Title
Kainu, Markus
Last updated: 2022-03-20 19:33:52
library(rnaturalearth)
library(ggplot2)
library(sf)
library(fs)
library(dplyr)
library(readxl)
library(tidyr)
library(janitor)
library(patchwork)
# _ _ _ _ _ _ _
# __ _| |_ _ ___ __| | __ _| |_ __ _ (_) __ _ _ __ __ _ (_) __ _ _ _| | _____ ___| |_
# / _` | | | | |/ _ \/ _` |/ _` | __/ _` | | |/ _` | _____| '__/ _` || |/ _` | | | | |/ / __|/ _ \ __|
# | (_| | | |_| | __/ (_| | (_| | || (_| | | | (_| | |_____| | | (_| || | (_| | |_| | <\__ \ __/ |_
# \__,_|_|\__,_|\___|\__,_|\__,_|\__\__,_| _/ |\__,_| |_| \__,_|/ |\__,_|\__,_|_|\_\___/\___|\__|
# |__/ |__/ world <- ne_countries(returnclass = "sf")
# Suomenkieliset maanimet
world$cldr.short.fi <- countrycode::countryname(sourcevar = world$name, destination = "cldr.short.fi")
bbox <- st_as_sfc(st_bbox(obj = c(xmin = 19.1,
xmax = 50.3,
ymax = 40.0,
ymin = 71.9),
crs = st_crs(world)))
lon = c(756065.70, 757428.78)
lat = c(4074435.19,4075144.12)
Poly_Coord_df = data.frame(lon, lat)
shapew <- st_intersection(st_make_valid(world), bbox) %>%
# exclude countries of Ex-Jugoslavia
filter(!grepl("Albania|Croa|Serb|Montene|Koso|Bosni|Mace|Greec", name))
## Tehdään maalistat
cntry_code_adm0_a3 <- shapew$adm0_a3
cntry_code_iso_a2 <- shapew$iso_a2
cntry_code_iso_a3 <- shapew$iso_a3
cntry_code_wb_a3 <- shapew$wb_a3
cntry_code_un_a3 <- shapew$un_a3
cntry_name <- shapew$name
cntry_name_long <- shapew$name_long
cntry_name_fi <- shapew$cldr.short.fi
cntry_id_df <- shapew %>%
select(name,name_long,cldr.short.fi,adm0_a3,iso_a2,iso_a3,wb_a3,un_a3) %>%
st_drop_geometry()
# > cntry_id_df
# name name_long cldr.short.fi adm0_a3 iso_a2 iso_a3 wb_a3 un_a3
# 1 Armenia Armenia Armenia ARM AM ARM ARM 051
# 2 Azerbaijan Azerbaijan Azerbaidžan AZE AZ AZE AZE 031
# 3 Bulgaria Bulgaria Bulgaria BGR BG BGR BGR 100
# 4 Belarus Belarus Valko-Venäjä BLR BY BLR BLR 112
# 5 Estonia Estonia Viro EST EE EST EST 233
# 6 Finland Finland Suomi FIN FI FIN FIN 246
# 7 Georgia Georgia Georgia GEO GE GEO GEO 268
# 8 Hungary Hungary Unkari HUN HU HUN HUN 348
# 9 Kazakhstan Kazakhstan Kazakstan KAZ KZ KAZ KAZ 398
# 10 Lithuania Lithuania Liettua LTU LT LTU LTU 440
# 11 Latvia Latvia Latvia LVA LV LVA LVA 428
# 12 Moldova Moldova Moldova MDA MD MDA MDA 498
# 13 Norway Norway Norja NOR NO NOR NOR 578
# 14 Poland Poland Puola POL PL POL POL 616
# 15 Romania Romania Romania ROU RO ROU ROM 642
# 16 Russia Russian Federation Venäjä RUS RU RUS RUS 643
# 17 Slovakia Slovakia Slovakia SVK SK SVK SVK 703
# 18 Sweden Sweden Ruotsi SWE SE SWE SWE 752
# 19 Turkey Turkey Turkki TUR TR TUR TUR 792
# 20 Ukraine Ukraine Ukraina UKR UA UKR UKR 804
## Rajataan uudetaan aluenimien mukaan
shape_raw <- world %>% filter(name %in% cntry_name) %>%
mutate(group_political = case_when(
grepl("Nor|Swe|Fin|Tur", name) ~ "Itsenäiset valtiot",
grepl("Polan|Slova|Hun|Roma|Bul", name) ~ "Itsenäiset sosialistiset valtiot",
TRUE ~ "Neuvostoliitto"))
bbox <- st_as_sfc(st_bbox(obj = c(xmin = 1.1,
xmax = 52.3,
ymax = 30.0,
ymin = 71.9),
crs = st_crs(world)))
shape <- st_intersection(st_make_valid(shape_raw), bbox) %>%
st_transform(crs = '+proj=robin +lon_0=35 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs')
# piirretään asemakartta
ggplot(shape, aes(label = cldr.short.fi, fill = group_political)) +
geom_sf(color = alpha("white", 2/3), alpha = .6, show.legend = TRUE) +
ggrepel::geom_text_repel(data = shape %>%
sf::st_set_geometry(NULL) %>%
bind_cols(shape %>% sf::st_centroid() %>% sf::st_coordinates() %>% as_tibble()),
aes(label = cldr.short.fi, x = X, y = Y),
family = "Lato")+
theme_minimal(base_family = "Lato") +
scale_fill_brewer(type = "qual") +
theme(axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
legend.position = "right") +
labs(title = "Analyysin aluerajaus ja alueiden poliittinen asema vuonna 1988",
fill = "Alueen asema vuonna 1988") -> p
ggsave(filename = "./kuvat/rajaus.png", plot = p)0.1 Sisäiset aluejaot
if (F){
fs::dir_create("./data")
fs::dir_create("./data/aluejako_ukr")
download.file("https://data.humdata.org/dataset/d23f529f-31e4-4021-a65b-13987e5cfb42/resource/4105bb4d-5a9d-4824-a1d7-53141cf47c44/download/ukr_adm_sspe_20220131.zip",
destfile = "./data/ukr_adm_sspe_20220131.zip")
unzip(zipfile = "./data/ukr_adm_sspe_20220131.zip", exdir = "./data/aluejako_ukr/")
shapes <- dir_ls("./data/aluejako_ukr", glob = "*.shp")
shapes
# ./data/aluejako_ukr/ukr_admbnda_adm0_sspe_20220114.shp
# ./data/aluejako_ukr/ukr_admbnda_adm1_sspe_20220114.shp
# ./data/aluejako_ukr/ukr_admbnda_adm2_sspe_20220114.shp
# ./data/aluejako_ukr/ukr_admbnda_adm3_sspe_20220114.shp
# ./data/aluejako_ukr/ukr_admbnda_adm4_sspe_20220114.shp
# ./data/aluejako_ukr/ukr_admbndl_adm0123_sspe_itos_20220114.shp
# ./data/aluejako_ukr/ukr_admbndp_adm0123_sspe_itos_20220114.shp
for (i in seq_along(shapes)){
tmp <- sf::st_read(shapes[i])
pp <- ggplot(tmp) + geom_sf() + labs(title = shapes[i])
ggsave(filename = paste0("./kuvat/aluejaot/", gsub("^.+/|\\.shp", "", shapes[i]), ".png"))
}
}
adm1 <- st_read("./data/aluejako_ukr/ukr_admbnda_adm1_sspe_20220114.shp")## Reading layer `ukr_admbnda_adm1_sspe_20220114' from data source
## `/home/aurelius/btsync/kela/ukraine22/data/aluejako_ukr/ukr_admbnda_adm1_sspe_20220114.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 27 features and 20 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 22.13691 ymin: 44.38641 xmax: 40.22788 ymax: 52.37929
## Geodetic CRS: WGS 84# regional data
dir_create("./data/ukrstat/")
download.file("http://www.ukrstat.gov.ua/operativ/operativ2021/gdn/szpshp/szpshp_reg_rik.xlsx",
destfile = "./data/ukrstat/szpshp_reg_rik.xlsx")
