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A Model of West African Millet Prices in Rural Markets

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  • Brown, Molly
  • Higgins, Nathaniel
  • Hintermann, Beat

Abstract

In this article we specify a model of millet prices in the three West African countries of Burkina Faso, Mali, and Niger. Using data obtained from USAID’s Famine Early Warning Systems Network (FEWS NET) we present a unique regional cereal price forecasting model that takes advantage of the panel nature of our data, and accounts for the flow of millet across markets. Another novel aspect of our analysis is our use of the Normalized Difference Vegetation Index (NDVI) to detect and control for variation in conditions for productivity. The average absolute out-of-sample prediction error for 4- month-ahead millet prices is about 20 %.

Suggested Citation

  • Brown, Molly & Higgins, Nathaniel & Hintermann, Beat, 2013. "A Model of West African Millet Prices in Rural Markets," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150714, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea13:150714
    DOI: 10.22004/ag.econ.150714
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    Cited by:

    1. Sanusi, Olajide I. & Safi, Samir K. & Adeeko, Omotara & Tabash, Mosab I., 2022. "Forecasting agricultural commodity price using different models: a case study of widely consumed grains in Nigeria," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 8(2), June.
    2. Msafiri Y. Mkonda & Xinhua He, 2017. "Yields of the Major Food Crops: Implications to Food Security and Policy in Tanzania’s Semi-Arid Agro-Ecological Zone," Sustainability, MDPI, vol. 9(8), pages 1-16, August.
    3. Essam, Timothy M., 2012. "Using Satellite-Based Remote Sensing Data to Assess Millet Price Regimes and Market Performance in Niger," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124654, Agricultural and Applied Economics Association.
    4. Rampa, Alexis & Lovo, Stefania, 2023. "Revisiting the effects of the Ethiopian land tenure reform using satellite data. A focus on agricultural productivity, climate change mitigation and adaptation," World Development, Elsevier, vol. 171(C).
    5. Ruolin Li & Celestin Sindikubwabo & Qi Feng & Yang Cui, 2023. "Short-Term Climate Prediction over China Mainland: An Attempt Using Machine Learning, Considering Natural and Anthropic Factors," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
    6. Brown, Molly E. & Carr, Edward R. & Grace, Kathryn L. & Wiebe, Keith & Funk, Christopher C. & Attavanich, Witsanu & Backlund, Peter & Buja, Lawrence, 2017. "Do markets and trade help or hurt the global food system adapt to climate change?," Food Policy, Elsevier, vol. 68(C), pages 154-159.

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    More about this item

    Keywords

    Crop Production/Industries; Demand and Price Analysis; International Relations/Trade;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q17 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agriculture in International Trade
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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