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Monthly food price estimates by product and market
Bangladesh, 73 markets, 2007/01/01-2024/11/01, version 2024-11-18

Bangladesh, 2007 - 2024
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Reference ID
BGD_2021_RTFP_v02_M
Producer(s)
Bo Pieter Johannes Andrée
Collection(s)
Fragility, Conflict and Violence
Metadata
DDI/XML JSON
Created on
Jan 31, 2024
Last modified
Nov 21, 2024
Page views
4070
Downloads
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  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Data collection
  • Access policy
  • Data Access
  • Disclaimer and copyrights
  • Additional metadata

    • Identification

    Survey ID number

    BGD_2021_RTFP_v02_M
    Title

    Monthly food price estimates by product and market
    Subtitle

    Bangladesh, 73 markets, 2007/01/01-2024/11/01, version 2024-11-18
    Abbreviation or Acronym

    Real Time Food Prices
    Country/Economy
    Name Country code
    Bangladesh BGD
    Study type

    Monthly food price 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.

    To produce smooth price series, outliers in the data are often adjusted using non-parametric density estimation and other techniques. Generalized Auto-Regressive Conditional Heteroskedasticity models are used to estimate intra-month price ranges. These models allow for excess kurtosis using a Generalized Error Distribution (GED). Open, High, Low, and Close price estimates are provided based on the modeled time-varying price distributions.

    Data are produced from 2007 to the present and estimates are given for individual commodity items at geo-referenced market locations. Predicted data for missing entries are based on exchange rates, and price data available either at other market locations or from related price items.

    RTP estimates of historical and current prices may serve as proxies for sub-national price inflation series or substitute national-level Consumer Price Inflation (CPI) indicators when complete information is unavailable. Therefore, RTP data may differ from other sources with official data, including the World Bank’s International Comparison Program (ICP) or inflation series reported in the World Development Indicators.

    The following datasets are part of this sub-series:

    Country-level inflation:

    Market-level estimates:

    HIGH-LOW CHART, AND INFLATION
    LOCATION OF MARKETS
    DATA PREVIEW
    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.

    Version

    Version Date

    2024/11/18
    Version Responsibility Statement

    FCV Data Platform

    Scope

    Notes

    List of food products included in estimates (not all products are included in country-level estimates): lentils, oil, rice, wheat flour
    Keywords
    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 Bangladesh

    Coverage

    Geographic Coverage notes

    The data cover the following sub-national areas: Khulna, Chittagong, Barisal, Rajshahi, Dhaka, Rangpur, Sylhet, Mymensingh, 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), Office of the Chief Statistician (DECCS)
    Funding Agency/Sponsor
    Name Grant number Role
    Foreign, Commonwealth & Development Office of the United Kingdom Support to data analytics
    Foreign, Commonwealth & Development Office of the United Kingdom KP-P174529-KMCE-TF0B4149 Data documentation and dissemination (FCV Data Platform)
    Department of Foreign Affairs and Trade of Australia TF0B6892 Support to methodological development in low data regions
    Department of Foreign Affairs and Trade of Australia TF0B6579 Support to methodological development in low data regions
    Federal Ministry for Economic Cooperation and Development of Germany as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund TF073570 Expansion of coverage and maintenance
    Federal Ministry for Economic Cooperation and Development of Germany as part of the World Bank’s Food Systems 2030 Multi-Donor Trust Fund TF0C0728 Expansion of coverage and maintenance
    Other Identifications/Acknowledgments
    Name Affiliation Role
    World Food Programme (WFP) United Nations Source of market price data
    Food and Agriculture Organization (FAO) United Nations Source of market price data

    Data collection

    Dates of Data Collection
    Start End
    2007/01/01 2024/11/01
    Time periods
    Start date End date
    2007/01/01 2024/11/01
    Sources
    Data source Origin of source Characteristics
    World Food Programme (WFP) https://data.humdata.org/organization/wfp?vocab_Topics=prices World Food Programme (WFP); data published in the Humanitarian Data Exchange (HDX) data catalog at https://data.humdata.org/
    Food and Agriculture Organization (FAO) https://fpma.fao.org/giews/fpmat4/#/dashboard/tool/domestic Local exchange rates and implied exchange rates data derived from commodity pairs published by FAO through the Food Price Monitoring and Analysis (FMPA) Tool

    Access policy

    Location of Data Collection

    World Bank Microdata Library, FCV Collection
    URL for Location of Data Collection

    https://microdata.worldbank.org

    Data Access

    Access authority
    Name Affiliation URL
    Data Help Desk World Bank, Development Data Group https://datahelpdesk.worldbank.org/
    Citation requirements

    Please cite this dataset as follows: Andrée, B. P. J. (2021). Monthly food price estimates by product and market (Version 2024-11-18). BGD_2021_RTFP_v02_M. Washington, DC: World Bank Microdata Library. https://doi.org/10.48529/2ZH0-JF55
    Restrictions

    The estimates presented in this dataset are all based on publicly-available data.
    The dataset of price estimates is published as open data.

    Disclaimer and copyrights

    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.

    Additional metadata

    Ticker info
    ISO Country Title Unit Food index weight Data coverage Imputation
    BGD Bangladesh Unofficial exchange rate (Parallel-market Estimate)(FAO GIEWS completed with Int. Forex) USD/LCU 0 100% n/a
    BGD Bangladesh Food Price Index LCU, Indexed, January 2018 = 1 Laspreyes 21.58% 0.96
    BGD Bangladesh Lentils (masur) KG 1 19.62% 0.96
    BGD Bangladesh Oil (palm) L 1 22.81% 0.97
    BGD Bangladesh Rice (coarse) KG 1 18.79% 0.96
    BGD Bangladesh Wheat flour KG 1 23.96% 0.96
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