tmp <- read_excel("./data/ukrstat/szpshp_reg_rik.xlsx", skip = 4)
names(tmp[1]) <- "region_ukr"
names(tmp[29]) <- "region_en"
tmp <- clean_names(tmp)
tmp <- tmp %>% mutate_all(as.character)
dat <- pivot_longer(tmp, cols = 2:28, names_to = "year", values_to = "value") %>%
mutate(value = as.integer(value)) %>%
setNames(., c("region_ua","region_en","year","value")) %>%
mutate(year = as.integer(sub("x", "", year)))
ggplot(dat, aes(x = year, y = value, color = region_en)) +
geom_line(show.legend = FALSE) +
geom_label(data = dat %>% filter(year == max(year)), aes(label = region_en), show.legend = FALSE)
dat_map <- left_join(adm1, dat, by = c("ADM1_UA" = "region_ua"))
maplist <- list()
barlist <- list()
yrs <- sort(unique(dat_map$year))
for (i in seq_along(yrs)){
maplist[[i]] <- ggplot(dat_map[dat_map$year == yrs[i],], aes(fill = value)) +
geom_sf(color = alpha("white", 1/3)) +
labs(title = yrs[i]) +
theme(legend.position = "none")
barlist[[i]] <- ggplot(dat_map[dat_map$year == yrs[i],], aes(x = order(region_en, value), y = value, fill = value)) +
geom_col() +
labs(title = yrs[i]) +
theme(legend.position = "none")
}
wrap_plots(maplist)
wrap_plots(barlist)
# _ _ _ _ _ _ _ _
# __| | __ _| |_ __ _| (_)_(_) |__ | |_ ___ ___| |_
# / _` |/ _` | __/ _` | |/ _` | '_ \| __/ _ \/ _ \ __|
# | (_| | (_| | || (_| | | (_| | | | | || __/ __/ |_
# \__,_|\__,_|\__\__,_|_|\__,_|_| |_|\__\___|\___|\__|
#
# datalähteet
## Social Development & Economy
### WDI (World Development Indicators)
grep("poverty", WDI::WDI_data$series, value = T)## [1] "5.51.01.01.poverty"
## [2] "Income poverty"
## [3] "Affordability of an energy sufficient diet: ratio of cost to the food poverty line"
## [4] "Affordability of a nutrient adequate diet: ratio of cost to the food poverty line"
## [5] "Affordability of a healthy diet: ratio of cost to the food poverty line"
## [6] "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health care expenditure (%)"
## [7] "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health care expenditure (%): Q1 (lowest)"
## [8] "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health care expenditure (%): Q2"
## [9] "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health care expenditure (%): Q3"
## [10] "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health care expenditure (%): Q4"
## [11] "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health care expenditure (%): Q5 (highest)"
## [12] "Change in poverty gap due to out-of-pocket health spending ($ 2011 PPP), $1.90 poverty line"
## [13] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%)"
## [14] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q1 (lowest)"
## [15] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q2"
## [16] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q3"
## [17] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q4"
## [18] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q5 (highest)"
## [19] "Change in poverty gap due to out-of-pocket health spending ($ 2011 PPP), $3.20 poverty line"
## [20] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%)"
## [21] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q1 (lowest)"
## [22] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q2"
## [23] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q3"
## [24] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q4"
## [25] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q5 (highest)"
## [26] "Change in poverty gap due to out-of-pocket health spending ($ 2011 PPP), $5.50 poverty line"
## [27] "Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%)"
## [28] "Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q1 (lowest)"
## [29] "Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q2"
## [30] "Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q3"
## [31] "Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q4"
## [32] "Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q5 (highest)"
## [33] "Change in poverty gap due to out-of-pocket health spending ($ 2011 PPP), $21.70 poverty line"
## [34] "Proportion of population pushed below the $21.70 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%)"
## [35] "Proportion of population pushed below the $21.70 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q1 (lowest)"
## [36] "Proportion of population pushed below the $21.70 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q2"
## [37] "Proportion of population pushed below the $21.70 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q3"
## [38] "Proportion of population pushed below the $21.70 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q4"
## [39] "Proportion of population pushed below the $21.70 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%): Q5 (highest)"
## [40] "Proportion of population pushed by out-of-pocket health care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%)"
## [41] "Proportion of population pushed by out-of-pocket health care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) : Q1 (lowest)"
## [42] "Proportion of population pushed by out-of-pocket health care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) : Q2"
## [43] "Proportion of population pushed by out-of-pocket health care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) : Q3"
## [44] "Proportion of population pushed by out-of-pocket health care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) : Q4"
## [45] "Proportion of population pushed by out-of-pocket health care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) : Q5 (highest)"
## [46] "Learning poverty: Share of Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)"
## [47] "Learning poverty: Share of Female Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)"
## [48] "Learning poverty: Share of Male Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)"
## [49] "(De Jure) Are anti poverty interventions that focus on ECD publicly supported?"
