Worker outcomes

These analyses test whether MQ is associated with wages and whether it predicts the worker's observed next employer at separation.

flowchart TB
    regression[(Disaggregated regression data)]
    ranks[(Destination ranks)]

    wage_code[[Wage-regression code]]
    destination_code[[Destination-evaluation code]]

    wage_cache[(Compact fits, clustered covariance,<br/>and metrics)]
    destination_metrics[(Ranking and MQ-gain metrics)]

    wage[/Wage-regression LaTeX tables/]
    destination[/Next-employer-prediction LaTeX table/]

    regression --> wage_code --> wage_cache --> wage
    ranks --> destination_code --> destination_metrics --> destination

    classDef input fill:#eee5f5,stroke:#76528c,stroke-width:2px
    classDef code fill:#f3f3f3,stroke:#666,stroke-width:2px
    classDef support fill:#fff0cc,stroke:#a66b00,stroke-width:2px
    classDef tableOutput fill:#e2f2e7,stroke:#3b7a4b,stroke-width:2px
    class regression,ranks input
    class wage_code,destination_code code
    class wage_cache,destination_metrics support
    class wage,destination tableOutput

Analysis	Main comparison	Final fragment
Wage regressions	MQ coefficients across controls, fixed effects, tenure, and model samples	One wage_regressions.tex per requested sample
Next-employer prediction	Destination ranking and MQ change across model samples	destination_prediction.tex