Monthly food price estimates by product and market
36 countries, 2331 markets, 2007/01/01-2024/12/01, version 2024/12/02
Afghanistan, Armenia, Burundi...and 33 more, 2007 - 2024
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WLD_2021_RTFP_v02_M
Monthly food price estimates by product and market
36 countries, 2331 markets, 2007/01/01-2024/12/01, version 2024/12/02
Real Time Food Prices
| Name | Country code |
|---|---|
| Afghanistan | AFG |
| Armenia | ARM |
| Burundi | BDI |
| Burkina Faso | BFA |
| Bangladesh | BGD |
| Central African Republic | CAF |
| Cameroon | CMR |
| Congo, Dem. Rep. | COD |
| Congo, Rep. | COG |
| Guinea | GIN |
| Gambia, The | GMB |
| Guinea-Bissau | GNB |
| Haiti | HTI |
| Indonesia | IDN |
| Iraq | IRQ |
| Kenya | KEN |
| Lao PDR | LAO |
| Lebanon | LBN |
| Liberia | LBR |
| Libya | LBY |
| Sri Lanka | LKA |
| Mali | MLI |
| Myanmar | MMR |
| Mozambique | MOZ |
| Mauritania | MRT |
| Malawi | MWI |
| Niger | NER |
| Nigeria | NGA |
| Philippines | PHL |
| Sudan | SDN |
| Senegal | SEN |
| Somalia | SOM |
| South Sudan | SSD |
| Syrian Arab Republic | SYR |
| Chad | TCD |
| Yemen, Rep. | YEM |
Monthly food price estimates in fragile countries
Real Time Prices (RTP) is a live dataset compiled and updated weekly by the World Bank Development Economics Data Group (DECDG) using a combination of direct price measurement and Machine Learning estimation of missing price data. The historical and current estimates are based on price information gathered from the World Food Program (WFP), UN-Food and Agricultural Organization (FAO), select National Statistical Offices, and are continually updated and revised as more price information becomes available. Real-time exchange rate data used in this process are from official and public sources.
RTP consists of three sub-series, Real Time Food Prices (RTFP) includes prices on a variety of food items that primarily include country-specific staple foods, Real Time Energy Prices (RTEP) includes fuel prices, and Real Time Exchange Rates (RTFX) and includes unofficial exchange rate estimates as well as possible other unofficial deflators.
- RTFP: https://microdata.worldbank.org/index.php/catalog/study/WLD_2021_RTFP_v02_M
- RTEP: https://microdata.worldbank.org/index.php/catalog/study/WLD_2023_RTEP_v01_M
- RTFX: https://microdata.worldbank.org/index.php/catalog/study/WLD_2023_RTFX_v01_M
To produce smooth price series, outliers in the data are often adjusted using non-parametric density estimation and other techniques. Generalized Auto-Regressive Conditional Heteroskedasticity models are used to estimate intra-month price ranges. These models allow for excess kurtosis using a Generalized Error Distribution (GED). Open, High, Low, and Close price estimates are provided based on the modeled time-varying price distributions.
Data are produced from 2007 to the present and estimates are given for individual commodity items at geo-referenced market locations. Predicted data for missing entries are based on exchange rates, and price data available either at other market locations or from related price items.
RTP estimates of historical and current prices may serve as proxies for sub-national price inflation series or substitute national-level Consumer Price Inflation (CPI) indicators when complete information is unavailable. Therefore, RTP data may differ from other sources with official data, including the World Bank’s International Comparison Program (ICP) or inflation series reported in the World Development Indicators.
The following datasets are part of this sub-series:
Country-level inflation:
Market-level estimates:
- All countries: https://microdata.worldbank.org/index.php/catalog/study/WLD_2021_RTFP_v02_M
- Afghanistan: https://microdata.worldbank.org/index.php/catalog/study/AFG_2021_RTFP_v02_M
- Armenia: https://microdata.worldbank.org/index.php/catalog/study/ARM_2021_RTFP_v02_M
- Bangladesh: https://microdata.worldbank.org/index.php/catalog/study/BGD_2021_RTFP_v02_M
- Burkina Faso: https://microdata.worldbank.org/index.php/catalog/study/BFA_2021_RTFP_v02_M
- Burundi: https://microdata.worldbank.org/index.php/catalog/study/BDI_2021_RTFP_v02_M
- Cameroon: https://microdata.worldbank.org/index.php/catalog/study/CMR_2021_RTFP_v02_M
- Central African Republic: https://microdata.worldbank.org/index.php/catalog/study/CAF_2021_RTFP_v02_M
- Chad: https://microdata.worldbank.org/index.php/catalog/study/TCD_2021_RTFP_v02_M
- Congo, Dem. Rep.: https://microdata.worldbank.org/index.php/catalog/study/COD_2021_RTFP_v02_M
- Congo, Rep.: https://microdata.worldbank.org/index.php/catalog/study/COG_2021_RTFP_v02_M
- Gambia, The: https://microdata.worldbank.org/index.php/catalog/study/GMB_2021_RTFP_v02_M
- Guinea: https://microdata.worldbank.org/index.php/catalog/study/GIN_2021_RTFP_v02_M
- Guinea-Bissau: https://microdata.worldbank.org/index.php/catalog/study/GNB_2021_RTFP_v02_M
- Haiti: https://microdata.worldbank.org/index.php/catalog/study/HTI_2021_RTFP_v02_M
- Indonesia: https://microdata.worldbank.org/index.php/catalog/study/IDN_2021_RTFP_v02_M
- Iraq: https://microdata.worldbank.org/index.php/catalog/study/IRQ_2021_RTFP_v02_M
- Kenya: https://microdata.worldbank.org/index.php/catalog/study/KEN_2021_RTFP_v02_M
- Lao PDR: https://microdata.worldbank.org/index.php/catalog/study/LAO_2021_RTFP_v02_M
- Lebanon: https://microdata.worldbank.org/index.php/catalog/study/LBN_2021_RTFP_v02_M
- Liberia: https://microdata.worldbank.org/index.php/catalog/study/LBR_2021_RTFP_v02_M
- Libya: https://microdata.worldbank.org/index.php/catalog/study/LBY_2021_RTFP_v02_M
- Malawi: https://microdata.worldbank.org/index.php/catalog/study/MWI_2021_RTFP_v02_M
- Mali: https://microdata.worldbank.org/index.php/catalog/study/MLI_2021_RTFP_v02_M
- Mauritania: https://microdata.worldbank.org/index.php/catalog/study/MRT_2021_RTFP_v02_M
- Mozambique: https://microdata.worldbank.org/index.php/catalog/study/MOZ_2021_RTFP_v02_M
- Myanmar: https://microdata.worldbank.org/index.php/catalog/study/MMR_2021_RTFP_v02_M
- Niger: https://microdata.worldbank.org/index.php/catalog/study/NER_2021_RTFP_v02_M
- Nigeria: https://microdata.worldbank.org/index.php/catalog/study/NGA_2021_RTFP_v02_M
- Philippines: https://microdata.worldbank.org/index.php/catalog/study/PHL_2021_RTFP_v02_M
- Senegal: https://microdata.worldbank.org/index.php/catalog/study/SEN_2021_RTFP_v02_M
- Somalia: https://microdata.worldbank.org/index.php/catalog/study/SOM_2021_RTFP_v02_M
- South Sudan: https://microdata.worldbank.org/index.php/catalog/study/SSD_2021_RTFP_v02_M
- Sri Lanka: https://microdata.worldbank.org/index.php/catalog/study/LKA_2021_RTFP_v02_M
- Sudan: https://microdata.worldbank.org/index.php/catalog/study/SDN_2021_RTFP_v02_M
- Syrian Arab Republic: https://microdata.worldbank.org/index.php/catalog/study/SYR_2021_RTFP_v02_M
- Yemen, Rep.: https://microdata.worldbank.org/index.php/catalog/study/YEM_2021_RTFP_v02_M
| Type | Identifier |
|---|---|
| doi | https://doi.org/10.48529/2ZH0-JF55 |
| DOI | https://doi.org/10.48529/2ZH0-JF55 |
This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.
