[DP_LIVE] OECD Data Live dataset
Retrieved by DBnomics on January 11, 2024 (1:19 PM).
[AFG] Afghanistan
[AGO] Angola
[ALB] Albania
[ARE] United Arab Emirates
[ARG] Argentina
[ARM] Armenia
[AUS] Australia
[AUT] Austria
[AZE] Azerbaijan
[BDI] Burundi
[BEL] Belgium
[BEN] Benin
[BFA] Burkina Faso
[BGD] Bangladesh
[BGR] Bulgaria
[BHR] Bahrain
[BIH] Bosnia and Herzegovina
[BLR] Belarus
[BOL] Bolivia
[BRA] Brazil
[BRICS]
[BRN] Brunei Darussalam
[BTN] Bhutan
[BWA] Botswana
[CAF] Central African Republic
[CAN] Canada
[CHE] Switzerland
[CHL] Chile
[CHN] China (People's Republic of)
[CIV] Côte d'Ivoire
[CMR] Cameroon
[COD] Democratic Republic of the Congo
[COG] Congo
[COL] Colombia
[CRI] Costa Rica
[CUB] Cuba
[CYP] Cyprus
[CZE] Czechia
[DAC] DAC Countries
[DAE] Dynamic Asian Economies
[DEU] Germany
[DEW] Former Federal Republic of Germany
[DNK] Denmark
[DOM] Dominican Republic
[DZA] Algeria
[EA] Euro area
[EA17] Euro area (17 countries)
[EA18] Euro area (18 countries)
[EA19] Euro area (19 countries)
[ECU] Ecuador
[EGY] Egypt
[ERI] Eritrea
[ESP] Spain
[EST] Estonia
[ETH] Ethiopia
[EU] European Union
[EU27] European Union (27 countries)
[EU27_2020] European Union – 27 countries (from 01/02/2020)
[EU28] European Union (28 countries)
[FIN] Finland
[FJI] Fiji
[FRA] France
[G-20] G20
[G-7] G7
[G20]
[G7M] G7
[GAB] Gabon
[GBR] United Kingdom
[GEO] Georgia
[GHA] Ghana
[GIN] Guinea
[GMB] Gambia
[GNB] Guinea-Bissau
[GNQ] Equatorial Guinea
[GRC] Greece
[GTM] Guatemala
[HKG] Hong Kong, China
[HND] Honduras
[HRV] Croatia
[HTI] Haiti
[HUN] Hungary
[IDN] Indonesia
[IND] India
[IRL] Ireland
[IRN] Iran
[IRQ] Iraq
[ISL] Iceland
[ISR] Israel
[ITA] Italy
[JAM] Jamaica
[JOR] Jordan
[JPN] Japan
[KAZ] Kazakhstan
[KEN] Kenya
[KGZ] Kyrgyzstan
[KHM] Cambodia
[KOR] Korea
[KWT] Kuwait
[LAO] Lao People's Democratic Republic
[LBN] Lebanon
[LBR] Liberia
[LBY] Libya
[LIE] Liechtenstein
[LKA] Sri Lanka
[LSO] Lesotho
[LTU] Lithuania
[LUX] Luxembourg
[LVA] Latvia
[MAC] Macau, China
[MAR] Morocco
[MDA] Moldova
[MDG] Madagascar
[MEX] Mexico
[MKD] North Macedonia
[MLI] Mali
[MLT] Malta
[MMR] Myanmar
[MNE] Montenegro
[MNG] Mongolia
[MOZ] Mozambique
[MRT] Mauritania
[MUS] Mauritius
[MWI] Malawi
[MYS] Malaysia
[NAM] Namibia
[NER] Niger
[NGA] Nigeria
[NIC] Nicaragua
[NLD] Netherlands
[NMEC] Non-OECD Economies
[NOR] Norway
[NPL] Nepal
[NZL] New Zealand
[OAVG] OECD - Average
[OECD] OECD - Total
[OECDE] OECD - Europe
[OEU] OECD - Europe
[OIL] Oil Producers
[OMN] Oman
[PAK] Pakistan
[PAN] Panama
[PER] Peru
[PHL] Philippines
[PNG] Papua New Guinea
[POL] Poland
[PRK] Democratic People's Republic of Korea
[PRT] Portugal
[PRY] Paraguay
[PSE] Palestinian Authority or West Bank and Gaza Strip
[QAT] Qatar
[ROU] Romania
[RUS] Russia
[RWA] Rwanda
[SAU] Saudi Arabia
[SDN] Sudan
[SEN] Senegal
[SGP] Singapore
[SLE] Sierra Leone
[SLV] El Salvador
[SOM] Somalia
[SRB] Serbia
[SVK] Slovak Republic
[SVN] Slovenia
[SWE] Sweden
[SWZ] Eswatini
[SYR] Syrian Arab Republic
[TCD] Chad
[TGO] Togo
[THA] Thailand
[TJK] Tajikistan
[TKM] Turkmenistan
[TLS] Timor-Leste
[TTO] Trinidad and Tobago
[TUN] Tunisia
[TUR] Türkiye
[TWN] Chinese Taipei
[TZA] Tanzania
[UGA] Uganda
[UKR] Ukraine
[URY] Uruguay
[USA] United States
[UZB] Uzbekistan
[VEN] Venezuela
[VNM] Viet Nam
[WLD] World
[YEM] Yemen
[ZAF] South Africa
[ZMB] Zambia
[ZWE] Zimbabwe
[AGRLANDAREA] Agricultural land
[AGRPNPC] Producer protection
[AGRSUPP] Agricultural support
[AIREMISSION] Air and GHG emissions
[ALCOHOL] Alcohol consumption
[AQUAPROD] Aquaculture production
[AVWAGE] Average wages
[BANKLEVERAGE] Banking sector leverage
[BCI] Business confidence index (BCI)
[BENUNEMPPC] Benefits in unemployment, share of previous income
[BOP] Current account balance
[BOPFORECAST] Current account balance forecast
[BSNSBROADBAND] Business use of broadband
[BUILT_UP] Built-up area
[CCI] Consumer confidence index (CCI)
[CGEXP] Central government spending
[CHILDVACCIN] Child vaccination rates
[CHLDCARECOST] Net childcare costs
[CLI] Composite leading indicator (CLI)
[COMPEMPLOYEEACTY] Employee compensation by activity
[CONTTRANSP] Container transport
[CPA] Country Programmable Aid (CPA)
[CPI] Inflation (CPI)
[CPIFORECAST] Inflation forecast
[CROPYIELD] Crop production
[CSECTIONS] Caesarean sections
[CTEXAM] Computed tomography (CT) exams
[CTSCANNER] Computed tomography (CT) scanners
[DDEMANDFORECAST] Domestic demand forecast
[DEATHCANCER] Deaths from cancer
[DISCRIMFAMCODE] Discrimination in the family
[DISTNODA] Distribution of net ODA
[DOCCONSULT] Doctors' consultations
[EDUADULT] Adult education level
[EDUEXP] Education spending
[EDUEXPTRY] Spending on tertiary education
[EDUPRIVEXP] Private spending on education
[EDUPUBEXP] Public spending on education
[EDUTRY] Population with tertiary education
[ELDLYPOP] Elderly population
[ELECTRICITY] Electricity generation
[EMP] Employment rate
[EMPAGE] Employment rate by age group
