Tag Archives | Happiness

The Happiness Paradox of Birth Order

Tamkinat Rauf

Sociological Science November 10, 2026
10.15195/v13.a50


That happiness tracks income is an abiding finding in the social science literature. First-born children tend to have higher socioeconomic attainment than later-borns, and therefore are expected to be relatively happier. Using data from representative U.S. surveys (approximately 15,000 individuals and 7,000 siblings), I find that although first-borns have substantially higher income levels, birth order effects on indicators of psychological well-being—life satisfaction, positive affect, and mental health—are statistically non-significant. Nevertheless, observed first-born effects on life satisfaction, albeit small, align with differences implied by birth order income gaps and the income–well-being gradient. By contrast, first-borns have significantly lower levels of positive affect and mental health than implied by their income advantage, revealing a happiness paradox. Possible explanations for the paradox are explored. These findings highlight the relevance of social context in shaping the income–happiness link, and invite investigation into relational determinants of well-being that may be independent of material success.

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.


Tamkinat Rauf: Department of Sociology, University of Wisconsin-Madison.
E-mail: trauf@wisc.edu

Acknowledgments: This article benefited greatly from Eric Grodsky’s detailed comments on an early version of the manuscript. Subsequent feedback from Felix Elwert and Jeremy Freese helped further clarify the analyses and arguments presented here. The study uses data from the National Longitudinal Surveys of Youth, sponsored by the U.S. Department of Labor Statistics, and managed by the Center for Human Resource Research (CHRR) at The Ohio State University. Interviews are conducted by the National Opinion Research Center (NORC) at the University of Chicago.


Supplemental Materials

Reproducibility Package: The datasets used in this article are publicly available at https://www.nlsinfo.org/. Tagsets for downloading variables used in these analyses and complete replication code is available at the Open Science Framework repository: https://doi.org/10.17605/OSF.IO/2DZGU.


  • Citation: Rauf, Tamkinat. 2026. “The Happiness Paradox of Birth Order” Sociological Science 13: 1329-1353.
  • Received: August 21, 2026
  • Accepted: September 18, 2026
  • Editors: Ari Adut, Michael Rosenfeld
  • DOI: 10.15195/v13.a50


0

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
SiteLock