A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.
Version
2024/12/02
FCV Data Platform
Scope
List of food products included in estimates (not all products are included in country-level estimates): apples, bananas, beans, bread, bulgur, cabbage, carrots, cassava, cassava flour, cassava meal, cheese, chickpeas, chili, coffee instant, couscous, cowpeas, cucumbers, dates, eggs, fish, fish catfish, fish mackerel, fish sardine canned, fish tilapia, fish tuna canned, gari, garlic, groundnuts, lentils, livestock sheep two year old male, livestockgoat castrated male, livestocksheep castrated male, maize, maize flour, maize meal, meat beef, meat beef chops, meat beef minced, meat buffalo, meat chicken, meat chicken broiler, meat chicken plucked, meat chicken whole, meat goat, meat lamb, meat pork, milk, millet, oil, onions, oranges, parsley, pasta, peas, plantains, potatoes, pulses, rice, rice various, salt, sesame, sorghum, sorghum food aid, sugar, tea, tomatoes, tomatoes paste, wheat, wheat flour, yam, yogurt
Coverage
The data cover the following sub-national areas: Badakhshan, Badghis, Baghlan, Balkh, Bamyan, Daykundi, Farah, Faryab, Paktya, Ghazni, Ghor, Hilmand, Hirat, Nangarhar, Jawzjan, Kabul, Kandahar, Kapisa, Khost, Kunar, Kunduz, Laghman, Logar, Wardak, Nimroz, Nuristan, Paktika, Panjsher, Parwan, Samangan, Sar-e-pul, Takhar, Uruzgan, Zabul, Market Average, Lori, Ararat, Aragatsotn, Tavush, Gegharkunik, Shirak, Kotayk, Syunik, Armavir, Vayotz Dzor, Yerevan, Kayanza, Ruyigi, Bubanza, Karuzi, Bujumbura Mairie, Muramvya, Gitega, Rumonge, Bururi, Kirundo, Cankuzo, Cibitoke, Muyinga, Rutana, Bujumbura Rural, Makamba, Ngozi, Mwaro, SAHEL, CASCADES, SUD-OUEST, EST, BOUCLE DU MOUHOUN, CENTRE-NORD, PLATEAU-CENTRAL, HAUTS-BASSINS, CENTRE, NORD, CENTRE-SUD, CENTRE-OUEST, CENTRE-EST, Khulna, Chittagong, Barisal, Rajshahi, Dhaka, Rangpur, Sylhet, Mymensingh, Ouaka, Mbomou, Bangui, Nana-Mambéré, Ouham, Sangha-Mbaéré, Ombella M'Poko, Mambéré-Kadéï, Vakaga, Ouham Pendé, Lobaye, Haute-Kotto, Kémo, Nana-Gribizi, Bamingui-Bangoran, Haut-Mbomou, Nord, Extrême-Nord, Ouest, Nord-Ouest, Adamaoua, Sud-Ouest, Est, Littoral, Centre, Haut-Uele, Nord-Kivu, Ituri, Tshopo, Kwilu, Kasai, Sud-Kivu, Kongo-Central, Nord-Ubangi, Sud-Ubangi, Kasai-Central, Bas-Uele, Tanganyika, Lualaba, Kasai-Oriental, Kwango, Haut-Lomami, Haut-Katanga, Maniema, Kinshasa, Equateur, Lomami, Likouala, Brazzaville, Point-Noire, Pool, Bouenza, Cuvette, Lekoumou, Nzerekore, Boke, Kindia, Kankan, Faranah, Mamou, Labe, Kanifing Municipal Council, Central River, Upper River, West Coast, North Bank, Lower River, Bafata, Tombali, Cacheu, Sector Autonomo De Bissau, Biombo, Oio, Gabu, Bolama, Quinara, North, South, Artibonite, South-East, Grande'Anse, North-East, West, North-West, SULAWESI UTARA, SUMATERA UTARA, KALIMANTAN UTARA, JAWA BARAT, NUSA TENGGARA BARAT, NUSA TENGGARA TIMUR, SULAWESI SELATAN, JAMBI, JAWA TIMUR, KALIMANTAN SELATAN, BALI, BANTEN, JAWA TENGAH, RIAU, SUMATERA BARAT, KEPULAUAN RIAU, PAPUA, SULAWESI BARAT, BENGKULU, MALUKU UTARA, DAERAH ISTIMEWA YOGYAKARTA, KALIMANTAN BARAT, KALIMANTAN TENGAH, PAPUA BARAT, SUMATERA SELATAN, MALUKU, KEPULAUAN BANGKA BELITUNG, ACEH, DKI JAKARTA, SULAWESI TENGGARA, KALIMANTAN TIMUR, LAMPUNG, GORONTALO, SULAWESI TENGAH, Anbar, Babil, Baghdad, Basrah, Diyala, Dahuk, Erbil, Ninewa, Kerbala, Kirkuk, Missan, Muthanna, Najaf, Qadissiya, Salah al-Din, Sulaymaniyah, Thi-Qar, Wassit, Coast, North Eastern, Nairobi, Rift Valley, Eastern, Central, Nyanza, Attapeu, Bokeo, Bolikhamxai, Champasack, Houaphan, Khammouan, Louangphabang, Louangnamtha, Oudomxai, Phongsaly, Salavan, Savannakhet, Sekong, Vientiane Capital, Vientiane, Xaignabouly, Xiengkhouang, Akkar, Mount Lebanon, Baalbek-El Hermel, Beirut, Bekaa, El Nabatieh, Nimba, Grand Kru, Grand Cape Mount, Gbarpolu, Grand Bassa, Rivercess, Montserrado, River Gee, Lofa, Bong, Sinoe, Maryland, Margibi, Grand Gedeh, Bomi, East, North Central, Uva, Western, Sabaragamuwa, Southern, Northern, North Western, Kidal, Gao, Tombouctou, Bamako, Kayes, Koulikoro, Mopti, Segou, Sikasso, Yangon, Rakhine, Shan (North), Kayin, Kachin, Shan (South), Mon, Tanintharyi, Mandalay, Shan (East), Kayah, Chin, Magway, Sagaing, Zambezia, Cabo_Delgado, Tete, Manica, Sofala, Maputo, Gaza, Niassa, Inhambane, Maputo City, Nampula, Hodh Ech Chargi, Hodh El Gharbi, Brakna, Adrar, Assaba, Guidimakha, Gorgol, Trarza, Tagant, Dakhlet-Nouadhibou, Nouakchott, Tiris-Zemmour, Central Region, Southern Region, Northern