1. General Presentation
widr provides direct R access to the WID API. The
primary interface is download_wid(), which returns a
wid_df – a classed data.frame compatible with
dplyr, ggplot2, and base R.
download_wid(
indicators = "all",
areas = "all",
years = "all",
perc = "all",
ages = "992", # default: adults 20+
pop = "j", # default: equal-split
metadata = FALSE,
include_extrapolations = TRUE,
verbose = FALSE,
cache = TRUE)
metadata = TRUE attaches source documentation as
attr(result, "wid_meta"). Cache responses are managed with
wid_cache(), wid_cache_list(), and
wid_cache_clear(). Set an API key with
wid_set_key().
2. General Structure
Every series has a WID code (concept), a percentile code, a
country/region code, and a year. Codes are built by combining series
type, concept, age group, and population unit.
2.1 WID Code Examples
The three canonical examples from the official dictionary:
s |
ptinc |
992 |
j |
p99p100 |
US |
1970 |
share of pretax national income, top 1%, equal-split adults, United
States |
l |
pfghg |
999 |
i |
p90p100 |
CH |
2014 |
avg. per capita group emissions, personal carbon footprint, top 10%,
Switzerland |
s |
pllin |
992 |
f |
p0p100 |
UY |
2023 |
share of pretax labour income, female, entire adult population,
Uruguay |
wid_decode("sptinc992j")
#> $series_type "s" $concept "ptinc" $age "992" $pop "j"
wid_encode("s", "ptinc", "992", "j") #> [1] "sptinc992j"
wid_encode("m", "nninc") #> [1] "mnninc"
wid_encode(wid_decode("sptinc992j")) # round-trip: identical to input
# Validate (throws on failure) or check silently
wid_validate(series_type = "s", concept = "ptinc", age = 992, pop = "j")
wid_is_valid(series_type = "s", concept = "ptinc") #> [1] TRUE
wid_is_valid(series_type = "Z") #> [1] FALSE
2.1.1 Series Type (one-letter code)
There are 17 types.
wid_series_types
wid_search("share", tables = "series_types")
a |
average |
local currency, last year’s prices |
b |
inverted Pareto-Lorenz coefficient |
no unit |
e |
total emissions |
tonnes CO2-equivalent |
f |
female population |
fraction (0 to 1) |
g |
Gini coefficient |
0 to 1 |
i |
index |
no unit |
k |
per capita emissions |
tonnes CO2-equivalent |
l |
average per capita group emissions |
tonnes CO2-equivalent |
m |
total |
local currency, last year’s prices |
n |
population |
people |
p |
proportion of women |
fraction (0 to 1) |
r |
top 10 / bottom 50 ratio |
no unit |
s |
share |
fraction (0 to 1) |
t |
threshold |
local currency, last year’s prices |
w |
wealth-to-income ratio or labor/capital share |
fraction of national income |
x |
exchange rate (market or PPP) |
local currency per foreign currency |
y |
wealth-to-GDP ratio |
fraction of GDP |
All monetary amounts are in local currency at constant prices. For
world regions: XX-MER (USD MER) or XX-PPP (USD
PPP). Shares and ratios are fractions: a top-1% share of 20% =
0.2; a 300% wealth/income ratio = 3. Series
types s, g, b, w,
r, p, i, y are
dimensionless; wid_convert() passes them through
unchanged.
2.1.2 Concept (five-letter code)
Characters 2-6 (or 2-7 for six-letter concepts). There are 464
concepts.
nrow(wid_concepts)
head(wid_concepts)
wid_search("wealth")
wid_search("^ptinc$", tables = "concepts")
wid_search("wealth", type = "s")
wid_search("income", tables = "all")
2.1.3 Age Group (three-digit code)
There are 40 defined age groups. anninc999i = national
income per capita; anninc992i = national income per
adult.
wid_ages
wid_validate(age = 992)
999 |
All ages |
992 |
Adults 20+ (default) |
996 |
Working-age, 20-64 |
995 |
Adults 60+ |
994 |
Adults 40-59 |
993 |
Adults 20-39 |
997 |
Elderly 65+ |
998 |
Aged 80+ |
991 |
Below 20 |
014 |
Ages 0-14 |
156 |
Ages 15-64 |
001 |
Ages 0-4 |
051 |
Ages 5-9 |
101 |
Ages 10-14 |
151 |
Ages 15-19 |
201 |
Ages 20-24 |
251 |
Ages 25-29 |
301 |
Ages 30-34 |
351 |
Ages 35-39 |
401 |
Ages 40-44 |
451 |
Ages 45-49 |
501 |
Ages 50-54 |
551 |
Ages 55-59 |
601 |
Ages 60-64 |
651 |
Ages 65-69 |
701 |
Ages 70-74 |
751 |
Ages 75-79 |
801 |
Ages 80-84 |
851 |
Ages 85-89 |
901 |
Ages 90-94 |
951 |
Ages 95-99 |
111 |
Ages 99+ |
202 |
Ages 20-29 |
302 |
Ages 30-39 |
402 |
Ages 40-49 |
502 |
Ages 50-59 |
602 |
Ages 60-69 |
702 |
Ages 70-79 |
802 |
Ages 80-89 |
902 |
Ages 90-99 |
2.1.4 Population Unit (one-letter code)
There are 6 population unit codes. Only affects distributional
series; aggregate series default to i.
i |
individuals |
j |
equal-split adults (default) |
m |
male |
f |
female |
t |
tax unit |
e |
employed |
2.1.5 Series Type x Population Unit Availability
wid_is_valid(series_type = "s", concept = "ptinc") # TRUE
wid_is_valid(series_type = "b", pop = "f") # FALSE
a average |
+ |
+ |
+ |
+ |
+ |
b Pareto coef. |
|
+ |
+ |
|
|
f female pop. |
|
+ |
|
|
|
i index |
|
+ |
|
|
|
m total |
|
+ |
|
|
+ |
n population |
+ |
+ |
|
+ |
+ |
p prop. women |
|
+ |
|
|
|
s share |
+ |
+ |
+ |
+ |
+ |
t threshold |
+ |
+ |
+ |
+ |
+ |
w wealth/income ratio |
|
+ |
|
|
+ |
y wealth-to-GDP ratio |
|
+ |
|
|
+ |
x exchange rate |
|
+ |
|
|
|
e/k/l emissions |
|
+ |
|
|
|
2.2 Country Codes
There are 281 entries in wid_countries.