[EMPEDU] Employment by education level
[EMPINDUS] Employment by activity
[EMPLOYEE] Employees by business size
[ENROLMENT] Enrolment rate in secondary and tertiary education
[ENROLMENT_ECE] Enrolment rate in early childhood education
[ENTERPRISE] Enterprises by business size
[EXCH] Exchange rates
[EXPBSNS] Exports by business size
[FAMPUBEXP] Family benefits public spending
[FBORNEMP] Foreign-born employment
[FBORNPARTICIP] Foreign-born participation rates
[FBORNPOP] Foreign-born population
[FBORNUNEMP] Foreign-born unemployment
[FDIFLOW] FDI flows
[FDIFLOW_IN_CTRY] Inward FDI flows by partner country
[FDIFLOW_IN_IND] Inward FDI flows by industry
[FDIFLOW_OUT_CTRY] Outward FDI flows by partner country
[FDIFLOW_OUT_IND] Outward FDI flows by industry
[FDIRESTR] FDI restrictiveness
[FDISTOCK] FDI stocks
[FDISTOCK_IN_CTRY] Inward FDI stocks by partner country
[FDISTOCK_IN_IND] Inward FDI stocks by industry
[FDISTOCK_OUT_CTRY] Outward FDI stocks by partner country
[FDISTOCK_OUT_IND] Outward FDI stocks by industry
[FDI_INC_PAY_CTRY] FDI income payments by partner country
[FDI_INC_PAY_IND] FDI income payments by industry
[FDI_INC_REC_CTRY] FDI income receipts by partner country
[FDI_INC_REC_IND] FDI income receipts by industry
[FERTILITY] Fertility rates
[FINCORP] Financial corporations debt to equity ratio
[FINDISINCHLDCARE] Financial disincentive to enter employment with childcare costs
[FINDISINWKHR] Financial disincentive to increase working hours
[FINDISINWORK] Financial disincentive to return to work
[FISHLAND] Fish landings
[FISHPATENT] Fisheries patents
[FIXWIRED] Fixed broadband subscriptions
[FLUVACCIN] Influenza vaccination rates
[FOODAID] Food aid
[FORESTRESOURCE] Forest resources
[FPOP] Foreign population
[FREIGHTTRANSP] Freight transport
[GDEXPRD] Gross domestic spending on R&D
[GDINSURANCEPREM] Gross direct insurance premiums
[GDP] Gross domestic product (GDP)
[GDPCAPCONTR] Labour productivity and utilisation
[GDPHRWKD] GDP per hour worked
[GDPHRWKDFORECAST] Labour productivity forecast
[GDPLTFORECAST] Real GDP long-term forecast
[GFCF] Investment (GFCF)
[GFCFASSET] Investment by asset
[GFCFFORECAST] Investment forecast
[GFCFSECTOR] Investment by sector
[GGCOST] Government production costs
[GGDEBT] General government debt
[GGEXP] General government spending
[GGEXPDEST] General government spending by destination
[GGNLEND] General government deficit
[GGREV] General government revenue
[GGRSV] Government reserves
[GGWEALTH] General government financial wealth
[GINSURANCEPREM] Gross insurance premiums
[GNI] Gross national income
[GOVRESEARCHER] Government researchers
[GPENSION] Gross pension replacement rates
[GPENSIONWEALTH] Gross pension wealth
[GRADRATE] Secondary graduation rate
[GRADRATEFIELD] Tertiary graduates by field
[GRADRATETRY] Tertiary graduation rate
[GRANT] Grants by private agencies and NGOs
[GVCPARTICIP] Import content of exports
[HEALTHEXP] Health spending
[HHBROADHBAND] Households with broadband access
[HHDEBT] Household debt
[HHDI] Household disposable income
[HHEXP] Household spending
[HHFA] Household financial assets
[HHFT] Household financial transactions
[HHSAV] Household savings
[HHSAVFORECAST] Household savings forecast
[HHWEALTH] Household net worth
[HOMECOMP] Access to computers from home
[HOSPITALBED] Hospital beds
[HOSPITALDISCHARGE] Hospital discharge rates
[HOSPITALSTAY] Length of hospital stay
[HOUSECOST] Housing prices
[HRWKD] Hours worked
[HUR] Unemployment rate
[ICTEMP] ICT employment
[ICTGOODSEXP] ICT goods exports
[ICTINVST] ICT investment
[ICTVA] ICT value added
[IMMIGINFLOW] Permanent immigrant inflows
[IMPBSNS] Imports by business size
[INCOMEINEQ] Income inequality
[INDPROD] Industrial production
[INFANTMORTALITY] Infant mortality rates
[INFRAINVEST] Infrastructure investment
[INFRAMAINT] Infrastructure maintenance
[INSURANCEEXP] Insurance spending
[INTERNET] Internet access
[INVENTORS] Inventors
[LABCOMP] Labour compensation per hour worked
[LANDCOVER] Land cover change
[LF] Labour force
[LFFORECAST] Labour force forecast
[LFPR] Labour force participation rate
[LIFEEXP] Life expectancy at birth
[LIFEEXP65] Life expectancy at 65
[LTINT] Long-term interest rates
[LTINTFORECAST] Long-term interest rates forecast
[LTUNEMP] Long-term unemployment rate
[M1] Narrow money (M1)
[M3] Broad money (M3)
[MAMMOMACHINE] Mammography machines
[MATCONSUMP] Material consumption
[MATPROD] Material productivity
[MEATCONSUMP] Meat consumption
[MEDICALDOC] Doctors
[MEDICALGRAD] Medical graduates
[MFP] Multifactor productivity
[MININCBEN] Adequacy of minimum income benefits
[MRIEXAM] Magnetic resonance imaging (MRI) exams
[MRIUNITS] Magnetic resonance imaging (MRI) units
[NATAREADIST] National area distribution
[NATINSURANCESH] National insurance market share
[NATPOPDIST] National population distribution
[NBORNEMP] Native-born employment
[NBORNPARTICIP] Native-born participation rates