Region, Tillaberi, Tahoua, Agadez, Zinder, Dosso, Niamey, Maradi, Diffa, Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Jigawa, Kebbi, Oyo, Zamfara, Lagos, Adamawa, Cordillera Administrative region, Region XIII, Region VI, Region V, Region III, Autonomous region in Muslim Mindanao, Region IV-A, Region VIII, Region VII, Region X, Region II, Region IV-B, Region XII, Region XI, Region I, National Capital region, Region IX, North Darfur, Blue Nile, Nile, Eastern Darfur, West Kordofan, Gedaref, West Darfur, North Kordofan, South Kordofan, Kassala, Khartoum, White Nile, South Darfur, Red Sea, Sennar, Al Gezira, Central Darfur, Tambacounda, Diourbel, Ziguinchor, Kaffrine, Dakar, Saint Louis, Fatick, Kolda, Louga, Kaolack, Kedougou, Matam, Thies, Sedhiou, Shabelle Hoose, Juba Hoose, Bay, Banadir, Shabelle Dhexe, Gedo, Hiraan, Woqooyi Galbeed, Awdal, Bari, Juba Dhexe, Togdheer, Nugaal, Galgaduud, Bakool, Sanaag, Mudug, Sool, , Warrap, Jonglei, Unity, Northern Bahr el Ghazal, Upper Nile, Central Equatoria, Western Bahr el Ghazal, Eastern Equatoria, Western Equatoria, Lakes, Aleppo, Dar'a, Quneitra, Homs, Deir-ez-Zor, Damascus, Ar-Raqqa, Al-Hasakeh, Hama, As-Sweida, Rural Damascus, Tartous, Idleb, Lattakia, Ouaddai, Salamat, Wadi Fira, Sila, Ennedi Est, Batha, Tibesti, Logone Oriental, Logone Occidental, Guera, Hadjer Lamis, Lac, Mayo Kebbi Est, Chari Baguirmi, Ennedi Ouest, Borkou, Tandjile, Mandoul, Moyen Chari, Mayo Kebbi Ouest, Kanem, Barh El Gazal, Ndjaména, Al Dhale'e, Aden, Al Bayda, Al Maharah, Lahj, Al Jawf, Raymah, Al Hudaydah, Hajjah, Amran, Shabwah, Dhamar, Ibb, Sana'a, Al Mahwit, Marib, Hadramaut, Sa'ada, Amanat Al Asimah, Socotra, Taizz, Abyan
Sub-national level, Admin 2 (selected)
Producers and sponsors
| Name | Affiliation |
|---|---|
| Bo Pieter Johannes Andrée | World Bank, Development Data Group (DECDG), Office of the Chief Statistician (DECCS) |
| Name | Grant number | Role |
|---|---|---|
| Foreign, Commonwealth & Development Office of the United Kingdom | Support to data analytics | |
| Foreign, Commonwealth & Development Office of the United Kingdom | KP-P174529-KMCE-TF0B4149 | Data documentation and dissemination (FCV Data Platform) |
| Department of Foreign Affairs and Trade of Australia | TF0B6892 | Support to methodological development in low data regions |
| Department of Foreign Affairs and Trade of Australia | TF0B6579 | Support to methodological development in low data regions |
| Federal Ministry for Economic Cooperation and Development of Germany as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund | TF073570 | Expansion of coverage and maintenance |
| Federal Ministry for Economic Cooperation and Development of Germany as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund | TF0C0728 | Expansion of coverage and maintenance |
| Name | Affiliation | Role |
|---|---|---|
| World Food Programme (WFP) | United Nations | Source of market price data |
| Food and Agriculture Organization (FAO) | United Nations | Source of market price data |
Data collection
| Start | End |
|---|---|
| 2007/01/01 | 2024/12/01 |
| Start date | End date |
|---|---|
| 2007/01/01 | 2024/12/01 |
| Data source | Origin of source | Characteristics |
|---|---|---|
| World Food Programme (WFP) | https://data.humdata.org/organization/wfp?vocab_Topics=prices | World Food Programme (WFP); data published in the Humanitarian Data Exchange (HDX) data catalog at https://data.humdata.org/ |
| Food and Agriculture Organization (FAO) | https://fpma.fao.org/giews/fpmat4/#/dashboard/tool/domestic | Local exchange rates and implied exchange rates data derived from commodity pairs published by FAO through the Food Price Monitoring and Analysis (FMPA) Tool |
Access policy
World Bank Microdata Library, FCV Collection
Data Access
| Name | Affiliation | URL |
|---|---|---|
| Data Help Desk | World Bank, Development Data Group | https://datahelpdesk.worldbank.org/ |
Please cite this dataset as follows: Andrée, B. P. J. (2021). Monthly food price estimates by product and market (Version 2024-12-02). WLD_2021_RTFP_v02_M. Washington, DC: World Bank Microdata Library. https://doi.org/10.48529/2ZH0-JF55
The estimates presented in this dataset are all based on publicly-available data.
The dataset of price estimates is published as open data.
Disclaimer and copyrights
The RTFP data and metadata provided are "as is" and "as available," and every effort is made to ensure their timeliness, accuracy, and completeness. When errors are discovered, they are corrected as appropriate and feasible. For details on the terms and conditions for usage of the RTFP database, please refer to the license details.
