Return main poverty and inequality statistics
Arguments
- country
(
character()) countries for which statistics are to be computed, specified as ISO3 codes. DefaultNULL.- year
(
character()|numeric()) year(s) 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.(
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
(
character(1)) version of the data release in YYYYMMDD format. DefaultNULL.- ppp_version
(
character(1)|numeric(1)) version of the data. DefaultNULL.- version
(
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{
pip_data(c("ZAF", "ZMB"))
#> 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
#> 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
#> 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
#> 7 national HBS national 1991.00 consumption
#> 8 national HBS national 1993.00 consumption
#> 9 national LCMS-I national 1996.00 consumption
#> 10 national LCMS-II national 1998.00 consumption
#> 11 national LCMS-III national 2002.83 consumption
#> 12 national LCMS-IV national 2004.67 consumption
#> 13 national LCMS-V national 2006.50 consumption
#> 14 national LCMS-VI national 2010.00 consumption
#> 15 national LCMS-VII national 2015.00 consumption
#> 16 national LCMS-VIII national 2022.00 consumption
#> survey_comparability comparable_spell poverty_line headcount poverty_gap
#> 1 0 1993 2.15 0.3354000 0.11971810
#> 2 2 2000 2.15 0.3682500 0.14291195
#> 3 3 2005 - 2014 2.15 0.2833133 0.09288520
#> 4 3 2005 - 2014 2.15 0.1866297 0.05448886
#> 5 3 2005 - 2014 2.15 0.1803596 0.05487818
#> 6 3 2005 - 2014 2.15 0.2049256 0.06870356
#> 7 0 1991 2.15 0.5743860 0.35951387
#> 8 1 1993 2.15 0.5905600 0.30813174
#> 9 2 1996 2.15 0.4677338 0.18942891
#> 10 3 1998 - 2006 2.15 0.4722561 0.19783822
#> 11 3 1998 - 2006 2.15 0.5638885 0.21314192
#> 12 3 1998 - 2006 2.15 0.6106246 0.30677434
#> 13 3 1998 - 2006 2.15 0.6469803 0.33600251
#> 14 4 2010 - 2022 2.15 0.6440190 0.31418902
#> 15 4 2010 - 2022 2.15 0.6079309 0.31802458
#> 16 4 2010 - 2022 2.15 0.6434975 0.33094933
#> poverty_severity watts mean median mld gini
#> 1 0.05363426 0.16153411 7.512568 3.433418 0.6366259 0.5933394
#> 2 0.06945470 0.20017310 6.417391 3.118238 0.5999924 0.5776966
#> 3 0.04238680 0.12914374 9.539026 3.543823 0.7781977 0.6476209
#> 4 0.02290619 0.07313433 12.030882 4.754775 0.7351245 0.6300900
#> 5 0.02380089 0.07497618 12.693438 4.975511 0.7526825 0.6338269
#> 6 0.03252772 0.09708224 11.943078 4.753422 0.7502534 0.6302580
#> 7 0.26697867 0.72325000 3.119898 1.647333 0.7346184 0.5940293
#> 8 0.19953101 0.53839710 2.799716 1.706298 0.5083919 0.5255011
#> 9 0.09978449 0.28267047 3.619184 2.330480 0.4041692 0.4832838
#> 10 0.10749534 0.30277298 3.583934 2.277596 0.4229948 0.4912212
#> 11 0.10566047 0.30698124 2.732604 1.930888 0.2983276 0.4205863
#> 12 0.18804439 0.50586948 2.910987 1.609220 0.5216132 0.5426393
#> 13 0.21038845 0.56284589 2.680506 1.465410 0.5250066 0.5456934
#> 14 0.18728590 0.50608655 2.680243 1.537594 0.4672895 0.5201111
#> 15 0.20214089 0.54189873 2.976326 1.608135 0.5640261 0.5583758
#> 16 0.20631427 0.55236223 2.527800 1.485089 0.4655922 0.5148312
#> polarization decile1 decile2 decile3 decile4 decile5
#> 1 0.7147437 0.012500158 0.016969663 0.02260853 0.02990889 0.03968160
#> 2 0.6770340 0.012816826 0.017827628 0.02403983 0.03193381 0.04229243
#> 3 0.7549428 0.009987132 0.015865706 0.02091393 0.02623096 0.03312269
#> 4 0.7609605 0.010057582 0.016028558 0.02129058 0.02735578 0.03503969
#> 5 0.7837881 0.009383491 0.015307528 0.02053137 0.02663766 0.03442384
#> 6 0.7876801 0.008573526 0.015071925 0.02074484 0.02708844 0.03505582