[NBORNUNEMP] Native-born unemployment
[NEET] Youth not in employment, education or training (NEET)
[NLNBSECTOR] Net lending/borrowing by sector
[NNI] Net national income
[NODA] Net ODA
[NOMGDPFORECAST] Nominal GDP forecast
[NONFINCORP] Non-Financial corporations debt to surplus ratio
[NPENSION] Net pension replacement rates
[NPENSIONWEALTH] Net pension wealth
[NUCLEARPLANT] Nuclear power plants
[NURSE] Nurses
[NURSEGRAD] Nursing graduates
[NUTRBALANCE] Nutrient balance
[ODASECTOR] ODA by sector
[OILIMPPRICE] Crude oil import prices
[OILPROD] Crude oil production
[OLDAGEDEP] Old-age dependency ratio
[OOF] Other official flows (OOF)
[OVERCROWDING] Housing overcrowding
[OVEROBESE] Overweight or obese population
[PARTEMP] Part-time employment rate
[PASSCAR] Passenger car registrations
[PASSTRANSP] Passenger transport
[PATENT] Triadic patent families
[PATENT_ENV] Patents on environment technologies
[PENSIONASSET] Pension funds' assets
[PENSIONEXP] Pension spending
[PHARMAEXP] Pharmaceutical spending
[PISAMATH] Mathematics performance (PISA)
[PISAREAD] Reading performance (PISA)
[PISASCIENCE] Science performance (PISA)
[PLI] Price level indices
[POLLUTIONEFFECT] Air pollution effects
[POLLUTIONEXP] Air pollution exposure
[POP] Population
[POVERTY] Poverty rate
[POVERTYGAP] Poverty gap
[PPI] Producer price indices (PPI)
[PPP] Purchasing power parities (PPP)
[PRINCIPAL] School principals
[PRIVFLOW] Private flows
[PRIVPENSIONASSET] Private pension assets
[PROTECTEDAREA] Protected areas
[PRYENRGSUPPLY] Primary energy supply
[PUBEXPINCAPACITY] Public spending on incapacity
[PUBLMPEXP] Public spending on labour markets
[PUBUNEMPEXP] Public unemployment spending
[QGDP] Quarterly GDP
[RADIOEQT] Radiotherapy equipment
[REALGDPFORECAST] Real GDP forecast
[RENEWABLE] Renewable energy
[RESEARCHER] Researchers
[ROADACCID] Road accidents
[RUNBUSINESS] Running a business
[SAVING] Saving rate
[SELFEMP] Self-employment rate
[SELFEMPBYACTVTY] Self-employment by activity
[SELFEMPWEMP] Self-employed with employees
[SELFEMPWNOEMP] Self-employed without employees
[SELFEMPWTEREDU] Self-employed with tertiary education
[SHPRICE] Share prices
[SIGI] Social Institutions and Gender
[SMOKERS] Daily smokers
[SOCBENHH] Social benefits to households
[SOCEXP] Social spending
[SOCSUPPORT] Social support
[STARTBSNS] Starting a business
[STINT] Short-term interest rates
[STINTFORECAST] Short-term interest rates forecast
[STOCKFPOP] Stocks of foreign-born population in OECD countries
[STUDENT] Number of students
[STUDPERTEACHER] Students per teaching staff
[STUMOBILITY] International student mobility
[SUICIDE] Suicide rates
[TAXCORP] Tax on corporate profits
[TAXENV] Environmental tax
[TAXGOODSERV] Tax on goods and services
[TAXINCOME] Tax on personal income
[TAXPAYROLL] Tax on payroll
[TAXPROPERTY] Tax on property
[TAXREV] Tax revenue
[TAXSS] Social security contributions
[TAXWEDGE] Tax wedge
[TEACHER] Teachers by age
[TEACHERSALARY] Teachers' salaries
[TEACHINGHR] Teaching hours
[TEACHINGSTAFF] Teaching staff
[TEMPEMP] Temporary employment
[TERMTRADE] Terms of trade
[THREATENED] Threatened species
[TOTFLOW] Total official and private flows
[TOUR_EMP] Tourism employment
[TOUR_FLOW] Tourism flows
[TOUR_GDP] Tourism GDP
[TOUR_REC_EXP] Tourism receipts and spending
[TRADEGOOD] Trade in goods
[TRADEGOODSERV] Trade in goods and services
[TRADEGOODSERVFORECAST] Trade in goods and services forecast
[TRADESERV] Trade in services
[TRUSTGOV] Trust in government
[ULC] Unit labour costs
[UNEMP] Unemployment rate by age group
[UNEMPEDU] Unemployment rates by education level
[UNEMPFORECAST] Unemployment rate forecast
[URBANPOP] Urban population by city size
[VAACTY] Value added by activity
[VAFINCORP] Value-added in financial corporations
[VAGEXP] Domestic value added in gross exports
[VANONFINCORP] Value-added in non-financial corporations
[VIOLWOMEN] Violence against women
[WAGEGAP] Gender wage gap
[WAGELEVEL] Wage levels
[WASTEMUN] Municipal waste
[WASTEWATERTREAT] Wastewater treatment
[WATERABST] Water withdrawals
[WIRELESSWIRED] Mobile broadband subscriptions
[WKGPOP] Working age population
[WOMENPOLVOICE] Women in politics
[WOMENTEACHER] Women teachers
[WORKEXPOV] Working hours needed to exit poverty
[YNGPOP] Young population
[YOUNGSELF] Young self-employed
[YOUTHUNEMP] Youth unemployment rate
[YRLIFELOST] Potential years of life lost
[0_17] 0-17 year-olds
[0_9_EMPLOYEE] 0-9 employees
[10_19_EMPLOYED] 10-19 persons employed
[10_49] 10-49 employees
[10_49_EMPLOYEE] 10-49 employees
[15MORE] 15 year-olds or more
[15_19] 15-19 year-olds
[15_19_MEN] 15-19 year-old men
[15_19_WOMEN] 15-19 year-old women
[15_24] 15-24 year-olds
[15_29] 15-29 year-olds
[15_29_MEN] 15-29 year-old men
[15_29_WOMEN] 15-29 year-old women
[15_64] 15-64 year-olds
[18_65] 18-65 year-olds
[1INCOMEQ] First income quartile
[1YEAR] After 1 year