Citation
Additional metadata
| ISO | Country | Title | Unit | Food index weight | Data coverage | Imputation |
|---|---|---|---|---|---|---|
| AFG | Afghanistan | Bread | KG | 1 | 27.95% | 0.92 |
| AFG | Afghanistan | Exchange rate | USD/LCU | 0 | 27.55% | 1 |
| AFG | Afghanistan | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 34.21% | 0.92 |
| AFG | Afghanistan | Fuel (diesel) | L | 0 | 27.87% | 0.97 |
| AFG | Afghanistan | Rice (low quality) | KG | 1 | 36.13% | 0.9 |
| AFG | Afghanistan | Wage (non-qualified labour, non-agricultural) | Day | 0 | 24.39% | 0.96 |
| AFG | Afghanistan | Wage (qualified labour) | Day | 0 | 24.49% | 0.98 |
| AFG | Afghanistan | Wheat | KG | 1 | 36.04% | 0.94 |
| ARM | Armenia | Apples (red) | KG | 1 | 44.64% | 0.91 |
| ARM | Armenia | Bread (high grade flour) | KG | 1 | 44.77% | 0.99 |
| ARM | Armenia | Cabbage | KG | 1 | 44.77% | 0.94 |
| ARM | Armenia | Carrots | KG | 1 | 44.74% | 0.93 |
| ARM | Armenia | Cheese (dry) | KG | 1 | 44.51% | 0.99 |
| ARM | Armenia | Cucumbers (greenhouse) | KG | 1 | 44.67% | 0.88 |
| ARM | Armenia | Eggs | Unit | 12 | 44.97% | 0.99 |
| ARM | Armenia | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with CB) | USD/LCU | 0 | 100% | n/a |
| ARM | Armenia | Fish (fresh) | KG | 1 | 44.31% | 0.99 |
| ARM | Armenia | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 47.97% | 0.98 |
| ARM | Armenia | Fuel (diesel) | L | 0 | 42.68% | 0.99 |
| ARM | Armenia | Fuel (petrol-gasoline) | L | 0 | 45.36% | 0.99 |
| ARM | Armenia | Lentils | KG | 1 | 44.87% | 0.97 |
| ARM | Armenia | Meat (beef) | KG | 1 | 44.74% | 0.99 |
| ARM | Armenia | Meat (chicken) | KG | 1 | 44.25% | 0.99 |
| ARM | Armenia | Meat (pork) | KG | 1 | 44.74% | 0.99 |
| ARM | Armenia | Milk | L | 1 | 44.05% | 0.98 |
| ARM | Armenia | Oil (vegetable) | L | 1 | 44.84% | 0.98 |
| ARM | Armenia | Onions | KG | 1 | 44.77% | 0.95 |
| ARM | Armenia | Pasta | KG | 1 | 44.58% | 0.97 |
| ARM | Armenia | Potatoes | KG | 1 | 44.74% | 0.94 |
| ARM | Armenia | Rice (white) | KG | 1 | 46.73% | 0.98 |
| ARM | Armenia | Sugar | KG | 1 | 44.67% | 0.98 |
| ARM | Armenia | Tomatoes | KG | 1 | 44.74% | 0.9 |
| ARM | Armenia | Wheat flour | KG | 1 | 45.1% | 0.98 |
| BDI | Burundi | Bananas | KG | 1 | 35.15% | 0.9 |
| BDI | Burundi | Beans | KG | 1 | 40.27% | 0.9 |
| BDI | Burundi | Cassava flour | KG | 1 | 38.62% | 0.9 |
| BDI | Burundi | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| BDI | Burundi | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 37.43% | 0.91 |
| BDI | Burundi | Maize (white) | KG | 1 | 36.74% | 0.87 |
| BDI | Burundi | Maize flour | KG | 1 | 34.58% | 0.93 |
| BDI | Burundi | Meat (goat) | KG | 1 | 33.55% | 0.97 |
| BDI | Burundi | Onions | KG | 1 | 36.41% | 0.83 |
| BDI | Burundi | Sweet potatoes | KG | 1 | 40.27% | 0.86 |
| BDI | Burundi | Rice (low quality, local) | KG | 1 | 37.5% | 0.95 |
| BDI | Burundi | Tomatoes | KG | 1 | 36.16% | 0.83 |
| BFA | Burkina Faso | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| BFA | Burkina Faso | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 53.6% | 0.84 |
| BFA | Burkina Faso | Maize (white) | KG | 1 | 49.32% | 0.86 |
| BFA | Burkina Faso | Millet | KG | 1 | 56% | 0.84 |
| BFA | Burkina Faso | Sorghum (white) | KG | 1 | 52.98% | 0.83 |
| BGD | Bangladesh | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| BGD | Bangladesh | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 18.63% | 0.96 |
| BGD | Bangladesh | Lentils (masur) | KG | 1 | 16.81% | 0.96 |
| BGD | Bangladesh | Oil (palm) | L | 1 | 20.41% | 0.97 |
| BGD | Bangladesh | Rice (coarse) | KG | 1 | 15.73% | 0.96 |
| BGD | Bangladesh | Wheat flour | KG | 1 | 20.62% | 0.96 |
| CAF | Central African Republic | Cassava (cossette) | KG | 1 | 27.73% | 0.92 |
| CAF | Central African Republic | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| CAF | Central African Republic | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 26.23% | 0.91 |
| CAF | Central African Republic | Maize | KG | 1 | 24.53% | 0.86 |
| CAF | Central African Republic | Meat (beef) | KG | 1 | 25.9% | 0.95 |
| CAF | Central African Republic | Oil (palm) | L | 1 | 23.63% | 0.89 |
| CAF | Central African Republic | Rice | KG | 1 | 26.29% | 0.91 |
| CMR | Cameroon | Bananas | 12 KG | 0.0833 | 4.52% | 0.95 |
| CMR | Cameroon | Cassava (fresh) | 5 KG | 0.2 | 4.61% | 0.93 |
| CMR | Cameroon | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| CMR | Cameroon | Fish (mackerel, fresh) | KG | 1 | 11.51% | 0.94 |
| CMR | Cameroon | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 9.27% | 0.95 |
| CMR | Cameroon | Maize (white) | KG | 1 | 9.13% | 0.93 |
| CMR | Cameroon | Meat (beef) | KG | 1 | 13.69% | 0.97 |
| CMR | Cameroon | Oil (palm) | L | 1 | 12.22% | 0.93 |
| CMR | Cameroon | Rice (long grain, imported) | KG | 1 | 14.46% | 0.95 |
| CMR | Cameroon | Sorghum (red) | 100 KG | 0.01 | 4.53% | 0.98 |
| CMR | Cameroon | Wheat flour | KG | 1 | 7.79% | 0.96 |
| COD | Congo, Dem. Rep. | Beans | KG | 1 | 10.2% | 0.9 |
| COD | Congo, Dem. Rep. | Cassava flour | KG | 1 | 10.07% | 0.9 |
| COD | Congo, Dem. Rep. | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| COD | Congo, Dem. Rep. | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 9.07% | 0.91 |
| COD | Congo, Dem. Rep. | Maize | KG | 1 | 9.24% | 0.89 |
