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      <titl>Monthly food price inflation estimates by country</titl>
      <subTitl>25 countries, 2008/01/01-2023/06/01, version 2023/06/26</subTitl>
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      <AuthEnty affiliation="World Bank, Development Data Group (DECDG), Data Analytics and Tools unit (DECAT)">Bo Pieter Johannes Andrée</AuthEnty>
      <othId role="Source of market price data" affiliation="United Nations" email="">
        <p>World Food Programme (WFP)</p>
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      <fundAg abbr="FCDO (formerly DFID)" role="Support to data analytics">Foreign, Commonwealth &amp; Development Office</fundAg>
      <fundAg abbr="FCDO (formerly DFID)" role="Data documentation and dissemination (FCV Data Platform)">Foreign, Commonwealth &amp; Development Office</fundAg>
      <fundAg abbr="DFAT" role="Support to methodological development in low data regions">Department of Foreign Affairs and Trade</fundAg>
      <fundAg abbr="DFAT" role="Support to methodological development in low data regions">Department of Foreign Affairs and Trade</fundAg>
      <fundAg abbr="BMZ" role="Expansion of coverage and maintenance">Federal Ministry for Economic Cooperation and Development as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund</fundAg>
      <fundAg abbr="BMZ" role="Expansion of coverage and maintenance">Federal Ministry for Economic Cooperation and Development as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund</fundAg>
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      <serName>Monthly food price estimates in fragile countries</serName>
      <serInfo><![CDATA[Real Time Food Prices (RTFP) 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.
      
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.
      
RTFP estimates of historical and current prices may serve as proxies for sub-national price inflation series or national-level Consumer Price Inflation (CPI) indicators when complete information is unavailable. Therefore, RTFP 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 series: 

 Country-level inflation: 
 - All countries: https://microdata.worldbank.org/index.php/catalog/study/WLD_2021_RTFP-CTRY_v02_M 

 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 
 - Burundi: https://microdata.worldbank.org/index.php/catalog/study/BDI_2021_RTFP_v02_M 
 - Burkina Faso: https://microdata.worldbank.org/index.php/catalog/study/BFA_2021_RTFP_v02_M 
 - Central African Republic: https://microdata.worldbank.org/index.php/catalog/study/CAF_2021_RTFP_v02_M 
 - Cameroon: https://microdata.worldbank.org/index.php/catalog/study/CMR_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-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 
 - Iraq: https://microdata.worldbank.org/index.php/catalog/study/IRQ_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 
 - Mali: https://microdata.worldbank.org/index.php/catalog/study/MLI_2021_RTFP_v02_M 
 - Myanmar: https://microdata.worldbank.org/index.php/catalog/study/MMR_2021_RTFP_v02_M 
 - Mozambique: https://microdata.worldbank.org/index.php/catalog/study/MOZ_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 
 - Sudan: https://microdata.worldbank.org/index.php/catalog/study/SDN_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 
 - Syrian Arab Republic: https://microdata.worldbank.org/index.php/catalog/study/SYR_2021_RTFP_v02_M 
 - Chad: https://microdata.worldbank.org/index.php/catalog/study/TCD_2021_RTFP_v02_M 
 - Yemen, Rep.: https://microdata.worldbank.org/index.php/catalog/study/YEM_2021_RTFP_v02_M 
]]></serInfo>
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      <keyword vocab="" vocabURI="">Food Price Monitor</keyword>
      <keyword vocab="" vocabURI="">FPM</keyword>
      <keyword vocab="" vocabURI="">Real Time Food Prices</keyword>
      <keyword vocab="" vocabURI="">RTFP</keyword>
      <keyword vocab="" vocabURI="">Inflation</keyword>
      <keyword vocab="" vocabURI="">Food Price Inflation</keyword>
      <keyword vocab="" vocabURI="">Food security</keyword>
      <keyword vocab="" vocabURI="">Food Insecurity</keyword>
      <keyword vocab="" vocabURI="">Food Crisis</keyword>
      <keyword vocab="" vocabURI="">Famine</keyword>
      <keyword vocab="" vocabURI="">Fragility</keyword>
      <keyword vocab="" vocabURI="">FCS</keyword>
      <keyword vocab="" vocabURI="">FCV</keyword>
      <keyword vocab="" vocabURI="">Food Price Crisis</keyword>
      <keyword vocab="" vocabURI="">Commodity prices</keyword>
      <keyword vocab="" vocabURI="">Maize</keyword>
      <keyword vocab="" vocabURI="">Sorghum</keyword>
      <keyword vocab="" vocabURI="">Wheat</keyword>
      <keyword vocab="" vocabURI="">Rice</keyword>
      <keyword vocab="" vocabURI="">Agricultural prices</keyword>
      <keyword vocab="" vocabURI="">Food prices</keyword>
      <keyword vocab="" vocabURI="">Real Time Food Prices</keyword>
      <keyword vocab="" vocabURI="">Price measurement</keyword>
      <keyword vocab="" vocabURI="">Real-time exchange rate data</keyword>
      <keyword vocab="" vocabURI="">Commodity items</keyword>
      <keyword vocab="" vocabURI="">Geo-referenced market locations</keyword>
      <keyword vocab="" vocabURI="">Sub-national price inflation series</keyword>
      <keyword vocab="" vocabURI="">Consumer Price Inflation (CPI)</keyword>
      <keyword vocab="" vocabURI="">National-level CPI indicators</keyword>
      <keyword vocab="" vocabURI="">International Comparison Program (ICP)</keyword>
      <keyword vocab="" vocabURI="">Inflation series</keyword>
      <keyword vocab="" vocabURI="">Market prices</keyword>
      <keyword vocab="" vocabURI="">Price analysis</keyword>
      <keyword vocab="" vocabURI="">Real-time data</keyword>
      <keyword vocab="" vocabURI="">National prices</keyword>
      <keyword vocab="" vocabURI="">International prices</keyword>
      <keyword vocab="" vocabURI="">Price fluctuations</keyword>
      <keyword vocab="" vocabURI="">Price trends</keyword>
      <keyword vocab="" vocabURI="">Price Volatility</keyword>
    </subject>
    <abstract><![CDATA[Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations.
                  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.]]></abstract>
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      <nation abbr="AFG">Afghanistan</nation>
      <nation abbr="BFA">Burkina Faso</nation>
      <nation abbr="BDI">Burundi</nation>
      <nation abbr="CMR">Cameroon</nation>
      <nation abbr="CAF">Central African Republic</nation>
      <nation abbr="TCD">Chad</nation>
      <nation abbr="COD">Congo, Dem. Rep.</nation>
      <nation abbr="COG">Congo, Rep.</nation>
      <nation abbr="GMB">Gambia, The</nation>
      <nation abbr="GNB">Guinea-Bissau</nation>
      <nation abbr="HTI">Haiti</nation>
      <nation abbr="IRQ">Iraq</nation>
      <nation abbr="LAO">Lao PDR</nation>
      <nation abbr="LBN">Lebanon</nation>
      <nation abbr="LBR">Liberia</nation>
      <nation abbr="MLI">Mali</nation>
      <nation abbr="MOZ">Mozambique</nation>
      <nation abbr="MMR">Myanmar</nation>
      <nation abbr="NER">Niger</nation>
      <nation abbr="NGA">Nigeria</nation>
      <nation abbr="SOM">Somalia</nation>
      <nation abbr="SSD">South Sudan</nation>
      <nation abbr="SDN">Sudan</nation>
      <nation abbr="SYR">Syrian Arab Republic</nation>
      <nation abbr="YEM">Yemen, Rep.</nation>
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    <notes><![CDATA[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, cocoyam, coffee instant, cowpeas, cucumbers, dates, eggplants, eggs, fish, fish catfish, fish mackerel, fish salted, fish sardine canned, fish smoked, fish tilapia farmed, fish tuna canned, gari, garlic, groundnuts, lentils, lettuce, livestock sheep two year old male, maize, maize flour, maize meal, meat beef, meat beef canned, meat beef first quality, meat beef minced, meat beef second quality, meat buffalo first quality, meat buffalo second quality, meat chicken, meat chicken plucked, meat chicken whole frozen, meat goat, meat goat with bones, meat pork first quality, meat pork second quality, milk, millet, oil, onions, oranges, parsley, pasta, peas, plantains, potatoes, pulses, rice, salt, sesame, sorghum, sorghum food aid, sugar, tea, tomatoes, tomatoes paste, wheat, wheat flour, yogurt]]></notes>
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    <notes><![CDATA[Information on the model used for Afghanistan (see working paper for more information)
Components: Bread (1 KG, Index Weight = 1), Rice (Low Quality) (1 KG, Index Weight = 1), Wheat (1 KG, Index Weight = 1)
Currency: AFN
Number of markets used: 40
Number of markets covered: 40
Number of food items: 3
Number of observations (food): bread: 2209, rice: 2599, wheat: 2569
Number of observations (other): exchange_rate: 1846, fuel_diesel: 1856, wage_non_qualified_labour_non_agricultural: 1826, wage_qualified_labour: 1841
Data coverage (food): 31.05%
Data coverage previous 12 months (food): 81.18%
Average annualized food inflation: 6.34%
Maximum food drawdown: -40.39%
Average annualized food volatility: 8.18%
Average monthly food price correlation between markets: 0.63
Average annual food price correlation between markets: 0.86
R squared individual food items: bread: 0.93, rice: 0.89, wheat: 0.93
R squared individual other items: exchange_rate: 1, fuel_diesel: 0.97, wage_non_qualified_labour_non_agricultural: 0.97, wage_qualified_labour: 0.98
Index confidence score: 0.92
Imputation model: bread: cubist (Andree, 2021), rice: cubist (Andree, 2021), wheat: cubist (Andree, 2021)
 