#> 7 0.7582579 0.008024062 0.008667579 0.01582433 0.02725084 0.04317652
#> 8 0.5411877 0.011067811 0.019735176 0.02961919 0.04072260 0.05365048
#> 9 0.4541652 0.017246059 0.027708256 0.03687062 0.04620273 0.05726297
#> 10 0.4574639 0.016031158 0.027195332 0.03583848 0.04555774 0.05724019
#> 11 0.3480729 0.024213961 0.037077847 0.04643740 0.05537981 0.06517655
#> 12 0.5443317 0.013519311 0.022170250 0.03018672 0.03852603 0.04905841
#> 13 0.5484201 0.013640085 0.022110678 0.02962806 0.03823438 0.04860521
#> 14 0.5069726 0.015926239 0.024963175 0.03315291 0.04145005 0.05179524
#> 15 0.5838927 0.011593392 0.019786983 0.02742864 0.03583844 0.04743057
#> 16 0.5356241 0.014730372 0.023792915 0.03206024 0.04119664 0.05223906
#> decile6 decile7 decile8 decile9 decile10 cpi ppp
#> 1 0.05336964 0.07383648 0.10780574 0.1767219 0.4665975 0.250919243 6.549363
#> 2 0.05649406 0.07724597 0.11084411 0.1772000 0.4493053 0.427680670 6.549363
#> 3 0.04201139 0.05651415 0.08522598 0.1679379 0.5421901 0.523158205 6.549363
#> 4 0.04551465 0.06298532 0.09485078 0.1743129 0.5125641 0.643191146 6.549363
#> 5 0.04529468 0.06279671 0.09618910 0.1768473 0.5125883 0.717928132 6.549363
#> 6 0.04650066 0.06531552 0.09957491 0.1771186 0.5049558 0.893796432 6.549363
#> 7 0.06373679 0.09083097 0.12825572 0.1881510 0.4260822 0.002368799 4.223818
#> 8 0.06942920 0.09002134 0.11990938 0.1731933 0.3926515 17.831811990 4.223818
#> 9 0.07184293 0.08995160 0.11674991 0.1630785 0.3730865 0.053219872 4.223818
#> 10 0.07123715 0.08951033 0.11549372 0.1603932 0.3815027 0.082410771 4.223818
#> 11 0.07712225 0.09201815 0.11447193 0.1509535 0.3371486 0.230108468 4.223818
#> 12 0.06330786 0.08213626 0.11150286 0.1630353 0.4265570 0.314197420 4.223818
#> 13 0.06190788 0.08118061 0.11027127 0.1629910 0.4314308 0.380220828 4.223818
#> 14 0.06385541 0.08224747 0.11178960 0.1645366 0.4102833 0.552641656 4.223818
#> 15 0.06169146 0.08219847 0.11158199 0.1682373 0.4342127 0.796036473 4.223818
#> 16 0.06696812 0.08708625 0.11781478 0.1732533 0.3908583 1.839073644 4.223818
#> reporting_pop reporting_gdp reporting_pce is_interpolated distribution_type
#> 1 42525440 4269.7002 2415.8990 FALSE group
#> 2 47125602 4735.6655 2811.5279 FALSE group
#> 3 49017147 5458.2302 3324.3577 FALSE micro
#> 4 50971140 6074.9427 3779.0585 FALSE micro
#> 5 51784921 6018.2308 3798.8744 FALSE micro
#> 6 55681522 6252.3180 3948.9717 FALSE micro
#> 7 7880466 867.7624 NA FALSE micro
#> 8 8270917 867.7130 NA FALSE group
#> 9 8902019 805.1419 NA FALSE micro
#> 10 9372430 790.8356 NA FALSE micro
#> 11 10781928 844.0920 NA FALSE micro
#> 12 11440516 907.4937 NA FALSE micro
#> 13 12186820 981.3455 NA FALSE micro
#> 14 13792086 1198.3048 NA FALSE micro
#> 15 16248230 1307.9096 662.4129 FALSE micro
#> 16 20017675 1308.1018 NA FALSE imputed
#> estimation_type spl spr pg estimate_type
#> 1 survey 2.866709 0.4377100 9.782268 NA
#> 2 survey 2.709119 0.4506500 10.949629 NA
#> 3 survey 2.921912 0.4191221 9.251945 NA
#> 4 survey 3.527387 0.3796311 7.097350 NA
#> 5 survey 3.637755 0.3777062 7.060190 NA
#> 6 survey 3.526711 0.3856719 7.668721 NA
#> 7 survey 2.150000 0.5743860 32.953354 NA
#> 8 survey 2.150000 0.5905600 23.711825 NA
#> 9 survey 2.315240 0.4976326 14.467603 NA
#> 10 survey 2.288798 0.5024772 15.302274 NA
#> 11 survey 2.150000 0.5638885 15.518775 NA
#> 12 survey 2.150000 0.6106246 21.526754 NA
#> 13 survey 2.150000 0.6469803 23.388736 NA
#> 14 survey 2.150000 0.6440190 21.211359 NA
#> 15 survey 2.150000 0.6079309 23.087937 NA
#> 16 survey 2.150000 0.6434975 23.058921 NA
# }