## [50] "Number of people pushed below the 50% median consumption poverty line by out-of-pocket health care expenditure"
## [51] "Proportion of population pushed below the 50% median consumption poverty line by out-of-pocket health care expenditure (%)"
## [52] "Increase in poverty gap at $1.90 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure (USD)"
## [53] "Number of people pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure"
## [54] "Increase in poverty gap at $1.90 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure (% of poverty line)"
## [55] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%)"
## [56] "Increase in poverty gap at $3.20 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure (USD)"
## [57] "Number of people pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure"
## [58] "Increase in poverty gap at $3.20 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure (% of poverty line)"
## [59] "Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure (%)"
## [60] "Multidimensional poverty, Educational attainment (% of population deprived)"
## [61] "Number of people live below the poverty line (in number of people)"
## [62] "Survey coverage for poverty headcount ratio (at $1.90 a day, 2011 PPP)"
## [63] "Multidimensional poverty, Monetary poverty (% of population deprived)"
## [64] "Multidimensional poverty, Electricity (% of population deprived)"
## [65] "Multidimensional poverty, Educational enrollment (% of population deprived)"
## [66] "Multidimensional poverty, Headcount ratio (% of population)"
## [67] "Multidimensional poverty headcount ratio (% of total population)"
## [68] "Multidimensional poverty headcount ratio, children (% of population ages 0-17)"
## [69] "Multidimensional poverty index, children (population ages 0-17) (scale 0-1)"
## [70] "Multidimensional poverty headcount ratio, female (% of female population)"
## [71] "Multidimensional poverty headcount ratio, household (% of total households)"
## [72] "Multidimensional poverty intensity (average share of deprivations experienced by the poor)"
## [73] "Multidimensional poverty headcount ratio, male (% of male population)"
## [74] "Multidimensional poverty index (scale 0-1)"
## [75] "Poverty gap at national poverty lines (%)"
## [76] "Poverty gap at national poverty lines (%), including noncomparable values"
## [77] "Poverty headcount ratio at national poverty lines (% of population)"
## [78] "Poverty headcount ratio at national poverty lines (% of population), including noncomparable values"
## [79] "Rural poverty gap at national poverty lines (%)"
## [80] "Rural poverty headcount ratio at national poverty lines (% of rural population)"
## [81] "Multidimensional poverty, Sanitation (% of population deprived)"
## [82] "Urban poverty gap at national poverty lines (%)"
## [83] "Urban poverty headcount ratio at national poverty lines (% of urban population)"
## [84] "Multidimensional poverty, Drinking water (% of population deprived)"
## [85] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2011 PPP) below the poverty line."
## [86] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [87] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [88] "The poverty headcount index measures the proportion of the population with daily per capita income below the official poverty line developed by each country."
## [89] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [90] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [91] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [92] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [93] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [94] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [95] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [96] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [97] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2011 PPP) below the poverty line."
## [98] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [99] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [100] "The poverty headcount index measures the proportion of the population with daily per capita income below the official poverty line developed by each country."
## [101] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [102] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [103] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [104] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [105] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [106] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [107] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [108] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [109] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2011 PPP) below the poverty line."
## [110] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [111] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [112] "The poverty headcount index measures the proportion of the population with daily per capita income below the official poverty line developed by each country."
## [113] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [114] "The poverty headcount index measures the proportion of the population with daily per capita income (in 2005 PPP) below the poverty line."
