Return main poverty and inequality statistics

Return main poverty and inequality statistics

Usage

pip_data(
  country = NULL,
  year = NULL,
  povline = 2.15,
  popshare = NULL,
  fill_gaps = FALSE,
  welfare_type = c("all", "consumption", "income"),
  reporting_level = c("all", "national", "rural", "urban"),
  additional_ind = FALSE,
  release_version = NULL,
  ppp_version = NULL,
  version = NULL
)

Source

https://pip.worldbank.org/api

Arguments

country

character() countries for which statistics are to be computed, specified as ISO3 codes. Default NULL.

year

character() | numeric() year(s) for which statistics are to be computed, specified as YYYY. Default NULL.

povline

numeric(1) poverty line to be used to compute poverty mesures. Poverty lines are only accepted up to 3 decimals. Default 2.15.

popshare

numeric(1) proportion of the population living below the poverty line. Will be ignored if povline is specified. Default NULL.

fill_gaps

logical(1) whether to fill gaps in the data. Default FALSE.

welfare_type

character(1) type of welfare measure to be used. Default "all".

reporting_level

character(1) level of reporting for the statistics. Default "all".

additional_ind

logical(1) whether to include additional indicators. Default FALSE.

release_version

character(1) version of the data release in YYYYMMDD format. Default NULL.

ppp_version

character(1) | numeric(1) version of the data. Default NULL.

version

character(1) version of the data. Default NULL.

Value

A data.frame() with the requested statistics.

See also

Other poverty and inequality statistics: pip_aux(), pip_citation(), pip_group(), pip_health_check(), pip_info(), pip_valid_params(), pip_versions()

Examples

# \donttest{
pip_data(c("ZAF", "ZMB"))
#> # A tibble: 16 × 44
#>    region_name        region_code country_name country_code reporting_year
#>    <chr>              <chr>       <chr>        <chr>                 <int>
#>  1 Sub-Saharan Africa SSA         South Africa ZAF                    1993
#>  2 Sub-Saharan Africa SSA         South Africa ZAF                    2000
#>  3 Sub-Saharan Africa SSA         South Africa ZAF                    2005
#>  4 Sub-Saharan Africa SSA         South Africa ZAF                    2008
#>  5 Sub-Saharan Africa SSA         South Africa ZAF                    2010
#>  6 Sub-Saharan Africa SSA         South Africa ZAF                    2014
#>  7 Sub-Saharan Africa SSA         Zambia       ZMB                    1991
#>  8 Sub-Saharan Africa SSA         Zambia       ZMB                    1993
#>  9 Sub-Saharan Africa SSA         Zambia       ZMB                    1996
#> 10 Sub-Saharan Africa SSA         Zambia       ZMB                    1998
#> 11 Sub-Saharan Africa SSA         Zambia       ZMB                    2002
#> 12 Sub-Saharan Africa SSA         Zambia       ZMB                    2004
#> 13 Sub-Saharan Africa SSA         Zambia       ZMB                    2006
#> 14 Sub-Saharan Africa SSA         Zambia       ZMB                    2010
#> 15 Sub-Saharan Africa SSA         Zambia       ZMB                    2015
#> 16 Sub-Saharan Africa SSA         Zambia       ZMB                    2022
#> # ℹ 39 more variables: reporting_level <chr>, survey_acronym <chr>,
#> #   survey_coverage <chr>, survey_year <dbl>, welfare_type <chr>,
#> #   survey_comparability <int>, comparable_spell <chr>, poverty_line <dbl>,
#> #   headcount <dbl>, poverty_gap <dbl>, poverty_severity <dbl>, watts <dbl>,
#> #   mean <dbl>, median <dbl>, mld <dbl>, gini <dbl>, polarization <dbl>,
#> #   decile1 <dbl>, decile2 <dbl>, decile3 <dbl>, decile4 <dbl>, decile5 <dbl>,
#> #   decile6 <dbl>, decile7 <dbl>, decile8 <dbl>, decile9 <dbl>, …
# }