Information on the model used for Burundi (see working paper for more information)
Components: Bananas (1 KG, Index Weight = 1), Beans (1 KG, Index Weight = 1), Cassava Flour (1 KG, Index Weight = 1), Maize (White) (1 KG, Index Weight = 1), Maize Flour (1 KG, Index Weight = 1), Meat (Goat) (1 KG, Index Weight = 1), Onions (1 KG, Index Weight = 1), Sweet Potatoes (1 KG, Index Weight = 1), Rice (Low Quality, Local) (1 KG, Index Weight = 1), Tomatoes (1 KG, Index Weight = 1)
Currency: BIF
Number of markets used: 72
Number of markets covered: 72
Number of food items: 10
Number of observations (food): bananas: 5231, beans: 5830, cassava_flour: 5825, maize: 5450, maize_flour: 5003, meat_goat: 4984, onions: 5356, potatoes: 5829, rice: 5601, tomatoes: 5307
Number of observations (other): : 
Data coverage (food): 38.17%
Data coverage previous 12 months (food): 92.89%
Average annualized food inflation: 7.38%
Maximum food drawdown: -39.25%
Average annualized food volatility: 14.05%
Average monthly food price correlation between markets: 0.63
Average annual food price correlation between markets: 0.82
R squared individual food items: bananas: 0.87, beans: 0.89, cassava_flour: 0.88, maize: 0.86, maize_flour: 0.93, meat_goat: 0.96, onions: 0.8, potatoes: 0.82, rice: 0.95, tomatoes: 0.8
R squared individual other items: : 
Index confidence score: 0.89
Imputation model: bananas: two-stage cubist (Andree and Pape, 2023), beans: cubist (Andree, 2021), cassava_flour: cubist (Andree, 2021), maize: cubist (Andree, 2021), maize_flour: two-stage cubist (Andree and Pape, 2023), meat_goat: two-stage cubist (Andree and Pape, 2023), onions: two-stage cubist (Andree and Pape, 2023), potatoes: cubist (Andree, 2021), rice: cubist (Andree, 2021), tomatoes: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Burkina Faso (see working paper for more information)
Components: Maize (White) (1 KG, Index Weight = 1), Millet (1 KG, Index Weight = 1), Sorghum (White) (1 KG, Index Weight = 1)
Currency: XOF
Number of markets used: 64
Number of markets covered: 64
Number of food items: 3
Number of observations (food): maize: 6504, millet: 7495, sorghum: 7062
Number of observations (other): : 
Data coverage (food): 55.4%
Data coverage previous 12 months (food): 83.33%
Average annualized food inflation: 7.21%
Maximum food drawdown: -36.76%
Average annualized food volatility: 13.84%
Average monthly food price correlation between markets: 0.57
Average annual food price correlation between markets: 0.79
R squared individual food items: maize: 0.83, millet: 0.82, sorghum: 0.8
R squared individual other items: : 
Index confidence score: 0.82
Imputation model: maize: cubist (Andree, 2021), millet: cubist (Andree, 2021), sorghum: cubist (Andree, 2021)
 

Information on the model used for Central African Republic (see working paper for more information)
Components: Cassava (Cossette) (1 KG, Index Weight = 1), Maize (1 KG, Index Weight = 1), Meat (Beef) (1 KG, Index Weight = 1), Oil (Palm) (1 L, Index Weight = 1), Rice (1 KG, Index Weight = 1)
Currency: XAF
Number of markets used: 42
Number of markets covered: 42
Number of food items: 5
Number of observations (food): cassava: 2173, maize: 1942, meat_beef: 2056, oil: 1885, rice: 2059
Number of observations (other): : 
Data coverage (food): 24.33%
Data coverage previous 12 months (food): 51.71%
Average annualized food inflation: 4.92%
Maximum food drawdown: -38.75%
Average annualized food volatility: 14.88%
Average monthly food price correlation between markets: 0.39
Average annual food price correlation between markets: 0.74
R squared individual food items: cassava: 0.89, maize: 0.87, meat_beef: 0.95, oil: 0.71, rice: 0.89
R squared individual other items: : 
Index confidence score: 0.88
Imputation model: cassava: cubist (Andree, 2021), maize: cubist (Andree, 2021), meat_beef: cubist (Andree, 2021), oil: two-stage cubist (Andree and Pape, 2023), rice: cubist (Andree, 2021)
 

