Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate 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.

Geographic coverage notes

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, Armavir, Ararat, Aragatsotn, Tavush, Gegharkunik, Shirak, Kotayk, Syunik, Lori, 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, Mai-Ndombe, 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, North Eastern, Rift Valley, Coast, Eastern, Nairobi, , Central, Nyanza, Attapeu, Louangnamtha, Champasack, Bokeo, Bolikhamxai, Khammouan, Oudomxai, Phongsaly, Vientiane, Xiengkhouang, Louangphabang, Salavan, Savannakhet, Sekong, Vientiane Capital, Houaphan, Xaignabouly, Akkar, Mount Lebanon, Baalbek-El Hermel, Beirut, Bekaa, El Nabatieh, Nimba, Grand Kru, Grand Cape Mount, Gbarpolu, Grand Bassa, Rivercess, Montserrado, River Gee, Lofa, Bomi, Bong, Sinoe, Maryland, Margibi, Grand Gedeh, 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, Sagaing, Kayah, Shan (East), Chin, Magway, Bago (East), 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, Adamawa, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, 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, Unity, Jonglei, Northern Bahr el Ghazal, Upper Nile, Eastern Equatoria, Central Equatoria, Western Bahr el Ghazal, 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

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate 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.

Geographic coverage notes

The data cover the following sub-national areas: Attapeu, Bokeo, Bolikhamxai, Champasack, Houaphan, Khammouan, Louangphabang, Louangnamtha, Oudomxai, Phongsaly, Salavan, Savannakhet, Sekong, Vientiane Capital, Vientiane, Xaignabouly, Xiengkhouang, Market Average

Japan JP: Official Exchange Rate: Average: per USD data was reported at 112.166 JPY/USD in 2017. This records an increase from the previous number of 108.793 JPY/USD for 2016. Japan JP: Official Exchange Rate: Average: per USD data is updated yearly, averaging 141.301 JPY/USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 360.000 JPY/USD in 1970 and a record low of 79.790 JPY/USD in 2012. Japan JP: Official Exchange Rate: Average: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).; ; International Monetary Fund, International Financial Statistics.; ;

Indonesia Official Exchange Rate: Period Average: Local Currency to USD data was reported at 16,466.999 USD/IDR in 2025. This records an increase from the previous number of 15,856.567 USD/IDR for 2024. Indonesia Official Exchange Rate: Period Average: Local Currency to USD data is updated yearly, averaging 9,319.032 USD/IDR from Dec 1987 (Median) to 2025, with 39 observations. The data reached an all-time high of 16,466.999 USD/IDR in 2025 and a record low of 1,640.844 USD/IDR in 1987. Indonesia Official Exchange Rate: Period Average: Local Currency to USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Indonesia – Table ID.World Bank.GEM: Foreign Exchange Rates: Annual. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).

Hong Kong SAR HK: Real Effective Exchange Rate Index data was reported at 124.430 2010=100 in 2018. This records a decrease from the previous number of 125.184 2010=100 for 2017. Hong Kong SAR HK: Real Effective Exchange Rate Index data is updated yearly, averaging 116.693 2010=100 from Dec 1995 (Median) to 2018, with 24 observations. The data reached an all-time high of 152.442 2010=100 in 1998 and a record low of 98.962 2010=100 in 2011. Hong Kong SAR HK: Real Effective Exchange Rate Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong SAR – Table HK.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. Real effective exchange rate is the nominal effective exchange rate (a measure of the value of a currency against a weighted average of several foreign currencies) divided by a price deflator or index of costs.; ; International Monetary Fund, International Financial Statistics.; ;

Kenya KE: Official Exchange Rate: Average: per USD data was reported at 103.374 KES/USD in 2017. This records an increase from the previous number of 101.504 KES/USD for 2016. Kenya KE: Official Exchange Rate: Average: per USD data is updated yearly, averaging 19.160 KES/USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 103.374 KES/USD in 2017 and a record low of 7.001 KES/USD in 1973. Kenya KE: Official Exchange Rate: Average: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).; ; International Monetary Fund, International Financial Statistics.; ;

Nigeria NG: Official Exchange Rate: Average: per USD data was reported at 305.790 NGN/USD in 2017. This records an increase from the previous number of 253.492 NGN/USD for 2016. Nigeria NG: Official Exchange Rate: Average: per USD data is updated yearly, averaging 5.951 NGN/USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 305.790 NGN/USD in 2017 and a record low of 0.547 NGN/USD in 1980. Nigeria NG: Official Exchange Rate: Average: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).; ; International Monetary Fund, International Financial Statistics.; ;

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate 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.

