Creates synthetic data for testing and demonstrating inequalitykit functions. Three types are available: individual incomes, a two-period panel for growth incidence analysis, and grouped incomes for decomposition.
Usage
iq_sample_data(type = c("income", "panel", "grouped"))Value
A data.frame.
"income"1000 rows with columns
incomeandweight. Drawn from a lognormal distribution (mean log 10.5, sd log 0.8), producing realistic income-like data centred around 40,000."panel"1000 rows with columns
income_t0,income_t1,weight. Two periods with heterogeneous growth (bottom grows slower than top, mimicking rising inequality)."grouped"1000 rows with columns
income,group,weight. Three groups (A, B, C) with different mean incomes for between/within decomposition.
Details
The data is generated from a fixed seed, so a given type always returns
the same values. The seed applies for the duration of the call only: your
own random stream is restored on exit, so calling this function does not
affect the reproducibility of anything you do afterwards.
Examples
d <- iq_sample_data("income")
head(d)
#> income weight
#> 1 108745.63 1
#> 2 23115.10 1
#> 3 48557.44 1
#> 4 60251.94 1
#> 5 50182.15 1
#> 6 33359.58 1
panel <- iq_sample_data("panel")
head(panel)
#> income_t0 income_t1 weight
#> 1 108745.63 124508.50 1
#> 2 23115.10 24345.83 1
#> 3 48557.44 52856.81 1
#> 4 60251.94 64806.34 1
#> 5 50182.15 51703.77 1
#> 6 33359.58 34353.55 1
grouped <- iq_sample_data("grouped")
head(grouped)
#> income group weight
#> 1 61241.18 A 1
#> 2 19171.52 A 1
#> 3 33452.34 A 1
#> 4 39329.00 A 1
#> 5 34288.35 A 1
#> 6 25243.53 A 1