Information on the model used for Cameroon (see working paper for more information)
Components: Bananas (12 KG, Index Weight = 0.08), Cassava (Fresh) (5 KG, Index Weight = 0.2), Cocoyam (Macabo) (20 KG, Index Weight = 0.05), Fish (Mackerel, Fresh) (1 KG, Index Weight = 1), Maize (White) (1 KG, Index Weight = 1), Meat (Beef) (1 KG, Index Weight = 1), Oil (Palm) (1 L, Index Weight = 1), Plantains (12 KG, Index Weight = 0.08), Rice (Long Grain, Imported) (1 KG, Index Weight = 1), Sorghum (Red) (100 KG, Index Weight = 0.01), Wheat Flour (1 KG, Index Weight = 1)
Currency: XAF
Number of markets used: 82
Number of markets covered: 82
Number of food items: 11
Number of observations (food): bananas: 606, cassava: 606, cocoyam: 606, fish_mackerel: 1417, maize: 1183, meat_beef: 1745, oil: 1518, plantains: 606, rice: 1744, sorghum: 600, wheat_flour: 948
Number of observations (other): : 
Data coverage (food): 8.07%
Data coverage previous 12 months (food): 29.06%
Average annualized food inflation: 2.88%
Maximum food drawdown: -3.47%
Average annualized food volatility: 2.42%
Average monthly food price correlation between markets: 0.37
Average annual food price correlation between markets: 0.59
R squared individual food items: bananas: 0.96, cassava: 0.95, cocoyam: 0.98, fish_mackerel: 0.97, maize: 0.96, meat_beef: 0.98, oil: 0.97, plantains: 0.96, rice: 0.97, sorghum: 0.99, wheat_flour: 0.99
R squared individual other items: : 
Index confidence score: 0.97
Imputation model: bananas: two-stage cubist (Andree and Pape, 2023), cassava: two-stage cubist (Andree and Pape, 2023), cocoyam: two-stage cubist (Andree and Pape, 2023), fish_mackerel: two-stage cubist (Andree and Pape, 2023), maize: two-stage cubist (Andree and Pape, 2023), meat_beef: two-stage cubist (Andree and Pape, 2023), oil: two-stage cubist (Andree and Pape, 2023), plantains: two-stage cubist (Andree and Pape, 2023), rice: two-stage cubist (Andree and Pape, 2023), sorghum: two-stage cubist (Andree and Pape, 2023), wheat_flour: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Congo, Dem. Rep. (see working paper for more information)
Components: Beans (1 KG, Index Weight = 1), Cassava (Cossette) (1 KG, Index Weight = 1), Cassava Flour (1 KG, Index Weight = 1), Fish (Fresh) (1 KG, Index Weight = 1), Fish (Salted) (1 KG, Index Weight = 1), Fish (Smoked) (1 KG, Index Weight = 1), Maize (1 KG, Index Weight = 1), Maize Meal (1 KG, Index Weight = 1), Meat (Beef) (1 KG, Index Weight = 1), Meat (Chicken) (1 KG, Index Weight = 1), Meat (Goat, With Bones) (1 KG, Index Weight = 1), Oil (Palm) (1 L, Index Weight = 1), Plantains (1 KG, Index Weight = 1), Rice (Local) (1 KG, Index Weight = 1), Salt (1 KG, Index Weight = 1), Sugar (1 KG, Index Weight = 1), Wheat Flour (1 KG, Index Weight = 1)
Currency: CDF
Number of markets used: 86
Number of markets covered: 86
Number of food items: 17
Number of observations (food): beans: 3310, cassava: 2659, cassava_flour: 3258, fish: 2660, fish_salted: 2504, fish_smoked: 2443, maize: 3160, maize_meal: 2871, meat_beef: 2391, meat_chicken: 1545, meat_goat_with_bones: 2471, oil: 3464, plantains: 2777, rice: 3029, salt: 2890, sugar: 2958, wheat_flour: 1831
Number of observations (other): exchange_rate: 2977
Data coverage (food): 15.97%
Data coverage previous 12 months (food): 16.65%
Average annualized food inflation: 6.63%
Maximum food drawdown: -14.02%
Average annualized food volatility: 7.18%
Average monthly food price correlation between markets: 0.23
Average annual food price correlation between markets: 0.42
R squared individual food items: beans: 0.84, cassava: 0.93, cassava_flour: 0.81, fish: 0.94, fish_salted: 0.94, fish_smoked: 0.95, maize: 0.93, maize_meal: 0.93, meat_beef: 0.97, meat_chicken: 0.95, meat_goat_with_bones: 0.96, oil: 0.8, plantains: 0.91, rice: 0.93, salt: 0.91, sugar: 0.93, wheat_flour: 0.94
R squared individual other items: exchange_rate: 0.98
Index confidence score: 0.93
Imputation model: beans: cubist (Andree, 2021), cassava: two-stage cubist (Andree and Pape, 2023), cassava_flour: cubist (Andree, 2021), fish: two-stage cubist (Andree and Pape, 2023), fish_salted: two-stage cubist (Andree and Pape, 2023), fish_smoked: two-stage cubist (Andree and Pape, 2023), maize: two-stage cubist (Andree and Pape, 2023), maize_meal: two-stage cubist (Andree and Pape, 2023), meat_beef: two-stage cubist (Andree and Pape, 2023), meat_chicken: two-stage cubist (Andree and Pape, 2023), meat_goat_with_bones: two-stage cubist (Andree and Pape, 2023), oil: cubist (Andree, 2021), plantains: two-stage cubist (Andree and Pape, 2023), rice: two-stage cubist (Andree and Pape, 2023), salt: two-stage cubist (Andree and Pape, 2023), sugar: two-stage cubist (Andree and Pape, 2023), wheat_flour: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Congo, Rep. (see working paper for more information)
Components: Beans (White) (1 KG, Index Weight = 1), Cassava Flour (1 KG, Index Weight = 1), Oil (Vegetable) (1 L, Index Weight = 1), Rice (Mixed, Low Quality) (1 KG, Index Weight = 1)
Currency: XAF
Number of markets used: 13
Number of markets covered: 13
Number of food items: 4
Number of observations (food): beans: 643, cassava_flour: 564, oil: 484, rice: 661
Number of observations (other): : 
Data coverage (food): 30.15%
Data coverage previous 12 months (food): 0%
Average annualized food inflation: 1.08%
Maximum food drawdown: -8.59%
Average annualized food volatility: 5.54%
Average monthly food price correlation between markets: 0.2
Average annual food price correlation between markets: 0.24
R squared individual food items: beans: 0.86, cassava_flour: 0.8, oil: 0.79, rice: 0.83
R squared individual other items: : 
Index confidence score: 0.82
Imputation model: beans: two-stage cubist (Andree and Pape, 2023), cassava_flour: two-stage cubist (Andree and Pape, 2023), oil: two-stage cubist (Andree and Pape, 2023), rice: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Gambia, The (see working paper for more information)
Components: Apples (Red) (1 KG, Index Weight = 1), Bananas (1 KG, Index Weight = 1), Beans (Dry) (1 KG, Index Weight = 1), Bread (1 KG, Index Weight = 1), Cabbage (1 KG, Index Weight = 1), Carrots (1 KG, Index Weight = 1), Cassava (1 KG, Index Weight = 1), Coffee (Instant) (1 Unit, Index Weight = 1), Eggs (1 Unit, Index Weight = 12), Fish (Bonga) (1 KG, Index Weight = 1), Garlic (1 KG, Index Weight = 1), Groundnuts (Shelled) (1 KG, Index Weight = 1), Maize (1 KG, Index Weight = 1), Meat (Beef) (1 KG, Index Weight = 1), Meat (Chicken) (1 KG, Index Weight = 1), Milk (1 KG, Index Weight = 1), Millet (1 KG, Index Weight = 1), Oil (Vegetable) (1 L, Index Weight = 1), Onions (1 KG, Index Weight = 1), Oranges (Big Size) (1 KG, Index Weight = 1), Sweet Potatoes (1 KG, Index Weight = 1), Rice (Small Grain, Imported) (1 KG, Index Weight = 1), Salt (1 KG, Index Weight = 1), Sugar (1 KG, Index Weight = 1), Tea (1 Unit, Index Weight = 1), Tomatoes (1 KG, Index Weight = 1)
Currency: GMD
Number of markets used: 28
Number of markets covered: 28
Number of food items: 26
Number of observations (food): apples: 1431, bananas: 1570, beans: 1544, bread: 1489, cabbage: 1546, carrots: 1573, cassava: 1256, coffee_instant: 995, eggs: 1508, fish: 1508, garlic: 1479, groundnuts: 2847, maize: 1473, meat_beef: 1529, meat_chicken: 1425, milk: 1543, millet: 2725, oil: 1566, onions: 1549, oranges: 1333, potatoes: 1475, rice: 3189, salt: 1537, sugar: 1535, tea: 1506, tomatoes: 1537
Number of observations (other): fuel_diesel: 1560, fuel_petrol_gasoline: 1547
Data coverage (food): 29.6%
Data coverage previous 12 months (food): 78.87%
Average annualized food inflation: 6.24%
Maximum food drawdown: -21.72%
Average annualized food volatility: 7.35%
Average monthly food price correlation between markets: 0.58
Average annual food price correlation between markets: 0.84
R squared individual food items: apples: 0.95, bananas: 0.91, beans: 0.91, bread: 0.91, cabbage: 0.85, carrots: 0.85, cassava: 0.89, coffee_instant: 0.95, eggs: 0.97, fish: 0.88, garlic: 0.91, groundnuts: 0.88, maize: 0.91, meat_beef: 0.97, meat_chicken: 0.93, milk: 0.9, millet: 0.83, oil: 0.95, onions: 0.9, oranges: 0.91, potatoes: 0.88, rice: 0.92, salt: 0.96, sugar: 0.94, tea: 0.96, tomatoes: 0.86
R squared individual other items: fuel_diesel: 0.98, fuel_petrol_gasoline: 0.98
Index confidence score: 0.94
Imputation model: apples: two-stage cubist (Andree and Pape, 2023), bananas: two-stage cubist (Andree and Pape, 2023), beans: two-stage cubist (Andree and Pape, 2023), bread: two-stage cubist (Andree and Pape, 2023), cabbage: two-stage cubist (Andree and Pape, 2023), carrots: two-stage cubist (Andree and Pape, 2023), cassava: two-stage cubist (Andree and Pape, 2023), coffee_instant: two-stage cubist (Andree and Pape, 2023), eggs: two-stage cubist (Andree and Pape, 2023), fish: two-stage cubist (Andree and Pape, 2023), garlic: two-stage cubist (Andree and Pape, 2023), groundnuts: cubist (Andree, 2021), maize: two-stage cubist (Andree and Pape, 2023), meat_beef: two-stage cubist (Andree and Pape, 2023), meat_chicken: two-stage cubist (Andree and Pape, 2023), milk: two-stage cubist (Andree and Pape, 2023), millet: cubist (Andree, 2021), oil: two-stage cubist (Andree and Pape, 2023), onions: two-stage cubist (Andree and Pape, 2023), oranges: two-stage cubist (Andree and Pape, 2023), potatoes: two-stage cubist (Andree and Pape, 2023), rice: cubist (Andree, 2021), salt: two-stage cubist (Andree and Pape, 2023), sugar: two-stage cubist (Andree and Pape, 2023), tea: two-stage cubist (Andree and Pape, 2023), tomatoes: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Guinea-Bissau (see working paper for more information)
Components: Millet (1 KG, Index Weight = 1), Oil (Palm) (1 L, Index Weight = 1), Rice (Imported) (1 KG, Index Weight = 1), Sorghum (1 KG, Index Weight = 1), Sugar (1 KG, Index Weight = 1)
Currency: XOF
Number of markets used: 45
Number of markets covered: 45
Number of food items: 5
Number of observations (food): millet: 877, oil: 1538, rice: 1526, sorghum: 528, sugar: 1496
Number of observations (other): : 
Data coverage (food): 13.39%
Data coverage previous 12 months (food): 45.96%
Average annualized food inflation: 1.56%
Maximum food drawdown: -27.39%
Average annualized food volatility: 11.99%
Average monthly food price correlation between markets: 0.78
Average annual food price correlation between markets: 0.9
R squared individual food items: millet: 0.76, oil: 0.92, rice: 0.93, sorghum: 0.8, sugar: 0.86
R squared individual other items: : 
Index confidence score: 0.87
Imputation model: millet: cubist (Andree, 2021), oil: cubist (Andree, 2021), rice: cubist (Andree, 2021), sorghum: cubist (Andree, 2021), sugar: cubist (Andree, 2021)
 