[1_9_EMPLOYED] 1-9 persons employed
[20_24] 20-24 year-olds
[20_24_MEN] 20-24 year-old men
[20_24_WOMEN] 20-24 year-old women
[20_29_MEN] 20-29 year-old men
[20_29_WOMEN] 20-29 year-old women
[20_49_EMPLOYED] 20-49 persons employed
[250MORE] 250 employees or more
[250MORE_EMPLOYED] 250 or more persons employed
[250MORE_EMPLOYEE] 250 or more employees
[25_34] 25-34 year-olds
[25_34_MEN] 25-34 year-old men
[25_34_WOMEN] 25-34 year-old women
[25_54] 25-54 year-olds
[25_64] 25-64 years olds
[25_74] 25-74 year-olds
[2INCOMEQ] Second income quartile
[2MTH] After 2 months
[2YEAR] After 2 years
[3INCOMEQ] Third income quartile
[4INCOMEQ] Fourth income quartile
[50_249] 50-249 employees
[50_249_EMPLOYED] 50-249 persons employed
[50_249_EMPLOYEE] 50-249 employees
[55_64] 55-64 year-olds
[55_64_MEN] 55-64 year-old men
[55_64_WOMEN] 55-64 year-old women
[5YEAR] After 5 years
[65MORE] 65 year-olds or more
[66MORE] 66 year-olds or more
[67PC_AVEWAGE] Earning 67% of average wage
[6MTH] After 6 months
[ACCIDENTCASUAL] Accidents involving casualties
[ACCOUNT_MEN] Financial account holders - men
[ACCOUNT_WOMEN] Financial account holders - women
[ACC_NIGHTS] Tourist accommodation nights
[ACUTE] Acute care
[ADCT] Advanced developing countries and territories
[AFRICA] Africa
[AGE_17] 17 year-olds
[AGE_18] 18 year-olds
[AGE_19] 19 year-olds
[AGE_3] 3 year-olds
[AGE_4] 4 year-olds
[AGE_5] 5 year-olds
[AGR] Agriculture
[AGRFORTFISH] Agriculture, forestry, fishing
[AIR] Air
[ALLLEVEL] All levels
[ALLSIZE] All sizes
[AMERICA] Americas
[AMPLITUD] Amplitude adjusted
[AQUACULT] Aquaculture
[ARTS] Arts
[ASIA] Asia
[ATTITUDEVIOL] Attitudes towards violence
[ATTWORKMUM] Attitudes towards working mothers
[AVEWAGE] Earning average wage
[BACHR_MEN] Bachelor's or equivalent level, men
[BACHR_WOMEN] Bachelor's or equivalent level, women
[BEEF] Beef and veal
[BIRD] Birds
[BOY] Boys
[BSNSSERV] Business services
[BUPPSRY] Below upper secondary
[BUSINESS] Business
[CABLE] Cable
[CAN] Canada
[CHILDBIRTH] Childbirth
[CHN] China
[CO] Carbon monoxide (CO)
[CO2] Carbon dioxide (CO2)
[COAST] Coastal
[COMPEMPLOYEE] Compensation of employees
[COMPULSORY] Government/compulsory
[CONSTR] Construction
[CORP] Corporate
[COUPL2CHLD] Couple, 2 children
[COUPLNOCHLD] Couple, no child
[COUPL_67PC_AVEWAGE] Couple, 67% of average wage
[COUPL_AVEWAGE] Couple, average wage
[COUPL_MINWAGE] Couple, minimum wage
[CROPLAND] Arable and permanent cropland
[CSE] Consumer support (CSE)
[CULTASSET] Biological resources
[CURDEP] Currency and deposits
[CURRENTMEN] Current state, men
[CURRENTWOMEN] Current state, women
[DEATH] Deaths
[DEBTRELIEF] Debt relief
[DEF] Defence
[DEU] Germany
[DISCRIMFAMCODE] Discrimination in the family
[DISTRIB] Distribution
[DOCTL_MEN] Doctoral or equivalent level, men
[DOCTL_WOMEN] Doctoral or equivalent level, women
[DOMESTIC] Manufacturing, domestic market
[DSL]
[DTP] Diphtheria, tetanus, pertussis
[DWELLING] Dwellings
[EARLYCHILDEDU] Early childhood education
[EARLYCHILDEDU_15YREXP] Early childhood education, 15 years' experience
[EARLYCHILDEDU_START] Early childhood education, start
[EARLYCHILDEDU_TOP] Early childhood education, top of scale
[EARMARRIAGE] Child marriage
[ECOAFF] Economic affairs
[ECOINFRA] Economic infrastructure
[EDU] Education
[ELECGAS] Electricity, gas etc
[ELECTRICITY] Electricity
[EMP] By persons employed
[EMPINCENTIVE] Employment incentives
[EMPLOYEE] Employees
[ENGINEERING] Engineering
[ENRG] Energy
[ENVPROT] Environmental protection
[EUROPE] Europe
[EXCLUSOLIDBIO] Total excluding solid biofuels
[EXP] Exports
[EXPMRKTGRWTH] Export market growth
[EXPOS2PM25] Exposure to PM2.5
[FAM] Family
[FAMWORKR] Family accompanying workers
[FIBRE] Fibre/LAN
[FINAN] Financial
[FINANCEINS] Finance and insurance
[FINANSERV] Financial services
[FIXASSET] Intellectual property products
[FOOD] Food
[FRA] France
[FREEMOVS] Free movements
[FUTUREMEN] Future outlook, men
[FUTUREWOMEN] Future outlook, women
[GBR] United Kingdom
[GG] General government
[GHG] Greenhouse gas (GHG)
[GINI] Gini coefficient
[GIRL] Girls
[GOVTRANSF] Including government transfers
[GRALPUBSER] General public services
[GROSS] Gross
[GROSSADJ] Gross, incl. social transfers in kind
[GROSSINCREASE] Gross increase
[GSSE] General services support (GSSE)
[GSUSE] Goods and services used
[HEALTH] Health
[HH] Household
[HOUCOMM] Housing and community amenities
[HOUSING] Housing
[HPAY] High pay
[HRWKD] By hours worked
[HTELREST] Hotels and restaurants
[HUMAID] Humanitarian aid
[HUMNTRN] Humanitarian
[IMP] Imports
[INAMBULATORY] In ambulatory care providers
[INCASH] In cash
[INCENTIVE] Start-up incentives
[INDIVIDUAL] Individual
[INDUSCONSTR] Industry including construction
[INDUSENRG] Industry, including energy
[INDUSTRY] Industry
[INFCOMM] Information, communication
[INHOSPITAL] In hospitals
[INJURE] Injuries
[INKIND] In kind
[INLAND] Inland total
[INLANDWATER] Inland waterways
