Tag Archives | Life Course

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

0

Life-Course Transitions and Political Orientations

Turgut Keskintürk

Sociological Science September 27, 2024
10.15195/v11.a33


Do life-course transitions in adulthood shape political orientations? One framework suggests that life events expose people to new information, allowing actors to assess their political beliefs and preferences in response to these social experiences. An alternative framework suggests that the link between one’s life-course position and personal politics may be ambiguous, and early experiences should be more informative for political orientations. In this article, I use four household surveys across three countries and 40 items on political beliefs and preferences to test whether lifecourse transitions change one’s political orientations. In doing this, I employ difference-in-differences models to identify the effects of six life transitions across family and work domains on a wide variety of propositional survey items. I find that life-course transitions have no substantive influence on political orientations, and the general findings are not sensitive to differences in political interest or the age at which individuals experience these life events.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Turgut Keskintürk: Department of Sociology, Duke University
E-mail: turgut.keskinturk@duke.edu

Acknowledgements: I thank Stephen Vaisey, Craig Rawlings, and Christopher Wildeman for their extensive feedback on different versions of this manuscript, and Andrés Castro Araújo, Kevin Kiley, and the participants of the Worldview Lab at the Kenan Institute for Ethics at Duke University for their thoughtful comments on the project.

Supplemental Materials

Reproducibility Package: The code to reproduce the full set of analyses and instructions on how to access the household surveys are provided at https://osf.io/hu3yj/.

  • Citation: Keskintürk, Turgut 2024. “Life-Course Transitions and Political Orientations” Sociological Science 11: 907-933.
  • Received: July 3, 2024
  • Accepted: September 10, 2024
  • Editors: Arnout van de Rijt, Jeremy Freese
  • DOI: 10.15195/v11.a33


0

Life-Course Differences in Occupational Mobility Between Vocationally and Generally Trained Workers in Germany

Viktor Decker, Thijs Bol, Hanno Kruse

Sociological Science November 14, 2023
10.15195/v10.a30


Vocational education is considered beneficial to young workers entering the labor market but disadvantageous late in their careers. Many studies assume that late-career disadvantages stem from lower levels of occupational mobility, but do not explicitly study this mechanism. This study is the first to empirically assess whether and to what extent occupational mobility differs between workers with a general education and those with vocational training and to examine how these differences develop over workers’ life courses. Using multilevel linear probability models on panel data spanning 36 years of labor market participation in Germany, we find that vocationally educated workers are less mobile, but only in the first half of their careers. In the second half, mobility rates for vocationally and generally trained workers converge. Our findings support earlier research that links vocational education to less turbulent early careers. Yet, they do not support the notion of late-career mobility disparities between workers with different types of training. Implications for research on education-based differences in career outcomes are discussed.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Viktor Decker: Department of Sociology, University of Amsterdam
E-mail: v.v.decker@uva.nl

Thijs Bol: Department of Sociology, University of Amsterdam
E-mail: t.bol@uva.nl

Hanno Kruse: Institute of Political Science and Sociology, University of Bonn
E-mail: hkruse@uni-bonn.de

Acknowledgements: The research was supported by the ERC starting grant From School to Career: Towards A Career Perspective on the Labor Market Returns to Education (ID: 950189). Previous versions of this article were presented at the ISA RC28 conference 2022 at London School of Economics, the ECSR annual conference 2022 at University of Amsterdam, and at multiple events organized by the Dutch Interuniversity Center for Social Science Theory and Methodology.

  • Citation: Decker, Viktor, Thijs Bol, and Hanno Kruse. 2023. “Life-Course Differences in Occupational Mobility Between Vocationally and Generally Trained Workers in Germany.” Sociological Science 10: 857-879.
  • Received: May 3, 2023
  • Accepted: May 26, 2023
  • Editors: Ari Adut, Richard Breen
  • DOI: 10.15195/v10.a30


0

Using Sequence Analysis to Quantify How Strongly Life Courses Are Linked

Tim F. Liao

Sociological Science January 19, 2021
10.15195/v8.a3


Dyadic or, more generally, polyadic life course sequences can be more associated within dyads or polyads than between randomly assigned dyadic/polyadic member sequences, a phenomenon reflecting the life course principle of linked lives. In this article, I propose a method of U and V measures for quantifying and assessing linked life course trajectories in sequence data. Specifically, I compare the sequence distance between members of an observed dyad/polyad against a set of randomly generated dyads/polyads. TheU measure quantifies how much greater, in terms of a given distance measure, the members in a dyad/polyad resemble one another than do members of randomly generated dyads/polyads, and the V measure quantifies the degree of linked lives in terms of how much observed dyads/polyads outperform randomized dyads/polyads. I present a simulation study, an empirical study analyzing dyadic family formation sequence data from the Longitudinal Study of Generations, and a random seed sensitivity analysis in the online supplement. Through these analyses, I demonstrate the versatility and usefulness of the proposed method for quantifying linked lives analysis with sequence data. The method has broad applicability to sequence data in life course, business and organizational, and social network research.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Tim F. Liao: Department of Sociology, University of Illinois
E-mail: tfliao@illinois.edu

