Monthly food price estimates by product and market
Syrian Arab Republic, 95 markets, 2011/01/01-2023/11/01, version 2023-11-27
Syrian Arab Republic, 2011 - 2023
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Reference ID
SYR_2021_RTFP_v02_M
Producer(s)
Bo Pieter Johannes Andrée
Collection(s)
Metadata
Created on
Nov 28, 2023
Last modified
Nov 28, 2023
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9615
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Identification
Survey ID Number
SYR_2021_RTFP_v02_M
Title
Monthly food price estimates by product and market
Subtitle
Syrian Arab Republic, 95 markets, 2011/01/01-2023/11/01, version 2023-11-27
Abbreviation or Acronym
Real Time Food Prices
Country/Economy
| Name | Country code |
|---|---|
| Syrian Arab Republic | SYR |
Study type
Monthly food price estimates in fragile countries
HIGH-LOW CHART, AND INFLATION
DATA PREVIEW
Series Information
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
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
Abstract
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.
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.
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
Version Date
2023/11/27
Scope
Notes
List of food products included in estimates (not all products are included in country-level estimates): apples, bananas, beans, bread, bulgur, carrots, cheese, chickpeas, dates, eggplants, eggs, fish tuna canned, lentils, livestock sheep two year old male, meat beef minced, meat chicken plucked, oil, parsley, potatoes, rice, salt, sugar, tomatoes, wheat flour, yogurt
Keywords
| Keyword |
|---|
| Food Price Monitor |
| FPM |
| Real Time Food Prices |
| RTFP |
| Inflation |
| Food Price Inflation |
| Food security |
| Food Insecurity |
| Food Crisis |
| Famine |
| Fragility |
| FCS |
| FCV |
| Food Price Crisis |
| Commodity prices |
| Maize |
| Sorghum |
| Wheat |
| Rice |
| Agricultural prices |
| Food prices |
| Real Time Food Prices |
| Price measurement |
| Real-time exchange rate data |
| Commodity items |
| Geo-referenced market locations |
| Sub-national price inflation series |
| Consumer Price Inflation (CPI) |
| National-level CPI indicators |
| International Comparison Program (ICP) |
| Inflation series |
| Market prices |
| Price analysis |
| Real-time data |
| National prices |
| International prices |
| Price fluctuations |
| Price trends |
| Price Volatility |
| Syrian Arab Republic |
Coverage
Geographic Coverage notes
The data cover the following sub-national areas: Aleppo, Dar'a, Quneitra, Homs, Deir-ez-Zor, Damascus, Ar-Raqqa, Al-Hasakeh, Hama, As-Sweida, Rural Damascus, Tartous, Idleb, Lattakia, Market Average
Geographic Unit
Sub-national level, Admin 2 (selected)
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Bo Pieter Johannes Andrée | World Bank, Development Data Group (DECDG), Data Analytics and Tools unit (DECAT) |
Funding Agency/Sponsor
| Name | Abbreviation | Grant number | Role |
|---|---|---|---|
| Foreign, Commonwealth & Development Office | FCDO (formerly DFID) | Support to data analytics | |
| Foreign, Commonwealth & Development Office | FCDO (formerly DFID) | KP-P174529-KMCE-TF0B4149 | Data documentation and dissemination (FCV Data Platform) |
| Department of Foreign Affairs and Trade | DFAT | TF0B6892 | Support to methodological development in low data regions |
| Department of Foreign Affairs and Trade | DFAT | TF0B6579 | Support to methodological development in low data regions |
| Federal Ministry for Economic Cooperation and Development as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund | BMZ | TF073570 | 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 | BMZ | TF0C0728 | Expansion of coverage and maintenance |
Other Identifications/Acknowledgments
| Name | Role | Affiliation |
|---|---|---|
| World Food Programme (WFP) | Source of market price data | United Nations |
| Food and Agriculture Organization (FAO) | Source of market price data | United Nations |
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2011/01/01 | 2023/11/01 |
Time periods
| Start date | End date |
|---|---|
| 2011/01/01 | 2023/11/01 |
Access policy
Restrictions
The estimates presented in this dataset are all based on publicly-available data from the World Food Programme.
The dataset of price estimates is published as open data.
The dataset of price estimates is published as open data.
Citation requirements
Please cite this dataset as follows: Andrée, B. P. J. (2021). Monthly food price estimates by product and market (Version 2023-11-27). SYR_2021_RTFP_v02_M. Washington, DC: World Bank Microdata Library. https://doi.org/10.48529/2ZH0-JF55
Access authority
| Name | Affiliation | URL |
|---|---|---|
| Data Help Desk | World Bank, Development Data Group | Link |
Location of Data Collection
World Bank Microdata Library, FCV Collection
Disclaimer and copyrights
Disclaimer
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.