head(wid_countries)
wid_search("^US", tables = "countries")
wid_validate(areas = c("US", "FR", "US-CA"))
Country Codes
| AD |
Andorra |
Europe |
|
Other Western Europe |
|
| AE |
United Arab Emirates |
MENA |
|
Main Country |
|
| AF |
Afghanistan |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| AG |
Antigua and Barbuda |
Latin America |
|
Other Latin America |
|
| AI |
Anguilla |
Latin America |
|
Other Latin America |
|
| AL |
Albania |
Europe |
|
Eastern Europe |
|
| AM |
Armenia |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| AO |
Angola |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| AR |
Argentina |
Latin America |
|
Main Country |
|
| AT |
Austria |
Europe |
|
Other Western Europe |
|
| AU |
Australia |
North America & Oceania |
Oceania |
Main Country |
|
| AW |
Aruba |
Latin America |
|
Other Latin America |
|
| AZ |
Azerbaijan |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| BA |
Bosnia and Herzegovina |
Europe |
|
Eastern Europe |
|
| BB |
Barbados |
Latin America |
|
Other Latin America |
|
| BD |
Bangladesh |
South & Southeast Asia |
|
Main Country |
|
| BE |
Belgium |
Europe |
|
Other Western Europe |
|
| BF |
Burkina Faso |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| BG |
Bulgaria |
Europe |
|
Eastern Europe |
|
| BH |
Bahrain |
MENA |
|
Other MENA |
|
| BI |
Burundi |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| BJ |
Benin |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| BM |
Bermuda |
North America & Oceania |
North America |
Other North America & Oceania |
Other North America |
| BN |
Brunei Darussalam |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| BO |
Bolivia |
Latin America |
|
Other Latin America |
|
| BQ |
Bonaire |
Latin America |
|
Other Latin America |
|
| BR |
Brazil |
Latin America |
|
Main Country |
|
| BS |
Bahamas |
Latin America |
|
Other Latin America |
|
| BT |
Bhutan |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| BW |
Botswana |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| BY |
Belarus |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| BZ |
Belize |
Latin America |
|
Other Latin America |
|
| CA |
Canada |
North America & Oceania |
North America |
Main Country |
|
| CD |
DR Congo |
Sub-Saharan Africa |
|
Main Country |
|
| CF |
Central African Republic |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| CG |
Congo |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| CH |
Switzerland |
Europe |
|
Other Western Europe |
|
| CI |
Cote d’Ivoire |
Sub-Saharan Africa |
|
Main Country |
|
| CL |
Chile |
Latin America |
|
Main Country |
|
| CM |
Cameroon |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| CN |
China |
East Asia |
|
Main Country |
|
| CO |
Colombia |
Latin America |
|
Main Country |
|
| CR |
Costa Rica |
Latin America |
|
Other Latin America |
|
| CU |
Cuba |
Latin America |
|
Other Latin America |
|
| CV |
Cabo Verde |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| CW |
Curacao |
Latin America |
|
Other Latin America |
|
| CY |
Cyprus |
Europe |
|
Eastern Europe |
|
| CZ |
Czechia |
Europe |
|
Eastern Europe |
|
| DE |
Germany |
Europe |
|
Main Country |
|
| DJ |
Djibouti |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| DK |
Denmark |
Europe |
|
Main Country |
|
| DM |
Dominica |
Latin America |
|
Other Latin America |
|
| DO |
Dominican Republic |
Latin America |
|
Other Latin America |
|
| DZ |
Algeria |
MENA |
|
Main Country |
|
| EC |
Ecuador |
Latin America |
|
Other Latin America |
|
| EE |
Estonia |
Europe |
|
Eastern Europe |
|
| EG |
Egypt |
MENA |
|
Main Country |
|
| ER |
Eritrea |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| ES |
Spain |
Europe |
|
Main Country |
|
| ET |
Ethiopia |
Sub-Saharan Africa |
|
Main Country |
|
| FI |
Finland |
Europe |
|
Other Western Europe |
|
| FJ |
Fiji |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| FM |
Micronesia |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| FR |
France |
Europe |
|
Main Country |
|
| GA |
Gabon |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| GB |
United Kingdom |
Europe |
|
Main Country |
|
| GD |
Grenada |
Latin America |
|
Other Latin America |
|
| GE |
Georgia |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| GG |
Guernsey |
Europe |
|
Other Western Europe |
|
| GH |
Ghana |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| GI |
Gibraltar |
Europe |
|
Other Western Europe |
|
| GL |
Greenland |
North America & Oceania |
North America |
Other North America & Oceania |
Other North America |
| GM |
Gambia |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| GN |
Guinea |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| GQ |
Equatorial Guinea |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| GR |
Greece |
Europe |
|
Other Western Europe |
|
| GT |
Guatemala |
Latin America |
|
Other Latin America |
|
| GW |
Guinea-Bissau |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| GY |
Guyana |
Latin America |
|
Other Latin America |
|
| HK |
Hong Kong |
East Asia |
|
Other East Asia |
|
| HN |
Honduras |
Latin America |
|
Other Latin America |
|
| HR |
Croatia |
Europe |
|
Eastern Europe |
|
| HT |
Haiti |
Latin America |
|
Other Latin America |
|
| HU |
Hungary |
Europe |
|
Eastern Europe |
|
| ID |
Indonesia |
South & Southeast Asia |
|
Main Country |
|
| IE |
Ireland |
Europe |
|
Other Western Europe |
|
| IL |
Israel |
MENA |
|
Other MENA |
|
| IM |
Isle of Man |
Europe |
|
Other Western Europe |
|
| IN |
India |
South & Southeast Asia |
|
Main Country |
|
| IQ |
Iraq |
MENA |
|
Other MENA |
|
| IR |
Iran |
MENA |
|
Main Country |
|
| IS |
Iceland |
Europe |
|
Other Western Europe |
|
| IT |
Italy |
Europe |
|
Main Country |
|
| JE |
Jersey |
Europe |
|
Other Western Europe |
|
| JM |
Jamaica |
Latin America |
|
Other Latin America |
|
| JO |
Jordan |
MENA |
|
Other MENA |
|
| JP |
Japan |
East Asia |
|
Main Country |
|
| KE |
Kenya |
Sub-Saharan Africa |
|
Main Country |
|
| KG |
Kyrgyzstan |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| KH |
Cambodia |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| KI |
Kiribati |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| KM |
Comoros |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| KN |
Saint Kitts and Nevis |
Latin America |
|
Other Latin America |
|
| KP |
North Korea |
East Asia |
|
Other East Asia |
|
| KR |
South Korea |
East Asia |
|
Main Country |
|
| KS |
Kosovo |
Europe |
|
Eastern Europe |
|
| KW |
Kuwait |
MENA |
|
Other MENA |
|
| KY |
Cayman Islands |
Latin America |
|
Other Latin America |
|
| KZ |
Kazakhstan |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| LA |
Lao PDR |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| LB |