Information on the model used for Haiti (see working paper for more information)
Components: Beans (Black) (1 Marmite, Index Weight = 0.37), Maize Meal (Local) (1 Marmite, Index Weight = 0.37), Oil (Vegetable, Imported) (1 Gallon, Index Weight = 0.26), Pasta (350 G, Index Weight = 2.86), Rice (Tchako) (1 Marmite, Index Weight = 0.37), Sorghum (1 Marmite, Index Weight = 0.37), Sugar (White) (1 Marmite, Index Weight = 0.37), Wheat Flour (Imported) (1 Marmite, Index Weight = 0.37)
Currency: HTG
Number of markets used: 9
Number of markets covered: 9
Number of food items: 8
Number of observations (food): beans: 1121, maize_meal: 1682, oil: 1022, pasta: 579, rice: 1304, sorghum: 676, sugar: 723, wheat_flour: 1673
Number of observations (other): : 
Data coverage (food): 61.59%
Data coverage previous 12 months (food): 48.38%
Average annualized food inflation: 14.08%
Maximum food drawdown: -32.67%
Average annualized food volatility: 11.48%
Average monthly food price correlation between markets: 0.53
Average annual food price correlation between markets: 0.9
R squared individual food items: beans: 0.92, maize_meal: 0.83, oil: 0.96, pasta: 0.97, rice: 0.92, sorghum: 0.91, sugar: 0.93, wheat_flour: 0.87
R squared individual other items: : 
Index confidence score: 0.95
Imputation model: beans: two-stage cubist (Andree and Pape, 2023), maize_meal: cubist (Andree, 2021), oil: two-stage cubist (Andree and Pape, 2023), pasta: two-stage cubist (Andree and Pape, 2023), rice: cubist (Andree, 2021), sorghum: two-stage cubist (Andree and Pape, 2023), sugar: two-stage cubist (Andree and Pape, 2023), wheat_flour: cubist (Andree, 2021)
 

Information on the model used for Iraq (see working paper for more information)
Components: Beans (White) (1 KG, Index Weight = 1), Bread (Khoboz) (1 Unit, Index Weight = 1), Cheese (Local) (1 KG, Index Weight = 1), Dates (1 KG, Index Weight = 1), Eggs (1 Unit, Index Weight = 12), Fish (1 KG, Index Weight = 1), Lentils (1 KG, Index Weight = 1), Meat (Beef) (1 KG, Index Weight = 1), Meat (Chicken) (1 KG, Index Weight = 1), Milk (1 L, Index Weight = 1), Oil (Vegetable) (1 L, Index Weight = 1), Potatoes (1 KG, Index Weight = 1), Rice (1 KG, Index Weight = 1), Salt (Iodised) (1 KG, Index Weight = 1), Sugar (1 KG, Index Weight = 1), Tea (1 KG, Index Weight = 1), Tomatoes (1 KG, Index Weight = 1), Wheat Flour (1 KG, Index Weight = 1)
Currency: IQD
Number of markets used: 20
Number of markets covered: 20
Number of food items: 18
Number of observations (food): beans: 1192, bread: 1835, cheese: 1133, dates: 1184, eggs: 1214, fish: 1239, lentils: 1021, meat_beef: 1201, meat_chicken: 1201, milk: 1258, oil: 1755, potatoes: 1093, rice: 2122, salt: 1156, sugar: 1716, tea: 1189, tomatoes: 1238, wheat_flour: 1596
Number of observations (other): fuel_gas: 1234, fuel_kerosene: 1175, fuel_petrol_gasoline: 1147, wage_non_qualified_labour: 1083
Data coverage (food): 49%
Data coverage previous 12 months (food): 77.94%
Average annualized food inflation: 1.17%
Maximum food drawdown: -11.71%
Average annualized food volatility: 3.01%
Average monthly food price correlation between markets: 0.21
Average annual food price correlation between markets: 0.42
R squared individual food items: beans: 0.97, bread: 0.98, cheese: 0.97, dates: 0.92, eggs: 0.98, fish: 0.95, lentils: 0.95, meat_beef: 0.99, meat_chicken: 0.96, milk: 0.96, oil: 0.96, potatoes: 0.94, rice: 0.95, salt: 0.96, sugar: 0.95, tea: 0.98, tomatoes: 0.91, wheat_flour: 0.93
R squared individual other items: fuel_gas: 0.99, fuel_kerosene: 0.97, fuel_petrol_gasoline: 0.99, wage_non_qualified_labour: 0.99
Index confidence score: 0.97
Imputation model: beans: two-stage cubist (Andree and Pape, 2023), bread: cubist (Andree, 2021), cheese: two-stage cubist (Andree and Pape, 2023), dates: two-stage cubist (Andree and Pape, 2023), eggs: two-stage cubist (Andree and Pape, 2023), fish: two-stage cubist (Andree and Pape, 2023), lentils: two-stage cubist (Andree and Pape, 2023), meat_beef: two-stage cubist (Andree and Pape, 2023), meat_chicken: two-stage cubist (Andree and Pape, 2023), milk: two-stage cubist (Andree and Pape, 2023), oil: cubist (Andree, 2021), potatoes: two-stage cubist (Andree and Pape, 2023), rice: cubist (Andree, 2021), salt: two-stage cubist (Andree and Pape, 2023), sugar: cubist (Andree, 2021), tea: two-stage cubist (Andree and Pape, 2023), tomatoes: two-stage cubist (Andree and Pape, 2023), wheat_flour: cubist (Andree, 2021)
 

