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Track professional group trajectories over time

Source: R/trajectory_analysis.R
track_professional_group_trajectories.Rd

This function analyzes how individuals move between professional groups after completing a specific contract type. It tracks whether individuals stay in the same professional group, move to different groups, become unemployed, or have no information available over a specified number of quarters.

Usage

track_professional_group_trajectories(
  data,
  contract_type_var = "COD_TIPOLOGIA_CONTRATTUALE",
  contract_type_value,
  group_col,
  n_quarters = 4,
  person_id = "cf",
  start_date_col = "inizio",
  end_date_col = "fine",
  arco_col = "arco",
  return_plot = TRUE,
  palette = "professional_group",
  use_bw = FALSE,
  plot_title = NULL,
  plot_subtitle = NULL,
  person_vars = NULL,
  chunk_size = 10000,
  language = "it"
)

Arguments

data

data.table containing employment contract data processed by vecshift

contract_type_var

Character string specifying the contract type variable name

contract_type_value

Character string specifying the contract type to analyze

group_col

Character string specifying the professional group column name (required)

n_quarters

Integer specifying number of quarters to track (1-20)

person_id

Character string specifying the person identifier column

start_date_col

Character string specifying the contract start date column

end_date_col

Character string specifying the contract end date column

arco_col

Character string specifying the employment intensity column

return_plot

Logical indicating whether to create an alluvial plot

palette

Character string specifying the color palette to use

use_bw

Logical indicating whether to use black and white colors

plot_title

Character string for plot title (auto-generated if NULL)

plot_subtitle

Character string for plot subtitle (auto-generated if NULL)

person_vars

Character vector of person-level variable names to include in the output data (e.g., c("eta", "sesso", "istruzione")). Variables are extracted from the first target contract for each person. Default is NULL (no additional variables).

chunk_size

Integer specifying the chunk size for processing large datasets

language

Character. Language for status labels: "it" for Italian, "en" for English (default: "it")

Value

A list containing:

  • data: data.table with individual-level quarterly group trajectories

  • summary: data.table with aggregated trajectory patterns

  • transitions: data.table with aggregated transition counts between quarters, including columns: from_quarter, to_quarter, from_status, to_status, person_vars (if provided), count

  • plot: ggplot2 alluvial plot (if return_plot = TRUE)

  • parameters: List of function parameters used

Details

The function requires exactly 4 unique professional groups in the data and uses the actual group names found in the data (no relabeling).

The function identifies individuals who completed the specified contract type and tracks their professional group transitions over the following quarters. For each person-quarter, the function shows which of the 4 professional groups the person is working in, or:

  • Group Name: Person works in one of the 4 professional groups (actual group names from data)

  • Not Working: Person has contracts but with arco = 0 (unemployment/inactivity)

  • No Information: Person has no contracts in the quarter

The function validates that exactly 4 unique professional groups exist in the target contracts and uses the actual group names found in the data:

  • Groups preserve their original names from the data

  • Colors assigned automatically: first group (Red), second group (Blue), third group (Green), fourth group (Orange)

  • Additional categories: "Not Working" (Grey), "No Information" (Dark Grey)

See also

track_contract_trajectories, track_sector_trajectories, track_employer_trajectories, theme_vecshift

Examples

if (FALSE) { # \dontrun{
# Track professional group trajectories after temporary contracts
result <- track_professional_group_trajectories(
  data = employment_data,
  contract_type_value = "B.01.00",
  group_col = "professional_category",
  n_quarters = 4
)

# View the summary of group trajectory patterns
print(result$summary)

# Display the alluvial plot
print(result$plot)

# Track trajectories with custom visualization
result_custom <- track_professional_group_trajectories(
  data = employment_data,
  contract_type_value = "B.01.00",
  group_col = "job_level",
  n_quarters = 6,
  plot_title = "Professional Group Mobility After Temporary Contracts"
)

# Black and white visualization
result_bw <- track_professional_group_trajectories(
  data = employment_data,
  contract_type_value = "B.01.00",
  group_col = "professional_category",
  use_bw = TRUE
)
} # }