## [115] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [116] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [117] "The poverty gap captures the mean aggregate income or consumption shortfall relative to the poverty line across the entire population. It measures the total resources needed to bring all the poor to the level of the poverty line (averaged over the total population). "
## [118] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [119] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [120] "The poverty severity index combines information on both poverty and inequality among the poor by averaging the squares of the poverty gaps relative the poverty line"
## [121] "Poverty surveys collect data on household income, consumption and expenditure, including income in kind. They typically include income, expenditure, and consumption surveys, household budget surveys, Integrated Surveys, Living Standard Measuring Surveys, and other poverty related surveys. It is recommended that poverty surveys be conducted at least every 3 to 5 years."
## [122] "Proportion of population below US$1.25 a day is the percentage of the population living on less than $1.25 a day at 2005 international prices. The US$1.25 poverty line is compared to consumption or income per person and includes consumption from own production and income in kind. This poverty line has fixed purchasing power across countries. This indicator measures progress toward the reduction of extreme poverty and relates to the first MDG goal to eradicate extreme poverty and hunger."
## [123] "Prevalence of underweight children under-five years of age, also known as prevalence of child malnutrition (weight for age), is the percentage of children under-five whose weight for age is less than minus two standard deviations from the median for the international reference population ages 0 to 59 months. The data are based on the World Health Organization’s new child growth standards released in 2006. Child malnutrition is linked to poverty, low levels of education, and poor access to health services. Sufficient and good-quality nutrition is therefore critical for development, health, and survival of current and succeeding generations. This indicator monitors nutritional status and health in populations and relates to the first MDG aiming at reducing poverty and hunger."
## [124] "Under-five mortality rate is the probability that a newborn baby will die before reaching age five, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000. The indicator measures child survival. Survival of a child is closely linked to the provision of primary health-care services; but poverty, malnutrition, a decline in breast-feeding, maternal education, use of improved water, and inadequacy sanitation and health facilities are all associated with high child mortality. The indicator relates to the fourth MDG calling for reducing child mortality."
## [125] "GDP per capita is the sum of gross value added by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output, divided by mid-year population. Growth is calculated from constant price GDP data in local currency. Sustained economic growth increases average incomes and is strongly linked to poverty reduction. GDP per capita provides a basic measure of the value of output per person, which is an indirect indicator of per capita income. Growth in GDP and GDP per capita are considered broad measures of economic growth."
## [126] "The Labor Income Poverty Index (LIPI) measures changes in the share of households that have per capita labor income below the regional poverty line of $4 per day, relative to a selected reference period. This reference period is the third quarter in 2010 (2010Q3 = 1), except for Chile and Guatemala, where 2010Q4 = 1."
## [127] "Economic Fitness (EF) is both a measure of a country’s diversification and ability to produce complex goods on a globally competitive basis. Countries with the highest levels of EF have capabilities to produce a diverse portfolio of products, ability to upgrade into ever-increasing complex goods, tend to have more predictable long-term growth, and to attain good competitive position relative to other countries. Countries with low EF levels tend to suffer from poverty, low capabilities, less predictable growth, low value-addition, and trouble upgrading and diversifying faster than other countries. The starting data is the COMTRADE list of products exported by each country. This data defines a bipartite network of countries and products, or goods and services. A suitably designed mathematical algorithm applied to this network leads to the Economic Fitness of all countries and the Complexity of all products. The comparison of the Fitness to the GDP reveals hidden information for the development and the growth of the countries."
## [128] "Economic Fitness (EF) is both a measure of a country’s diversification and ability to produce complex goods on a globally competitive basis. Countries with the highest levels of EF have capabilities to produce a diverse portfolio of products, ability to upgrade into ever-increasing complex goods, tend to have more predictable long-term growth, and to attain good competitive position relative to other countries. Countries with low EF levels tend to suffer from poverty, low capabilities, less predictable growth, low value-addition, and trouble upgrading and diversifying faster than other countries. The starting data is the COMTRADE list of products exported by each country. This data defines a bipartite network of countries and products. A suitably designed mathematical algorithm applied to this network leads to the Economic Fitness of all countries and the Complexity of all products. The comparison of the Fitness to the GDP reveals hidden information for the development and the growth of the countries."
## [129] "\tThe Universal Economic Fitness (UEF) is both a measure of a country’s diversification and ability to produce complex goods on a globally competitive basis. Countries with the highest levels of EF have capabilities to produce a diverse portfolio of products, ability to upgrade into ever-increasing complex goods, tend to have more predictable long-term growth, and to attain good competitive position relative to other countries. Countries with low UEF levels tend to suffer from poverty, low capabilities, less predictable growth, low value-addition, and trouble upgrading and diversifying faster than other countries. The starting data is the COMTRADE list of products and the IMF-BOP list of services exported by each country. This data defines a bipartite network of countries and sectors, or goods and services. A suitably designed mathematical algorithm applied to this network leads to the Universal Economic Fitness of all countries and the Complexity of all sectors. The comparison of the Fitness to the GDP reveals hidden information for the development and the growth of the countries."