| COD | Congo, Dem. Rep. | Meat (beef) | KG | 1 | 6.8% | 0.97 |
| COD | Congo, Dem. Rep. | Oil (palm) | L | 1 | 10.09% | 0.88 |
| COD | Congo, Dem. Rep. | Plantains | KG | 1 | 7.79% | 0.88 |
| COD | Congo, Dem. Rep. | Rice (local) | KG | 1 | 9.14% | 0.9 |
| COD | Congo, Dem. Rep. | Sugar | KG | 1 | 8.8% | 0.92 |
| COG | Congo, Rep. | Beans (white) | KG | 1 | 28.1% | 0.87 |
| COG | Congo, Rep. | Cassava flour | KG | 1 | 25.38% | 0.83 |
| COG | Congo, Rep. | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| COG | Congo, Rep. | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 27.93% | 0.84 |
| COG | Congo, Rep. | Oil (vegetable) | L | 1 | 21.09% | 0.79 |
| COG | Congo, Rep. | Rice (mixed, low quality) | KG | 1 | 29.17% | 0.86 |
| GIN | Guinea | Beans (niebe, white) | KG | 1 | 26.65% | 0.87 |
| GIN | Guinea | Bread | Unit | 1 | 17.85% | 0.97 |
| GIN | Guinea | Cassava meal (gari) | KG | 1 | 22.15% | 0.86 |
| GIN | Guinea | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| GIN | Guinea | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 24.67% | 0.91 |
| GIN | Guinea | Maize | KG | 1 | 21.91% | 0.86 |
| GIN | Guinea | Meat (beef) | KG | 1 | 26.49% | 0.98 |
| GIN | Guinea | Oil (palm) | L | 1 | 29.52% | 0.92 |
| GIN | Guinea | Onions (imported) | KG | 1 | 14.28% | 0.81 |
| GIN | Guinea | Potatoes | KG | 1 | 23.11% | 0.88 |
| GIN | Guinea | Rice (local) | KG | 1 | 35.37% | 0.94 |
| GIN | Guinea | Salt | KG | 1 | 19.79% | 0.9 |
| GIN | Guinea | Sugar | KG | 1 | 24.55% | 0.94 |
| GIN | Guinea | Tomatoes | KG | 1 | 19.55% | 0.83 |
| GMB | Gambia, The | Apples (red) | KG | 1 | 22.59% | 0.94 |
| GMB | Gambia, The | Bananas | KG | 1 | 24.01% | 0.92 |
| GMB | Gambia, The | Beans (dry) | KG | 1 | 23.29% | 0.91 |
| GMB | Gambia, The | Bread | KG | 1 | 24.78% | 0.92 |
| GMB | Gambia, The | Cabbage | KG | 1 | 26.84% | 0.84 |
| GMB | Gambia, The | Carrots | KG | 1 | 26.8% | 0.86 |
| GMB | Gambia, The | Cassava | KG | 1 | 23.52% | 0.91 |
| GMB | Gambia, The | Coffee (instant) | Unit | 1 | 16.89% | 0.95 |
| GMB | Gambia, The | Eggs | Unit | 12 | 22.13% | 0.97 |
| GMB | Gambia, The | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| GMB | Gambia, The | Fish (bonga) | KG | 1 | 27.04% | 0.9 |
| GMB | Gambia, The | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 27.63% | 0.94 |
| GMB | Gambia, The | Fuel (diesel) | L | 0 | 26.96% | 0.97 |
| GMB | Gambia, The | Fuel (petrol-gasoline) | L | 0 | 27.06% | 0.97 |
| GMB | Gambia, The | Garlic | KG | 1 | 23.12% | 0.9 |
| GMB | Gambia, The | Groundnuts (shelled) | KG | 1 | 46.26% | 0.89 |
| GMB | Gambia, The | Maize | KG | 1 | 25.89% | 0.91 |
| GMB | Gambia, The | Meat (beef) | KG | 1 | 23.48% | 0.97 |
| GMB | Gambia, The | Meat (chicken) | KG | 1 | 23.58% | 0.94 |
| GMB | Gambia, The | Milk | KG | 1 | 20.31% | 0.9 |
| GMB | Gambia, The | Millet | KG | 1 | 43.76% | 0.85 |
| GMB | Gambia, The | Oil (vegetable) | L | 1 | 26.76% | 0.95 |
| GMB | Gambia, The | Onions | KG | 1 | 26.79% | 0.92 |
| GMB | Gambia, The | Oranges (big size) | KG | 1 | 19.57% | 0.91 |
| GMB | Gambia, The | Sweet potatoes | KG | 1 | 25.16% | 0.9 |
| GMB | Gambia, The | Rice (small grain, imported) | KG | 1 | 50.49% | 0.93 |
| GMB | Gambia, The | Salt | KG | 1 | 24.79% | 0.96 |
| GMB | Gambia, The | Sugar | KG | 1 | 26.66% | 0.95 |
| GMB | Gambia, The | Tea | Unit | 1 | 22.53% | 0.96 |
| GMB | Gambia, The | Tomatoes | KG | 1 | 26.45% | 0.87 |
| GNB | Guinea-Bissau | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| GNB | Guinea-Bissau | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 17.97% | 0.9 |
| GNB | Guinea-Bissau | Maize | KG | 1 | 7.92% | 0.82 |
| GNB | Guinea-Bissau | Oil (vegetable, imported) | L | 1 | 22.35% | 0.93 |
| GNB | Guinea-Bissau | Rice (imported) | KG | 1 | 22.45% | 0.93 |
| HTI | Haiti | Beans (black) | Marmite | 0.3704 | 59.81% | 0.93 |
| HTI | Haiti | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| HTI | Haiti | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 63.52% | 0.95 |
| HTI | Haiti | Maize meal (local) | Marmite | 0.3704 | 85.28% | 0.92 |
| HTI | Haiti | Oil (vegetable, imported) | Gallon | 0.2646 | 54.44% | 0.96 |
| HTI | Haiti | Pasta | 350 G | 2.8571 | 30.51% | 0.96 |
| HTI | Haiti | Rice (tchako) | Marmite | 0.3704 | 63.8% | 0.95 |
| HTI | Haiti | Sorghum | Marmite | 0.3704 | 38.43% | 0.93 |
| HTI | Haiti | Sugar (white) | Marmite | 0.3704 | 39.49% | 0.95 |
| HTI | Haiti | Wheat flour (imported) | Marmite | 0.3704 | 85.6% | 0.93 |
| IDN | Indonesia | Chili (red) | KG | 1 | 25.64% | 0.85 |
| IDN | Indonesia | Eggs | KG | 1 | 25.59% | 0.92 |
| IDN | Indonesia | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| IDN | Indonesia | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 25.66% | 0.92 |
| IDN | Indonesia | Meat (chicken, broiler) | KG | 1 | 25.2% | 0.9 |
| IDN | Indonesia | Rice | KG | 1 | 25.94% | 0.96 |
| IDN | Indonesia | Sugar | KG | 1 | 25.33% | 0.95 |
| IRQ | Iraq | Beans (white) | KG | 1 | 45.85% | 0.97 |
| IRQ | Iraq | Bread (khoboz) | Unit | 1 | 44.54% | 0.98 |
| IRQ | Iraq | Cheese (local) | KG | 1 | 43.04% | 0.97 |
| IRQ | Iraq | Dates | KG | 1 | 43.32% | 0.92 |
| IRQ | Iraq | Eggs | Unit | 12 | 46.79% | 0.98 |
| IRQ | Iraq | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| IRQ | Iraq | Fish | KG | 1 | 47.04% | 0.95 |