[INT-EXP] International spending
[INTER_ARR] International arrivals
[INTER_DEP] International departures
[INTMD] Intermediate regions
[INT_REC] International receipts
[INWARD] Inward
[ITA] Italy
[JOBCREATION] Direct job creation
[JPN] Japan
[LAWDOMVIOL] Laws on domestic violence
[LDC] Least developed countries
[LIFEINSRSV] Life insurance reserves
[LMETROP] Large metropolitan areas
[LMIC] Lower middle-income countries
[LOWSRY] Lower secondary
[LOWSRY_15YREXP] Lower secondary,15 years' experience
[LOWSRY_AVGAGE] Lower secondary, average age
[LOWSRY_START] Lower secondary, starting
[LOWSRY_TOP] Lower secondary, top of scale
[LOWSRY_WOMEN] Lower secondary, women
[LOWSRY_WORK] Lower secondary, work experience
[LPAY] Low pay
[LPRDTY] Labour productivity
[LUTILISATION] Labour utilisation
[MAIZE] Maize
[MAMMAL] Mammals
[MANUFACTURE_MEN] Manufacturing: Men
[MANUFACTURE_WOMEN] Manufacturing: Women
[MARINE] Marine
[MARINECAPT] Sea fishing
[MEASLES] Measles
[MEASURED] Measured
[MEDIA] Media
[MEN] Men
[METROP] Metropolitan areas
[MFG] Manufacturing
[MFSH] Mutual fund shares
[MIDDLE_AGED] Middle-aged
[MINEQUARR] Mining and quarrying
[MINISTERWOMEN] Women in cabinet ministerial positions
[MINWAGE] Earning minimum wage
[MKTPROC] Marketing and processing
[MONEY_MEN] Borrowing needed, men
[MONEY_WOMEN] Borrowing needed, women
[MORTALITY] Mortality
[MSTR_MEN] Master's or equivalent level, men
[MSTR_WOMEN] Master's or equivalent level, women
[MULTISEC] Multisector
[MURBAN] Medium-sized urban areas
[NET] Net
[NETBALANCE] Net balance
[NETOPERATING] Net operating surplus
[NITROGEN] Nitrogen
[NLD] National landings in domestic ports
[NLF] National landings in foreign ports
[NOMINAL] Nominal house prices
[NONNRGMAT] Non-energy materials
[NOX] Nitrogen oxides (NOx)
[NTRADE] Net trade
[NUCLEAR] Nuclear
[OCEANIA] Oceania
[ODAFLOWS] ODA flows basis
[ODAGRANT] ODA grant equivalent
[OLD] Old
[OOPEXP] Out-of-pocket
[OOWORKINCOME] Out-of-work income maintenance and support
[ORGANIC] Organic farmland
[OTH] Other
[OTHBUILDING] Other buildings and structures
[OTHLIC] Other low income countries
[OTHMACHINEQT] Information and communication technology
[OTHPRIVENT] Other private entities
[OTHSERVACT] Other services activities
[OUTWARD] Outward
[P50P10] Interdecile P50/P10
[P90P10] Interdecile P90/P10
[P90P50] Interdecile P90/P50
[PALMA] Palma ratio
[PASTURE] Permanent pasture
[PENSIONF] Pension funds
[PHOSPHORUS] Phosphorus
[PIG] Pork meat
[PLANT] Plants
[POL] Pollution
[POLREPRES] Women parliamentarians
[POULTRY] Poultry meat
[PRERET] Early retirement
[PREVVIOLLIFETIME] Prevalence in the lifetime
[PRICEINCOME] Price to income ratio
[PRICERENT] Price to rent ratio
[PRIMSECT] Primary sector
[PRIV] Private
[PROD] Production
[PROGASSIST] Programme assistance
[PROSCISUPP] Professional, scientific, support services
[PRY] Primary
[PRY15YREXP] Primary, 15 years' experience
[PRY_30_39] Primary, 30-39 years
[PRY_40_49] Primary, 40-49 years
[PRY_50_OVER] Primary, 50 years and over
[PRY_LT30] Primary, under 30 years
[PRY_NTRY] Primary to post-secondary non-tertiary
[PRY_START] Primary, starting
[PRY_TOP] Primary, top of scale
[PRY_TRY] Primary to tertiary
[PSE] Producer support (PSE)
[PSYCHIATRIC] Psychiatric care
[PUB] Public
[PUBADMINEDUSOC] Public administration, defence, education, health, social work
[PUBEMPSERV] Public employment services and administration
[PUBNET] Public net
[PUBORD] Public order and safety
[P_SRY_NTRY] Post-secondary non-tertiary
[P_SRY_NTRY_MEN] Post-secondary non-tertiary, men
[P_SRY_NTRY_WOMEN] Post-secondary non-tertiary, women
[RAIL] Rail
[REAL] Real house prices
[REALEST] Real estate
[REALRENTBSNS] Real estate, renting and business services
[RECULTREL] Recreation, culture and religion
[RENT] Rent price
[RES] Resources
[RESTRCIVLIB] Restricted civil liberties
[RESTRPHYSINTEG] Restricted physical integrity
[RESTRRESASSETS] Restricted access to resources and assets
[RETAILTRADE] Retail trade
[RICE] Rice
[ROAD] Road
[RURAL] Rural regions
[S80S20] S80/S20 quintile share
[SEA] Sea
[SECOTHSH] Securities other than shares
[SELFEMPLOYED] Self-employed
[SELFREPORTED] Self-reported
[SERV] Services
[SERVICE_MEN] Services : Men
[SERVICE_WOMEN] Services : Women
[SHEEP] Sheep meat
[SHOTHEQTY] Shares and other equity
[SNGL2CHLD] Single, 2 children
[SNGLNOCHLD] Single, no child
[SNGL_67PC_AVEWAGE] Single, 67% of average wage
[SOCIETY] Collective
[SOCINFRA] Social infrastructure
[SOCPROT] Social protection
[SOC_SCI] Social sciences
[SOX] Sulphur oxides (SOx)
[SOYBEAN] Soybean
[SRY] Secondary
[SRY_30_39] Secondary, 30-39 years
[SRY_40_49] Secondary, 40-49 years
[SRY_50_OVER] Secondary, 50 years and over
[SRY_LT30] Secondary, under 30 years
[SUPPEMP] Sheltered and supported employment and rehabilitation
[SURBAN] Small urban areas
[TELECOMMS] Telecommunications
[TERREST] Terrestrial
[TOT] Total
[TOTMAT] Total materials
