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Data

The project turns employment histories and external firm data into model outputs and analysis-ready datasets. This page shows only the main path; each dataset page documents its exact grain, inputs, builder, location, and consumers.

flowchart TB
    revelio[(Revelio employment data)]
    linked[(Compustat, CRSP, patents,<br/>executives, and governance data)]

    employment[(Employment data)]
    firmdata[(Reusable firm-linked data)]
    periods[(Model-ready relationship periods)]
    hct[HCT training and scoring]
    scores[(Model outputs)]
    analysis[(Analysis-ready datasets)]

    revelio --> employment --> periods --> hct --> scores --> analysis
    linked --> firmdata --> analysis
    employment --> firmdata

    classDef source fill:#e8eef7,stroke:#52739e,stroke-width:2px
    classDef data fill:#e2f2e7,stroke:#3b7a4b,stroke-width:2px
    classDef model fill:#fff0cc,stroke:#a66b00,stroke-width:2px
    classDef output fill:#eee5f5,stroke:#76528c,stroke-width:2px

    class revelio,linked source
    class employment,firmdata,periods data
    class hct model
    class scores,analysis output

How the documentation is organized

Source data

Files obtained from vendors or external providers. These pages describe how the data were obtained, the source files available, and the identifiers used by the project. Source files are treated as immutable.

Processed datasets

Project-built datasets that clean, reshape, sample, or link source data. Each page begins with a small input–transformation–output diagram and identifies the dataset's grain and keys. The pages are grouped into employment, accounting and market, patent, and executive and governance data.

Model outputs

Datasets written by an HCT scorer. The training outputs preserve an out-of-sample worker group; full_training outputs provide the final MQ measure used by most downstream analyses. Training itself is documented under Model.

Analysis datasets

Datasets built for statistical analyses, grouped by their unit and research use. LaTeX tables, fitted models, metrics, and figures are not data products; they are stored under /artifacts and documented with their analysis.

Storage conventions

/data/<coverage>/processed/          canonical processed and model-ready data
/data/<coverage>/analyses/           coverage-level analysis support data
/data/<coverage>/analyses/<mode>/    model outputs and mode-specific analysis data
/artifacts/<coverage>/               checkpoints and analysis results

<coverage> is samples, one_percent, or full. <mode> is training or full_training. These are the intended conventions, but some legacy products remain under raw or analyses; those exceptions are stated on their dataset pages. Some firm-linked products exist only at full coverage.