Lebanon |
MENA |
|
Other MENA |
|
| LC |
Saint Lucia |
Latin America |
|
Other Latin America |
|
| LI |
Liechtenstein |
Europe |
|
Other Western Europe |
|
| LK |
Sri Lanka |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| LR |
Liberia |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| LS |
Lesotho |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| LT |
Lithuania |
Europe |
|
Eastern Europe |
|
| LU |
Luxembourg |
Europe |
|
Other Western Europe |
|
| LV |
Latvia |
Europe |
|
Eastern Europe |
|
| LY |
Libya |
MENA |
|
Other MENA |
|
| MA |
Morocco |
MENA |
|
Main Country |
|
| MC |
Monaco |
Europe |
|
Other Western Europe |
|
| MD |
Moldova |
Europe |
|
Eastern Europe |
|
| ME |
Montenegro |
Europe |
|
Eastern Europe |
|
| MG |
Madagascar |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| MH |
Marshall Islands |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| MK |
North Macedonia |
Europe |
|
Eastern Europe |
|
| ML |
Mali |
Sub-Saharan Africa |
|
Main Country |
|
| MM |
Myanmar |
South & Southeast Asia |
|
Main Country |
|
| MN |
Mongolia |
East Asia |
|
Other East Asia |
|
| MO |
Macao |
East Asia |
|
Other East Asia |
|
| MR |
Mauritania |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| MS |
Montserrat |
Latin America |
|
Other Latin America |
|
| MT |
Malta |
Europe |
|
Other Western Europe |
|
| MU |
Mauritius |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| MV |
Maldives |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| MW |
Malawi |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| MX |
Mexico |
Latin America |
|
Main Country |
|
| MY |
Malaysia |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| MZ |
Mozambique |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| NA |
Namibia |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| NC |
New Caledonia |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| NE |
Niger |
Sub-Saharan Africa |
|
Main Country |
|
| NG |
Nigeria |
Sub-Saharan Africa |
|
Main Country |
|
| NI |
Nicaragua |
Latin America |
|
Other Latin America |
|
| NL |
Netherlands |
Europe |
|
Main Country |
|
| NO |
Norway |
Europe |
|
Main Country |
|
| NP |
Nepal |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| NR |
Nauru |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| NZ |
New Zealand |
North America & Oceania |
Oceania |
Main Country |
|
| OM |
Oman |
MENA |
|
Other MENA |
|
| PA |
Panama |
Latin America |
|
Other Latin America |
|
| PE |
Peru |
Latin America |
|
Other Latin America |
|
| PF |
French Polynesia |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| PG |
Papua New Guinea |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| PH |
Philippines |
South & Southeast Asia |
|
Main Country |
|
| PK |
Pakistan |
South & Southeast Asia |
|
Main Country |
|
| PL |
Poland |
Europe |
|
Eastern Europe |
|
| PR |
Puerto Rico |
Latin America |
|
Other Latin America |
|
| PS |
Palestine |
MENA |
|
Other MENA |
|
| PT |
Portugal |
Europe |
|
Other Western Europe |
|
| PW |
Palau |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| PY |
Paraguay |
Latin America |
|
Other Latin America |
|
| QA |
Qatar |
MENA |
|
Other MENA |
|
| RO |
Romania |
Europe |
|
Eastern Europe |
|
| RS |
Serbia |
Europe |
|
Eastern Europe |
|
| RU |
Russia |
Russia & Central Asia |
|
Main Country |
|
| RW |
Rwanda |
Sub-Saharan Africa |
|
Main Country |
|
| SA |
Saudi Arabia |
MENA |
|
Main Country |
|
| SB |
Solomon Islands |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| SC |
Seychelles |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| SD |
Sudan |
Sub-Saharan Africa |
|
Main Country |
|
| SE |
Sweden |
Europe |
|
Main Country |
|
| SG |
Singapore |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| SI |
Slovenia |
Europe |
|
Eastern Europe |
|
| SK |
Slovakia |
Europe |
|
Eastern Europe |
|
| SL |
Sierra Leone |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| SM |
San Marino |
Europe |
|
Other Western Europe |
|
| SN |
Senegal |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| SO |
Somalia |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| SR |
Suriname |
Latin America |
|
Other Latin America |
|
| SS |
South Sudan |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| ST |
Sao Tome and Principe |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| SV |
El Salvador |
Latin America |
|
Other Latin America |
|
| SX |
Sint Maarten (Dutch part) |
Latin America |
|
Other Latin America |
|
| SY |
Syria |
MENA |
|
Other MENA |
|
| SZ |
Eswatini |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| TC |
Turks and Caicos Islands |
Latin America |
|
Other Latin America |
|
| TD |
Chad |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| TG |
Togo |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| TH |
Thailand |
South & Southeast Asia |
|
Main Country |
|
| TJ |
Tajikistan |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| TL |
Timor-Leste |
South & Southeast Asia |
|
Other South & Southeast Asia |
|
| TM |
Turkmenistan |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| TN |
Tunisia |
MENA |
|
Other MENA |
|
| TO |
Tonga |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| TR |
Turkiye |
MENA |
|
Main Country |
|
| TT |
Trinidad and Tobago |
Latin America |
|
Other Latin America |
|
| TV |
Tuvalu |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| TW |
Taiwan |
East Asia |
|
Main Country |
|
| TZ |
Tanzania |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| UA |
Ukraine |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| UG |
Uganda |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| US |
USA |
North America & Oceania |
North America |
Main Country |
|
| UY |
Uruguay |
Latin America |
|
Other Latin America |
|
| UZ |
Uzbekistan |
Russia & Central Asia |
|
Other Russia & Central Asia |
|
| VC |
Saint Vincent and the Grenadines |
Latin America |
|
Other Latin America |
|
| VE |
Venezuela |
Latin America |
|
Other Latin America |
|
| VG |
Virgin Islands, British |
Latin America |
|
Other Latin America |
|
| VN |
Viet Nam |
South & Southeast Asia |
|
Main Country |
|
| VU |
Vanuatu |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| WS |
Samoa |
North America & Oceania |
Oceania |
Other North America & Oceania |
Other Oceania |
| YE |
Yemen |
MENA |
|
Other MENA |
|
| ZA |
South Africa |
Sub-Saharan Africa |
|
Main Country |
|
| ZM |
Zambia |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
| ZW |
Zimbabwe |
Sub-Saharan Africa |
|
Other Sub-Saharan Africa |
|
World Region Codes
Regions available in two currency variants. The decomposition
(=) WO = (+) QE + (+) QL + (+) XB + (+) XF + (+) XL + (+) XN + (+) XR + (+) XS.
