Journal-Beiträge
Friedrich, U., Moschen, L., Münnich R. & Schmidt , M. (in press): Computational Methods for the Household Assignment Problem. Optimization Online. URL: https://optimization-online.org/?p=27073
Weymeirsch, J., Ernst, J. & Münnich R. (2024): Model Recalibration for Regional Bias Reduction in Dynamic Microsimulations. Mathematics; 12(10):1550 doi: https://doi.org/10.3390/math12101550
Emmenegger, J., & Obersneider, M. (2024): Dynamic Microsimulations of Regional Income Inequalities in Germany. International Journal of Microsimulation; 17(1):1-33 doi: https://doi.org/10.34196/ijm.00304
Ernst, J., Dräger, S., Schmaus, S., Weymeirsch, J., Alsaloum, A. & Münnich, R. (2023): The Influence of Migration Patterns on Regional Demographic Development in Germany. Social Sciences; 12(5):255. doi: https://doi.org/10.3390/socsci12050255
Emmenegger, J., Münnich, R. & Schaller, J. (in press): Evaluating Data Fusion Methods to Improve Income Modeling. Journal of Survey Statistics and Methodology. URL: https://doi.org/10.1093/jssam/smac033
Emmenegger, J. & Münnich, R. (2022): Localising the Upper Tail: How Top Income Corrections Affect Measures of Regional Inequality. Jahrbücher für Nationalökonomie und Statistik (Journal of Economics and Statistics). doi: https://doi.org/10.1515/jbnst-2022-0015
Münnich, R., Schnell, R., Brenzel, H., Dieckmann, H., Dräger, S., Emmenegger, J., Höcker, P., Kopp, J., Merkle, H., Neufang, K., Obersneider, M., Reinhold, J., Schaller, J., Schmaus, S., and Stein, P. (2021): A Population Based Regional Dynamic Microsimulation of Germany: The MikroSim Model. methods, data, analyses, 0, 23. doi: https://doi.org/10.12758/mda.2021.03
Articus, C., C. Caratiola, H. Dieckmann, M. Gerhards, R. Münnich und T. Udelhoven (2019): Measuring Well-Being Using Remote Sensing and Official Statistics Data. In: Rivista di statistica ufficiale, 2-3/2019. S. 9-42. URL: https://www.istat.it/it/archivio/255340
Burgard, J. P., H. Dieckmann, J. Krause, H. Merkle, R. Münnich, K. Neufang und S. Schmaus (2020): A Generic Business Process Model for Conducting Microsimulation Studies. In: Statistics in Transition New Series 21.4, S. 191–211. URL: https://sit.stat.gov.pl/Article/190
Burgard, J. P., J. Krause und S. Schmaus (2020): Estimation of Regional Transition Probabilities for Spatial Dynamic Microsimulations from Survey Data Lacking in Regional Detail. In: Computational Statistics & Data Analysis 154. doi: https://doi.org/10.1016/j.csda.2020.107048
Konferenz-Beiträge
Brenzel, H., Palm, M., Weymeirsch, J. & Münnich, R (2024): Privacy and Disclosure Risks in Spatial Dynamic Microsimulations. In: Privacy in Statistical Databases. PSD 2024, LNCS 14915, Springer Nature, S. 1–17.
Obersneider, M. und P. Stein (2019): A Spatial Microsimulation Model of Labor Market Integration in Germany. In: JSM Proceedings 2019, Social Statistics Section. American Statistical Association, S. 2620–2628.
Stein, P., C. Frohn und M. Obersneider (2019): Dynamische Mikrosimulationen in den Sozialwissenschaften – Exemplarische Anwendungsfelder. In: Komplexe Dynamiken globaler und lokaler Entwicklungen. Verhandlungen des 39. Kongresses der Deutschen Gesellschaft für Soziologie in Göttingen 2018. Hrsg. von N. Burzan, S. 1–10.
Konferenz-Vorträge
2024
Bohnensteffen, S., Münnich, R. (2024): Exploring ways to analyse future housing demand with microsimulation. 9th World Congress of the International Microsimulation Association, Wien, Österreich.
Daykin, A. & Stein, P. (2024): Modelling the future development of the choice of mode of transportation for everyday travel. 9th World Congress of the International Microsimulation Association, Wien, Österreich.
Ernst, J., Weymeirsch, J., Münnich, R. (2024): Within-city projections using the MikroSim model. 9th World Congress of the International Microsimulation Association, Wien, Österreich.