## [130] "Percentage of population pushed below 1.90 international $ per day consumption poverty line by out-of-pocket health spending"
## [131] "Percentage of population pushed below 1.90 international $ per day consumption poverty line by out-of-pocket health spending"
## [132] "Percentage of population pushed below 1.90 international $ per day consumption poverty line by out-of-pocket health spending"
## [133] "Percentage of population pushed below 1.90 international $ per day consumption poverty line by out-of-pocket health spending"
## [134] "Percentage of population pushed below 1.90 international $ per day consumption poverty line by out-of-pocket health spending"
## [135] "Percentage of population pushed below 1.90 international $ per day consumption poverty line by out-of-pocket health spending"
## [136] "Percentage of population pushed below 3.20 international $ per day consumption poverty line by out-of-pocket health spending"
## [137] "Percentage of population pushed below 3.20 international $ per day consumption poverty line by out-of-pocket health spending"
## [138] "Percentage of population pushed below 3.20 international $ per day consumption poverty line by out-of-pocket health spending"
## [139] "Percentage of population pushed below 3.20 international $ per day consumption poverty line by out-of-pocket health spending"
## [140] "Percentage of population pushed below 3.20 international $ per day consumption poverty line by out-of-pocket health spending"
## [141] "Percentage of population pushed below 3.20 international $ per day consumption poverty line by out-of-pocket health spending"
## [142] "Poverty Head Count Ratio is the percentage of the rural population living below the poverty line estimated based on population-weighted subgroup estimates (rural and urban) from household surveys."
## [143] "Poverty Head Count Ratio is the percentage of the total population living below the poverty line estimated based on population-weighted subgroup estimates (rural and urban) from household surveys."
## [144] "Poverty Head Count Ratio is the percentage of the urban population living below the poverty line estimated based on population-weighted subgroup estimates (rural and urban) from household surveys."
## [145] "Equity of public resource use assesses the extent to which the pattern of public expenditures and revenue collection affects the poor and is consistent with national poverty reduction priorities."
## [146] "Health and Welfare: Within this sub-category the Ibrahim Index measures: (i) Incidence of TB – incidence of new cases of Tuberculosis. (ii) Child Mortality – likelihood that a newborn baby will die before the age of five, assuming that he/she is subject to current, age-specific mortality rates. (iii) Immunisation against Measles – proportion of one year olds (children aged 12–23 months) who have received one dose of measles vaccine. (iv) Immunisation against DTP – proportion of one year olds (children aged 12–23 months) who have received three doses of DTP vaccine. (v) Welfare Regime – equality of access to social safety nets that compensate for poverty and other risks. (vi) Social Protection and Labour – clustered indicator (average) of variables from the African Development Bank and the World Bank measuring government policies and regulations to ensure a minimum level of welfare to all people. (vii) Social Exclusion – extent to which significant parts of society are isolated due to poverty and inequality. (viii) Antiretroviral Treatment Provision – people with advanced HIV infection who are receiving antiretroviral treatment (ART) according to nationally approved or international standards. (ix) Antiretroviral Treatment Provision for Pregnant Women – HIV positive pregnant women who received antiretroviral treatment (ART) to reduce the risk of mother-to-child transmission. (x) Access to Piped Water – proportion of the population with access to water piped into their dwelling or just outside it. (xi) Access to Improved Water – proportion of the population with access to a water source protected from outside contamination. (xii) Access to Improved Sanitation – proportion of the population served with a sanitation facility that hygienically separates human excreta from human contact. (xiii) Open Defecation Sanitation – proportion of the population forced to dispose of human faeces in open bodies of water or outdoor open spaces."
## [147] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [148] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [149] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [150] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [151] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [152] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [153] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [154] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [155] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [156] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [157] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [158] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [159] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [160] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [161] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [162] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [163] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [164] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [165] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [166] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [167] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [168] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [169] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [170] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [171] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [172] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [173] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [174] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [175] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [176] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [177] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [178] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [179] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [180] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [181] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [182] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [183] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [184] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [185] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [186] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [187] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [188] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [189] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [190] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [191] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [192] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [193] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [194] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [195] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [196] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [197] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [198] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [199] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [200] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [201] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [202] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [203] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [204] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [205] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [206] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [207] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [208] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [209] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [210] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [211] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [212] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [213] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [214] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [215] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [216] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [217] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [218] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [219] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [220] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [221] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [222] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [223] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [224] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [225] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [226] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [227] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [228] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [229] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [230] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [231] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [232] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [233] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [234] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [235] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [236] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [237] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [238] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [239] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [240] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [241] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [242] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [243] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [244] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [245] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [246] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [247] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [248] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [249] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [250] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [251] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [252] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [253] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [254] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [255] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [256] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [257] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [258] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [259] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [260] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [261] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [262] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [263] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [264] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [265] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [266] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [267] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [268] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [269] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [270] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [271] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [272] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [273] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [274] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [275] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [276] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [277] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [278] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [279] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [280] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [281] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [282] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [283] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [284] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [285] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [286] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [287] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [288] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [289] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [290] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [291] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [292] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [293] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [294] "Poverty headcount reduction due to SPL programs as % of pre-transfer poverty headcount"
## [295] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [296] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [297] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [298] "Poverty gap reduction due to SPL programs as % of pre-transfer poverty gap"
## [299] "The proportion of population at risk of impoverishing expenditure when surgical care is required. Impoverishing expenditure is defined as direct out of pocket payments for surgical and anaesthesia care which drive people below a poverty threshold (using a threshold of $1.90 PPP/day)."
## [300] "Number of people pushed below the 50% median consumption poverty line by out-of-pocket health care expenditure"
## [301] "Proportion of population pushed below the 50% median consumption poverty line by out-of-pocket health care expenditure, expressed as a percentage of a total population of a country"
## [302] "Increase in poverty gap at $1.90 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, expressed in US dollars (2011 PPP). The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending."
## [303] "Number of people pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure. This indicator shows the number of households experiencing impoverishing expenditures, defined as expenditures without which the household would have been above the $1.90 poverty line, but because of the expenditures is below the poverty line."
## [304] "Increase in poverty gap at $1.90 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, as a percentage of the $1.90 poverty line. The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending."