[TOTNET] Total net
[TOT_FOODENRG] Total less food, less energy
[TOT_MKT] Manufacturing, total market
[TRAINING] Training
[TRANSG_CROPLAND] Transgenic cropland
[TRANSPCOM] Transport, storage and communications
[TRANSPEQT] Transport equipment
[TRANSPORT] Transport
[TREEFELLING] Tree fellings
[TRY] Tertiary
[TRY_30_39] Tertiary, 30-39 years
[TRY_40_49] Tertiary, 40-49 years
[TRY_50_OVER] Tertiary, 50 years and over
[TRY_INFLOW] Tertiary student inflow
[TRY_LT30] Tertiary, under 30 years
[TRY_MEN] Tertiary, men
[TRY_WOMEN] Tertiary, women
[TSE] Total support (TSE)
[UMIC] Upper middle-income countries
[UNALLOCATED] Unallocated
[UNEMP_COUPL2CHLD] Jobless couple, 2 children
[UNEMP_COUPLNOCHLD] Jobless couple, no child
[UNSPECIFIED] Unspecified
[UPPSRY] Upper secondary
[UPPSRY_15YREXP] Upper secondary,15 years' experience
[UPPSRY_MEN] Upper secondary, men
[UPPSRY_NTRY] Upper secondary, non-tertiary
[UPPSRY_START] Upper secondary, starting
[UPPSRY_TOP] Upper secondary, top of scale
[UPPSRY_WOMEN] Upper secondary, women
[URBAN] Urban regions
[USA] United States
[USEINTENSITY] Intensity of use
[VEGEGAIN1992] Vegetation gain since 1992
[VEGEGAIN2004] Vegetation gain since 2004
[VEGELOSS1992] Vegetation loss since 1992
[VEGELOSS2004] Vegetation loss since 2004
[VOC] Volatile organic compounds (VOC)
[VOLIDX] Volume index
[VOLUNTARY] Voluntary
[WATERSUPP] Water supply and waste management
[WHEAT] Wheat
[WHLEHTELTRANSP] Wholesale, retail trade, repairs, transport; accommodation, food services
[WHLETRADE] Wholesale trade
[WLD] World
[WOMEN] Women
[WORK] Work
[YOUNG] Young
[1000000HAB] Per 1 000 000 inhabitants
[1000000VEH] Per 1 000 000 vehicles
[100000HAB] Per 100 000 inhabitants
[100000HAB_0_69] Per 100 000 inhabitants aged 0-69
[100000PER] Per 100 000 persons
[1000BIRTH] Per 1 000 live births
[1000EMPLOYED] Per 1 000 employed
[1000HAB] Per 1 000 inhabitants
[100HAB] Per 100 inhabitants
[AGRWTH] Annual growth rate (%)
[BLN_USD] Billion US dollars
[CAP] Per capita
[CHD_WOMAN] Children/woman
[COINVENTION] Co-inventions
[DAY] Days
[DEATH_1000BIRTH] Deaths/1 000 live births
[EUR] Euro
[GROSSABSTRACTIONPCTOTALRR] Gross abstractions as percentage of total renewable resources
[GWH] Gigawatt-hours
[HEADCOUNT] Headcount
[HR_67PC_AVEWAGE] Hours at 67% average wage
[HR_AVEWAGE] Hours at average wage
[HR_MINWAGE] Hours at minimum wage
[HR_WKD] Hours/worker
[HR_YEAR] Hours per year
[IDX] Index
[IDX2010] 2010=100
[IDX2015] 2015=100
[INEQ] 0 = complete equality; 1 = complete inequality
[INVENTION] Inventions
[KG_CAP] Kilograms/capita
[KG_CO2USD] Kilograms of CO2/USD
[KG_HA] Kilograms/hectare
[KTOE] Thousand toe
[LTRENDIDX] Long-term average = 100
[LT_CAP15] Litres/capita (aged 15 and over)
[M3CAP] m3/capita
[MEANSCORE] Mean score
[MICGRCUBM] Micrograms per cubic metre
[MLN_EUR] Million Euros
[MLN_M3] Million m3
[MLN_PER] Million persons
[MLN_PKM] Million passenger-kilometres
[MLN_SDR] SDR millions
[MLN_TOE] Million toe
[MLN_TONNE] Million tonnes
[MLN_TONNEKM] Million tonne-kilometres
[MLN_USD] Million US dollars
[MULTAGEARN] Multiple of annual gross earnings
[NATUSD] National currency units/US dollar
[NBR] Number
[OECDIDX] OECD=100
[PC] Percentage
[PC_25_64] % of 25-64 year-olds
[PC_AGE] % in same age group
[PC_AGRCONSUMP] % of agricultural consumption
[PC_AGRSUPP] % of total agricultural support
[PC_AVEWAGE] % of average wage
[PC_CHGPP] Percentage change, previous period
[PC_CHGPPCAP] Per capita, percentage change, previous period
[PC_CHGPY] Percentage change, same period previous year
[PC_CHILD] % of children
[PC_DEPEMP] % of dependent employment
[PC_DI] % of disposable income
[PC_EARN] % of earnings
[PC_EDUEXP] % of education spending
[PC_EMP] % of employment
[PC_ENRGGEN] % of total energy generation
[PC_FBORNLF] % of foreign-born labour force
[PC_FBORNPOP] % of foreign-born population
[PC_FDI] % of total FDI
[PC_GDP] % of GDP
[PC_GEXP] % of gross exports
[PC_GFARM] % of gross farm receipts
[PC_GFCF] % of GFCF
[PC_GNI] % of gross national income
[PC_GVA] % of gross value added
[PC_HEALTHXP] % of health spending
[PC_HH] % of all households
[PC_HHDI] % of household disposable income
[PC_HHFA] % of total financial assets
[PC_HI] % of household income
[PC_LANDAREA] % of total land area
[PC_LC] % of labour cost
[PC_LF] % of labour force
[PC_MDI] % of median disposable income
[PC_NATIONAL] % of national total
[PC_NBORNLF] % of native-born labour force
[PC_NBORNPOP] % of native-born population
[PC_NDI] % of net disposable income
[PC_NHHDI] % of household net disposable income
[PC_NVA] % of net value added
[PC_PA] % per annum
[PC_PISITIVEANS] % of positive answers
[PC_POP] % of population
[PC_POP15] % of population aged 15+
[PC_POP65] % of population aged 65+
[PC_PRERETEARN] % of pre-retirement earnings
[PC_PRINCIPAL] % of principals
[PC_PRYENRGSUPPLY] % of primary energy supply
[PC_PWI] % of previous in-work income