Information on the model used for Lao PDR (see working paper for more information)
Components: Eggs (1 Unit, Index Weight = 12), Fish (Catfish) (1 KG, Index Weight = 1), Fish (Tilapia, Farmed) (1 KG, Index Weight = 1), Garlic (Small) (1 KG, Index Weight = 1), Meat (Beef, First Quality) (1 KG, Index Weight = 1), Meat (Beef, Second Quality) (1 KG, Index Weight = 1), Meat (Buffalo, First Quality) (1 KG, Index Weight = 1), Meat (Buffalo, Second Quality) (1 KG, Index Weight = 1), Meat (Chicken) (1 KG, Index Weight = 1), Meat (Pork, First Quality) (1 KG, Index Weight = 1), Meat (Pork, Second Quality) (1 KG, Index Weight = 1), Oil (Soybean) (1 L, Index Weight = 1), Rice (Glutinous, Second Quality) (1 KG, Index Weight = 1), Sugar (Brown) (1 KG, Index Weight = 1)
Currency: LAK
Number of markets used: 17
Number of markets covered: 17
Number of food items: 14
Number of observations (food): eggs: 1717, fish_catfish: 1668, fish_tilapia_farmed: 1663, garlic: 1674, meat_beef_first_quality: 1955, meat_beef_second_quality: 1948, meat_buffalo_first_quality: 1965, meat_buffalo_second_quality: 1957, meat_chicken: 1906, meat_pork_first_quality: 1953, meat_pork_second_quality: 1920, oil: 1665, rice: 2015, sugar: 1618
Number of observations (other): fuel_diesel: 1558, fuel_petrol_gasoline: 1588
Data coverage (food): 62.23%
Data coverage previous 12 months (food): 65.93%
Average annualized food inflation: 6.62%
Maximum food drawdown: -7.14%
Average annualized food volatility: 3.48%
Average monthly food price correlation between markets: 0.36
Average annual food price correlation between markets: 0.74
R squared individual food items: eggs: 0.99, fish_catfish: 0.97, fish_tilapia_farmed: 0.97, garlic: 0.9, meat_beef_first_quality: 0.99, meat_beef_second_quality: 0.99, meat_buffalo_first_quality: 0.99, meat_buffalo_second_quality: 0.98, meat_chicken: 0.96, meat_pork_first_quality: 0.99, meat_pork_second_quality: 0.99, oil: 0.95, rice: 0.99, sugar: 0.98
R squared individual other items: fuel_diesel: 0.92, fuel_petrol_gasoline: 0.98
Index confidence score: 0.99
Imputation model: eggs: cubist (Andree, 2021), fish_catfish: two-stage cubist (Andree and Pape, 2023), fish_tilapia_farmed: two-stage cubist (Andree and Pape, 2023), garlic: two-stage cubist (Andree and Pape, 2023), meat_beef_first_quality: cubist (Andree, 2021), meat_beef_second_quality: cubist (Andree, 2021), meat_buffalo_first_quality: cubist (Andree, 2021), meat_buffalo_second_quality: cubist (Andree, 2021), meat_chicken: cubist (Andree, 2021), meat_pork_first_quality: cubist (Andree, 2021), meat_pork_second_quality: cubist (Andree, 2021), oil: two-stage cubist (Andree and Pape, 2023), rice: cubist (Andree, 2021), sugar: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Lebanon (see working paper for more information)
Components: Beans (White) (1 KG, Index Weight = 1), Bread (Pita) (1 KG, Index Weight = 1), Bulgur (Brown) (1 KG, Index Weight = 1), Cabbage (1 KG, Index Weight = 1), Cheese (Picon) (160 G, Index Weight = 6.25), Chickpeas (1 KG, Index Weight = 1), Cucumbers (Greenhouse) (1 KG, Index Weight = 1), Eggs (30 pcs, Index Weight = 0.33), Fish (Sardine, Canned) (125 G, Index Weight = 8), Fish (Tuna, Canned) (185 G, Index Weight = 5.41), Lentils (Red) (1 KG, Index Weight = 1), Lettuce (1 Head, Index Weight = 2), Meat (Beef, Canned) (200 G, Index Weight = 5), Meat (Chicken, Whole, Frozen) (1 KG, Index Weight = 1), Milk (Powder) (900 G, Index Weight = 1.11), Oil (Sunflower) (5 L, Index Weight = 0.2), Pasta (Spaghetti) (1 KG, Index Weight = 1), Rice (Imported, Egyptian) (1 KG, Index Weight = 1), Salt (1 KG, Index Weight = 1), Sugar (White) (1 KG, Index Weight = 1), Tomatoes (Paste) (1.3 KG, Index Weight = 0.77), Wheat Flour (1 KG, Index Weight = 1)
Currency: LBP
Number of markets used: 27
Number of markets covered: 27
Number of food items: 22
Number of observations (food): beans: 2927, bread: 2767, bulgur: 2938, cabbage: 1302, cheese: 2908, chickpeas: 2212, cucumbers: 1154, eggs: 2813, fish_sardine_canned: 1349, fish_tuna_canned: 2603, lentils: 1775, lettuce: 892, meat_beef_canned: 2956, meat_chicken_whole_frozen: 1198, milk: 2889, oil: 2337, pasta: 2915, rice: 2916, salt: 2673, sugar: 2870, tomatoes_paste: 2381, wheat_flour: 1801
Number of observations (other): fuel_diesel: 1911, fuel_gas: 1909, fuel_petrol_gasoline_95_octane: 1911
Data coverage (food): 61.7%
Data coverage previous 12 months (food): 42.09%
Average annualized food inflation: 39.52%
Maximum food drawdown: -12.48%
Average annualized food volatility: 17.18%
Average monthly food price correlation between markets: 0.76
Average annual food price correlation between markets: 0.99
R squared individual food items: beans: 0.9, bread: 0.97, bulgur: 0.94, cabbage: 0.9, cheese: 0.95, chickpeas: 0.91, cucumbers: 0.88, eggs: 0.89, fish_sardine_canned: 0.96, fish_tuna_canned: 0.92, lentils: 0.95, lettuce: 0.94, meat_beef_canned: 0.94, meat_chicken_whole_frozen: 0.94, milk: 0.97, oil: 0.97, pasta: 0.86, rice: 0.93, salt: 0.94, sugar: 0.95, tomatoes_paste: 0.92, wheat_flour: 0.91
R squared individual other items: fuel_diesel: 1, fuel_gas: 0.99, fuel_petrol_gasoline_95_octane: 0.99
Index confidence score: 0.94
Imputation model: beans: cubist (Andree, 2021), bread: cubist (Andree, 2021), bulgur: cubist (Andree, 2021), cabbage: cubist (Andree, 2021), cheese: cubist (Andree, 2021), chickpeas: cubist (Andree, 2021), cucumbers: cubist (Andree, 2021), eggs: cubist (Andree, 2021), fish_sardine_canned: cubist (Andree, 2021), fish_tuna_canned: cubist (Andree, 2021), lentils: two-stage cubist (Andree and Pape, 2023), lettuce: two-stage cubist (Andree and Pape, 2023), meat_beef_canned: cubist (Andree, 2021), meat_chicken_whole_frozen: cubist (Andree, 2021), milk: cubist (Andree, 2021), oil: cubist (Andree, 2021), pasta: cubist (Andree, 2021), rice: cubist (Andree, 2021), salt: cubist (Andree, 2021), sugar: cubist (Andree, 2021), tomatoes_paste: cubist (Andree, 2021), wheat_flour: cubist (Andree, 2021)
 

