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Partial stochastic analysis with the European Commission's version of the AGLINK-COSIMO model

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The Directorate-General for Agriculture and Rural Development (DG AGRI) publishes annually its medium-term agricultural outlook for the main agricultural sectors (i.e. cereals, oilseeds, sugar, meat, dairy, and biofuels) using a partial equilibrium model. The report contains EU-wide projections of supply balance sheets (production, consumption, exports, imports, and change in stocks) for the next 8-10 years. It is inevitable that the results from a partial equilibrium simulation model are conditional on values used for variables that enter the model exogenously. These exogenous variables include some of the key drivers of market behaviour. Because of the uncertainty surrounding their assumed values, it is very useful to conduct sensitivity analysis with respect to key exogenous variables. Stochastic analysis has been used in the DG AGRI agricultural outlooks in both 2011 and 2012 to assess the degree of sensitivity of the baseline projections to uncertainty in the macroeconomy and fluctuations in agricultural yields. This report presents the methodology underlying that analysis.

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  • Zebedee Nii-Naate & Alison Burrell, 2012. "Partial stochastic analysis with the European Commission's version of the AGLINK-COSIMO model," JRC Working Papers JRC76019, Joint Research Centre (Seville site).
  • Handle: RePEc:ipt:iptwpa:jrc76019
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    File URL: http://publications.jrc.ec.europa.eu/repository/handle/JRC76019
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    1. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    2. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    3. Lynch, Michael C., 2002. "Forecasting oil supply: theory and practice," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(2), pages 373-389.
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    Keywords

    Economic analysis; agricultural markets; modelling tools; price volatility; partial stochastic analysis; uncertainty analysis;

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