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 0.3273500 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
#> 7 0 1991 2.15 0.5381684 0.33395130
#> 8 1 1993 2.15 0.5424300 0.27433243
#> 9 2 1996 2.15 0.4133771 0.15654076
#> 10 3 1998 - 2006 2.15 0.4180117 0.16553755
#> 11 3 1998 - 2006 2.15 0.4906109 0.17206749
#> 12 3 1998 - 2006 2.15 0.5645888 0.27003818
#> 13 3 1998 - 2006 2.15 0.6028530 0.29820089
#> 14 4 2010 - 2022 2.15 0.5959820 0.27422965
#> 15 4 2010 - 2022 2.15 0.5653299 0.28276612
#> 16 4 2010 - 2022 2.15 0.5969237 0.29310627
#> 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
#> 7 0.24502732 0.65643750 3.527235 1.862636 0.7360095 0.5942023
#> 8 0.17391152 0.46908923 3.165553 1.929307 0.5086483 0.5255385
#> 9 0.07927822 0.22857635 4.092197 2.635068 0.4041857 0.4832856
#> 10 0.08672670 0.24822724 4.052331 2.575272 0.4230418 0.4912264
#> 11 0.08129958 0.24229162 3.089747 2.183250 0.2983345 0.4205873
#> 12 0.15994412 0.43382644 3.291411 1.819541 0.5217250 0.5426552
#> 13 0.18051083 0.48622575 3.030802 1.656936 0.5251344 0.5457134
#> 14 0.15732420 0.43006570 3.030522 1.738554 0.4673595 0.5201220
#> 15 0.17465904 0.46996718 3.365255 1.818314 0.5642529 0.5584075
#> 16 0.17671518 0.47631045 2.858142 1.679187 0.4657032 0.5148495
#> 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
#> 7 0.7583306 0.007949105 0.00862397 0.01582624 0.02725412 0.04318172
#> 8 0.5411901 0.011043074 0.01973567 0.02961993 0.04072362 0.05365183
#> 9 0.4541652 0.017244862 0.02770829 0.03687066 0.04620279 0.05726304
#> 10 0.4574639 0.016027705 0.02719543 0.03583861 0.04555790 0.05724039
#> 11 0.3480729 0.024213292 0.03707787 0.04643743 0.05537985 0.06517659
#> 12 0.5443322 0.013508999 0.02217048 0.03018703 0.03852643 0.04905893
#> 13 0.5484208 0.013627192 0.02211097 0.02962845 0.03823488 0.04860585
#> 14 0.5069728 0.015919193 0.02496335 0.03315314 0.04145034 0.05179562
#> 15 0.5838948 0.011572949 0.01978739 0.02742921 0.03583918 0.04743155
#> 16 0.5356247 0.014718426 0.02379320 0.03206063 0.04119714 0.05223970
#> decile6 decile7 decile8 decile9 decile10 cpi ppp
#> 1 0.05336964 0.07383648 0.10780574 0.1767219 0.4665975 0.213554679 7.524514
#> 2 0.05649406 0.07724597 0.11084411 0.1772000 0.4493053 0.363994436 7.524514
#> 3 0.04201133 0.05651407 0.08522587 0.1679377 0.5421895 0.445254343 7.524514
#> 4 0.04551465 0.06298532 0.09485078 0.1743129 0.5125641 0.547413093 7.524514
#> 5 0.04529464 0.06279666 0.09618902 0.1768472 0.5125879 0.611020941 7.524514
#> 6 0.04650064 0.06531549 0.09957486 0.1771185 0.5049555 0.760700567 7.524514
#> 7 0.06374448 0.09084192 0.12827118 0.1881736 0.4261336 0.001429636 6.189585
#> 8 0.06943093 0.09002360 0.11991238 0.1731977 0.3926613 10.761994155 6.189585
#> 9 0.07184301 0.08995171 0.11675005 0.1630787 0.3730869 0.032119672 6.189585
#> 10 0.07123740 0.08951064 0.11549412 0.1603937 0.3815041 0.049737191 6.189585
#> 11 0.07712230 0.09201821 0.11447201 0.1509536 0.3371489 0.138876856 6.189585
#> 12 0.06330852 0.08213712 0.11150403 0.1630370 0.4265615 0.189626876 6.189585
#> 13 0.06190869 0.08118167 0.11027271 0.1629932 0.4314364 0.229473838 6.189585
#> 14 0.06385587 0.08224806 0.11179040 0.1645378 0.4102862 0.333534600 6.189585
#> 15 0.06169273 0.08220017 0.11158430 0.1682408 0.4342217 0.480430136 6.189585
#> 16 0.06696894 0.08708731 0.11781621 0.1732554 0.3908631 1.109932059 6.189585
#> reporting_pop reporting_gdp reporting_pce is_interpolated distribution_type
#> 1 43297156 4193.5983 2372.8387 FALSE group
#> 2 47465030 4700.8756 2790.8733 FALSE group
#> 3 49490033 5406.0758 3292.5929 FALSE micro
#> 4 51525923 6009.7196 3738.4850 FALSE micro
#> 5 52344051 5953.9451 3758.2954 FALSE micro
#> 6 56531658 6155.0059 3887.5093 FALSE micro
#> 7 7981650 856.7617 NA FALSE micro
#> 8 8373921 857.0397 NA FALSE group
#> 9 9004053 796.0181 NA FALSE micro
#> 10 9482408 781.6634 NA FALSE micro
#> 11 10926535 833.0212 NA FALSE micro
#> 12 11593214 895.4753 NA FALSE micro
#> 13 12347319 968.5636 NA FALSE micro
#> 14 13965594 1183.4171 NA FALSE micro
#> 15 16399089 1295.8779 603.8121 FALSE micro
#> 16 20152938 1298.8480 NA FALSE imputed
#> 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
#> 7 survey 3.000 0.6298410 32.792041 NA
#> 8 survey 3.000 0.6705900 23.515498 NA
#> 9 survey 3.000 0.5606018 14.332490 NA
#> 10 survey 3.000 0.5662368 15.162530 NA
#> 11 survey 3.000 0.6798157 15.372702 NA
#> 12 survey 3.000 0.6893102 21.335260 NA
#> 13 survey 3.000 0.7196303 23.181471 NA
#> 14 survey 3.000 0.7136719 21.018355 NA
#> 15 survey 3.000 0.6789284 22.894125 NA
#> 16 survey 3.000 0.7165615 22.853020 NA
# }