Tag Archives | Panel Data

What You Need to Know When Estimating Monthly Impact Functions: Comment on Hudde and Jacob, “There’s More in the Data!”

Josef Brüderl, Ansgar Hudde, Marita Jacob

Sociological Science December 4, 2025
10.15195/v12.a34


In life course research, it is common practice to analyze the effects of life events on outcomes. This is usually done by estimating “impact functions.” To date, most studies have estimated yearly impact functions. However, Hudde and Jacob (2023) (hereafter H&J) pointed out that most panel data sets include information on the month of events. Consequently, they proposed exploiting this information by estimating monthly impact functions. In this adversarial collaboration, we address two issues regarding H&J’s work. First, H&J did not provide sufficient guidance on how to estimate monthly impact functions. We will provide a step-by-step description of how to do so. Second, the procedure H&J proposed for smoothing monthly estimates produces confidence intervals (CIs) that are likely too narrow. This can lead to misleading conclusions. Therefore, we suggest using more appropriate bootstrapped CIs.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Josef Brüderl: Department of Sociology, LMU Munich. E-mail: bruederl@lmu.de
Ansgar Hudde: Department of Sociology and Social Psychology, University of Cologne.
E-mail: hudde@wiso.uni-koeln.de
Marita Jacob: Department of Sociology and Social Psychology, University of Cologne.
E-mail: marita.jacob@uni-koeln.de

Acknowledgments: We thank Katrin Auspurg for her helpful comments. This article uses data from the German Family Panel pairfam, coordinated by Josef Brüderl, Sonja Drobniˇc, Karsten Hank, Johannes Huinink, Bernhard Nauck, Franz J. Neyer, and Sabine Walper. From 2004 to 2022, pairfam was funded as a priority program and a long-term project by the German Research Foundation (DFG).


Reproducibility Package: Stata replication code is available on the Open Science Framework (OSF), https://osf.io/kx9ne/ (file: “Monthly Impact Functions-Replication File.zip”). The replication file includes the prepared pairfam data that we used for all of our analyses. If you would like to reproduce our data preparation (also included in the replication file), you can order the pairfam data at https://www.pairfam.de/en/data/data-access/.

  • Citation: Brüderl, Josef, Ansgar Hudde, Marita Jacob. 2025. “What You Need to Know When Estimating Monthly Impact Functions: Comment on Hudde and Jacob, “There’s More in the Data!”” Sociological Science 12: 862-870.
  • Received: May 16, 2025
  • Accepted: August 31, 2025
  • Editors: Arnout van de Rijt, Kristian B. Karlson
  • DOI: 10.15195/v12.a34

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There's More in the Data! Using Month-Specific Information to Estimate Changes Before and After Major Life Events

Ansgar Hudde, Marita Jacob

Sociological Science November 9, 2023
10.15195/v10.a29


Sociological research is increasingly using survey panel data to examine changes in diverse outcomes over life course events. Most of these studies have one striking similarity: they analyze changes between yearly time intervals. In this article, we present a simple but effective method to model such trajectories more precisely using available data. The approach exploits month-specific information regarding interview and life event dates. Using fixed effects regression models, we calculate monthly dummy estimates around life events and then run nonparametric smoothing to create smoothed monthly estimates. We test the approach using Monte Carlo simulations and Socio-economic Panel (SOEP) data. Monte Carlo simulations show that the newly proposed smoothed monthly estimates outperform yearly dummy estimates, especially when there is rapid change or discontinuities in trends at the event. In the real data analyses, the novel approach reports an amplitude of change that is roughly twice as large as the yearly estimates showed. It also reveals a discontinuity in trajectories at bereavement, but not at childbirth; and remarkable gender differences. Our proposed method can be applied to several available data sets and a variety of outcomes and life events. Thus, for research on changes around life events, it serves as a powerful new tool in the researcher’s toolbox.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Ansgar Hudde: University of Cologne, Institute of Sociology and Social Psychology, Germany
E-mail: hudde@wiso.uni-koeln.de

Marita Jacob: University of Cologne, Institute of Sociology and Social Psychology, Germany
E-mail: marita.jacob@uni-koeln.de

Acknowledgements: Replication files are available here: https://osf.io/rhd8y/.

  • Citation: Hudde, Ansgar, and Marita Jacob. 2023. “There’s More in the Data! Using Month-Specific Information to Estimate Changes Before and After Major Life Events.” Sociological Science 10: 830-856.
  • Received: June 5, 2023
  • Accepted: July 27, 2023
  • Editors: Arnout van de Rijt, Vida Maralani
  • DOI: 10.15195/v10.a29


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