On the Dynamics of Price Discovery: Energy and Agricultural Markets with and without the Renewable Fuels Mandate

Layla Shiva, David Bessler () and Bruce McCarl

No 169780, 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota from Agricultural and Applied Economics Association

Abstract: We model the energy–agriculture linkage through structural vector autoregression (VAR) model. This model quantifies the relative importance of various contributing factors in driving prices in both markets. The LiNGAM algorithm from the machine learning literature is used to help identify structural parameters in contemporaneous time. We perform conditional forecasting, taking into account the renewable fuel standards policies, and compare the forecasted path of prices with and without the renewable fuels mandates.

Keywords: Agricultural and Food Policy; Environmental Economics and Policy; Resource/Energy Economics and Policy (search for similar items in EconPapers)
Pages: 35
Date: 2014
New Economics Papers: this item is included in nep-agr, nep-ene and nep-env
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea14:169780

DOI: 10.22004/ag.econ.169780

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