Timo Schmid

PROFESSOR OF STATISTICS AND ECONOMETRICS

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Office: Feldkirchenstrasse 21, Room: F21/00.76b, 96045 Bamberg, Germany
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E-Mail: timo.schmid(at)uni-bamberg.de
Phone: +49 (0)951/863-2530
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Pillar 2: Education and Social Inequality Across the Entire Life Course
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// CURRENT POSITIONS

 

  • Professor of Statistics and Econometrics
  • Faculty Member of the Bamberg Graduate School of Social Sciences
  • Head of the Bamberg center for empirical studies (BACES)



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// SUPERVISION


Professor Dr. Timo Schmid is particularly interested in supervising doctoral students with an interest in applied statistics, for instance in the areas of statistical modelling, machine learning, survey statistics and poverty mapping.


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// RESEARCH


His research focuses on computational statistics, poverty mapping, small area estimation, machine learning, survey statistics as well as statistical modelling, for instance the analysis of cross-sectional and longitudinal data based on regression models.

RESEARCH PROJECTS
 

  • TESAP: Time-consistent Estimates for the Household Finance and Consumption Survey - Small Area Estimation in the Panel Context
  • Construction of socio-demographic indicators with digital breadcrumbs (Mobile data)
  • Multidimensional poverty estimation using small area estimation - Two perspectives

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// SELECTED PUBLICATIONS

 

The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators, with Kreutzmann, A.-K., Pannier, S., Rojas-Perilla, N., Templ, M. and Tzavidis, N., Journal of Statistical Software, 2019, 91, pp. 1-33.

From start to finish: A framework for the production of small area official statistics, with Tzavidis, N., Zhang, L.-C., Luna Hernandez, A. and Rojas-Perilla, N., Journal of the Royal Statistical Society: Series A, Read paper, 2018, 181, pp. 927-979.

Constructing socio-demographic indicators for National Statistical Institutes using mobile phone data: Estimating literacy rates in Senegal, with Bruckschen, F., Salvati, N. and Zbiranski, T., Journal of the Royal Statistical Society: Series A, 2017, 180, pp. 1163-1190.

 

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Professor Schmid's website at the Chair of Statistics and Econometrics

 

 

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