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In this work we introduce a new unconditional quantile mixed model extending the Recentered Influence Function (RIF) regression approach for cross-sectional analysis to clustered data structures. To assess the effect of changes in the covariates on the quantiles of the unconditional distribution of the response in each group, we propose to estimate a random effects model for the conditional mean of the RIF on the explanatory variables. In the empirical analysis, we use a sample of US male workers from the 1983 Outgoing Rotation group supplement of the Current Population Survey to investigate the impact of unions on the distribution of hourly wages.

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Random Effects in Unconditional Quantile Regressions

  • 会议论文

  • 发表日期：

    2025年

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  • Luca Merlo,
  • Nicola Salvati,
  • Enrico Fabrizi,
  • Paolo Frumento,
  • Lea Petrella

摘要

In this work we introduce a new unconditional quantile mixed model extending the Recentered Influence Function (RIF) regression approach for cross-sectional analysis to clustered data structures. To assess the effect of changes in the covariates on the quantiles of the unconditional distribution of the response in each group, we propose to estimate a random effects model for the conditional mean of the RIF on the explanatory variables. In the empirical analysis, we use a sample of US male workers from the 1983 Outgoing Rotation group supplement of the Current Population Survey to investigate the impact of unions on the distribution of hourly wages.