| WO-PPP |
WO-MER |
World |
| QE-PPP |
QE-MER |
Europe |
| OC-PPP |
OC-MER |
Other Western Europe |
| QM-PPP |
QM-MER |
Eastern Europe |
| QL-PPP |
QL-MER |
East Asia |
| OB-PPP |
OB-MER |
Other East Asia |
| XB-PPP |
XB-MER |
North America and Oceania |
| QF-PPP |
QF-MER |
Oceania |
| OL-PPP |
OL-MER |
Other Oceania |
| QP-PPP |
QP-MER |
North America |
| OK-PPP |
OK-MER |
Other North America |
| OH-PPP |
OH-MER |
Other North America and Oceania |
| XF-PPP |
XF-MER |
Sub-Saharan Africa |
| OJ-PPP |
OJ-MER |
Other Sub-Saharan Africa |
| XL-PPP |
XL-MER |
Latin America |
| OD-PPP |
OD-MER |
Other Latin America |
| XN-PPP |
XN-MER |
MENA (Middle East and North Africa) |
| OE-PPP |
OE-MER |
Other MENA |
| XR-PPP |
XR-MER |
Russia and Central Asia |
| OA-PPP |
OA-MER |
Other Russia and Central Asia |
| XS-PPP |
XS-MER |
South and Southeast Asia |
| OI-PPP |
OI-MER |
Other South and Southeast Asia |
Historical Country Codes
| CS |
Czechoslovakia |
| DD |
German Democratic Republic |
| SU |
USSR |
| YU |
Yugoslavia |
| ZZ |
Zanzibar |
Country Subregion Codes
| CN-RU |
Rural China |
| CN-UR |
Urban China |
| DE-BD |
Baden |
| DE-BY |
Bavaria |
| DE-HB |
Bremen |
| DE-HE |
Hesse |
| DE-HH |
Hamburg |
| DE-PR |
Prussia |
| DE-SN |
Saxony |
| DE-WU |
Wurttemberg |
| US-AK |
Alaska |
| US-AL |
Alabama |
| US-AR |
Arkansas |
| US-AZ |
Arizona |
| US-CA |
California |
| US-CO |
Colorado |
| US-CT |
Connecticut |
| US-DC |
District of Columbia |
| US-DE |
Delaware |
| US-FL |
Florida |
| US-GA |
Georgia |
| US-HI |
Hawaii |
| US-IA |
Iowa |
| US-ID |
Idaho |
| US-IL |
Illinois |
| US-IN |
Indiana |
| US-KS |
Kansas |
| US-KY |
Kentucky |
| US-LA |
Louisiana |
| US-MA |
Massachusetts |
| US-MD |
Maryland |
| US-ME |
Maine |
| US-MI |
Michigan |
| US-MN |
Minnesota |
| US-MO |
Missouri |
| US-MS |
Mississippi |
| US-MT |
Montana |
| US-NC |
North Carolina |
| US-ND |
North Dakota |
| US-NE |
Nebraska |
| US-NH |
New Hampshire |
| US-NJ |
New Jersey |
| US-NM |
New Mexico |
| US-NV |
Nevada |
| US-NY |
New York |
| US-OH |
Ohio |
| US-OK |
Oklahoma |
| US-OR |
Oregon |
| US-PA |
Pennsylvania |
| US-RI |
Rhode Island |
| US-SC |
South Carolina |
| US-SD |
South Dakota |
| US-TN |
Tennessee |
| US-TX |
Texas |
| US-UT |
Utah |
| US-VA |
Virginia |
| US-VT |
Vermont |
| US-WA |
Washington |
| US-WI |
Wisconsin |
| US-WV |
West Virginia |
| US-WY |
Wyoming |
2.3 Percentile Codes
There are 184 enumerated codes of the form pXpY (X <
Y, both 0-100).
head(wid_percentiles)
wid_search("top 1", tables = "percentiles")
wid_validate(perc = "p99p100")
wid_validate(perc = "p90p10") # error: invalid order
Key groups (most widely used): p0p100,
p0p50, p50p90, p90p100,
p99p100, p99.9p100, p99.99p100,
and all deciles p0p10, p10p20, …,
p90p100.
Detailed percentile groups: all centiles
(p0p1 through p99p100), tenths within the top
1% (p99.1p99.2, …, p99.9p100), hundredths
within the top 0.1%, and thousandths within the top 0.01%.
Detailed top groups: population above a given
percentile – p1p100, p2p100, …
Detailed bottom groups: population below a given
percentile – p0p99, p0p98, …
For each group, WID provides: share
(s), average (a),
threshold (t), and for top groups the
inverted Pareto-Lorenz coefficient (b) –
the ratio of group average to group threshold, measuring fatness of the
distributional tail.
Note: individuals are not always ranked by the quantity being
measured. Use wid_decode() or wid_metadata()
to confirm the ranking variable.
