Compute earnings tier shares from LODES RAC or WAC data — compute_earnings

Computes the share of jobs (or workers) in each of the three LODES monthly earnings tiers:

Low (CE01): Earnings up to $1,250/month.
Mid (CE02): Earnings $1,251-$3,333/month.
High (CE03): Earnings above $3,333/month.

Earnings shares are useful for tracking wage polarization, identifying low-wage job concentration, and examining how the earnings structure of a labor market has shifted over time, especially when combined with compute_lodes_change().

The total denominator is the sum of the three tiers, ensuring shares sum to 1 within rounding error.

Usage

compute_earnings_share(
  lodes_df,
  type = c("wac", "rac"),
  geo_col = NULL,
  output = c("wide", "long")
)

Arguments

lodes_df: A data frame (tibble) of LODES RAC or WAC data returned by grab_lodes() with segment = "S000" (the total count segment, which includes all three earnings columns). Must contain columns CE01, CE02, and CE03. Both WAC and RAC files include these earnings tier columns; the type argument controls only which geography prefix is used for auto-detection.
type: One of "wac" (workplace area characteristics, default) or "rac" (residential area characteristics). Controls the expected geography column prefix (w_ for WAC, h_ for RAC) when geo_col = NULL. Does not affect which earnings columns are used, as both file types share the CE01/CE02/CE03 schema.
geo_col: The name of the geography column to group by, e.g. "w_tract" or "h_county". Defaults to NULL, which auto-detects the first geography column in lodes_df.
output: One of "wide" (default) or "long". Wide format appends three share columns. Long format returns one row per geography-tier combination.

Value

A tibble with earnings tier counts and shares. In "wide" format, columns are added for share_low, share_mid, and share_high. In "long" format, columns are tier, label, count, and share.

Examples

if (FALSE) { # \dontrun{
  wac <- grab_lodes(
    state = "md", year = 2019,
    lodes_type = "wac", job_type = "JT00",
    segment = "S000", agg_geo = "county"
  )
  compute_earnings_share(wac, type = "wac", geo_col = "w_county")

  # Long format, suitable for ggplot2
  compute_earnings_share(
    wac, type = "wac", geo_col = "w_county", output = "long"
  )
} # }