I propose partial-equilibrium models that describe the dynamics of global wheat and corn markets. These models extend the classic competitive storage framework by incorporating nonstationary variables. They are calibrated using data from Ukraine and key importing and exporting countries. The models enable the endogenous estimation of price trends, based on the observed movements in the underlying variables. This framework provides insights into how involuntary reductions in Ukraine’s global market presence, triggered by russia’s invasion, could have affected trend prices
Alquist, R., Kilian, L., Vigfusson, R. J. (2013). Forecasting the price of oil, in G. Elliott and A. Timmermann, eds, Handbook of Economic Forecasting, Vol. 2, Part A, pp. 427–507. https://doi.org/10.1016/B978-0-444-53683-9.00008-6
Arroyo-Marioli, F., Khadan, J., Ohnsorge, F., Yamazaki, T. (2023). Forecasting industrial commodity prices: Literature review and a model suite. Working Paper, 10611. Washington: World Bank. http://hdl.handle.net/10986/40657
Baffes, J., Nagle, P. (2022). Commodity demand: Drivers, outlook, and implications, in J. Baffes and P. Nagle, eds, Commodity Markets: Evolution, Challenges and Policies, ch. 2, pp. 121–183. Washington: World Bank. https://thedocs.worldbank.org/en/doc/b4ff84b2d5dc4d0963a5074102460cc1-0350012022/related/Commodity-Markets-Chapter-2.pdf
Baumeister, C., Hamilton, J. D. (2019). Structural interpretation of vector autoregressions with incomplete identification: Revisiting the role of oil supply and demand shocks. American Economic Review, 109(5), 1873–1910. https://doi.org/10.1257/aer.20151569
Bobenrieth, E. S., Bobenrieth, J. R., Guerra, E. A., Wright, B. D., Zeng, D. (2021). Putting the empirical commodity storage model back on track: Crucial implications of a ”negligible” trend. American Journal of Agricultural Economics, 103(3), 1034–1057. https://doi.org/10.1111/ajae.12133
Bobenrieth, E. S., Wright, B., Zeng, D. (2013). Stocks-to-use ratios and prices as indicators of vulnerability to spikes in global cereal markets. Agricultural Economics, 44(s1), 43–52. https://doi.org/10.1111/agec.12049
Bondarenko, O. (2023). Agricultural commodity price dynamics: Evidence from BVAR models. Working Paper 03/2023. Kyiv: National Bank of Ukraine. https://bank.gov.ua/admin_uploads/article/WP_2023-03_Bondarenko.pdf
Cafiero, C., Bobenrieth, E. S., Bobenrieth, J. R. (2011). Storage arbitrage and commodity price volatility, in A. Prakash, ed., Safeguarding Food Security in Volatile Global Markets, ch. 15, pp. 288–313. Food and Agriculture Organization of the United Nations. https://www.fao.org/4/i2107e/i2107e15.pdf
Canova, F. (2014). Bridging DSGE models and the raw data. Journal of Monetary Economics, 67, 1–15. https://doi.org/10.1016/j.jmoneco.2014.06.003
Carroll, C. D. (2006). The method of endogenous gridpoints for solving dynamic stochastic optimization problems. Economics Letters, 91(3), 312–320. https://doi.org/10.1016/j.econlet.2005.09.013
Ceglar, A., Turco, M., Toreti, A., Doblas-Reyes, F. J. (2017). Linking crop yield anomalies to large-scale atmospheric circulation in Europe. Agricultural and Forest Meteorology, 240–241, 35–45. https://doi.org/10.1016/j.agrformet.2017.03.019
Chahad, M., Hofmann-Drahonsky, A.-C., Page, A., Tirpak, M. (2023). An updated assessment of short-term inflation projections by Eurosystem and ECB staff. https://www.ecb.europa.eu/press/economic-bulletin/focus/2023/html/ecb.ebbox202301_06~df570a38fd.en.html
Chinn, M. D., Coibion, O. (2014). The predictive content of commodity futures. Journal of Futures Markets, 34(7), 607–636. https://doi.org/10.1002/fut.21615
Deaton, A., Laroque, G. (1992). On the behaviour of commodity prices. Review of Economic Studies, 59, 1–23. https://doi.org/10.2307/2297923
Deaton, A., Laroque, G. (1995). Estimating a nonlinear rational expectations commodity price model with unobservable: State variables. Journal of Applied Econometrics, 10(S1), S9–S40. https://doi.org/10.1002/jae.3950100503
Deaton, A., Laroque, G. (1996). Competitive storage and commodity price dynamics. Journal of Political Economy, 104(5), 896–923. https://doi.org/10.1086/262046
Deuss, A., Adenauer, M. (2020). China’s grain reserves, price support and import policies: Examining the medium-term market impacts of alternative policy scenarios. OECD Food, Agriculture and Fisheries Papers, 138. https://doi.org/10.1787/f813ed01-en
Fernandez-Villaverde, J., Ramirez, J. F. R., Schorfheide, F. (2016). Solution and estimation methods for DSGE models. Working Paper, 21862. National Bureau of Economic Research. http://www.nber.org/papers/w21862