## [305] "Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure. This indicator shows the fraction of a country's households experiencing impoverishing expenditures, defined as expenditures without which the household would have been above the $ 1.90 poverty line, but because of the expenditures is below the poverty line."
## [306] "Increase in poverty gap at $3.20 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, expressed in US dollars (2011 PPP). The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending."
## [307] "Number of people pushed below the $3.20 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure. This indicator shows the number of households experiencing impoverishing expenditures, defined as expenditures without which the household would have been above the $1.90 poverty line, but because of the expenditures is below the poverty line."
## [308] "Increase in poverty gap at $3.20 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, as a percentage of the $3.20 poverty line. The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending."
## [309] "Proportion of population pushed below the $3.20 ($2011 PPP) poverty line by out-of-pocket health care expenditure. This indicator shows the fraction of a country's households experiencing impoverishing expenditures, defined as expenditures without which the household would have been above the $3.20 poverty line, but because of the expenditures is below the poverty line."
## [310] "Poverty headcount ratio at $3.10 a day is the percentage of the population living on less than $3.10 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions."
## [311] "Multidimensional poverty, educational attainment (% of population deprived) is percentage of population deprived of primary educational attainment. A household is deprived if no adult (grade 9 equivalent age or above) has completed primary education."
## [312] "Poverty headcount ratio at $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions."
## [313] "Multidimensional poverty, Monetary poverty (% of population deprived) is the percentage of the population living on less than $1.90 a day at 2011 international prices. A household is deprived if income or expenditure, in 2011 purchasing power parity U.S. dollars, is less than US$1.90 per person per day. The indicator may differ from the one used for monitoring monetary poverty, if the multidimensional poverty measure comes from a different survey (or different version of the same survey)."
## [314] "Multidimensional poverty, electricity (% of population deprived) is percentage of population deprived of electricity. A household is deprived if it does not have access to electricity."
## [315] "Multidimensional poverty, educational enrollment (% of population deprived) is percentage of population deprived of school enrollment. A household is deprived if at least one child (grade 8 equivalent age or below) is not enrolled in school."
## [316] "Poverty gap at $3.10 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $3.10 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions."
## [317] "Poverty gap at $1.90 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $1.90 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions."
## [318] "Multidimensional poverty, headcount ratio (% of population) is the share of people who are considered multidimensionally deprived. It is estimated on the basis of three dimensions—monetary, education, and basic infrastructure access and an overall poverty cutoff of one-third of the weighted deprivations. Household is multidimensionally poor if it is deprived in more than a third of weighted deprivations."
## [319] "Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions."
## [320] "Poverty gap at $3.20 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $3.20 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence."
## [321] "Poverty gap at national poverty lines is the mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence."
## [322] "National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year."
## [323] "Poverty line is an indicator of household expenditure to measure how much poor people live in particular district. Every people who has per capita expenditure below the poverty line will be deemed as poor people."
## [324] "Poverty Rate: Number of people live below the poverty line compared to total population."
## [325] "Poverty Gap index: Average gap between expenditure of poor people and the poverty line."
## [326] "Rural poverty gap at national poverty lines is the rural population's mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence."
## [327] "Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines."
## [328] "Multidimensional poverty, sanitation (% of population deprived) is percentage of population deprived of sanitation. A household is deprived if it does not have access to even a limited standard of sanitation."
## [329] "Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions."
## [330] "Poverty gap at $5.50 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $5.50 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence."
## [331] "Urban poverty gap at national poverty lines is the urban population's mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence."
## [332] "Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines."
## [333] "Multidimensional poverty, drinking water (% of population deprived) is percentage of population deprived of drinking water. A household is deprived if it does not have access to even a limited standard of drinking water."
## [334] "Five measures usefulness or reliability of country produced measures for international organizations. First, on comparability of poverty estimates for the World Bank reporting on international poverty (Source: Povcalnet). Second on usable surveys for statistics on child mortality for the UN Inter-agency Group for Child Mortality Estimation (Source: https://childmortality.org/). Third on accuracy of debt reporting as classified by the World Bank (Source: World Bank WDI metadata). Fourth, on availability of safely managed drinking water data for use by JMP. Fifth, on labor force participation data for use by ILO. We recognize that these data sources provide only partial coverage but consider that they do at least provide some indication of the performance of the national statistical system. With more complete data sources it would be possible to assess this further"
## [335] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [336] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [337] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [338] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [339] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [340] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [341] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [342] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [343] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [344] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [345] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [346] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [347] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [348] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [349] "Total number of students of the official lower secondary school age group who attended primary or secondary education at any time during the reference academic year, expressed as a percentage of the corresponding population. The UNESCO Institute for Statistics (UIS) calculates household survey-based education indicators using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). School participation in household surveys and censuses is commonly measured by whether pupils or students attended a given grade or level of education at least one day during the academic reference year. Therefore, indicators of school participation derived from household survey data refer to attendance, e.g. “net attendance rate” or “adjusted net attendance rate”. The comparable indicator for administrative data is \"Total net enrolment rate, lower secondary\" because the data is based on numbers of students officially enrolled in educational institutions in the stated year. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [350] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [351] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [352] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [353] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [354] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [355] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [356] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [357] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [358] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [359] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [360] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [361] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [362] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [363] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [364] "Number of children of official primary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official primary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [365] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [366] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [367] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [368] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [369] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [370] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [371] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [372] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [373] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [374] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [375] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [376] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [377] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [378] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [379] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [380] "Number of children of official lower secondary school age who did not attend primary or secondary school at any time during the reference academic year, expressed as a percentage of the number of official lower secondary school age children in the household survey sample. Children attending pre-primary or non-formal education are considered out of school. The UNESCO Institute for Statistics (UIS) releases estimates of out-of-school children calculated from both administrative and household survey sources (Demographic and Health Surveys and Multiple Indicator Cluster Surveys). Administrative records and household surveys are two data sources which differ in fundamental ways: who collects the data, as well as how, when and for what purpose. As a result, the out-of-school children estimates calculated from one data source may not match those based on other data sources. Each poverty quintile represents one fifth of students with quintile 1 being the poorest 20 percent of students and quintile 5 being the richest 20 percent of students. For more information, consult the UIS website: http://www.uis.unesco.org/Education/"