Information on the model used for Liberia (see working paper for more information)
Components: Cassava (Fresh) (50 KG, Index Weight = 0.02), Cowpeas (1 KG, Index Weight = 1), Oil (Palm) (1 Gallon, Index Weight = 0.26), Rice (Imported) (50 KG, Index Weight = 0.02)
Currency: LRD
Number of markets used: 24
Number of markets covered: 24
Number of food items: 4
Number of observations (food): cassava: 1333, cowpeas: 1399, oil: 1331, rice: 1847
Number of observations (other): fuel_petrol_gasoline: 1728
Data coverage (food): 31.09%
Data coverage previous 12 months (food): 0%
Average annualized food inflation: 7.05%
Maximum food drawdown: -8.62%
Average annualized food volatility: 5.58%
Average monthly food price correlation between markets: 0.16
Average annual food price correlation between markets: 0.49
R squared individual food items: cassava: 0.89, cowpeas: 0.95, oil: 0.93, rice: 0.98
R squared individual other items: fuel_petrol_gasoline: 0.93
Index confidence score: 0.95
Imputation model: cassava: two-stage cubist (Andree and Pape, 2023), cowpeas: two-stage cubist (Andree and Pape, 2023), oil: two-stage cubist (Andree and Pape, 2023), rice: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Mali (see working paper for more information)
Components: Beans (Niebe) (1 KG, Index Weight = 1), Maize (1 KG, Index Weight = 1), Millet (1 KG, Index Weight = 1), Rice (Local) (1 KG, Index Weight = 1), Sorghum (1 KG, Index Weight = 1)
Currency: XOF
Number of markets used: 127
Number of markets covered: 127
Number of food items: 5
Number of observations (food): beans: 7318, maize: 8960, millet: 13298, rice: 12364, sorghum: 11674
Number of observations (other): : 
Data coverage (food): 42.64%
Data coverage previous 12 months (food): 31.61%
Average annualized food inflation: 3.98%
Maximum food drawdown: -33.65%
Average annualized food volatility: 7.97%
Average monthly food price correlation between markets: 0.5
Average annual food price correlation between markets: 0.78
R squared individual food items: beans: 0.92, maize: 0.91, millet: 0.92, rice: 0.94, sorghum: 0.92
R squared individual other items: : 
Index confidence score: 0.92
Imputation model: beans: cubist (Andree, 2021), maize: cubist (Andree, 2021), millet: cubist (Andree, 2021), rice: cubist (Andree, 2021), sorghum: cubist (Andree, 2021)
 

Information on the model used for Myanmar (see working paper for more information)
Components: Pulses (1 KG, Index Weight = 1), Rice (Low Quality) (1 KG, Index Weight = 1), Salt (1 KG, Index Weight = 1)
Currency: MMK
Number of markets used: 226
Number of markets covered: 226
Number of food items: 3
Number of observations (food): pulses: 5068, rice: 7427, salt: 6721
Number of observations (other): : 
Data coverage (food): 15.24%
Data coverage previous 12 months (food): 42.51%
Average annualized food inflation: 9.62%
Maximum food drawdown: -24.07%
Average annualized food volatility: 10.63%
Average monthly food price correlation between markets: 0.25
Average annual food price correlation between markets: 0.63
R squared individual food items: pulses: 0.91, rice: 0.9, salt: 0.86
R squared individual other items: : 
Index confidence score: 0.89
Imputation model: pulses: cubist (Andree, 2021), rice: cubist (Andree, 2021), salt: cubist (Andree, 2021)
 

Information on the model used for Mozambique (see working paper for more information)
Components: Cowpeas (1 KG, Index Weight = 1), Groundnuts (Small, Shelled) (1 KG, Index Weight = 1), Maize (White) (1 KG, Index Weight = 1), Maize Meal (White, First Grade) (1 KG, Index Weight = 1), Oil (Vegetable, Local) (1 L, Index Weight = 1), Rice (Imported) (1 KG, Index Weight = 1), Sugar (Brown, Local) (1 KG, Index Weight = 1), Wheat Flour (Local) (1 KG, Index Weight = 1)
Currency: MZN
Number of markets used: 99
Number of markets covered: 99
Number of food items: 8
Number of observations (food): cowpeas: 3663, groundnuts: 2774, maize: 4222, maize_meal: 3157, oil: 4164, rice: 4171, sugar: 4178, wheat_flour: 3233
Number of observations (other): : 
Data coverage (food): 18.85%
Data coverage previous 12 months (food): 13.91%
Average annualized food inflation: 7.77%
Maximum food drawdown: -31.25%
Average annualized food volatility: 7.99%
Average monthly food price correlation between markets: 0.47
Average annual food price correlation between markets: 0.89
R squared individual food items: cowpeas: 0.79, groundnuts: 0.89, maize: 0.94, maize_meal: 0.93, oil: 0.95, rice: 0.94, sugar: 0.96, wheat_flour: 0.91
R squared individual other items: : 
Index confidence score: 0.92
Imputation model: cowpeas: cubist (Andree, 2021), groundnuts: cubist (Andree, 2021), maize: cubist (Andree, 2021), maize_meal: cubist (Andree, 2021), oil: cubist (Andree, 2021), rice: cubist (Andree, 2021), sugar: cubist (Andree, 2021), wheat_flour: cubist (Andree, 2021)
 

Information on the model used for Niger (see working paper for more information)
Components: Millet (1 KG, Index Weight = 1), Rice (Imported) (1 KG, Index Weight = 1), Sorghum (1 KG, Index Weight = 1)
Currency: XOF
Number of markets used: 79
Number of markets covered: 79
Number of food items: 3
Number of observations (food): millet: 11554, rice: 10872, sorghum: 10444
Number of observations (other): : 
Data coverage (food): 70.05%
Data coverage previous 12 months (food): 47.5%
Average annualized food inflation: 3.27%
Maximum food drawdown: -23.75%
Average annualized food volatility: 9.38%
Average monthly food price correlation between markets: 0.43
Average annual food price correlation between markets: 0.75
R squared individual food items: millet: 0.86, rice: 0.94, sorghum: 0.82
R squared individual other items: : 
Index confidence score: 0.88
Imputation model: millet: cubist (Andree, 2021), rice: cubist (Andree, 2021), sorghum: cubist (Andree, 2021)
 

