Match-quality variation

This analysis measures how much pair-level MQ variation is explained by additive worker and firm components.

flowchart LR
    pairs[(Full-training worker-firm pair data)]
    fit[[Estimate worker, firm,<br/>and worker + firm FE models]]
    metrics[(R2 and residual-SD metrics)]
    latex[/pairs_variations.tex/]

    pairs --> fit --> metrics --> latex

    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 pairs input
    class fit code
    class metrics support
    class latex tableOutput

The table uses full-training in-sample pairs with nonmissing pair_mq. It compares all scored pairs with movers, where movers are workers observed at two or more firms. For each sample it reports the no-FE MQ standard deviation and the $R^2$ and residual standard deviation from worker FE, firm FE, and additive worker-plus-firm FE models. It also reports pair, worker, and firm counts.

The additive worker-plus-firm specification deliberately does not include a worker-firm fixed effect, which would absorb the pair component being measured.

Input: Worker-firm pair data Module: analyses/modules/pairs_variations.R

Rscript pipelines/pairs_variations.R \
  --config config/config_one_percent.yaml

slurm/submit.sh --task pairs-variations \
  --config config_full.yaml

/artifacts/<coverage>/analyses/pairs_variations/
  pairs_variations_metrics.csv
  pairs_variations.tex
  pairs_variations_metadata.yaml