Return main poverty and inequality statistics
Arguments
- country
(
NULL
|character()
)
Countries for which statistics are to be computed, specified as ISO3 codes. DefaultNULL
.- year
(
NULL
|character()
|numeric()
)
Years for which statistics are to be computed, specified as YYYY. DefaultNULL
.- povline
(
numeric(1)
)
Poverty line to be used to compute poverty mesures. Poverty lines are only accepted up to 3 decimals. Default2.15
.(
NULL
|numeric(1)
)
Proportion of the population living below the poverty line. Will be ignored if povline is specified. DefaultNULL
.- fill_gaps
(
logical(1)
)
Whether to fill gaps in the data. DefaultFALSE
.- 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. DefaultFALSE
.- release_version
(
NULL
|character(1)
)
Version of the data release in YYYYMMDD format. DefaultNULL
.- ppp_version
(
NULL
|character(1)
|numeric(1)
)
Version of the data. DefaultNULL
.- version
(
NULL
|character(1)
)
Version of the data. DefaultNULL
.
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{
data <- pip_data(c("ZAF", "ZMB"))
head(data)
#> region_name region_code country_name country_code reporting_year
#> 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
#> reporting_level survey_acronym survey_coverage survey_year welfare_type
#> 1 national KIDS national 1993.00 consumption
#> 2 national HIES national 2000.75 consumption
#> 3 national IES national 2005.00 consumption
#> 4 national LCS national 2008.67 consumption
#> 5 national IES national 2010.00 consumption
#> 6 national LCS national 2014.83 consumption
#> survey_comparability comparable_spell poverty_line headcount poverty_gap
#> 1 0 1993 2.15 0.3273500 0.11491448
#> 2 2 2000 2.15 0.3602300 0.13788884
#> 3 3 2005 - 2014 2.15 0.2738977 0.08866815
#> 4 3 2005 - 2014 2.15 0.1784118 0.05158000
#> 5 3 2005 - 2014 2.15 0.1736065 0.05210588
#> 6 3 2005 - 2014 2.15 0.1983516 0.06567713
#> poverty_severity watts mean median mld gini
#> 1 0.05071058 0.15409808 7.683054 3.511334 0.6366259 0.5933394
#> 2 0.06619755 0.19199955 6.563024 3.189002 0.5999924 0.5776966
#> 3 0.04015528 0.12285010 9.755512 3.624245 0.7781536 0.6476189
#> 4 0.02152328 0.06903565 12.303904 4.862677 0.7351245 0.6300900
#> 5 0.02242921 0.07096926 12.981507 5.088423 0.7526440 0.6338256
#> 6 0.03093106 0.09252674 12.214114 4.861294 0.7502294 0.6302572
#> polarization decile1 decile2 decile3 decile4 decile5
#> 1 0.7147437 0.012500158 0.01696966 0.02260853 0.02990889 0.03968160
#> 2 0.6770340 0.012816826 0.01782763 0.02403983 0.03193381 0.04229243
#> 3 0.7549428 0.009988367 0.01586569 0.02091390 0.02623093 0.03312265
#> 4 0.7609605 0.010057582 0.01602856 0.02129058 0.02735578 0.03503969
#> 5 0.7837881 0.009384293 0.01530752 0.02053135 0.02663764 0.03442381
#> 6 0.7876801 0.008574058 0.01507192 0.02074483 0.02708842 0.03505580
#> decile6 decile7 decile8 decile9 decile10 cpi ppp
#> 1 0.05336964 0.07383648 0.10780574 0.1767219 0.4665975 0.2135547 7.524514
#> 2 0.05649406 0.07724597 0.11084411 0.1772000 0.4493053 0.3639944 7.524514
#> 3 0.04201133 0.05651407 0.08522587 0.1679377 0.5421895 0.4452543 7.524514
#> 4 0.04551465 0.06298532 0.09485078 0.1743129 0.5125641 0.5474131 7.524514
#> 5 0.04529464 0.06279666 0.09618902 0.1768472 0.5125879 0.6110209 7.524514
#> 6 0.04650064 0.06531549 0.09957486 0.1771185 0.5049555 0.7607006 7.524514
#> reporting_pop reporting_gdp reporting_pce is_interpolated distribution_type
#> 1 43297156 4193.598 2372.839 FALSE group
#> 2 47465030 4700.876 2790.873 FALSE group
#> 3 49490033 5406.076 3292.593 FALSE micro
#> 4 51525923 6009.720 3738.485 FALSE micro
#> 5 52344051 5953.945 3758.295 FALSE micro
#> 6 56531658 6155.006 3887.509 FALSE micro
#> estimation_type spl spr pg estimate_type
#> 1 survey 3.056 0.4522100 10.713024 NA
#> 2 survey 3.000 0.4786800 11.991457 NA
#> 3 survey 3.112 0.4359328 10.127501 NA
#> 4 survey 3.731 0.3929107 7.772644 NA
#> 5 survey 3.844 0.3938811 7.727838 NA
#> 6 survey 3.731 0.3995142 8.395812 NA
# }