[PC_RESEARCHER] % of total researchers
[PC_SELFEMP] % of self-employed
[PC_SPECIES] % of known species
[PC_STUD_ENRL] % of students enrolled
[PC_TEACHER] % of teachers
[PC_TOTEMP] % of total employed
[PC_TOTINVENTORS] % of total inventors
[PC_TOT_TAX] % of taxation
[PC_UNEMP] % of unemployed
[PC_VA] % of value added
[PC_WATER] % of Exclusive Economic Zones
[PC_WKGPOP] % of working age population
[PC_YOUTHLF] % of youth labour force
[PER] Persons
[QGRWTH] Quarterly growth rate (%)
[RESTR] 0 = open; 1 = closed
[RT] Ratio
[SQM_CAP] Square metres per capita
[TFEU] Twenty Foot Equivalent Unit
[THND_HA] Thousand hectares
[THND_M3] Thousand m3
[THND_PER] Thousand persons
[THND_TONNE] Thousand tonnes
[THND_TONNECO2] Thousand tonnes CO2-eq
[THND_USD_CAP] Thousand US dollars/capita
[TOE_1000USD] Toe/1 000 US dollars
[TONNE] Tonnes
[TONNE_CAP] Tonnes/capita
[TONNE_HA] Tonnes/hectare
[USD] US dollars
[USD_BAR] US dollars/barrel
[USD_CAP] US dollars/capita
[USD_KG] US dollars/kilogram
[USD_STUDENT] US dollars/student
[YR] Years
[A] Annual
[M] Monthly
[Q] Quarterly
Search filters
Country [LOCATION] (189)
Indicator [INDICATOR] (295)
Subject [SUBJECT] (392)
Measure [MEASURE] (136)
Frequency [FREQUENCY] (3)
This dataset has 54,220 series:
[AFG.BUILT_UP.TOT.SQM_CAP.A] Afghanistan – Built-up area – Total – Square metres per capita – Annual
- from
- 1975=12.212
- to
- 2014=15.764
- min:
- 12.212
- max:
- 19.135
- avg:
- 16.113
- σ:
- 2.548
[AFG.DISCRIMFAMCODE.EARMARRIAGE.PC.A] Afghanistan – Discrimination in the family – Child marriage – Percentage – Annual
- from
- 2014=0.17
- to
- 2023=16.3
- min:
- 0.17
- max:
- 35
- avg:
- 17.157
- σ:
- 14.232
[AFG.LANDCOVER.VEGEGAIN1992.PC.A] Afghanistan – Land cover change – Vegetation gain since 1992 – Percentage – Annual
- from
- 2004=2.82
- to
- 2019=4.37
- min:
- 2.82
- max:
- 4.37
- avg:
- 3.595
- σ:
- 0.775
[AFG.LANDCOVER.VEGEGAIN2004.PC.A] Afghanistan – Land cover change – Vegetation gain since 2004 – Percentage – Annual
- from
- 2019=1.61
- to
- 2019=1.61
- min:
- 1.61
- max:
- 1.61
- avg:
- 1.61
- σ:
- 0
[AFG.LANDCOVER.VEGELOSS1992.PC.A] Afghanistan – Land cover change – Vegetation loss since 1992 – Percentage – Annual
- from
- 2004=1.82
- to
- 2019=2.52
- min:
- 1.82
- max:
- 2.52
- avg:
- 2.17
- σ:
- 0.35
[AFG.LANDCOVER.VEGELOSS2004.PC.A] Afghanistan – Land cover change – Vegetation loss since 2004 – Percentage – Annual
- from
- 2019=0.78
- to
- 2019=0.78
- min:
- 0.78
- max:
- 0.78
- avg:
- 0.78
- σ:
- 0
[AFG.MATCONSUMP.TOT.TONNE_CAP.A] Afghanistan – Material consumption – Total – Tonnes/capita – Annual
- from
- 1970=2.709
- to
- 2019=1.182
- min:
- 1.177
- max:
- 2.709
- avg:
- 1.814
- σ:
- 0.489
[AFG.MATPROD.NONNRGMAT.USD_KG.A] Afghanistan – Material productivity – Non-energy materials – US dollars/kilogram – Annual
- from
- 2002=0.92
- to
- 2019=1.87
- min:
- 0.92
- max:
- 1.87
- avg:
- 1.371
- σ:
- 0.302
[AFG.MATPROD.TOTMAT.USD_KG.A] Afghanistan – Material productivity – Total materials – US dollars/kilogram – Annual
- from
- 2002=0.91
- to
- 2019=1.776
- min:
- 0.91
- max:
- 1.776
- avg:
- 1.335
- σ:
- 0.278
[AFG.PATENT_ENV.TOT.PC.A] Afghanistan – Patents on environment technologies – Total – Percentage – Annual
- from
- 1967=100
- to
- 2019=100
- min:
- 33.4
- max:
- 100
- avg:
- 75.018
- σ:
- 27.613
Series code | 1967 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2023 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.BUILT_UP.TOT.SQM_CAP.A] | - | - | - | - | - | - | 12.212293831 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 19.135397806 | - | - | - | - | - | - | - | - | - | 17.34006473 | - | - | - | - | - | - | - | - | - | - | - | - | - | 15.763671417 | - | - | - | - | - | - |
[AFG.DISCRIMFAMCODE.EARMARRIAGE.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.17 | - | - | - | - | 35 | 16.3 |
[AFG.LANDCOVER.VEGEGAIN1992.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 2.82 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 4.37 | - |
[AFG.LANDCOVER.VEGEGAIN2004.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 1.61 | - |
[AFG.LANDCOVER.VEGELOSS1992.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 1.82 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 2.52 | - |
[AFG.LANDCOVER.VEGELOSS2004.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.78 | - |
[AFG.MATCONSUMP.TOT.TONNE_CAP.A] | - | 2.7085 | 2.6175 | 2.3868 | 2.4989 | 2.5534 | 2.6172 | 2.6505 | 2.4777 | 2.4502 | 2.3892 | 2.3102 | 2.345 | 2.3563 | 2.2686 | 2.2188 | 2.1138 | 1.9706 | 2.087 | 2.0046 | 1.8946 | 2.0595 | 2.1038 | 1.8012 | 1.6556 | 1.5368 | 1.5146 | 1.5011 | 1.5609 | 1.576 | 1.5141 | 1.2366 | 1.1771 | 1.4196 | 1.3985 | 1.2606 | 1.4334 | 1.2915 | 1.373 | 1.2406 | 1.4964 | 1.5323 | 1.4182 | 1.4574 | 1.4641 | 1.4342 | 1.356 | 1.3532 | 1.2249 | 1.222 | 1.1817 | - |