Information on the model used for Nigeria (see working paper for more information)
Components: Cassava Meal (Gari, Yellow) (100 KG, Index Weight = 0.01), Cowpeas (White) (100 KG, Index Weight = 0.01), Gari (White) (100 KG, Index Weight = 0.01), Groundnuts (Shelled) (100 KG, Index Weight = 0.01), Maize (White) (100 KG, Index Weight = 0.01), Millet (100 KG, Index Weight = 0.01), Rice (Imported) (50 KG, Index Weight = 0.02), Sorghum (White) (100 KG, Index Weight = 0.01)
Currency: NGN
Number of markets used: 35
Number of markets covered: 35
Number of food items: 8
Number of observations (food): cassava_meal: 1255, cowpeas: 1536, gari: 1426, groundnuts: 1473, maize: 1723, millet: 1610, rice: 1447, sorghum: 1708
Number of observations (other): fuel_diesel: 1522, fuel_petrol_gasoline: 1533
Data coverage (food): 21.97%
Data coverage previous 12 months (food): 25.45%
Average annualized food inflation: 8.16%
Maximum food drawdown: -35.26%
Average annualized food volatility: 12.01%
Average monthly food price correlation between markets: 0.81
Average annual food price correlation between markets: 0.96
R squared individual food items: cassava_meal: 0.98, cowpeas: 0.95, gari: 0.98, groundnuts: 0.97, maize: 0.87, millet: 0.87, rice: 0.97, sorghum: 0.85
R squared individual other items: fuel_diesel: 0.98, fuel_petrol_gasoline: 0.99
Index confidence score: 0.95
Imputation model: cassava_meal: two-stage cubist (Andree and Pape, 2023), cowpeas: two-stage cubist (Andree and Pape, 2023), gari: two-stage cubist (Andree and Pape, 2023), groundnuts: two-stage cubist (Andree and Pape, 2023), maize: cubist (Andree, 2021), millet: cubist (Andree, 2021), rice: two-stage cubist (Andree and Pape, 2023), sorghum: cubist (Andree, 2021)
 

Information on the model used for Sudan (see working paper for more information)
Components: Millet (3.5 KG, Index Weight = 0.29), Sorghum (3 KG, Index Weight = 0.33), Wheat (90 KG, Index Weight = 0.01)
Currency: SDG
Number of markets used: 14
Number of markets covered: 14
Number of food items: 4
Number of observations (food): millet: 2095, sorghum: 1713, sorghum_food_aid: 1004, wheat: 704
Number of observations (other): : 
Data coverage (food): 49.75%
Data coverage previous 12 months (food): 39.14%
Average annualized food inflation: 54.42%
Maximum food drawdown: -15.64%
Average annualized food volatility: 18.54%
Average monthly food price correlation between markets: 0.49
Average annual food price correlation between markets: 0.93
R squared individual food items: millet: 0.93, sorghum: 0.93, sorghum_food_aid: 0.93, wheat: 0.95
R squared individual other items: : 
Index confidence score: 0.93
Imputation model: millet: cubist (Andree, 2021), sorghum: cubist (Andree, 2021), sorghum_food_aid: cubist (Andree, 2021), wheat: cubist (Andree, 2021)
 

Information on the model used for Somalia (see working paper for more information)
Components: Maize (White) (1 KG, Index Weight = 1), Milk (Camel) (1 L, Index Weight = 1), Oil (Vegetable, Imported) (1 L, Index Weight = 1), Rice (Imported) (1 KG, Index Weight = 1), Sorghum (Red) (1 KG, Index Weight = 1)
Currency: SOS
Number of markets used: 30
Number of markets covered: 30
Number of food items: 5
Number of observations (food): maize: 2433, milk: 734, oil: 811, rice: 2542, sorghum: 2154
Number of observations (other): exchange_rate: 1416, fuel_diesel: 896
Data coverage (food): 29.21%
Data coverage previous 12 months (food): 30%
Average annualized food inflation: 5.23%
Maximum food drawdown: -37.62%
Average annualized food volatility: 9.52%
Average monthly food price correlation between markets: 0.53
Average annual food price correlation between markets: 0.84
R squared individual food items: maize: 0.93, milk: 0.89, oil: 0.91, rice: 0.88, sorghum: 0.87
R squared individual other items: exchange_rate: 0.96, fuel_diesel: 0.91
Index confidence score: 0.9
Imputation model: maize: two-stage cubist (Andree and Pape, 2023), milk: two-stage cubist (Andree and Pape, 2023), oil: two-stage cubist (Andree and Pape, 2023), rice: cubist (Andree, 2021), sorghum: cubist (Andree, 2021)
 

Information on the model used for South Sudan (see working paper for more information)
Components: Beans (Red) (1 KG, Index Weight = 1), Cassava (Dry) (3.5 KG, Index Weight = 0.29), Groundnuts (Shelled) (1 KG, Index Weight = 1), Maize (White) (3.5 KG, Index Weight = 0.29), Millet (White) (3.5 KG, Index Weight = 0.29), Oil (Vegetable) (1 L, Index Weight = 1), Sesame (3.5 KG, Index Weight = 0.29), Sorghum (White, Imported) (3.5 KG, Index Weight = 0.29), Wheat Flour (1 KG, Index Weight = 1)
Currency: SSP
Number of markets used: 29
Number of markets covered: 29
Number of food items: 9
Number of observations (food): beans: 1980, cassava: 508, groundnuts: 1506, maize: 1377, millet: 913, oil: 1728, sesame: 1313, sorghum: 1893, wheat_flour: 1763
Number of observations (other): fuel_diesel: 1106, fuel_petrol_gasoline: 1120
Data coverage (food): 25.12%
Data coverage previous 12 months (food): 53.48%
Average annualized food inflation: 40.84%
Maximum food drawdown: -15.58%
Average annualized food volatility: 25.01%
Average monthly food price correlation between markets: 0.54
Average annual food price correlation between markets: 0.95
R squared individual food items: beans: 0.9, cassava: 0.92, groundnuts: 0.88, maize: 0.86, millet: 0.91, oil: 0.9, sesame: 0.88, sorghum: 0.91, wheat_flour: 0.9
R squared individual other items: fuel_diesel: 0.91, fuel_petrol_gasoline: 0.91
Index confidence score: 0.9
Imputation model: beans: cubist (Andree, 2021), cassava: two-stage cubist (Andree and Pape, 2023), groundnuts: cubist (Andree, 2021), maize: cubist (Andree, 2021), millet: cubist (Andree, 2021), oil: two-stage cubist (Andree and Pape, 2023), sesame: cubist (Andree, 2021), sorghum: cubist (Andree, 2021), wheat_flour: cubist (Andree, 2021)
 