Gouel, C. (2013). Comparing numerical methods for solving the competitive storage model. Computational Economics, 41, 267–295. https://doi.org/10.1007/s10614-012-9318-y
Gouel, C., Legrand, N. (2017). Estimating the competitive storage model with trending commodity prices. Journal of Applied Econometrics, 32(4), 744–763. https://doi.org/10.1002/jae.2553
Greenspan, A. (2004). Remarks by Chairman Alan Greenspan before the Center for Strategic & International Studies, Washington, D.C., April 27, 2004). https://www.federalreserve.gov/boarddocs/speeches/2004/20040427/default.htm
Guerra, E. A., Bobenrieth, E. S., Bobenrieth, J. R., Cafiero, C. (2014). Empirical commodity storage model: the challenge of matching data and theory. European Review of Agricultural Economics, 42(4), 607–623. https://doi.org/10.1093/erae/jbu037
Gustafson, R. L. (1958). Carryover levels for grains: A method for determining amounts that are optimal under specified conditions. Technical Bulletin, 1178. United States Department of Agriculture. https://doi.org/10.22004/ag.econ.157231
Iizumi, T., Luo, J.-J., Challinor, A. J., Sakurai, G., Yokozawa, M., Sakuma, H., Brown, M. E., Yamagata, T. (2014). Impacts of El Niño Southern Oscillation on the global yields of major crops. Nature Communications, 5, 3712. https://doi.org/10.1038/ncomms4712
Janzen, J. P., Carter, C. A., Smith, A. D., Adjemian, M. K. (2014). Deconstructing wheat price spikes: A model of supply and demand, financial speculation, and commodity price comovement. Economic Research Report, 165. United States Department of Agriculture. https://ers.usda.gov/sites/default/files/_laserfiche/publications/45199/46439_err165.pdf
Kilian, L., Murphy, D. P. (2014). The role of inventories and speculative trading in the global market for crude oil. Journal of Applied Econometrics, 29(3), 454–478. https://doi.org/10.1002/jae.2322
Lane, P. R. (2024). Monetary Policy Under Uncertainty: Keynote speech by Philip R. Lane, Member of the Executive Board of the ECB, at the Bank of England Watchers’ Conference 2024, King’s College London, London, 25 November 2024. https://www.ecb.europa.eu/press/key/date/2024/html/ecb.sp241125~df4c5a69c7.en.html
Maliar, L., Maliar, S., Taylor, J. B., Tsener, I. (2020). A tractable framework for analyzing a class of nonstationary Markov models. Quantitative Economics, 11(4), 1289–1323. https://doi.org/10.3982/QE1360
Miao, Y., Wu, W., Funke, N. (2011). Reviving the competitive storage model: A holistic approach to food commodity prices. IMF Working Paper, WP/11/64. International Monetary Fund. https://doi.org/10.5089/9781455228065.001
OECD (1993). Commodity price variability: Its nature and causes. Organisation for Economic Co-Operation And Development General Distribution, (93)71. https://one.oecd.org/document/OCDE/GD(93)71/en/pdf
OECD/FAO (2022). The Aglink Cosimo Model: a Partial Equilibrium Model of World Agricultural Markets. https://openknowledge.fao.org/server/api/core/bitstreams/568dd85a-c6dc-4a92-8728-c2b0e3233e29/content
OECD/FAO (2024). OECD-FAO Agricultural Outlook 2024-2033. https://www.oecd.org/en/publications/oecd-fao-agricultural-outlook-2024-2033_4c5d2cfb-en/support-materials.html
Osmundsen, K. K., Kleppe, T. S., Liesenfeld, R., Oglend, A. (2021). Estimating the competitive storage model with stochastic trends in commodity prices. Econometrics, 9(4), 40. https://doi.org/10.3390/econometrics9040040
Roberts, M. J. and Schlenker, W. (2013). Identifying supply and demand elasticities of agricultural commodities: Implications for the US ethanol mandate. American Economic Review, 103(6), 2265–2295. https://doi.org/10.1257/aer.103.6.2265
Trostle, R. (2008). Global agricultural supply and demand: Factors contributing to the recent increase in food commodity prices. USDA Report, WRS-0801. https://ers.usda.gov/sites/default/files/_laserfiche/outlooks/40463/12274_wrs0801_1_.pdf?v=32137
Trostle, R., Marti, D., Rosen, S., Westcott, P. (2011). Why have food commodity prices risen again? USDA Report, WRS-1103. https://ers.usda.gov/sites/default/files/_laserfiche/outlooks/40481/7392_wrs1103.pdf?v=59942
Vogel, F. A., Bange, G. A. (1999). Understanding crop statistics. USDA Miscellaneous Publication, 1554. https://www.nass.usda.gov/Education_and_Outreach/Understanding_Statistics/pub1554.pdf
Zulauf, C., Schnitkey, G., Swanson, K., Paulson, N. (2021). Stock-to-use ratios of us corn, soybeans, and wheat since 1960. farmdoc daily, 11(92). https://farmdocdaily.illinois.edu/2021/06/stock-to-use-ratios-of-us-corn-soybeans-and-wheat-since-1960.html