[AFG.MATPROD.NONNRGMAT.USD_KG.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.92 | 0.94 | 1.01 | 0.96 | 1.07 | 1.14 | 1.29 | 1.25 | 1.37 | 1.46 | 1.52 | 1.54 | 1.56 | 1.61 | 1.61 | 1.79 | 1.77 | 1.87 | - |
[AFG.MATPROD.TOTMAT.USD_KG.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.9103 | 0.9326 | 1.0088 | 0.9521 | 1.0682 | 1.1234 | 1.2665 | 1.23 | 1.3345 | 1.3955 | 1.47 | 1.4926 | 1.509 | 1.5694 | 1.5673 | 1.727 | 1.7018 | 1.7764 | - |
[AFG.PATENT_ENV.TOT.PC.A] | 100 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 66.67 | 33.4 | - | - | - | - | 100 | - |
Loading chart
Search filters
Country [LOCATION] (189)
Indicator [INDICATOR] (295)
Subject [SUBJECT] (392)
Measure [MEASURE] (136)
Frequency [FREQUENCY] (3)
This dataset has 54,220 series:
[AFG.BUILT_UP.TOT.SQM_CAP.A] Afghanistan – Built-up area – Total – Square metres per capita – Annual
- from
- 1975=12.212
- to
- 2014=15.764
- min:
- 12.212
- max:
- 19.135
- avg:
- 16.113
- σ:
- 2.548
[AFG.DISCRIMFAMCODE.EARMARRIAGE.PC.A] Afghanistan – Discrimination in the family – Child marriage – Percentage – Annual
- from
- 2014=0.17
- to
- 2023=16.3
- min:
- 0.17
- max:
- 35
- avg:
- 17.157
- σ:
- 14.232
[AFG.LANDCOVER.VEGEGAIN1992.PC.A] Afghanistan – Land cover change – Vegetation gain since 1992 – Percentage – Annual
- from
- 2004=2.82
- to
- 2019=4.37
- min:
- 2.82
- max:
- 4.37
- avg:
- 3.595
- σ:
- 0.775
[AFG.LANDCOVER.VEGEGAIN2004.PC.A] Afghanistan – Land cover change – Vegetation gain since 2004 – Percentage – Annual
- from
- 2019=1.61
- to
- 2019=1.61
- min:
- 1.61
- max:
- 1.61
- avg:
- 1.61
- σ:
- 0
[AFG.LANDCOVER.VEGELOSS1992.PC.A] Afghanistan – Land cover change – Vegetation loss since 1992 – Percentage – Annual
- from
- 2004=1.82
- to
- 2019=2.52
- min:
- 1.82
- max:
- 2.52
- avg:
- 2.17
- σ:
- 0.35
[AFG.LANDCOVER.VEGELOSS2004.PC.A] Afghanistan – Land cover change – Vegetation loss since 2004 – Percentage – Annual
- from
- 2019=0.78
- to
- 2019=0.78
- min:
- 0.78
- max:
- 0.78
- avg:
- 0.78
- σ:
- 0
[AFG.MATCONSUMP.TOT.TONNE_CAP.A] Afghanistan – Material consumption – Total – Tonnes/capita – Annual
- from
- 1970=2.709
- to
- 2019=1.182
- min:
- 1.177
- max:
- 2.709
- avg:
- 1.814
- σ:
- 0.489
[AFG.MATPROD.NONNRGMAT.USD_KG.A] Afghanistan – Material productivity – Non-energy materials – US dollars/kilogram – Annual
- from
- 2002=0.92
- to
- 2019=1.87
- min:
- 0.92
- max:
- 1.87
- avg:
- 1.371
- σ:
- 0.302
[AFG.MATPROD.TOTMAT.USD_KG.A] Afghanistan – Material productivity – Total materials – US dollars/kilogram – Annual
- from
- 2002=0.91
- to
- 2019=1.776
- min:
- 0.91
- max:
- 1.776
- avg:
- 1.335
- σ:
- 0.278
[AFG.PATENT_ENV.TOT.PC.A] Afghanistan – Patents on environment technologies – Total – Percentage – Annual
- from
- 1967=100
- to
- 2019=100
- min:
- 33.4
- max:
- 100
- avg:
- 75.018
- σ:
- 27.613
Series code | 1967 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2023 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.BUILT_UP.TOT.SQM_CAP.A] | - | - | - | - | - | - | 12.212293831 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 19.135397806 | - | - | - | - | - | - | - | - | - | 17.34006473 | - | - | - | - | - | - | - | - | - | - | - | - | - | 15.763671417 | - | - | - | - | - | - |
[AFG.DISCRIMFAMCODE.EARMARRIAGE.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.17 | - | - | - | - | 35 | 16.3 |
[AFG.LANDCOVER.VEGEGAIN1992.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 2.82 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 4.37 | - |
[AFG.LANDCOVER.VEGEGAIN2004.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 1.61 | - |
[AFG.LANDCOVER.VEGELOSS1992.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 1.82 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 2.52 | - |
[AFG.LANDCOVER.VEGELOSS2004.PC.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.78 | - |
[AFG.MATCONSUMP.TOT.TONNE_CAP.A] | - | 2.7085 | 2.6175 | 2.3868 | 2.4989 | 2.5534 | 2.6172 | 2.6505 | 2.4777 | 2.4502 | 2.3892 | 2.3102 | 2.345 | 2.3563 | 2.2686 | 2.2188 | 2.1138 | 1.9706 | 2.087 | 2.0046 | 1.8946 | 2.0595 | 2.1038 | 1.8012 | 1.6556 | 1.5368 | 1.5146 | 1.5011 | 1.5609 | 1.576 | 1.5141 | 1.2366 | 1.1771 | 1.4196 | 1.3985 | 1.2606 | 1.4334 | 1.2915 | 1.373 | 1.2406 | 1.4964 | 1.5323 | 1.4182 | 1.4574 | 1.4641 | 1.4342 | 1.356 | 1.3532 | 1.2249 | 1.222 | 1.1817 | - |
[AFG.MATPROD.NONNRGMAT.USD_KG.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.92 | 0.94 | 1.01 | 0.96 | 1.07 | 1.14 | 1.29 | 1.25 | 1.37 | 1.46 | 1.52 | 1.54 | 1.56 | 1.61 | 1.61 | 1.79 | 1.77 | 1.87 | - |
[AFG.MATPROD.TOTMAT.USD_KG.A] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.9103 | 0.9326 | 1.0088 | 0.9521 | 1.0682 | 1.1234 | 1.2665 | 1.23 | 1.3345 | 1.3955 | 1.47 | 1.4926 | 1.509 | 1.5694 | 1.5673 | 1.727 | 1.7018 | 1.7764 | - |
[AFG.PATENT_ENV.TOT.PC.A] | 100 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 66.67 | 33.4 | - | - | - | - | 100 | - |
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