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A practical revealed preference model for separating preferences and availability effects in marriage formation.

Shuchi Goyal1, Mark S Handcock1, Heide M Jackson2

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Summary

This study introduces a new model for understanding partnership formation in populations. The developed estimator accurately identifies individual preferences, even with unobserved characteristics, proving robust across different population compositions.

Keywords:
discrete choicemarriage marketsmatchingsurvey on income and program participationtwo-sided partnership

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Area of Science:

  • Demographic modeling
  • Sociological research
  • Behavioral economics

Background:

  • Partnership formation is crucial for demographic analysis.
  • Existing models often struggle with unobserved individual characteristics.
  • Understanding partner preferences requires accounting for both observed and unobserved traits.

Purpose of the Study:

  • To develop a robust statistical model for partnership formation.
  • To create an estimator for preference parameters in bipartite populations.
  • To validate the estimator's performance using simulation studies.

Main Methods:

  • Utilized a matching model for bipartite populations.
  • Incorporated individual utility functions based on observed and unobserved characteristics.
  • Developed an estimator using sample survey data on partnerships and population composition.
  • Conducted simulation studies using Survey of Income and Program Participation (SIPP) data.

Main Results:

  • The estimator successfully recovers preference parameters.
  • Identified preference parameters are invariant to changes in partner availability.
  • The estimator demonstrates accurate confidence interval coverage in simulations.
  • The model effectively captures individual preferences considering both observable and unobservable factors.

Conclusions:

  • The developed estimator provides a reliable method for analyzing partnership formation.
  • The model's robustness to population composition variations is confirmed.
  • This approach enhances demographic modeling by accounting for complex individual preferences.