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From International to Regional Commodity Price Pass-through Using Self-Driven Recurrent Networks

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  • Ramos
  • Pablo Negri
  • Martín Breitkopf
  • María Laura Ojeda

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  • Ramos & Pablo Negri & Martín Breitkopf & María Laura Ojeda, 2021. "From International to Regional Commodity Price Pass-through Using Self-Driven Recurrent Networks," Asociación Argentina de Economía Política: Working Papers 4513, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4513
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    References listed on IDEAS

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    1. Nemati, Mehdi, 2016. "Relationship among Energy, Bioenergy, and Agricultural Commodity Prices: Re-Considering Structural Changes," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229793, Southern Agricultural Economics Association.
    2. Cornelis Gardebroek & Manuel A. Hernandez & Miguel Robles, 2016. "Market interdependence and volatility transmission among major crops," Agricultural Economics, International Association of Agricultural Economists, vol. 47(2), pages 141-155, March.
    3. Andrea Coppola, 2008. "Forecasting oil price movements: Exploiting the information in the futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(1), pages 34-56, January.
    4. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    5. Wang, Jie & Wang, Jun, 2016. "Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations," Energy, Elsevier, vol. 102(C), pages 365-374.
    6. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    7. Nazlioglu, Saban & Soytas, Ugur, 2012. "Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis," Energy Economics, Elsevier, vol. 34(4), pages 1098-1104.
    8. Yongmei Fang & Bo Guan & Shangjuan Wu & Saeed Heravi, 2020. "Optimal forecast combination based on ensemble empirical mode decomposition for agricultural commodity futures prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 877-886, September.
    9. Gil-Alana, Luis A. & Yaya, OlaOluwa S. & Awe, Olushina O., 2017. "Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach," Resources Policy, Elsevier, vol. 53(C), pages 117-124.
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    More about this item

    Keywords

    Recurrent Neural Networks; Regional Commodities Prices; Shock Simulations;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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