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Labor Market Segmentation and Immigrant Competition: A Quantal Response Statistical Equilibrium Analysis.

Noé M Wiener1

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This study introduces a new measure for labor market competition intensity using limited data. It applies maximum entropy and quantal response equilibrium models to understand wage inequality and worker mobility.

Keywords:
immigrationlabor market competitionstatistical equilibriumwage inequality

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Area of Science:

  • Labor Economics
  • Econometrics
  • Sociology

Background:

  • Labor markets exhibit competition within and between worker groups, often segmented by unobservable factors.
  • Persistent wage inequality is a significant challenge in understanding labor market dynamics.
  • Limited data availability often hinders the accurate measurement of labor market competition.

Purpose of the Study:

  • To propose a novel measure for quantifying labor market competition intensity.
  • To develop a robust microfoundation for persistent wage inequality patterns.
  • To analyze labor market competition between native-born and foreign-born workers in the US.

Main Methods:

  • Utilizing the maximum entropy principle for inferring unobserved worker mobility decisions.
  • Employing the quantal response statistical equilibrium (QRSE) class of models.
  • Applying the methodology to US household data for empirical validation.

Main Results:

  • The proposed measure effectively quantifies labor market competition intensity with limited data.
  • QRSE models provide robust microfoundations for observed wage inequality.
  • The application demonstrated that these models capture significant information from wage distributions.

Conclusions:

  • The developed methodology offers a powerful tool for analyzing labor market competition.
  • Understanding competition dynamics is crucial for addressing wage inequality.
  • The findings have implications for labor market policy and worker mobility studies.