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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. It does so by accessing the
Poverty and Inequality Platform (PIP) API. PIP is a computational tool
that allows users to estimate poverty rates for regions, sets of
countries or individual countries, over time and at any poverty
line.
You can install the development version from GitHub with:
# From CRAN
install.packages("devtools")
# From Github
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: 15
#> Columns: 44
#> $ region_name <chr> "Europe & Central Asia", "Europe & Central Asia",…
#> $ 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, 3
#> $ comparable_spell <chr> "1996", "2002 - 2012", "2002 - 2012", "2002 - 201…
#> $ poverty_line <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
#> $ headcount <dbl> 0.029678411, 0.041947222, 0.026502176, 0.00827307…
#> $ poverty_gap <dbl> 0.0043977900, 0.0072032820, 0.0040605484, 0.00135…
#> $ poverty_severity <dbl> 1.176030e-03, 2.111000e-03, 1.064328e-03, 3.86292…
#> $ watts <dbl> 0.0052255168, 0.0087713516, 0.0047720677, 0.00161…
#> $ mean <dbl> 8.442033, 8.628334, 9.753929, 10.682071, 10.12771…
#> $ median <dbl> 7.419330, 7.117154, 8.300111, 8.939033, 8.768967,…
#> $ 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> 0.03881788, 0.03523453, 0.03487046, 0.03738298, 0…
#> $ decile2 <dbl> 0.05279230, 0.04848445, 0.04936295, 0.05143395, 0…
#> $ decile3 <dbl> 0.06370657, 0.05852072, 0.05965820, 0.06098502, 0…
#> $ decile4 <dbl> 0.07524026, 0.06737630, 0.06935466, 0.06984726, 0…
#> $ decile5 <dbl> 0.08346224, 0.07640787, 0.07965423, 0.07901133, 0…
#> $ decile6 <dbl> 0.09245731, 0.08838444, 0.09039091, 0.08937947, 0…
#> $ decile7 <dbl> 0.1077896, 0.1023247, 0.1040651, 0.1028830, 0.105…
#> $ decile8 <dbl> 0.1261162, 0.1198690, 0.1210287, 0.1192047, 0.122…
#> $ decile9 <dbl> 0.1525077, 0.1499992, 0.1482984, 0.1454680, 0.148…
#> $ decile10 <dbl> 0.2071100, 0.2533988, 0.2433163, 0.2444043, 0.229…
#> $ cpi <dbl> 0.3724766, 0.6539548, 0.7027200, 0.7643803, 0.854…
#> $ ppp <dbl> 50.7723, 50.7723, 50.7723, 50.7723, 50.7723, 50.7…
#> $ pop <dbl> 3168033, 3051010, 3011487, 2947314, 2900401, 2889…
#> $ gdp <dbl> 1633.552, 2247.498, 2675.509, 3298.479, 3736.340,…
#> $ hfce <dbl> 1716.337, 1685.203, 2079.203, 2820.280, 2990.397,…
#> $ 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",…
#> $ spl <dbl> 5.010, 4.859, 5.450, 5.770, 5.684, 5.714, 6.644, …
#> $ spr <dbl> 0.2039019, 0.2244040, 0.2099751, 0.1726098, 0.189…
#> $ pg <dbl> 4.209428, 4.429310, 3.860997, 3.450628, 3.634575,…
#> $ estimate_type <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…get_aux("dictionary")
#> # A tibble: 41 × 2
#> variable definition
#> <chr> <chr>
#> 1 region_name World Bank region name
#> 2 region_code Three-letter World Bank abbreviation of world regions
#> 3 year Year
#> 4 country_name World Bank country name
#> 5 country_code Three-letter ISO (alpha-3) country code system for internati…
#> 6 reporting_level Reporting level
#> 7 survey_acronym Country survey acronym
#> 8 survey_coverage Geographic coverage of the country survey (i.e. national, ur…
#> 9 welfare_time Welfare time
#> 10 welfare_type Type of welfare vector used for estimates (income or consump…
#> # ℹ 31 more rowsTo 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/},
}These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.