| IRQ | Iraq | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 51.75% | 0.97 |
| IRQ | Iraq | Fuel (gas) | Cylinder | 0 | 33.39% | 0.99 |
| IRQ | Iraq | Fuel (kerosene) | L | 0 | 40.81% | 0.96 |
| IRQ | Iraq | Fuel (petrol-gasoline) | L | 0 | 29.18% | 0.98 |
| IRQ | Iraq | Lentils | KG | 1 | 47.19% | 0.95 |
| IRQ | Iraq | Meat (beef) | KG | 1 | 37.85% | 0.98 |
| IRQ | Iraq | Meat (chicken) | KG | 1 | 48.44% | 0.95 |
| IRQ | Iraq | Milk (powder) | KG | 1 | 45.33% | 0.96 |
| IRQ | Iraq | Oil (vegetable) | L | 1 | 63.52% | 0.96 |
| IRQ | Iraq | Potatoes | KG | 1 | 46.09% | 0.94 |
| IRQ | Iraq | Rice | KG | 1 | 62.3% | 0.95 |
| IRQ | Iraq | Salt (iodised) | KG | 1 | 42.25% | 0.96 |
| IRQ | Iraq | Sugar | KG | 1 | 70.6% | 0.95 |
| IRQ | Iraq | Tea | KG | 1 | 39.68% | 0.98 |
| IRQ | Iraq | Tomatoes | KG | 1 | 43.53% | 0.91 |
| IRQ | Iraq | Wage (non-qualified labour) | Day | 0 | 30.56% | 0.99 |
| IRQ | Iraq | Wheat flour | KG | 1 | 69.81% | 0.93 |
| KEN | Kenya | Beans (dry) | 90 KG | 0.0111 | 5.1% | 0.95 |
| KEN | Kenya | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| KEN | Kenya | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 5.61% | 0.98 |
| KEN | Kenya | Maize (white) | KG | 1 | 7.02% | 0.98 |
| KEN | Kenya | Potatoes (Irish) | 50 KG | 0.02 | 5.04% | 0.97 |
| KEN | Kenya | Sorghum | 90 KG | 0.0111 | 4.91% | 0.93 |
| LAO | Lao PDR | Eggs | Unit | 12 | 53.96% | 0.99 |
| LAO | Lao PDR | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| LAO | Lao PDR | Fish (catfish) | KG | 1 | 46.66% | 0.98 |
| LAO | Lao PDR | Fish (tilapia, farmed) | KG | 1 | 53.03% | 0.97 |
| LAO | Lao PDR | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 60.18% | 0.99 |
| LAO | Lao PDR | Fuel (diesel) | L | 0 | 49.48% | 0.91 |
| LAO | Lao PDR | Fuel (petrol-gasoline) | L | 0 | 51.95% | 0.97 |
| LAO | Lao PDR | Garlic (small) | KG | 1 | 56.4% | 0.96 |
| LAO | Lao PDR | Meat (beef, second quality) | KG | 1 | 58.93% | 0.99 |
| LAO | Lao PDR | Meat (buffalo, first quality) | KG | 1 | 64.17% | 0.99 |
| LAO | Lao PDR | Meat (chicken) | KG | 1 | 55.64% | 0.97 |
| LAO | Lao PDR | Meat (pork, first quality) | KG | 1 | 64.37% | 0.99 |
| LAO | Lao PDR | Oil (soybean) | L | 1 | 54.13% | 0.98 |
| LAO | Lao PDR | Rice (glutinous, second quality) | KG | 1 | 65.07% | 0.98 |
| LAO | Lao PDR | Sugar (brown) | KG | 1 | 52.85% | 0.99 |
| LBN | Lebanon | Cabbage | KG | 1 | 31.25% | 0.93 |
| LBN | Lebanon | Cucumbers (greenhouse) | KG | 1 | 25.25% | 0.92 |
| LBN | Lebanon | Eggs | 30 pcs | 0.3333 | 64.95% | 0.86 |
| LBN | Lebanon | Unofficial exchange rate (Parallel-market Estimate)(Int. Forex, unofficial ground obs. extended) | USD/LCU | 0 | 100% | n/a |
| LBN | Lebanon | Fish (sardine, canned) | 125 G | 8 | 33.06% | 0.96 |
| LBN | Lebanon | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 43.45% | 0.95 |
| LBN | Lebanon | Fuel (diesel) | 20 L | 0 | 44.73% | 0.93 |
| LBN | Lebanon | Fuel (gas) | 10 KG | 0 | 45.58% | 0.94 |
| LBN | Lebanon | Fuel (petrol-gasoline, 95 octane) | 20 L | 0 | 47.71% | 0.95 |
| LBN | Lebanon | Oil (sunflower) | 5 L | 0.2 | 54.97% | 0.88 |
| LBR | Liberia | Cassava (fresh) | 50 KG | 0.02 | 21.74% | 0.88 |
| LBR | Liberia | Cowpeas | KG | 1 | 25.31% | 0.94 |
| LBR | Liberia | Exchange rate | USD/LCU | 0 | 21.65% | 0.97 |
| LBR | Liberia | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 28.23% | 0.94 |
| LBR | Liberia | Fuel (petrol-gasoline) | Gallon | 0 | 30.96% | 0.93 |
| LBR | Liberia | Oil (palm) | Gallon | 0.2646 | 29.91% | 0.93 |
| LBR | Liberia | Rice (imported) | 50 KG | 0.02 | 31.43% | 0.98 |
| LBY | Libya | Beans | 400 G | 2.5 | 53.58% | 0.91 |
| LBY | Libya | Bread | 5 pcs | 2 | 58.1% | 0.94 |
| LBY | Libya | Chickpeas | 400 G | 2.5 | 59.86% | 0.91 |
| LBY | Libya | Couscous | KG | 1 | 56.81% | 0.91 |
| LBY | Libya | Eggs | 30 pcs | 0.3333 | 60.92% | 0.96 |
| LBY | Libya | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| LBY | Libya | Fish (tuna, canned) | 200 G | 5 | 60.42% | 0.91 |
| LBY | Libya | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 59.3% | 0.91 |
| LBY | Libya | Meat (chicken) | KG | 1 | 56.33% | 0.94 |
| LBY | Libya | Meat (lamb) | KG | 1 | 51.27% | 0.98 |
| LBY | Libya | Milk (condensed) | 200 ML | 5 | 55.11% | 0.85 |
| LBY | Libya | Oil (vegetable) | L | 1 | 58.46% | 0.93 |
| LBY | Libya | Onions | KG | 1 | 59.83% | 0.84 |
| LBY | Libya | Pasta | 500 G | 2 | 55.95% | 0.89 |
| LBY | Libya | Potatoes | KG | 1 | 61.59% | 0.85 |
| LBY | Libya | Rice | KG | 1 | 64% | 0.9 |
| LBY | Libya | Salt | KG | 1 | 52.39% | 0.92 |
| LBY | Libya | Sugar | KG | 1 | 55.26% | 0.92 |
| LBY | Libya | Tea (black) | 250 G | 4 | 61.23% | 0.92 |
| LBY | Libya | Tomatoes | KG | 1 | 55.49% | 0.8 |
| LBY | Libya | Tomatoes (paste) | 400 G | 2.5 | 57.93% | 0.92 |
| LBY | Libya | Water (drinking) | L | 0 | 34.55% | 0.94 |
| LBY | Libya | Wheat flour | KG | 1 | 62.63% | 0.9 |
| LKA | Sri Lanka | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| LKA | Sri Lanka | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 19.01% | 0.71 |
| LKA | Sri Lanka | Rice Various | KG | 1 | 22.88% | 0.86 |
| LKA | Sri Lanka | Wheat flour | KG | 1 | 14.3% | 0.45 |
| MLI | Mali | Beans (niebe) | KG | 1 | 28.81% | 0.91 |
| MLI | Mali | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| MLI | Mali | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 42.67% | 0.92 |