3. Aggregate Income Variables
3.1.1 GDP and Net National Income
download_wid(indicators = "anninc992i", areas = "FR", years = 1900:2023)
nninc |
(=) net national income |
B5n |
S1 |
ndpro |
(+) net domestic product |
|
|
gdpro |
(+) gross domestic product |
B1g |
S14+S15 |
confc |
(-) consumption of fixed capital |
P51c |
S1 |
nnfin |
(+) foreign income |
(-) B5n |
S2 |
3.1.2 Decomposition of Foreign Income
Paid/Received
nnfin |
(=) net foreign income |
|
|
finrx |
(+) foreign income received from the rest of the world |
|
|
flcir |
(+) labor and capital income from the rest of the world |
D1+D4 |
S2 |
comrx |
(+) compensation of employees received |
D1 |
S2 |
pinrx |
(+) property income received |
D4 |
S2 |
fdirx |
(+) foreign direct investment income |
|
|
ptfrx |
(+) portfolio and other income |
|
|
ptdrx |
(+) debt income |
|
|
pterx |
(+) equity income |
|
|
ptrrx |
(+) reserves income |
|
|
ptfrr |
(+) reinvested earnings on foreign portfolio investment |
|
|
fsubx |
(+) subsidies on prod. received from rest of world |
D3 |
S2 |
fpsub |
(+) subsidies on products |
D31 |
S2 |
fosub |
(+) other subsidies on production |
D39 |
S2 |
finpx |
(-) foreign income paid to the rest of the world |
|
|
flcip |
(+) labor and capital income paid to rest of world |
|
|
compx |
(+) compensation of employees paid |
D1 |
S2 |
pinpx |
(+) property income paid |
D4 |
S2 |
fdipx |
(+) foreign direct investment income paid |
|
|
ptfpx |
(+) portfolio and other income paid |
|
|
ptdpx |
(+) debt income paid |
|
|
ptepx |
(+) equity income paid |
|
|
ptfrp |
(+) reinvested earnings on foreign portfolio investment paid |
|
|
ftaxx |
(+) taxes on prod. paid to rest of world |
D2 |
S2 |
fptax |
(+) taxes on products |
D21 |
S2 |
fotax |
(+) other taxes on production |
D29 |
S2 |
Labor/Capital
nnfin |
(=) net foreign income |
|
|
flcin |
(+) net foreign labor and capital income |
|
|
pinnx |
(+) net foreign capital income |
D4 |
S2 |
fdinx |
(+) net foreign direct investment income |
|
|
ptfnx |
(+) net portfolio income |
|
|
ptdnx |
(+) net debt income |
|
|
ptenx |
(+) net equity income |
|
|
ptfrn |
(+) net reinvested earnings on foreign portfolio investment |
|
|
ptrrx |
(+) reserves income |
|
|
comnx |
(+) net foreign labor income |
D1 |
S2 |
taxnx |
(+) subsidies less taxes on production and imports |
D3-D2 |
S2 |
prtxn |
(+) subsidies less taxes on products |
D31-D21 |
S2 |
optxn |
(+) other subsidies less taxes on production |
D39-D29 |
S2 |
3.1.3 Decomposition of Foreign Wealth
nwnxa |
(=) net foreign assets |
fdixn |
(+) net foreign direct investment |
fdixa |
(+) foreign direct investment assets |
fdixd |
(-) foreign direct investment liabilities |
ptfxn |
(+) net foreign portfolio |
ptfxa |
(+) portfolio assets |
ptexa |
(+) portfolio equity assets |
ptdxa |
(+) portfolio debt assets |
ptrxa |
(+) foreign reserve exchange assets |
ptfxd |
(-) portfolio liabilities |
ptexd |
(+) portfolio equity liabilities |
ptdxd |
(+) portfolio debt liabilities |
3.1.4 Decomposition of National Income between Sectors
Primary Income Decomposition
nninc |
(=) net national income |
B5n |
S1 |
prigo |
(+) net primary income of the general government |
B5n |
S13 |
prihn |
(+) net primary income of households and non-profits |
B5n |
S14+S15 |
priho |
(+) net primary income of households |
B5n |
S14 |
prinp |
(+) net primary income of non-profits |
B5n |
S15 |
prico |
(+) net primary income of corporations |
B5n |
S11+S12 |
prinf |
(+) net primary income of non-financial corporations |
B5n |
S11 |
prifc |
(+) net primary income of financial corporations |
B5n |
S12 |
Secondary Income Decomposition
nninc |
(=) net national income |
B5n |
S1 |
secgo |
(+) net secondary income of the general government |
B6n+D7 |
S13 |
sechn |
(+) net secondary income of households and non-profits |
B6n+D7 |
S14+S15 |
secho |
(+) net secondary income of households |
B6n+D7 |
S14 |
secnp |
(+) net secondary income of non-profits |
B6n+D7 |
S15 |
secco |
(+) net secondary income of corporations |
B6n+D7 |
S11+S12 |
secnf |
(+) net secondary income of non-financial corporations |
B6n+D7 |
S11 |
secfc |
(+) net secondary income of financial corporations |
B6n+D7 |
S12 |
Decomposition of Property Income between Sectors
pinnx |
(=) net foreign property income |
(-) D4 |
S2 |
prphn |
(+) property income of households and NPISH |
D4 |
S14+S15 |
prpco |
(+) property income of corporations |
D4 |
S11+S12 |
prpgo |
(+) property income of the government |
D4 |
S13 |
Decomposition of Direct Taxes on Income and Wealth between
Sectors
taxgo |
(=) direct taxes received by the government |
D5 |
S13 |
tiwhn |
(+) taxes on income and wealth paid by households |
D5 |
S14+S15 |
taxco |
(+) corporate tax |
D5 |
S11+S12 |
Decomposition of Social Security Contributions between
Sectors
sschn |
(=) social contributions paid by households and NPISH |
D61 |
S14+S15 |
sscgo |
(+) social contributions received by the government |
D61 |
S13 |
sscco |
(+) social contributions to private employer social insurance |
D61 |
S11+S12 |
Decomposition of Social Security Benefits between
Sectors
ssbhn |
(=) social benefits received by households and NPISH |
D61 |
S14+S15 |
ssbgo |
(+) social benefits paid by the government |
D61 |
S13 |
ssbco |
(+) social benefits from private employer social insurance |
D61 |
S11+S12 |
Decomposition of Net Savings between Sectors
savin |
(=) net savings of the total economy |
B8n+D7 |
S1 |
savhn |
(+) net savings of households and NPISH |
B8n+D7 |
S14+S15 |
savho |
(+) net savings of households |
B8n+D7 |
S14 |
savnp |
(+) net savings of NPISH |
B8n+D7 |
S15 |
savco |
(+) net savings/secondary income of corporations |
B8n+D7 |
S11+S12 |
secnf |
(+) net savings of non-financial corporations |
B8n+D7 |
S11 |
secfc |
(+) net savings of financial corporations |
B8n+D7 |
S12 |
savgo |
(+) net savings of the general government |
B8n+D7 |
S13 |
Decomposition of Gross Savings between Sectors
savig |
(=) gross savings of the total economy |
B8g+D7 |
S1 |
saghn |
(+) gross savings of households and NPISH |
B8g+D7 |
S14+S15 |
sagho |
(+) gross savings of households |
B8g+D7 |
S14 |
sagnp |
(+) gross savings of NPISH |
B8g+D7 |
S15 |
sagco |
(+) gross savings/secondary income of corporations |
B8g+D7 |
S11+S12 |
segnf |
(+) gross savings of non-financial corporations |
B8g+D7 |
S11 |
segfc |
(+) gross savings of financial corporations |
B8g+D7 |
S12 |
saggo |
(+) gross savings of the general government |
B8g+D7 |
S13 |
Net and Gross Variables across Sectors
confc |
(=) consumption of fixed capital of the total economy |
P51c |
S1 |
cfchn |
(+) CFC of households and NPISH |
P51c |
S14+S15 |
cfcho |
(+) CFC of households |
P51c |
S14 |
cfcnp |
(+) CFC of NPISH |
P51c |
S15 |
cfcco |
(+) CFC of corporations |
P51c |
S11+S12 |
cfcnf |
(+) CFC of non-financial corporations |
P51c |
S11 |
cfcfc |
(+) CFC of financial corporations |
P51c |
S12 |
cfcgo |
(+) CFC of the general government |
P51c |
S13 |
savin |
(=) net savings of the total economy |
B8n+D7 |
S1 |
savig |
(+) gross savings of the total economy |
B8g+D7 |
S1 |
confc |
(-) consumption of fixed capital of the total economy |
P51c |
S1 |
3.1.5 Labor and Capital Share of National Income
nninc |
(=) net national income |
B5n |
S1 |
comhn |
(+) compensation of employees |
D1 |
S14+S15 |
fkpin |
(+) net capital income |
|
|
prphn |
(+) property income distributed to households and NPISH |
D4 |
S14+S15 |
prpgo |
(+) property income distributed to the government |
D4 |
S13 |
nsrhn |
(+) net operating surplus of households and NPISH |
B2n |
S14+S15 |
prico |
(+) net primary income of corporations |
B5n |
S11+S12 |
nmxho |
(+) net mixed income of households |
B3n |
S14 |
ptxgo |
(+) taxes on products and production |
D2-D3 |
S13 |
Mixed income is conventionally split 70% labor / 30% capital for
computing factor shares. The full four-way decomposition (pure labor,
pure capital, mixed income, production taxes) is available when the
treatment of mixed income matters.