Acknowledgments: The author wishes to acknowledge the benefit of an Australian Research Council Discovery Project (DP#160101063, chief investigators Irma Mooi-Reci and Mark Wooden, and partner investigator Tim Liao). The abovementioned project anticipated the need for the research reported in this article. The author would also like to thank Anette Fasang and Marcel Raab, who kindly shared the Longitudinal Study of Generations data used in their 2014 Demography publication, and Yifan Shen for comments.

  • Citation: Liao, Tim F. 2021. “Using Sequence Analysis to Quantify How Strongly Life Courses Are Linked.” Sociological Science 8: 48-72.
  • Received: November 5, 2020
  • Accepted: December 13, 2020
  • Editors: Jesper Sørensen, Olav Sorenson
  • DOI: 10.15195/v8.a3


0

On Elastic Ties: Distance and Intimacy in Social Relationships

Stacy Torres

Sociological Science, April 9, 2019
10.15195/v6.a10


Drawing on five years of ethnographic fieldwork among older adults in a New York City neighborhood, I present empirical data that complement survey approaches to social isolation and push our understanding of social ties beyond weak and strong by analyzing relationships that defy binary classification. Usual survey items would describe these participants as isolated and without social support. When questioned, they minimize neighborhood relationships outside of close friends and family. But ethnographic observations of their social interactions with neighbors reveal the presence of “elastic ties.” By elastic ties, I mean nonstrong, nonweak relations between people who spend hours each day and share intimate details of their lives with those whom they do not consider “confidants.” Nonetheless, they provide each other with the support and practical assistance typically seen in strong-tie relationships. These findings show how people’s accounts may not accurately reflect the character and structure of their social ties. Furthermore, they demonstrate how a single social tie can vary between strong and weak depending on the social situation. Many social ties fall outside weak and strong; they are elastic in allowing elders (and other marginal groups) to connect and secure informal support while maintaining their distance and preserving their autonomy.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Stacy Torres: Department of Social and Behavioral Sciences, University of California, San Francisco
E-mail: stacy.torres@ucsf.edu

Acknowledgements: I thank Kathleen Gerson, Colin Jerolmack, Lynne Haney, Steven Lukes, Dalton Conley, Ronald Breiger, Anthony Paik, and Claude Fischer for their guidance and feedback on earlier versions of this article. A special thanks to my study participants, who shared their lives with me for several years. Support for data collection and project write-up was funded in part by fellowships from New York University, the American Sociological Association Minority Fellowship Program (cosponsored by Sociologists for Women in Society), the Ford Foundation, and the UC President’s Postdoctoral Fellowship Program. Publication is made possible in part by support from the UCSF Open Access Publishing Fund.

  • Citation: Torres, Stacy. 2019. “On Elastic Ties: Distance and Intimacy in Social Relationships.” Sociological Science 6: 235-263.
  • Received: November 15, 2018
  • Accepted: February 18, 2019
  • Editors: Jesper Sørensen, Mario Small
  • DOI: 10.15195/v6.a10


0

Age Trajectories of Poverty During Childhood and High School Graduation

Dohoon Lee

Sociological Science, September 1, 2014
DOI 10.15195/v1.a21

This article examines distinct trajectories of childhood exposure to poverty and provides estimates of their effect on high school graduation. The analysis incorporates three key insights from the life course and human capital formation literatures: (1) the temporal dimensions of exposure to poverty, that is, timing, duration, stability, and sequencing, are confounded with one another; (2) age-varying exposure to poverty not only affects, but also is affected by, other factors that vary with age; and (3) the effect of poverty trajectories is heterogeneous across racial and ethnic groups. Results from the Children of the National Longitudinal Survey of Youth show that any extended exposures to poverty substantially lower children’s odds of graduating from high school. Persistent, early, and middle-to-late childhood exposures to poverty reduce the odds of high school graduation by 77 percent, 55 percent, and 58 percent, respectively, compared to no childhood exposure to poverty. The findings thus suggest that the impact of poverty trajectories is insensitive to observed age-varying confounders. These impacts are more pronounced for white children than for black and Hispanic children.

Dohoon Lee:New York University. E-mail: dl111@nyu.edu

  • Citation: Lee, Dohoon. 2014. “Age trajectories of poverty during childhood and high school graduation.” Sociological Science 1: 344-365.
  • Received: May 22, 2014
  • Accepted: June 12, 2014
  • Editors: Jesper Sørensen, Stephen L. Morgan
  • DOI: 10.15195/v1.a21

0
SiteLock