## [381] "World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines."
## [382] "World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines."
## [383] "World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines."
## [384] "World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines."
## [385] "World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines."
## [386] "World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines."
## [387] "World Bank, Global Database of Shared Prosperity (GDSP) circa 2011-2016 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity)."
## [388] "World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity)."
## [389] "World Bank, Global Database of Shared Prosperity (GDSP) circa 2011-2016 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity)."
## [390] "World Bank, Global Database of Shared Prosperity (GDSP) circa 2011-2016 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity)."
## [391] "World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity)."
## [392] "World Bank, Global Database of Shared Prosperity (GDSP) circa 2011-2016 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity)."### WHO Global Health Expenditure Database
# https://apps.who.int/nha/database/Select/Indicators/en
### FAOSTAT (World Development Indicators) Agricultural production
# remotes::install_github("muuankarski/faobulk")
library(faobulk)
datalist <- get_datalist()
head(datalist)## # A tibble: 6 × 12
## DatasetCode DatasetName Topic DatasetDescript… Contact Email DateUpdate
## <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 AE Discontinued arch… All … "ASTI collects … Nienke… asti… 2019-11-1…
## 2 AF Discontinued arch… All … "ASTI collects … Nienke… asti… 2019-11-1…
## 3 CB Food Balances: Co… Most… "Food Balance S… Mr. Sa… faos… 2021-12-0…
## 4 CISP Investment: Count… Agri… "The Country In… Mukesh… Muke… 2022-02-0…
## 5 CP Prices: Consumer … Hous… "The FAOSTAT mo… Veroni… faos… 2022-02-1…
## 6 CS Macro-Economic In… Agri… "As part of the… Ms. Bo… macr… 2021-09-2…
## # … with 5 more variables: CompressionFormat <chr>, FileType <chr>,
## # FileSize <chr>, FileRows <chr>, FileLocation <chr># # A tibble: 6 × 12
# DatasetCode DatasetName Topic DatasetDescript… Contact Email DateUpdate CompressionForm… FileType FileSize FileRows
# <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
# 1 AE Discontinued … All … "ASTI collects … Nienke… asti… 2019-11-1… zip csv 26KB 3094
# 2 AF Discontinued … All … "ASTI collects … Nienke… asti… 2019-11-1… zip csv 25KB 3154
# 3 CB Food Balances… Most… "Food Balance S… Mr. Sa… faos… 2021-12-0… zip csv 7576KB 1194781
# 4 CISP Investment: C… Agri… "The Country In… Mukesh… Muke… 2022-02-0… zip csv 1043KB 103399
# 5 CP Prices: Consu… Hous… "The FAOSTAT mo… Veroni… faos… 2022-02-1… zip csv 1591KB 175908
# 6 CS Macro-Economi… Agri… "As part of the… Ms. Bo… macr… 2021-09-2… zip csv 1193KB 130578
# # … with 1 more variable: FileLocation <chr>
datalist[grepl("production", datalist$DatasetName, ignore.case = TRUE),
c("DatasetCode","DatasetName","Topic")]## # A tibble: 4 × 3
## DatasetCode DatasetName Topic
## <chr> <chr> <chr>
## 1 FO Forestry: Forestry Production and Trade Forestry and logging…
## 2 QCL Production: Crops and livestock products Most crop products u…
## 3 QI Production: Production Indices Most crop products u…
## 4 QV Production: Value of Agricultural Production Most crop products u…# # A tibble: 4 × 3
# DatasetCode DatasetName Topic
# <chr> <chr> <chr>
# 1 FO Forestry: Forestry Production and Trade Forestry and logging, Manufacture of wood and wood products,…
# 2 QCL Production: Crops and livestock products Most crop products under agricultural activity.
# 3 QI Production: Production Indices Most crop products under agricultural activity.
# 4 QV Production: Value of Agricultural Production Most crop products under agricultural activity.
## Political
### QOG
library(rqog)
meta_std_ts_2022[grepl("corruption", rqog::meta_std_ts_2022$name, ignore.case = TRUE),] %>%
select(code,name) %>%
print(n = 100)## # A tibble: 47 × 2