3.1.6 Income Decomposition by Institutional Sector
Factor-Price GDP Decomposition
gdpro |
(=) gross domestic product at market prices |
B1g |
S1 |
ptxgo |
(+) net taxes on products and production |
D2-D3 |
S1 |
gvato |
(+) gross domestic product at factor-price |
B1g |
S1 |
gvago |
(+) gross value added of the government |
B1g |
S13 |
ceugo |
(+) compensation of employees of the government |
D1 |
S13 |
gsrgo |
(+) gross operating surplus of the government |
B2g |
S13 |
nsrgo |
(+) net operating surplus of the government (=0) |
B2n |
S13 |
cfcgo |
(+) CFC of the government |
P51c |
S13 |
gvaco |
(+) gross value added of the corporate sector |
B1g |
S11+S12 |
ceuco |
(+) compensation of employees of the corporate sector |
D1 |
S11+S12 |
gsrco |
(+) gross operating surplus of the corporate sector |
B2g |
S11+S12 |
nsrco |
(+) net operating surplus of the corporate sector |
B2n |
S11+S12 |
cfcco |
(+) CFC of the corporate sector |
P51c |
S11+S12 |
gvahn |
(+) gross value added of household sector |
B1g |
S14+S15 |
ceuhn |
(+) compensation of employees of household sector |
D1 |
S14+S15 |
gmxhn |
(+) gross mixed income of household sector |
B3g |
S14+S15 |
nmxhn |
(+) net mixed income of household sector |
B3n |
S14+S15 |
ccmhn |
(+) CFC of mixed income of household sector |
P51c |
S14+S15 |
gsrhn |
(+) gross operating surplus of household sector |
B2g |
S14+S15 |
nsrhn |
(+) net operating surplus of household sector |
B2n |
S14+S15 |
ccshn |
(+) CFC of operating surplus of household sector |
P51c |
S14+S15 |
Factor Shares
ylsgdp |
labor share of gross domestic product at factor-price |
S1 |
ylsndp |
labor share of net domestic product at factor-price |
S1 |
ycsgdp |
capital share of gross domestic product at factor-price |
S1 |
ycsndp |
capital share of net domestic product at factor-price |
S1 |
wlsgni |
labor share of gross national income at factor-price |
S1 |
wlsnni |
labor share of national income at factor-price |
S1 |
wcsgni |
capital share of gross national income at factor-price |
S1 |
wcsnni |
capital share of national income at factor-price |
S1 |
ylscgv |
labor share in corporate gross value added at factor-price |
S11+S12 |
ylscnv |
labor share in corporate net value added at factor-price |
S11+S12 |
ycscgv |
capital share in corporate gross value added at factor-price |
S11+S12 |
ycscnv |
capital share in corporate net value added at factor-price |
S11+S12 |
3.4 Income of the Government Sector
3.4.1 Primary Income of the Government
Net of Consumption of Fixed Capital
prigo |
(=) net primary income of the general government |
B5n |
S13 |
ptxgo |
(+) taxes on production and imports, less subsidies |
D2-D3 |
S13 |
tpigo |
(+) taxes on production and imports |
D2 |
S13 |
tprgo |
(+) taxes on products |
D21 |
S13 |
otpgp |
(+) other taxes on production |
D29 |
S13 |
spigo |
(-) subsidies on production and imports |
D3 |
S13 |
sprgo |
(+) subsidies on products |
D31 |
S13 |
ospgo |
(+) other subsidies on production |
D39 |
S13 |
prpgo |
(+) property income (net) |
D4 |
S13 |
nsrgo |
(+) net operating surplus and miscellaneous |
B2n |
S13 |
Gross of Consumption of Fixed Capital
prggo |
(=) gross primary income of the general government |
B5n |
S13 |
ptxgo |
(+) taxes on production and imports, less subsidies |
D2-D3 |
S13 |
tpigo |
(+) taxes on production and imports |
D2 |
S13 |
tprgo |
(+) taxes on products |
D21 |
S13 |
otpgp |
(+) other taxes on production |
D29 |
S13 |
spigo |
(-) subsidies on production and imports |
D3 |
S13 |
sprgo |
(+) subsidies on products |
D31 |
S13 |
ospgo |
(+) other subsidies on production |
D39 |
S13 |
prpgo |
(+) property income (net) |
D4 |
S13 |
gsrgo |
(+) gross operating surplus and miscellaneous |
B2n |
S13 |
3.4.2 Secondary Income of the Government
Net of Consumption of Fixed Capital
secgo |
(=) net secondary income of the general government |
B6n+D7 |
S13 |
prigo |
(+) net primary income of the general government |
B5n |
S13 |
taxgo |
(+) direct taxes |
D5+D61 |
S13 |
tiwgo |
(+) direct taxes on income and wealth |
D5 |
S13 |
sscgo |
(+) social contributions |
D61 |
S13 |
ssbgo |
(-) social benefits other than social transfers in kind |
D62 |
S13 |
Gross of Consumption of Fixed Capital
seggo |
(=) gross secondary income of the general government |
B6n+D7 |
S13 |
prggo |
(+) gross primary income of the general government |
B5n |
S13 |
taxgo |
(+) direct taxes |
D5+D61 |
S13 |
tiwgo |
(+) direct taxes on income and wealth |
D5 |
S13 |
sscgo |
(+) social contributions |
D61 |
S13 |
ssbgo |
(-) social benefits other than social transfers in kind |
D62 |
S13 |
3.4.3 Consumption and Savings of the Government
Net of Consumption of Fixed Capital
savgo |
(=) net savings of the general government |
B8n+D7 |
S13 |
secgo |
(+) net secondary income of the general government |
B6n+D7 |
S13 |
congo |
(-) final consumption expenditures |
P3 |
S13 |
indgo |
(+) individual consumption expenditures |
P31 |
S13 |
colgo |
(+) collective consumption expenditure |
P32 |
S13 |
Gross of Consumption of Fixed Capital
saggo |
(=) gross savings of the general government |
B8n+D7 |
S13 |
seggo |
(+) gross secondary income of the general government |
B6n+D7 |
S13 |
congo |
(-) final consumption expenditures |
P3 |
S13 |
indgo |
(+) individual consumption expenditures |
P31 |
S13 |
colgo |
(+) collective consumption expenditure |
P32 |
S13 |
Government Spending by Function
congo |
(=) final consumption expenditures |
S13 |
gpsgo |
(+) general public services |
S13 |
defgo |
(+) defense |
S13 |
polgo |
(+) public order and safety |
S13 |
ecogo |
(+) economic affairs |
S13 |
envgo |
(+) environment protection |
S13 |
hougo |
(+) housing and community amenities |
S13 |
heago |
(+) health |