Information on the model used for Syrian Arab Republic (see working paper for more information)
Components: Apples (1 KG, Index Weight = 1), Bananas (1 KG, Index Weight = 1), Beans (White) (1 KG, Index Weight = 1), Bread (Bakery) (1.1 KG, Index Weight = 0.91), Bulgur (1 KG, Index Weight = 1), Carrots (1 KG, Index Weight = 1), Cheese (1 KG, Index Weight = 1), Chickpeas (1 KG, Index Weight = 1), Dates (1 KG, Index Weight = 1), Eggplants (1 KG, Index Weight = 1), Eggs (30 pcs, Index Weight = 0.33), Fish (Tuna, Canned) (160 G, Index Weight = 6.25), Lentils (1 KG, Index Weight = 1), Meat (Beef, Minced) (1 KG, Index Weight = 1), Meat (Chicken, Plucked) (1 KG, Index Weight = 1), Oil (1 L, Index Weight = 1), Parsley (1 Packet, Index Weight = 2), Potatoes (1 KG, Index Weight = 1), Rice (1 KG, Index Weight = 1), Salt (Iodised) (1 KG, Index Weight = 1), Sugar (1 KG, Index Weight = 1), Tomatoes (1 KG, Index Weight = 1), Wheat Flour (1 KG, Index Weight = 1), Yogurt (1 KG, Index Weight = 1)
Currency: SYP
Number of markets used: 97
Number of markets covered: 97
Number of food items: 24
Number of observations (food): apples: 3635, bananas: 3483, beans: 4109, bread: 5034, bulgur: 4141, carrots: 3261, cheese: 4203, chickpeas: 4183, dates: 4357, eggplants: 3606, eggs: 3770, fish_tuna_canned: 4358, lentils: 5299, meat_beef_minced: 3917, meat_chicken_plucked: 3600, oil: 5409, parsley: 4366, potatoes: 3668, rice: 5205, salt: 4035, sugar: 5457, tomatoes: 4431, wheat_flour: 5146, yogurt: 4382
Number of observations (other): exchange_rate_unofficial: 3631, fuel_diesel: 5005, fuel_gas: 4986, livestock_sheep_two_year_old_male: 4667, wage_non_qualified_labour: 4755
Data coverage (food): 29.51%
Data coverage previous 12 months (food): 59.15%
Average annualized food inflation: 33.15%
Maximum food drawdown: -17.5%
Average annualized food volatility: 13.2%
Average monthly food price correlation between markets: 0.63
Average annual food price correlation between markets: 0.96
R squared individual food items: apples: 0.91, bananas: 0.92, beans: 0.96, bread: 0.98, bulgur: 0.95, carrots: 0.91, cheese: 0.95, chickpeas: 0.95, dates: 0.94, eggplants: 0.89, eggs: 0.96, fish_tuna_canned: 0.95, lentils: 0.96, meat_beef_minced: 0.97, meat_chicken_plucked: 0.95, oil: 0.97, parsley: 0.95, potatoes: 0.94, rice: 0.96, salt: 0.94, sugar: 0.97, tomatoes: 0.92, wheat_flour: 0.97, yogurt: 0.95
R squared individual other items: exchange_rate_unofficial: 0.97, fuel_diesel: 0.97, fuel_gas: 0.97, livestock_sheep_two_year_old_male: 0.99, wage_non_qualified_labour: 0.93
Index confidence score: 0.95
Imputation model: apples: two-stage cubist (Andree and Pape, 2023), bananas: two-stage cubist (Andree and Pape, 2023), beans: cubist (Andree, 2021), bread: cubist (Andree, 2021), bulgur: two-stage cubist (Andree and Pape, 2023), carrots: two-stage cubist (Andree and Pape, 2023), cheese: two-stage cubist (Andree and Pape, 2023), chickpeas: cubist (Andree, 2021), dates: two-stage cubist (Andree and Pape, 2023), eggplants: two-stage cubist (Andree and Pape, 2023), eggs: two-stage cubist (Andree and Pape, 2023), fish_tuna_canned: two-stage cubist (Andree and Pape, 2023), lentils: cubist (Andree, 2021), meat_beef_minced: two-stage cubist (Andree and Pape, 2023), meat_chicken_plucked: two-stage cubist (Andree and Pape, 2023), oil: cubist (Andree, 2021), parsley: two-stage cubist (Andree and Pape, 2023), potatoes: cubist (Andree, 2021), rice: cubist (Andree, 2021), salt: two-stage cubist (Andree and Pape, 2023), sugar: cubist (Andree, 2021), tomatoes: cubist (Andree, 2021), wheat_flour: cubist (Andree, 2021), yogurt: two-stage cubist (Andree and Pape, 2023)
 

Information on the model used for Chad (see working paper for more information)
Components: Maize (White) (1 KG, Index Weight = 1), Millet (1 KG, Index Weight = 1), Rice (Imported) (1 KG, Index Weight = 1), Sorghum (Red) (1 KG, Index Weight = 1)
Currency: XAF
Number of markets used: 62
Number of markets covered: 62
Number of food items: 4
Number of observations (food): maize: 2811, millet: 4565, rice: 1995, sorghum: 3978
Number of observations (other): : 
Data coverage (food): 27.19%
Data coverage previous 12 months (food): 45.5%
Average annualized food inflation: 3.28%
Maximum food drawdown: -37.47%
Average annualized food volatility: 12.56%
Average monthly food price correlation between markets: 0.58
Average annual food price correlation between markets: 0.82
R squared individual food items: maize: 0.84, millet: 0.85, rice: 0.95, sorghum: 0.86
R squared individual other items: : 
Index confidence score: 0.89
Imputation model: maize: cubist (Andree, 2021), millet: cubist (Andree, 2021), rice: cubist (Andree, 2021), sorghum: cubist (Andree, 2021)
 

Information on the model used for Yemen, Rep. (see working paper for more information)
Components: Beans (Kidney Red) (1 KG, Index Weight = 1), Eggs (1 Unit, Index Weight = 12), Lentils (1 KG, Index Weight = 1), Millet (1 KG, Index Weight = 1), Oil (Vegetable) (1 L, Index Weight = 1), Onions (1 KG, Index Weight = 1), Peas (Yellow, Split) (1 KG, Index Weight = 1), Potatoes (1 KG, Index Weight = 1), Rice (Imported) (1 KG, Index Weight = 1), Salt (1 KG, Index Weight = 1), Sorghum (1 KG, Index Weight = 1), Sugar (1 KG, Index Weight = 1), Tomatoes (1 KG, Index Weight = 1), Wheat (1 KG, Index Weight = 1), Wheat Flour (1 KG, Index Weight = 1)
Currency: YER
Number of markets used: 24
Number of markets covered: 24
Number of food items: 15
Number of observations (food): beans: 2231, eggs: 2170, lentils: 2148, millet: 413, oil: 2249, onions: 2318, peas: 1806, potatoes: 2274, rice: 2172, salt: 2175, sorghum: 413, sugar: 2219, tomatoes: 2273, wheat: 2506, wheat_flour: 2532
Number of observations (other): exchange_rate_unofficial: 1948, fuel_diesel: 2184, fuel_gas: 1923, fuel_petrol_gasoline: 2184, livestock_sheep_two_year_old_male: 1919, milling_cost_wheat: 1878, wage_non_qualified_labour: 1912, wage_qualified_labour: 1915
Data coverage (food): 47.73%
Data coverage previous 12 months (food): 65.9%
Average annualized food inflation: 12.66%
Maximum food drawdown: -17.82%
Average annualized food volatility: 10.96%
Average monthly food price correlation between markets: 0.58
Average annual food price correlation between markets: 0.76
R squared individual food items: beans: 0.94, eggs: 0.97, lentils: 0.93, millet: 0.97, oil: 0.94, onions: 0.82, peas: 0.87, potatoes: 0.84, rice: 0.96, salt: 0.93, sorghum: 0.97, sugar: 0.93, tomatoes: 0.75, wheat: 0.95, wheat_flour: 0.95
R squared individual other items: exchange_rate_unofficial: 0.98, fuel_diesel: 0.91, fuel_gas: 0.95, fuel_petrol_gasoline: 0.9, livestock_sheep_two_year_old_male: 0.97, milling_cost_wheat: 0.95, wage_non_qualified_labour: 0.97, wage_qualified_labour: 0.98
Index confidence score: 0.95
Imputation model: beans: cubist (Andree, 2021), eggs: cubist (Andree, 2021), lentils: cubist (Andree, 2021), millet: two-stage cubist (Andree and Pape, 2023), oil: cubist (Andree, 2021), onions: cubist (Andree, 2021), peas: cubist (Andree, 2021), potatoes: cubist (Andree, 2021), rice: cubist (Andree, 2021), salt: cubist (Andree, 2021), sorghum: two-stage cubist (Andree and Pape, 2023), sugar: cubist (Andree, 2021), tomatoes: cubist (Andree, 2021), wheat: cubist (Andree, 2021), wheat_flour: cubist (Andree, 2021)
 

]]></notes>
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