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Classify emerging professions

Source: R/emerging_profession.R
classify_emerging_professions.Rd

Applies the three-condition rule that defines an emerging profession: growing demand, profile change beyond sampling noise, and uptake of emerging skills faster than the regional average.

Usage

classify_emerging_professions(
  demand,
  turnover,
  turnover_null,
  uptake,
  prof_col,
  alpha = 0.05,
  slope_col = "pendenza",
  p_col = "p_adj"
)

Arguments

demand

Profession demand trends, e.g. compute_share_trend() on a panel of profession counts over all postings.

turnover

Output of compute_profile_turnover().

turnover_null

Output of compute_turnover_null().

uptake

Output of compute_emerging_uptake().

prof_col

Profession column.

alpha

Significance level. Default 0.05.

slope_col, p_col

Slope and adjusted p-value columns of demand. Defaults "pendenza", "p_adj".

Value

A data.table with the profession column, pendenza, turnover_netto, q_nullo, delta_quota, the three condition flags and emergente.

Details

A profession is emerging (emergente = TRUE) when all hold:

  1. crescita_significativa: the drift-net demand slope in demand is positive with p_col < alpha;

  2. turnover_oltre_nullo: turnover_netto exceeds the q_nullo quantile of its split-half null distribution;

  3. assorbimento_oltre_regione: delta_quota of the profession exceeds the upper bound delta_hi of the regional change.

Missing information makes a condition FALSE.

Examples

demand <- data.table::data.table(cp4 = c("p1", "p2"),
  pendenza = c(0.05, 0.05), p_adj = c(0.01, 0.01))
turnover <- data.table::data.table(cp4 = c("p1", "p2"),
  turnover_netto = c(0.3, 0.01))
null <- data.table::data.table(cp4 = c("p1", "p2"), q_nullo = 0.05)
uptake <- list(
  professioni = data.table::data.table(cp4 = c("p1", "p2"),
    delta_quota = c(0.2, 0.2)),
  regione = data.table::data.table(delta_hi = 0.05)
)
classify_emerging_professions(demand, turnover, null, uptake, "cp4")
#> Key: <cp4>
#>       cp4 pendenza turnover_netto q_nullo delta_quota crescita_significativa
#>    <char>    <num>          <num>   <num>       <num>                 <lgcl>
#> 1:     p1     0.05           0.30    0.05         0.2                   TRUE
#> 2:     p2     0.05           0.01    0.05         0.2                   TRUE
#>    turnover_oltre_nullo assorbimento_oltre_regione emergente
#>                  <lgcl>                     <lgcl>    <lgcl>
#> 1:                 TRUE                       TRUE      TRUE
#> 2:                FALSE                       TRUE     FALSE