S13 |
recgo |
(+) recreation, culture and religion |
S13 |
edugo |
(+) education |
S13 |
sopgo |
(+) social protection |
S13 |
othgo |
(+) other government spending |
S13 |
Government Expenditure by Function
expgo |
(=) total public spending (excl. interest payment) |
S13 |
gpsge |
(+) general public services (excl. interest payment) |
S13 |
defge |
(+) defense |
S13 |
polge |
(+) public order and safety |
S13 |
ecoge |
(+) economic affairs |
S13 |
envge |
(+) environment protection |
S13 |
houge |
(+) housing and community amenities |
S13 |
heage |
(+) health |
S13 |
recge |
(+) recreation, culture and religion |
S13 |
eduge |
(+) education |
S13 |
edpge |
(+) education: primary |
S13 |
edsge |
(+) education: secondary |
S13 |
edtge |
(+) education: tertiary |
S13 |
sopge |
(+) social protection |
S13 |
spige |
(+) social protection: social insurance |
S13 |
sacge |
(+) social protection: social assistance in cash |
S13 |
sakge |
(+) social protection: social assistance in kind |
S13 |
Government Revenue
revgo |
(=) total public revenue |
S13 |
pitgr |
(+) personal income tax |
S13 |
citgr |
(+) corporate income tax |
S13 |
scogr |
(+) social contributions |
S13 |
pwtgr |
(+) property and wealth taxes |
S13 |
intgr |
(+) indirect taxes |
S13 |
ottgr |
(+) other taxes |
S13 |
ntrgr |
(+) non-tax revenue |
S13 |
retgo |
(=) total public revenue (excl. non-tax revenue) |
S13 |
psugo |
(=) primary surplus of the government |
S13 |
ssugo |
(=) secondary surplus of the government |
S13 |
inpgo |
(-) interest paid by the government |
S13 |
4. Distributed Income Variables
# Top 1% pretax income share
download_wid(
indicators = "sptinc992j",
areas = c("US", "FR", "CN", "ZA"),
perc = "p99p100",
years = 1990:2023
)
# Gini from full distribution
dist <- download_wid("sptinc992j", areas = "US", perc = "all", years = 2022)
wid_gini(dist)
wid_top_share(dist, top = 0.01)
# Percentile ratio from threshold series
thresh <- download_wid("tptinc992j", areas = "US", perc = "all", years = 2022)
wid_percentile_ratio(thresh)
# Plot Lorenz curve
wid_plot_lorenz(dist)
4.1 DINA Income
DINA income concepts are consistent with national accounts
aggregates. Each five-letter code is associated with a concept (income
attributed) and a ranking variable (income used to rank individuals –
sometimes identical, sometimes not).
4.1.1 Pretax Income
Pretax income includes social insurance benefits (removing
corresponding contributions) but excludes other redistribution.
ptinc |
(=) pretax national income |
pretax national income |
ptlin |
(+) pretax labor income |
|
ptkin |
(+) pretax capital income |
|
pllin |
(+) pretax labor income |
pretax labor income |
pkkin |
(+) pretax capital income |
pretax capital income |
4.1.2 Post-tax Income
diinc |
(=) post-tax national income |
post-tax national income |
cainc |
(=) post-tax disposable income |
post-tax disposable income |
4.1.3 Factor Income
Factor income measures inequality before any redistribution (before
social insurance or social assistance). Sensitive to age structure – use
with care for international comparisons.
fainc |
(=) factor national income |
factor national income |
flinc |
(=) labor factor income |
labor factor income |
4.2 “Fiscal” Income
Fiscal income is a legacy concept from the World Top Income Database
(WTID). It is close to taxable income; its exact definition varies by
country and over time. In most cases, fiscal income is only available
for the top 10% of the distribution.
download_wid(
indicators = "sfiinc992j",
areas = "US",
perc = "p99p100",
years = 1913:2023
)
fiinc |
(=) fiscal income |
total fiscal income |
filin |
(+) fiscal labor income |
|
fiwag |
(+) wages and pensions |
|
fimil |
(+) labor component of mixed-income |
|
ficap |
(+) fiscal capital income |
|
firen |
(+) rents |
|
fiint |
(+) interests |
|
fidiv |
(+) dividends |
|
fikgi |
(+) capital gains |
|
fimik |
(+) capital component of mixed-income |
|
fimix |
(=) mixed-income |
total fiscal income |
6. Distributed Wealth Variables
The distributed wealth variables are identical to the aggregate
wealth variables of the household sector. Individuals are ranked by net
personal wealth.
download_wid(
indicators = "shweal992j",
areas = "GB",
perc = c("p90p100", "p99p100"),
years = 1995:2023)
wid_plot_lorenz(download_wid("shweal992j", areas = "US", perc = "all", years = 2019))
hweal |
(=) household net wealth |
hwnfa |
(+) household non-financial assets |
hwhou |
(+) household housing assets |
hwdwe |
(+) dwellings |
hwlan |
(+) land underlying dwellings |
hwbus |
(+) household business and other non-financial assets |
hwagr |
(+) agricultural land |
hwodk |
(+) other domestic capital |
hwfin |
(+) financial assets |
hwfiw |
(+) currency, deposits, bonds, and loans |
hwcud |
(+) currency and deposits |
hwbol |
(+) bonds and loans |
hweqi |
(+) equities and fund shares |
hwpen |
(+) pension funds and life insurance |
hwdeb |
(-) liabilities |
hwfie |
(=) financial assets except for currency and deposits |
hwfin |
(+) financial assets |
hwcud |
(-) currency and deposits |
7. Price Index, Exchange Rates, Populations, etc.
7.1 Price Index
The WID uses a single price index (inyixx) – the
national income deflator, typically the GDP deflator (CPI when
unavailable). It equals 1 in the data’s base year.
download_wid(indicators = "inyixx999i", areas = "US", years = 1950:2023)
inyixx999i |
national income price index |
intlcu999i |
local currency unit change indicator |
7.2 Exchange Rates
The WID provides PPP conversion factors and market exchange rates for
USD, EUR, and CNY. To convert between currencies in the benchmark
approach, use only the last value of each series.
wid_convert() handles this automatically.