## code name
## <chr> <chr>
## 1 aii_q10 Law: corruption is criminalized as a specific offense
## 2 aii_q11 Law: there are indep. bodies to investigate cases of pubsec. c…
## 3 aii_q12 Practice: corruption allegations are investigated by independe…
## 4 aii_q13 Practice: bodies investigating pubsector corruption allegation…
## 5 aii_q14 Practice: appointees to bodies investigating pubsec corruption…
## 6 aii_q35 Law: civil servants are required to report cases of alleged co…
## 7 aii_q36 Law: civil servants who report corruption cases are protected
## 8 bci_bci The Bayesian Corruption Indicator
## 9 bci_bcistd The standard deviation of The Bayesian Corruption Indicator
## 10 bti_acp Anti-Corruption Policy
## 11 ccp_cc Corruption Commission Present in Constitution
## 12 ccp_cc Corruption Commission Present in Constitution
## 13 ccp_cc Corruption Commission Present in Constitution
## 14 ccp_cc Corruption Commission Present in Constitution
## 15 ccp_cc Corruption Commission Present in Constitution
## 16 gcb_pb Corruption Perception: Business
## 17 gcb_ped Corruption Perception: Education
## 18 gcb_pj Corruption Perception: Judiciary/Legal System
## 19 gcb_pmed Corruption Perception: Medical Services
## 20 gcb_pmedia Corruption Perception: Media
## 21 gcb_pmil Corruption Perception: Military
## 22 gcb_pngo Corruption Perception: NGOs
## 23 gcb_ppa Corruption Perception: Political Parties
## 24 gcb_pparl Corruption Perception: Parliament
## 25 gcb_pper Corruption Perception: Registry and permit services
## 26 gcb_ppol Corruption Perception: Police
## 27 gcb_prel Corruption Perception: Religious Bodies
## 28 gcb_ptax Corruption Perception: Tax Revenue
## 29 gcb_putil Corruption Perception: Utilities
## 30 iiag_corr Anti-corruption
## 31 sgi_qdrlc Robust Democracy: Rule of Law - Corruption Prevention
## 32 ti_cpi Corruption Perceptions Index
## 33 ti_cpi_max Corruption Perceptions Index - max range
## 34 ti_cpi_max_om Corruption Perceptions Index - max range (old method.)
## 35 ti_cpi_min Corruption Perceptions Index - min range
## 36 ti_cpi_min_om Corruption Perceptions Index - min range (old method.)
## 37 ti_cpi_om Corruption Perceptions Index (old methodology)
## 38 ti_se Standard Error for Corruption Perceptions Index
## 39 vdem_corr Political corruption index
## 40 vdem_execorr Executive corruption index
## 41 vdem_jucorrdc Judicial corruption decision
## 42 vdem_pubcorr Public sector corruption index
## 43 wbgi_cce Control of Corruption, Estimate
## 44 wbgi_ccn Control of Corruption, Number of Sources
## 45 wbgi_ccs Control of Corruption, Standard Error
## 46 wdi_tacpsr CPIA transparency-accountability-corruption in public sector r…
## 47 wel_coc Control of Corruption# # A tibble: 47 × 2
# code name
# <chr> <chr>
# 1 aii_q10 Law: corruption is criminalized as a specific offense
# 2 aii_q11 Law: there are indep. bodies to investigate cases of pubsec. corruption
# 3 aii_q12 Practice: corruption allegations are investigated by independent body
# 4 aii_q13 Practice: bodies investigating pubsector corruption allegations are effective
# 5 aii_q14 Practice: appointees to bodies investigating pubsec corruption support independ.
# 6 aii_q35 Law: civil servants are required to report cases of alleged corruption
# 7 aii_q36 Law: civil servants who report corruption cases are protected
# 8 bci_bci The Bayesian Corruption Indicator
# 9 bci_bcistd The standard deviation of The Bayesian Corruption Indicator
# 10 bti_acp Anti-Corruption Policy
# 11 ccp_cc Corruption Commission Present in Constitution
# 12 ccp_cc Corruption Commission Present in Constitution
# 13 ccp_cc Corruption Commission Present in Constitution
# 14 ccp_cc Corruption Commission Present in Constitution
# 15 ccp_cc Corruption Commission Present in Constitution
# 16 gcb_pb Corruption Perception: Business
# 17 gcb_ped Corruption Perception: Education
# 18 gcb_pj Corruption Perception: Judiciary/Legal System
# 19 gcb_pmed Corruption Perception: Medical Services
# 20 gcb_pmedia Corruption Perception: Media
# 21 gcb_pmil Corruption Perception: Military
# 22 gcb_pngo Corruption Perception: NGOs
# 23 gcb_ppa Corruption Perception: Political Parties
# 24 gcb_pparl Corruption Perception: Parliament
# 25 gcb_pper Corruption Perception: Registry and permit services
# 26 gcb_ppol Corruption Perception: Police
# 27 gcb_prel Corruption Perception: Religious Bodies
# 28 gcb_ptax Corruption Perception: Tax Revenue
# 29 gcb_putil Corruption Perception: Utilities
# 30 iiag_corr Anti-corruption
# 31 sgi_qdrlc Robust Democracy: Rule of Law - Corruption Prevention
# 32 ti_cpi Corruption Perceptions Index
# 33 ti_cpi_max Corruption Perceptions Index - max range
# 34 ti_cpi_max_om Corruption Perceptions Index - max range (old method.)
# 35 ti_cpi_min Corruption Perceptions Index - min range
# 36 ti_cpi_min_om Corruption Perceptions Index - min range (old method.)
# 37 ti_cpi_om Corruption Perceptions Index (old methodology)
# 38 ti_se Standard Error for Corruption Perceptions Index
# 39 vdem_corr Political corruption index
# 40 vdem_execorr Executive corruption index
# 41 vdem_jucorrdc Judicial corruption decision
# 42 vdem_pubcorr Public sector corruption index
# 43 wbgi_cce Control of Corruption, Estimate
# 44 wbgi_ccn Control of Corruption, Number of Sources
# 45 wbgi_ccs Control of Corruption, Standard Error
# 46 wdi_tacpsr CPIA transparency-accountability-corruption in public sector rating (1-6)
# 47 wel_coc Control of Corruption
#