Geographic coverage notes

The data cover the following sub-national areas: 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, Market Average

Egypt EG: Official Exchange Rate: Average: per USD data was reported at 17.783 EGP/USD in 2017. This records an increase from the previous number of 10.025 EGP/USD for 2016. Egypt EG: Official Exchange Rate: Average: per USD data is updated yearly, averaging 0.783 EGP/USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 17.783 EGP/USD in 2017 and a record low of 0.348 EGP/USD in 1961. Egypt EG: Official Exchange Rate: Average: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Egypt – Table EG.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).; ; International Monetary Fund, International Financial Statistics.; ;

Comoros Official Exchange Rate: Period Average: Local Currency to USD data was reported at 434.474 USD/KMF in May 2025. This records a decrease from the previous number of 438.476 USD/KMF for Apr 2025. Comoros Official Exchange Rate: Period Average: Local Currency to USD data is updated monthly, averaging 401.029 USD/KMF from Jan 1987 (Median) to May 2025, with 461 observations. The data reached an all-time high of 1,060.522 USD/KMF in Dec 2020 and a record low of 246.026 USD/KMF in Sep 1992. Comoros Official Exchange Rate: Period Average: Local Currency to USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Comoros – Table KM.World Bank.GEM: Foreign Exchange Rates. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).

Real effective exchange rate index (2010 = 100) in Venezuela was reported at 742 % in 2016, according to the World Bank collection of development indicators, compiled from officially recognized sources. Venezuela - Real effective exchange rate index (2000 = 100) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

India Official Exchange Rate: Period Average: Local Currency to USD data was reported at 85.987 USD/INR in 2025. This records an increase from the previous number of 83.669 USD/INR for 2024. India Official Exchange Rate: Period Average: Local Currency to USD data is updated yearly, averaging 45.732 USD/INR from Dec 1987 (Median) to 2025, with 39 observations. The data reached an all-time high of 85.987 USD/INR in 2025 and a record low of 12.949 USD/INR in 1987. India Official Exchange Rate: Period Average: Local Currency to USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.GEM: Foreign Exchange Rates: Annual. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).

• © 2016 The World Bank Group, All Rights Reserved.
• (2010 = 100)
• Real effective exchange rate is the nominal effective exchange rate (a measure of the value of a currency against a weighted average of several foreign currencies) divided by a price deflator or index of costs.
• Based on data from the Saudi Central Department of Statistics and Information under the authority of the Ministry of Economy and Planning.

BD: DEC Alternative Conversion Factor: per USD data was reported at 102.668 USD/BDT in 2023. This records an increase from the previous number of 86.317 USD/BDT for 2022. BD: DEC Alternative Conversion Factor: per USD data is updated yearly, averaging 36.700 USD/BDT from Jun 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 102.668 USD/BDT in 2023 and a record low of 4.800 USD/BDT in 1971. BD: DEC Alternative Conversion Factor: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. The DEC alternative conversion factor is the underlying annual exchange rate used for the World Bank Atlas method. As a rule, it is the official exchange rate reported in the IMF's International Financial Statistics (line rf). Exceptions arise where further refinements are made by World Bank staff. It is expressed in local currency units per U.S. dollar.;International Monetary Fund, International Financial Statistics, supplemented by World Bank staff estimates.;;In the WDI database, the DEC alternative conversion factor is used to convert data in local currency units (LCU) into U.S. dollars.

The dataset is from world data bank and it is from 2020 to 2024 The dataset uses columns as : "country": country which data belong "iso3":short form of country "components":products "currency":currency "start_date_observations" start of observation date "end_date_observations": end of observation date "number_of_markets_modeled":number of market modeled "number_of_markets_covered":number of market covered "number_of_food_items":num of food item in components "number_of_observations_food":num of observation food "number_of_observations_other":observations of others "data_coverage_food"::data coverage of food "data_coverage_previous_12_months_food":for 12 months previous price "total_food_price_increase_since_start_date":total food price "average_annualized_food_inflation":average annualized inflation "maximum_food_drawdown":maximum food drawdown "average_annualized_food_volatility":avg food volatility "average_monthly_food_price_correlation_between_markets":avg monthly food price correlation "average_annual_food_price_correlation_between_markets":annulaly food price correlation "Rsquared_individual_food_items":food item error "Rsquared_individual_other_items":individual item error "index_confidence_score":confidence score "imputation_model":principle used

data source:https://microdata.worldbank.org/index.php/catalog/6160

STUDY TYPE Monthly currency exchange rate estimates in fragile countries

SERIES INFORMATION 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.

