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:
# 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 & 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
#> $ comparable_spell <chr> "1996", "2002 - 2012", "2002 - 2012", "2002 - 201~
#> $ poverty_line <dbl> 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2~
#> $ headcount <dbl> 0.0053484604, 0.0109264739, 0.0059108568, 0.00199~
#> $ poverty_gap <dbl> 9.821458e-04, 1.894350e-03, 8.972340e-04, 3.96411~
#> $ poverty_severity <dbl> 3.047592e-04, 5.942301e-04, 2.285120e-04, 8.69032~
#> $ watts <dbl> 1.203124e-03, 2.382840e-03, 1.042396e-03, 4.48972~
#> $ mean <dbl> 7.933157, 8.108228, 9.165974, 10.038168, 9.517231~
#> $ median <dbl> 6.972102, 6.688141, 7.799790, 8.400199, 8.240384,~
#> $ 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> 0.3996353, 0.7016371, 0.7539579, 0.8201141, 0.917~
#> $ ppp <dbl> 50.35737, 50.35737, 50.35737, 50.35737, 50.35737,~
#> $ 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",~
get_dictionary()
#> # A tibble: 41 x 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~
#> # ... with 31 more rows
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/},
}