Hammon, A. (2024): Exploring meta modeling techniques for the simulation of school transitions in Germany. 9th World Congress of the International Microsimulation Association, Wien, Österreich.
Münnich, R. (2024): Synthetic Data Generation - What is the Impact on Microsimulation? 9th World Congress of the International Microsimulation Association (Keynote), Wien, Österreich.
Palm, M., Brenzel, H., Münnich, R., Weymeirsch, J. (2024): Measuring statistical disclosure risks in synthetic data. 9th World Congress of the International Microsimulation Association (IMA), Wien, Österreich.
2023
Zinn, S. (2023): Modellierung des Unbeobachteten: Eine Erweiterung der traditionellen Mikrosimulation. Herbsttagung der Sektion ,,Modellbildung und Simulation’’, Düsseldorf.
Weymeirsch, J., Alsaloum, A. & Münnich, R. (2023): Methoden zur Regionalisierung und Fortschreibung in dynamischen Mikrosimulationen. SurvConf 2023, Bamberg.
Bohnensteffen, S., Münnich, R. (2023): Analyse zukünftiger regionaler Wohnraumbedarfe mittels dynamischer Mikrosimulation. Statistische Woche 2023, Dortmund.
Ernst, J. & Münnich, R. (2023): Within-city population projections using microsimulations. Statistische Woche 2023, Dortmund.
Palm, M., Brenzel, H., Münnich, R., Weymeirsch, J. (2023): Messung statistischer Enthüllungsrisiken bei synthetischen Daten. Statistische Woche 2023, Dortmund.
Weymeirsch, J., Alsaloum, A. & Münnich, R. (2023): Gruppenspezifische Alignment- und Fortschreibungsmethoden in Mikrosimulationen. Statistical Week 2023, Dortmund.
Bekalarczyk, D., Depenbrock, E., Frohn, C., Obersneider, M., Stein, P. (2023): Analyzing Wage Trajectories using Autoregressive Growth Curve Models in Microsimulations. Joint Statistical Meeting (JSM), Toronto.
Obersneider, M., Stein, P. (2023): Projection of Regional Labor Market Integration Potentials in Germany. Joint Statistical Meeting (JSM), Toronto.
Ernst, J., Schmaus, S. & Münnich, R. (2023): The influence of migration patterns on the regional demographic development in Germany. Current Perspectives on Spatial Mobilities 2023, Nürnberg.
Münnich, R. (2023): From data to policy: How important is statistics for microsimulations. ÖSG-Statistiktage 2023 (Keynote), Wien, Österreich.
Münnich, R. (2023): Mikrosimulationen als Verbindung zwischen Politik und Wissenschaft. Wissenschaftliche Fachtagung ,,Daten.Forschung.Zukunft’’, Wiesbaden.
Münnich, R. (2023): Microsimulations as a statistical problem with policy impact. 64th ISI World Statistics Congress (Keynote), Ottawa, Kanada.
Bohnensteffen, S., Münnich, R. (2023): Exploring ways to analyse future housing demand with microsimulation. Conference on New Techniques and Technologies for Statistics, Brüssel, Belgien.
Palm, M., Brenzel, H., Münnich, R., Weymeirsch, J. (2023): A confidentiality concept for a simulation data centre. Conference on New Techniques and Technologies for Statistics (NTTS), Brüssel, Belgien.
Bekalarczyk, D., Depenbrock, E., Frohn, C., Obersneider, M. (2023): Integrating Complex Panel Data Models into Dynamic Microsimulations. Advanced Techniques for Longitudinal Data Analysis in Social Science, Bielefeld.
2022
Bekalarczyk, D.; Frohn, C.; Obersneider, M. (2022): Dynamische Mikrosimulation zur Diskriminierung von Migrantinnen in Deutschland – Generationale Unterschiede in der Migrant Pay Gap. 41. Kongress der Deutschen Gesellschaft für Soziologie (DGS), Bielefeld.
Münnich, R. (2022): Microsimulations as a statistical problem or: Data for Science and Policy. Conference of European Statistics Stakeholders 2022, Rom, Italien.
Münnich, R. (2022): Small Area and Local Statistics for Microsimulations. Statistische Woche 2022, Münster.
Emmenegger, J. & Münnich, R. (2022): Localising the Upper Tail: How Top Income Corrections Affect Measures of Regional Inequality. Nachwuchsworkshop Statistische Woche 2022, Münster.
