender wage inequality: new evidence from penalized expectile regression," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(3), pages 511-535, September.

2. Stahlschmidt, Stephan & Eckardt, Matthias & Härdle, Wolfgang Karl, 2014. "Expectile treatment effects: An efficient alternative to compute the distribution of treatment effects," SFB 649 Discussion Papers 2014-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

   Cited by:

   1. Farooq, Muhammad & Steinwart, Ingo, 2017. "An SVM-like approach for expectile regression," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 159-181.
   2. Marina Bonaccolto-Töpfer & Giovanni Bonaccolto, 2023. "Gender wage inequality: new evidence from penalized expectile regression," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(3), pages 511-535, September.

Articles

1. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2013. "Bayesian networks for sex-related homicides: structure learning and prediction," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1155-1171, June.

   Cited by:

   1. E. Cene & F. Karaman, 2015. "Analysing organic food buyers' perceptions with Bayesian networks: a case study in Turkey," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1572-1590, 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 3 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-ECM: Econometrics (3) 2011-08-02 2014-03-01 2014-11-01
2. NEP-GEO: Economic Geography (1) 2014-03-01
3. NEP-URE: Urban and Real Estate Economics (1) 2014-03-01

Corrections

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