| MLI | Mali | Maize | KG | 1 | 37.69% | 0.91 |
| MLI | Mali | Millet | KG | 1 | 51.72% | 0.91 |
| MLI | Mali | Rice (local) | KG | 1 | 48.23% | 0.94 |
| MLI | Mali | Sorghum | KG | 1 | 45.21% | 0.92 |
| MMR | Myanmar | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| MMR | Myanmar | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 15.44% | 0.92 |
| MMR | Myanmar | Oil (palm) | L | 1 | 12.88% | 0.94 |
| MMR | Myanmar | Pulses | KG | 1 | 13.48% | 0.91 |
| MMR | Myanmar | Rice (low quality) | KG | 1 | 18.37% | 0.93 |
| MMR | Myanmar | Salt | KG | 1 | 16.8% | 0.9 |
| MOZ | Mozambique | Cowpeas | KG | 1 | 17.53% | 0.77 |
| MOZ | Mozambique | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| MOZ | Mozambique | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 18.16% | 0.91 |
| MOZ | Mozambique | Groundnuts (small, shelled) | KG | 1 | 13.63% | 0.7 |
| MOZ | Mozambique | Maize (white) | KG | 1 | 20.48% | 0.94 |
| MOZ | Mozambique | Maize meal (white, first grade) | KG | 1 | 15.56% | 0.93 |
| MOZ | Mozambique | Oil (vegetable, local) | L | 1 | 20.16% | 0.95 |
| MOZ | Mozambique | Rice (imported) | KG | 1 | 20.24% | 0.94 |
| MOZ | Mozambique | Sugar (brown, local) | KG | 1 | 20.4% | 0.96 |
| MOZ | Mozambique | Wheat flour (local) | KG | 1 | 15.86% | 0.91 |
| MRT | Mauritania | Unofficial exchange rate (Parallel-market Estimate)(Int. Forex) | USD/LCU | 0 | 100% | n/a |
| MRT | Mauritania | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 20.47% | 0.91 |
| MRT | Mauritania | Oil (vegetable) | L | 1 | 24.76% | 0.93 |
| MRT | Mauritania | Rice (imported) | KG | 1 | 23.47% | 0.92 |
| MRT | Mauritania | Sorghum (taghalit) | KG | 1 | 18.25% | 0.88 |
| MRT | Mauritania | Sugar | KG | 1 | 24.64% | 0.9 |
| MRT | Mauritania | Wheat | KG | 1 | 21.44% | 0.89 |
| MRT | Mauritania | Wheat flour | KG | 1 | 6.76% | 0.94 |
| MWI | Malawi | Beans | KG | 1 | 22.41% | 0.91 |
| MWI | Malawi | Cassava | KG | 1 | 7.38% | 0.85 |
| MWI | Malawi | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| MWI | Malawi | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 20.72% | 0.89 |
| MWI | Malawi | Groundnuts (shelled) | KG | 1 | 11.77% | 0.87 |
| MWI | Malawi | Maize | KG | 1 | 45.11% | 0.89 |
| MWI | Malawi | Rice | KG | 1 | 16.15% | 0.9 |
| NER | Niger | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| NER | Niger | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 68.69% | 0.89 |
| NER | Niger | Millet | KG | 1 | 71.38% | 0.87 |
| NER | Niger | Rice (imported) | KG | 1 | 67.42% | 0.94 |
| NER | Niger | Sorghum | KG | 1 | 64.69% | 0.83 |
| NGA | Nigeria | Bread | Unit | 1 | 13.13% | 0.97 |
| NGA | Nigeria | Cassava meal (gari, yellow) | 100 KG | 0.01 | 10.76% | 0.98 |
| NGA | Nigeria | Cowpeas (white) | 100 KG | 0.01 | 13.13% | 0.95 |
| NGA | Nigeria | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| NGA | Nigeria | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 13.01% | 0.97 |
| NGA | Nigeria | Fuel (diesel) | L | 0 | 13.12% | 0.97 |
| NGA | Nigeria | Fuel (petrol-gasoline) | L | 0 | 13.1% | 0.99 |
| NGA | Nigeria | Gari (white) | 100 KG | 0.01 | 12.23% | 0.98 |
| NGA | Nigeria | Groundnuts (shelled) | 100 KG | 0.01 | 12.63% | 0.97 |
| NGA | Nigeria | Maize (white) | 100 KG | 0.01 | 14.77% | 0.97 |
| NGA | Nigeria | Millet | 100 KG | 0.01 | 13.8% | 0.97 |
| NGA | Nigeria | Rice (imported) | 50 KG | 0.02 | 12.44% | 0.97 |
| NGA | Nigeria | Sorghum (white) | 100 KG | 0.01 | 14.64% | 0.96 |
| NGA | Nigeria | Yam | KG | 1 | 10.12% | 0.96 |
| PHL | Philippines | Cabbage | KG | 1 | 14.57% | 0.81 |
| PHL | Philippines | Carrots | KG | 1 | 14.19% | 0.81 |
| PHL | Philippines | Eggs | Unit | 12 | 22.41% | 0.99 |
| PHL | Philippines | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| PHL | Philippines | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 21.62% | 0.98 |
| PHL | Philippines | Garlic | KG | 1 | 12.55% | 0.84 |
| PHL | Philippines | Meat (beef, chops with bones) | KG | 1 | 24.27% | 0.97 |
| PHL | Philippines | Meat (chicken, whole) | KG | 1 | 23.69% | 0.97 |
| PHL | Philippines | Meat (pork) | KG | 1 | 26.11% | 0.98 |
| PHL | Philippines | Onions (red) | KG | 1 | 23.27% | 0.94 |
| PHL | Philippines | Potatoes (Irish) | KG | 1 | 21.61% | 0.94 |
| PHL | Philippines | Rice (regular, milled) | KG | 1 | 27.26% | 0.98 |
| PHL | Philippines | Tomatoes | KG | 1 | 25.67% | 0.92 |
| SDN | Sudan | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| SDN | Sudan | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 37.21% | 0.92 |
| SDN | Sudan | Millet | 3.5 KG | 0.2857 | 50.05% | 0.92 |
| SDN | Sudan | Sorghum | 3 KG | 0.3333 | 50.1% | 0.92 |
| SDN | Sudan | Sorghum (food aid) | 3 KG | 0 | 24.78% | 0.9 |
| SDN | Sudan | Wheat | 90 KG | 0.0111 | 16.08% | 0.89 |
| SEN | Senegal | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| SEN | Senegal | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 52.69% | 0.84 |
| SEN | Senegal | Maize (local) | KG | 1 | 47.98% | 0.81 |
| SEN | Senegal | Millet | KG | 1 | 60.1% | 0.84 |
| SEN | Senegal | Rice (imported) | KG | 1 | 58.97% | 0.87 |
| SEN | Senegal | Sorghum | KG | 1 | 40.47% | 0.82 |
| SOM | Somalia | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with FAO) | USD/LCU | 0 | 100% | n/a |
| SOM | Somalia | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 20.39% | 0.9 |
