Sample Employment Data — sample • longworkR

A sample dataset containing longitudinal employment records processed by the vecshift package. This dataset is suitable for testing and demonstrating longworkR functions for career trajectory analysis, survival analysis, and impact evaluation.

Usage

sample

Format

A data.table with 434,103 rows and 28 columns:

id: Unique record identifier
cf: Person identifier (codice fiscale anonymized)
inizio: Contract start date (Date)
fine: Contract end date (Date)
arco: Concurrent employment indicator (logical)
prior: Employment intensity (1 = full-time, 0-1 = part-time/other)
over_id: Employment period identifier for consolidation
durata: Contract duration in days
qualifica: Job qualification code
ateco: Economic activity sector code (ATECO)
ore: Working hours per week
retribuzione: Salary/compensation amount
COD_TIPOLOGIA_CONTRATTUALE: Contract type code (X.01.00 format)
eta: Age at contract start
sesso: Gender (M/F)
istruzione: Education level
datore: Employer identifier (anonymized)
area: Geographic area code
troncata: Truncation indicator for administrative censoring
provincia: Province code
COMUNE_LAVORATORE: Municipality code for worker
stato: Employment state/status
did_attribute: Difference-in-differences attribute for matching
did_distance: Distance metric for DiD matching
did_match_quality: Quality score for DiD match
pol_attribute: Policy evaluation attribute
pol_distance: Distance metric for policy matching
pol_match_quality: Quality score for policy match

Source

Synthetic data based on Italian administrative employment records

Details

This dataset has been processed by the vecshift package and includes:

Employment period consolidation via over_id
Concurrent employment detection via arco
Employment intensity adjustments via prior
Impact evaluation matching variables (DiD and policy attributes)

The data is suitable for:

Career trajectory analysis
Contract survival analysis
Employment transition network analysis
Impact evaluation (DiD, PSM, RDD methods)

Examples

if (FALSE) { # \dontrun{
# Load the dataset
data(sample)

# Basic exploration
str(sample)
summary(sample)

# Analyze employment transitions
transitions <- analyze_employment_transitions(sample)

# Estimate contract survival
survival_results <- estimate_contract_survival_optimized(sample)
} # }