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate 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.

Geographic coverage notes

The data cover the following sub-national areas: North, South, Artibonite, Centre, South-East, Grande'Anse, North-East, West, North-West, Market Average

Hungary HU: PPP Conversion Factor: to Market Exchange Rate: Price Level Ratio data was reported at 0.501 % in 2017. This records an increase from the previous number of 0.480 % for 2016. Hungary HU: PPP Conversion Factor: to Market Exchange Rate: Price Level Ratio data is updated yearly, averaging 0.490 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 0.761 % in 2008 and a record low of 0.390 % in 2000. Hungary HU: PPP Conversion Factor: to Market Exchange Rate: Price Level Ratio data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hungary – Table HU.World Bank: Gross Domestic Product: Purchasing Power Parity. Purchasing power parity conversion factor is the number of units of a country's currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. The ratio of PPP conversion factor to market exchange rate is the result obtained by dividing the PPP conversion factor by the market exchange rate. The ratio, also referred to as the national price level, makes it possible to compare the cost of the bundle of goods that make up gross domestic product (GDP) across countries. It tells how many dollars are needed to buy a dollar's worth of goods in the country as compared to the United States. PPP conversion factors are based on the 2011 ICP round.; ; World Bank, International Comparison Program database.; ;

BS: DEC Alternative Conversion Factor: per USD data was reported at 1.000 USD/BSD in 2023. This stayed constant from the previous number of 1.000 USD/BSD for 2022. BS: DEC Alternative Conversion Factor: per USD data is updated yearly, averaging 1.000 USD/BSD from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 1.020 USD/BSD in 1965 and a record low of 1.000 USD/BSD in 2023. BS: DEC Alternative Conversion Factor: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bahamas – Table BS.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. The DEC alternative conversion factor is the underlying annual exchange rate used for the World Bank Atlas method. As a rule, it is the official exchange rate reported in the IMF's International Financial Statistics (line rf). Exceptions arise where further refinements are made by World Bank staff. It is expressed in local currency units per U.S. dollar.;International Monetary Fund, International Financial Statistics, supplemented by World Bank staff estimates.;;In the WDI database, the DEC alternative conversion factor is used to convert data in local currency units (LCU) into U.S. dollars.

Trinidad and Tobago TT: DEC Alternative Conversion Factor: per USD data was reported at 6.772 TTD/USD in 2017. This records an increase from the previous number of 6.664 TTD/USD for 2016. Trinidad and Tobago TT: DEC Alternative Conversion Factor: per USD data is updated yearly, averaging 4.047 TTD/USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 6.772 TTD/USD in 2017 and a record low of 1.714 TTD/USD in 1966. Trinidad and Tobago TT: DEC Alternative Conversion Factor: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Trinidad and Tobago – Table TT.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. The DEC alternative conversion factor is the underlying annual exchange rate used for the World Bank Atlas method. As a rule, it is the official exchange rate reported in the IMF's International Financial Statistics (line rf). Exceptions arise where further refinements are made by World Bank staff. It is expressed in local currency units per U.S. dollar.; ; International Monetary Fund, International Financial Statistics, supplemented by World Bank staff estimates.; ; In the WDI database, the DEC alternative conversion factor is used to convert data in local currency units (LCU) into U.S. dollars.

Poland PL: Official Exchange Rate: Average: per USD data was reported at 3.779 PLN/USD in 2017. This records a decrease from the previous number of 3.943 PLN/USD for 2016. Poland PL: Official Exchange Rate: Average: per USD data is updated yearly, averaging 0.093 PLN/USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 4.346 PLN/USD in 2000 and a record low of 0.000 PLN/USD in 1977. Poland PL: Official Exchange Rate: Average: per USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Poland – Table PL.World Bank.WDI: Exchange Rates and Real Effective Exchange Rates. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).; ; International Monetary Fund, International Financial Statistics.; ;