Münnich, R. (2022): Open Geocoded Data for Science: A Microsimulation Approach. The 3rd Congress of Polish Statistics, Krakow, Polen.
Emmenegger, J.; Obersneider, M. (2022): Income and Inequality Projections in Germany. Joint Statistical Meeting (JSM), Washington, D.C.
Ernst, J.; Münnich, R. & Schmaus, S. (2022): Microsimulation and cohort-component methods for (small area) demographic projections. Statistische Woche 2022, Münster.
Bohnensteffen, S., Münnich, R. (2022): Modelling local level Housing Demand – Ideas & Model Outline. European Meeting of the International Microsimulation Association, Nürnberg.
Dieckmann, H.; Weymeirsch, J. & Münnich, R. (2022): External and Internal Validation of Dynamic Microsimulations in the context of the MikroSim Project. European Meeting of the International Microsimulation Association (IMA) 2022, Nuremberg, Germany.
Emmenegger, J.; Obersneider, M. (2022): Dynamic Microsimulations of Regional Income Inequalities in Germany. European Meeting of the International Microsimulation Association, Nürnberg.
Höcker, P.; Reinhold, J. & Schnell, R. (2022): A Major Accident in a Nuclear Power Plant. Modeling Selected Consequences Using Microsimulation. European Meeting of the International Microsimulation Association 2022, Nürnberg.
Münnich, R. (2022): Geospatial Microsimulations: are synthetic data always safe? European Meeting of the International Microsimulation Association (Keynote), Nürnberg.
Palm, M., Brenzel, H., Münnich, R., Weymeirsch, J. (2022): A confidentiality concept for a simulation data centre. European Meeting of the International Microsimulation Association (IMA), Nürnberg.
Obersneider, M.; Stein, P. (2022): Spatial Structure and Labor Market Integration Projections in Germany. Joint Statistical Meeting (JSM), Washington, D.C.
Weymeirsch, J. & Münnich, R. (2022): Disclosure Risk and Utility in Geocoded Microsimulations. Small Area Estimation Conference 2022 (Invited Presentation), Maryland, USA.
Weymeirsch, J. & Münnich, R. (2022): Internal Validation and Disclosure Control in Dynamic Microsimulations. Tagung des Arbeitskreises für mathematisch-statistische Methoden 2022, Wiesbaden, Germany.
2021
Emmenegger, J., Münnich, R. & Schaller, J. (2021): Microsimulations of income inequalities and potentials of data fusion methods to account for social disaggregation. NTTS, virtual conference.
Emmenegger, J. & Münnich, R. (2021): Localisation of the upper tail: Correcting regional top income distributions. Ninth Meeting of the Society for the Study of Economic Inequality (ECINEQ), virtual conference. 2020
2020
Frohn, C. und P. Stein (2020): Dynamische Mikrosimulation zur gesundheitlichen Ungleichheit in Deutschland – Exemplarische Ergebnisse. 40. Kongress der Deutschen Gesellschaft für Soziologie, Digital, Germany.
Heim, L., M. Obersneider, A.-K. Kuhnt und H. Baykara-Krumme (2020): Die Partnerwahl von Migrant*innen in Deutschland. 40. Kongress der Deutschen Gesellschaft für Soziologie, Digital, Germany. 2019
2019
Brenzel, H. und M. Zwick (2019): Mikroanalyse und Georeferenzierung in der amtlichen Statistik. Statistical Week 2019, Trier, Germany.
Burgard, J. P., J. Krause und S. Schmaus (2019): Small Area Estimation of Transition Probabilities for Spatial Dynamic Microsimulation Models in Socio-economic Research. 12th International Conference of the ERCIM WG on Computational and Methodological Statistics, London, Great Britain.
Dräger, S. (2019): Regional Microsimulation Model of the Future Need for Primary School Infrastructure in Trier. Statistical Week 2019, Trier, Germany.
Emmenegger, J. und R. Münnich (2019): Building a Longitudinal Income Module for Spatial Microsimulations Based on the German Taxpayer Panel. 7th World Congress of the International Microsimulation Association, Galway, Ireland.
Emmenegger, J. und R. Münnich (2019): Mikrosimulation von regionalen und familienspezifische Disparitäten des Einkommens. Statistical Week 2019, Trier, Germany.
Merkle, H. und R. Münnich (2019): Generating a German Small-Scale Base Population for Spatial Microsimulation. 7th World Congress of the International Microsimulation Association, Galway, Ireland.