| SOM | Somalia | Fuel (diesel) | L | 0 | 8.72% | 0.87 |
| SOM | Somalia | Maize (white) | KG | 1 | 24.26% | 0.88 |
| SOM | Somalia | Oil (vegetable, imported) | L | 1 | 8.42% | 0.91 |
| SOM | Somalia | Rice (imported) | KG | 1 | 24.94% | 0.91 |
| SOM | Somalia | Sorghum (red) | KG | 1 | 22.15% | 0.89 |
| SSD | South Sudan | Beans (red) | KG | 1 | 31.02% | 0.9 |
| SSD | South Sudan | Cassava (dry) | 3.5 KG | 0.2857 | 5.86% | 0.9 |
| SSD | South Sudan | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with CLiMIS) | USD/LCU | 0 | 100% | n/a |
| SSD | South Sudan | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 22.17% | 0.9 |
| SSD | South Sudan | Fuel (diesel) | L | 0 | 17.63% | 0.92 |
| SSD | South Sudan | Fuel (petrol-gasoline) | L | 0 | 18.17% | 0.9 |
| SSD | South Sudan | Groundnuts (shelled) | KG | 1 | 21.13% | 0.87 |
| SSD | South Sudan | Maize (white) | 3.5 KG | 0.2857 | 20.43% | 0.91 |
| SSD | South Sudan | Millet (white) | 3.5 KG | 0.2857 | 11.62% | 0.9 |
| SSD | South Sudan | Oil (vegetable) | L | 1 | 28.27% | 0.89 |
| SSD | South Sudan | Sesame | 3.5 KG | 0.2857 | 17.99% | 0.89 |
| SSD | South Sudan | Sorghum (white, imported) | 3.5 KG | 0.2857 | 29.6% | 0.91 |
| SSD | South Sudan | Wheat flour | KG | 1 | 27.6% | 0.91 |
| SYR | Syrian Arab Republic | Bananas | KG | 1 | 27.9% | 0.9 |
| SYR | Syrian Arab Republic | Beans (white) | KG | 1 | 31.89% | 0.91 |
| SYR | Syrian Arab Republic | Bread (bakery) | 1.1 KG | 0.9091 | 17.75% | 0.96 |
| SYR | Syrian Arab Republic | Bulgur | KG | 1 | 32.26% | 0.86 |
| SYR | Syrian Arab Republic | Carrots | KG | 1 | 25.87% | 0.91 |
| SYR | Syrian Arab Republic | Cheese | KG | 1 | 16.67% | 0.94 |
| SYR | Syrian Arab Republic | Chickpeas | KG | 1 | 31.56% | 0.85 |
| SYR | Syrian Arab Republic | Dates | KG | 1 | 16.99% | 0.92 |
| SYR | Syrian Arab Republic | Eggs | 30 pcs | 0.3333 | 29.89% | 0.95 |
| SYR | Syrian Arab Republic | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex, WFP & unofficial ground obs. extended) | USD/LCU | 0 | 100% | n/a |
| SYR | Syrian Arab Republic | Fish (tuna, canned) | 160 G | 6.25 | 16.53% | 0.94 |
| SYR | Syrian Arab Republic | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 28.68% | 0.93 |
| SYR | Syrian Arab Republic | Fuel (diesel) | L | 0 | 17.06% | 0.95 |
| SYR | Syrian Arab Republic | Fuel (gas) | 25 KG | 0 | 18.84% | 0.95 |
| SYR | Syrian Arab Republic | Lentils | KG | 1 | 39.2% | 0.94 |
| SYR | Syrian Arab Republic | Livestock (sheep, two-year-old male) | Head | 0 | 17.8% | 0.97 |
| SYR | Syrian Arab Republic | Meat (beef, minced) | KG | 1 | 29.26% | 0.95 |
| SYR | Syrian Arab Republic | Meat (chicken, plucked) | KG | 1 | 29% | 0.94 |
| SYR | Syrian Arab Republic | Oil | L | 1 | 40.22% | 0.95 |
| SYR | Syrian Arab Republic | Parsley | Packet | 2 | 16.99% | 0.94 |
| SYR | Syrian Arab Republic | Potatoes | KG | 1 | 29.29% | 0.82 |
| SYR | Syrian Arab Republic | Rice | KG | 1 | 36.43% | 0.93 |
| SYR | Syrian Arab Republic | Sugar | KG | 1 | 40.18% | 0.94 |
| SYR | Syrian Arab Republic | Tomatoes | KG | 1 | 33.95% | 0.84 |
| SYR | Syrian Arab Republic | Wage (non-qualified labour) | Day | 0 | 32.19% | 0.83 |
| SYR | Syrian Arab Republic | Wheat flour | KG | 1 | 37.89% | 0.94 |
| SYR | Syrian Arab Republic | Yogurt | KG | 1 | 16.4% | 0.94 |
| TCD | Chad | Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) | USD/LCU | 0 | 100% | n/a |
| TCD | Chad | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 23.47% | 0.93 |
| TCD | Chad | Livestock (goat, medium-sized castrated male) | Head | 0 | 19.4% | 0.95 |
| TCD | Chad | Livestock (sheep, medium-sized castrated male) | Head | 0 | 21.36% | 0.96 |
| TCD | Chad | Maize (white) | KG | 1 | 19.08% | 0.98 |
| TCD | Chad | Millet | KG | 1 | 31.62% | 0.76 |
| TCD | Chad | Rice (imported) | KG | 1 | 13.93% | 0.98 |
| TCD | Chad | Sorghum (red) | KG | 1 | 27.76% | 0.73 |
| YEM | Yemen, Rep. | Beans (white) | KG | 1 | 47.19% | 0.93 |
| YEM | Yemen, Rep. | Eggs | Unit | 12 | 47.27% | 0.97 |
| YEM | Yemen, Rep. | Exchange rate (unofficial) | USD/LCU | 0 | 46.29% | 0.99 |
| YEM | Yemen, Rep. | Food Price Index | LCU, Indexed, January 2018 = 1 | Laspreyes | 50.77% | 0.95 |
| YEM | Yemen, Rep. | Fuel (diesel) | L | 0 | 49.67% | 0.9 |
| YEM | Yemen, Rep. | Fuel (gas) | 18 KG | 0 | 43.06% | 0.93 |
| YEM | Yemen, Rep. | Fuel (petrol-gasoline) | L | 0 | 48.94% | 0.89 |
| YEM | Yemen, Rep. | Lentils | KG | 1 | 48.46% | 0.94 |
| YEM | Yemen, Rep. | Livestock (sheep, two-year-old male) | Head | 0 | 36.69% | 0.97 |
| YEM | Yemen, Rep. | Milling cost (wheat) | 50 KG | 0 | 41.65% | 0.96 |
| YEM | Yemen, Rep. | Oil (vegetable) | L | 1 | 50.15% | 0.94 |
| YEM | Yemen, Rep. | Onions | KG | 1 | 52.9% | 0.85 |
| YEM | Yemen, Rep. | Peas (yellow, split) | KG | 1 | 38.46% | 0.9 |
| YEM | Yemen, Rep. | Potatoes | KG | 1 | 51.31% | 0.86 |
| YEM | Yemen, Rep. | Rice (imported) | KG | 1 | 45.19% | 0.96 |
| YEM | Yemen, Rep. | Salt | KG | 1 | 48.27% | 0.94 |
| YEM | Yemen, Rep. | Sugar | KG | 1 | 47.62% | 0.95 |
| YEM | Yemen, Rep. | Tomatoes | KG | 1 | 50.85% | 0.76 |
| YEM | Yemen, Rep. | Wage (non-qualified labour) | Day | 0 | 41.48% | 0.97 |
| YEM | Yemen, Rep. | Wage (qualified labour) | Day | 0 | 42.38% | 0.98 |
| YEM | Yemen, Rep. | Wheat | KG | 1 | 51.65% | 0.95 |
| YEM | Yemen, Rep. | Wheat flour | KG | 1 | 54.31% | 0.95 |