The pipr package allows R users to compute poverty and inequality
indicators for more than 160 countries and regions from the World Bank’s
database of household surveys.
You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("worldbank/pipr")This is a basic example that shows how to retrieve some key poverty and inequity statistics.
library(dplyr)
library(pipr)
df <- get_stats(country = "ALB")
glimpse(df)
#> Rows: 14
#> Columns: 40
#> $ region_name <chr> "Europe and Central Asia", "Europe and Central As…
#> $ region_code <chr> "ECA", "ECA", "ECA", "ECA", "ECA", "ECA", "ECA", …
#> $ country_name <chr> "Albania", "Albania", "Albania", "Albania", "Alba…
#> $ country_code <chr> "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", …
#> $ year <dbl> 1996, 2002, 2005, 2008, 2012, 2014, 2015, 2016, 2…
#> $ reporting_level <chr> "national", "national", "national", "national", "…
#> $ survey_acronym <chr> "EWS", "LSMS", "LSMS", "LSMS", "LSMS", "HBS", "HB…
#> $ survey_coverage <chr> "national", "national", "national", "national", "…
#> $ welfare_time <dbl> 1996, 2002, 2005, 2008, 2012, 2014, 2015, 2016, 2…
#> $ welfare_type <chr> "consumption", "consumption", "consumption", "con…
#> $ survey_comparability <dbl> 0, 1, 1, 1, 1, 2, 2, 2, 4, 2, 4, 3, 4, 3
#> $ comparable_spell <chr> "1996", "2002 - 2012", "2002 - 2012", "2002 - 201…
#> $ poverty_line <dbl> 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9,…
#> $ headcount <dbl> 0.009206690, 0.015708434, 0.008605271, 0.00313649…
#> $ poverty_gap <dbl> 1.400507e-03, 2.617611e-03, 1.313255e-03, 5.12411…
#> $ poverty_severity <dbl> 4.111228e-04, 7.940742e-04, 3.348323e-04, 1.31118…
#> $ watts <dbl> 0.0016976386, 0.0032506353, 0.0015296081, 0.00059…
#> $ mean <dbl> 6.570821, 6.715828, 7.591930, 8.314345, 7.882867,…
#> $ median <dbl> 5.774805, 5.539607, 6.460357, 6.957659, 6.825289,…
#> $ mld <dbl> 0.1191043, 0.1648116, 0.1544128, 0.1488934, 0.138…
#> $ gini <dbl> 0.2701034, 0.3173898, 0.3059566, 0.2998467, 0.289…
#> $ polarization <dbl> 0.2412933, 0.2689816, 0.2545287, 0.2473111, 0.249…
#> $ decile1 <dbl> 0.03863286, 0.03494002, 0.03482536, 0.03733625, 0…
#> $ decile2 <dbl> 0.05289347, 0.04859444, 0.04920109, 0.05136781, 0…
#> $ decile3 <dbl> 0.06378683, 0.05842059, 0.05977283, 0.06088472, 0…
#> $ decile4 <dbl> 0.07322042, 0.06738204, 0.06921183, 0.06983584, 0…
#> $ decile5 <dbl> 0.08379662, 0.07653102, 0.07988158, 0.07912079, 0…
#> $ decile6 <dbl> 0.09354903, 0.08839459, 0.09037069, 0.08924133, 0…
#> $ decile7 <dbl> 0.1082309, 0.1022859, 0.1037214, 0.1029873, 0.105…
#> $ decile8 <dbl> 0.1247387, 0.1198443, 0.1212641, 0.1192908, 0.122…
#> $ decile9 <dbl> 0.1489955, 0.1492508, 0.1483394, 0.1453520, 0.148…
#> $ decile10 <dbl> 0.2121557, 0.2543564, 0.2434117, 0.2445831, 0.229…
#> $ cpi <dbl> 0.4445725, 0.7805330, 0.8387371, 0.9123323, 1.020…
#> $ ppp <dbl> 54.65258, 54.65258, 54.65258, 54.65258, 54.65258,…
#> $ pop <dbl> 3168033, 3051010, 3011487, 2947314, 2900401, 2889…
#> $ gdp <dbl> 1633.552, 2247.497, 2675.508, 3298.478, 3736.339,…
#> $ hfce <dbl> 1714.813, 1685.368, 2079.244, 2819.736, 2989.866,…
#> $ is_interpolated <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
#> $ distribution_type <chr> "micro", "micro", "micro", "micro", "micro", "mic…
#> $ estimation_type <chr> "survey", "survey", "survey", "survey", "survey",…To cite package pipr in publications use:
Tony Fujs, Aleksander Eilertsen, Ronak Shah and R. Andrés Castañeda (2022). pipr: Client for the PIP
API. https://github.com/worldbank/pipr, https://worldbank.github.io/pipr/.
A BibTeX entry for LaTeX users is
@Manual{,
title = {pipr: Client for the PIP API},
author = {Tony Fujs and Aleksander Eilertsen and Ronak Shah and R. Andrés Castañeda},
year = {2022},
note = {https://github.com/worldbank/pipr,https://worldbank.github.io/pipr/},
}