Münnich, R., R. Schnell, J. Kopp, P. Stein und M. Zwick (2019): MikroSim – A Dynamic Spatial Microsimulation Model for Germany. 7th World Congress of the International Microsimulation Association, Galway, Ireland.
Neufang, K. und R. Münnich (2019): Synthesizing Regression Models to Estimate Micro-Level Data With Multiple Sources. Statistical Week 2019, Trier, Germany.
Neufang, K. und R. Münnich (2019): Using Synthesis Methods to Estimate Micro-Level Data With Multiple sources – A Simulation Study. 7th World Congress of the International Microsimulation Association, Galway, Ireland.
Obersneider, M. und P. Stein (2019): A Spatial Microsimulation Model of Labor Market Integration in Germany. Joint Statistical Meeting of the American Statistical Association, Denver, USA.
Obersneider, M. und P. Stein (2019): Developing a Regional Microsimulation Model for Labor Market Integration of Migrants in Germany. Statistical Week 2019, Trier, Germany.
Reinhold, J., P. Höcker, S. Brocker und R. Schnell (2019): Die Anwendung von Mikrosimulationen zur Bevölkerungsfortschreibung. Statistical Week 2019, Trier, Germany.
Stein, P., M. Obersneider und K. Neufang (2019): Introduction to Microsimulation Modeling. Microsimulation Workshop: Women in Statistics, Statistical Week 2019, Trier, Germany.
2018
Kopp, J. (2018): Familie und Pflege. 27. Wissenschaftliches Kolloquium, Wiesbaden, Germany.
Münnich, R. (2018): Sektorenübergreifendes kleinräumiges Mikrosimulationsmodell. 27. Wissenschaftliches Kolloquium, Wiesbaden, Germany.
Schnell, R. (2018): Daten für Mikrosimulationen. 27. Wissenschaftliches Kolloquium, Wiesbaden, Germany.
Stein, P. (2018): Entwicklung der beruflichen Integration von Migranten. 27. Wissenschaftliches Kolloquium, Wiesbaden, Germany.
Stein, P., C. Frohn und M. Obersneider (2018): Dynamische Mikrosimulationen in den Sozialwissenschaften – exemplarische Anwendungsfelder. 39. Kongress der Deutschen Gesellschaft für Soziologie, Göttingen, Germany.
Zwick, M. (2018): Bedeutung von Mikrosimulationen für die Bundesstatistik. 27. Wissenschaftliches Kolloquium, Wiesbaden, Germany.
Sammelbände
Mikrosimulationen: Methodische Grundlagen und ausgewählte Anwendungsfelder
Editors: Marc Hannappel and Johannes Kopp
Contributions of the Research Group:
Markus Zwick, Jana Emmenegger: Mikrosimulation und Gesellschaftspolitik – ein kurzer historischer Abriss. (17-34)
Rainer Schnell, Thomas Handke: Neuere bevölkerungsbezogene Mikrosimulationen in Großbritannien und Deutschland. (35-56)
Ralf Münnich, Rainer Schnell, Johannes Kopp, Petra Stein, Markus Zwick, Sebastian Dräger, Hariolf Merkle, Monika Obersneider, Nico Richter, Simon Schmaus: Zur Entwicklung eines kleinräumigen und sektorenübergreifenden Mikrosimulationsmodells für Deutschland. (109-138)
Christopher Lütz, Petra Stein: Validierung in dynamischen Mikrosimulationsmodellen. (141-176)
Jan Pablo Burgard, Joscha Krause, Hariolf Merkle, Ralf Münnich, Simon Schmaus: Dynamische Mikrosimulationen zur Analyse und Planung regionaler Versorgungsstrukturen in der Pflege. (283-313)
Christoph Frohn, Monika Obersneider: Modellierung der Entwicklung des Pflegebedarfs in Deutschland. (315-353)
Working Paper
Weymeirsch, J., H. Dieckmann, and R. Münnich (2024). Construction of a Georeferenced House Data Set for the City of Trier within the MikroSim Project. Research Papers in Economics 9/24. Trier University.
Sebastian Dräger, Johannes Kopp, Ralf Münnich, Simon Schmaus: Analyse der Grundschulversorgung in Trier mit Hilfe kleinräumiger Mikrosimulationsmodelle.
Jana Emmenegger, Ralf Münnich, Jannik Schaller: Evaluating Data Fusion Methods to Improve Income Modelling.