# Retrieve PPP exchange rate directly
download_wid(indicators = "xlcusp999i", areas = "FR", years = 2023)
# Convert a monetary series to 2022 USD PPP in one step
download_wid("aptinc992j", areas = c("US", "FR", "CN", "IN"), perc = "p0p50") |>
wid_convert(target = "ppp", base_year = "2022")
Supported wid_convert() targets: "lcu" (no
conversion), "usd", "eur", "gbp",
"ppp", "yppp". Dimensionless series (types
s, g, b, w,
r, p, i, y) are
returned unchanged.
PPP Conversion Factors
xlcusp999i |
LCU per USD |
xlceup999i |
LCU per EUR |
xlcyup999i |
LCU per CNY |
Market Exchange Rates
xlcusx999i |
LCU per USD |
xlceux999i |
LCU per EUR |
xlcyux999i |
LCU per CNY |
Real Exchange Rates (PPP / market rate)
xrerus999i |
real exchange rate between LCU and USD |
xrereu999i |
real exchange rate between LCU and EUR |
xreryu999i |
real exchange rate between LCU and CNY |
7.3 Population
download_wid(indicators = "npopul999i", areas = "US", years = 1800:2023)
npopul |
population |
npopem |
employed population |
ntaxto |
total tax population |
ntaxma |
number of tax units – married couples and single adults |
ntaxad |
number of tax units – adults |
ntaxre |
number of tax returns |
Combined with age and population unit codes (e.g.,
npopul992i for adult population).
7.4 Wealth/Income Ratios and Labor/Capital Shares
wlabsh999i |
labor share of factor-price national income |
wcapsh999i |
capital share of factor-price national income |
wwealn999i |
net national wealth to net national income ratio |
wwealp999i |
net private wealth to net national income ratio |
wwealh999i |
net personal wealth to net national income ratio |
wweali999i |
net non-profit wealth to net national income ratio |
wwealc999i |
net corporate wealth to net national income ratio |
wwealg999i |
net public wealth to net national income ratio |
7.5 Inequality Transparency
WID produces a single inequality transparency index per country,
ranging from 0 to 20, weighting income and wealth data equally. Points
are awarded for: income/consumption survey tabulations (1 pt), survey
microdata (up to 3 pts), wealth survey tabulations (1 pt), wealth survey
microdata (up to 3 pts), income tax tabulations for labor (1 pt) and
capital (1 pt), income tax microdata for labor (2 pts) and capital (2
pts), wealth/estate tax tabulations (2 pts), and wealth/estate tax
microdata (4 pts).
iquali999i |
inequality transparency index (0-20) |
9. Distributed Carbon Variables
Personal carbon footprints assign national carbon and CO2 footprints
to income groups within countries, distinguishing between
consumption-related and investment-related emissions.
# WID canonical example: top 10% average per capita footprint, Switzerland 2014
download_wid(
indicators = "lpfghg999i",
areas = "CH",
perc = "p90p100",
years = 2014)
# Bottom 50% share of emissions
download_wid(
indicators = "spfghg999i",
areas = c("US", "FR", "IN"),
perc = "p0p50",
years = 2019)
pfcar |
(=) personal CO2 footprint |
pfghg |
(=) personal carbon footprint |
cfghg |
(+) personal carbon footprint (consumption only) |
ifghg |
(+) personal carbon footprint (investments only) |
Series types applicable to distributed carbon:
l |
lpfghg999i |
average per capita group emissions |
e |
epfghg999i |
total group emissions |
s |
spfghg999i |
share of total emissions |
t |
tpfghg999i |
threshold (minimum footprint to enter the group) |
k |
kpfghg999i |
per capita emissions |
10. Quick Reference
print.wid_df and print.wid_query are S3
print methods; see vignette("widr") for display examples
and full workflow demonstrations.
download_wid() |
Download data; returns a wid_df |
wid_decode() |
Parse a variable code string into components |
wid_encode() |
Build a variable code string from components |
wid_validate() |
Validate components; stops on failure |
wid_is_valid() |
Non-throwing validation; returns
TRUE/FALSE |
wid_search() |
Keyword/regex search across reference tables |
wid_tidy() |
Coerce types; append decoded and country name columns |
wid_convert() |
Currency conversion ("lcu", "usd",
"eur", "gbp", "ppp",
"yppp") |
wid_metadata() |
Retrieve source and methodological documentation |
wid_gini() |
Gini coefficient from a share (s) series |
wid_top_share() |
Top fractile income/wealth share |
wid_percentile_ratio() |
Percentile threshold ratio (default P90/P10) |
wid_plot_timeseries() |
Time-series line chart; returns a ggplot object |
wid_plot_compare() |
Cross-country bar/point chart; returns a ggplot
object |
wid_plot_lorenz() |
Lorenz curve; returns a ggplot object |
wid_query() |
Construct a reusable query object |
wid_filter() |
Update fields of a wid_query |
wid_fetch() |
Execute a wid_query; returns a wid_df |
wid_cache() |
Low-level cache access ("get", "set",
"list", "clear") |
wid_cache_list() |
List cached query keys |
wid_cache_clear() |
Remove all cached responses |
wid_set_key() |
Set the WID API key |
print.wid_df |
S3 print method for wid_df objects |
print.wid_query |
S3 print method for wid_query objects |
wid_series_types |
17 series type codes |
wid_concepts |
464 concept codes |
wid_ages |
Age group codes |
wid_pop_types |
Population unit codes |
wid_countries |
281 country and region codes |
wid_percentiles |
184 percentile group codes |
Disclaimer: widr is an independent
implementation unaffiliated with the World Inequality Lab (WIL) or the
Paris School of Economics. Data are sourced from WID.world, maintained
by WIL. Codes reference: wid.world/codes-dictionary.
Full getting-started guide: vignette("widr")