The planting real option in cash rent valuation

Du, Xiaodong; Hennessy, David A.

doi:10.1080/00036846.2010.522524

Cited by 10 publications

(4 citation statements)

References 44 publications

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“…For the same reasons, in this research I use monthly average prices, rather than single-day observations within a month. Furthermore, and albeit due to the reasons listed above, using monthly average prices appears to be a preferred choice in the relevant literature (e.g., Du & Hennessy, 2008;Holt & Craig, 2006;Irwin & Good, 2009). I obtain the soybean-to-corn price ratio by simply dividing soybean futures prices by corn futures prices.…”

Section: Data and Estimation Proceduresmentioning

confidence: 97%

Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach

Ubilava¹

2012

Agribusiness

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The soybean-to-corn price ratio has long been considered one of the triggers that farmers use in the decision to produce corn or soybeans, but little has been done to analyze its dynamics. Recently, the soybean-to-corn price ratio options were introduced on the Chicago Board of Trade, providing the market participants with an opportunity to trade the relative prices of the crops. In this study, the author investigates potentially nonlinear dynamics of the soybean-to-corn price ratio by applying the smooth transition autoregression (STAR) modeling framework to the soybean-to-corn price ratio, derived from monthly futures prices of corn and soybeans. The estimated model demonstrates nonlinear dynamics, resulting in asymmetries in the adjustment to the long-run equilibrium of the soybean-to-corn price ratio. The findings of this research provide insightful implications to crop producers, input suppliers, and other market participants. [EconLit Citations: C220; E370; Q110]. C 2011 Wiley Periodicals, Inc.

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Section: Data and Estimation Proceduresmentioning

confidence: 97%

Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach

Ubilava¹

2012

Agribusiness

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“…In addition, in the full sample data, the variance ratio of the prices of ethanol relative to sugar is higher, making the biorefinery start to switch away from a product that is highly volatile. Previous studies showed that higher relative price volatility will increase the value of flexibility and create increased investment in flexible technologies (Kulatilaka 1988, Due and Hennessy 2008). However, we do not find that the higher relative price volatility of ethanol with respect to sugar prices induces switching to alternative mode of production, given the parameters used for our study.…”

Section: Empirical Results and Discussionmentioning

confidence: 99%

The Value of Switching Production Options in a Flexible Biorefinery

Hossiso¹,

Ripplinger²

2017

Agric. Resour. Econom. Rev.

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This study analyses the value of a switching option in a flexible biorefinery plant that produces ethanol and sugar juice in a single plant using energy beets. A real-options approach is used to compute threshold prices and optimal switching decision rules for switching between sugar and ethanol production modes. The analysis shows that it is economically optimal to keep producing ethanol then switching to sugar juice, given the stochastic price parameters of the two products.

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“…Early work includes Arrow and Fisher (1974), Williams (1991), Reed (1993), Capozza and Li (1994), Geltner et al (1996), and Dixit and Pindyck (1994). Real option models have been used in the agricultural economics literature to study planting and harvesting decisions (e.g., Du & Hennessy, 2012; Ewald et al, 2016; Song et al, 2011), investment decisions (e.g., Feil et al, 2012; Pederson & Zou, 2009; Secor & Boland, 2017), and farm‐labor migration (Önel & Goodwin, 2015). Real option approaches have also been used to model natural resource management and, most relevant to our work here, the tension between forest and agriculture.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Maize price volatility and deforestation

Lundberg

Abman

2021

American J Agri Economics

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We develop a model of deforestation using a real option on agricultural land conversion and establish an important link between agricultural commodity price volatility and forest loss. Higher price volatility of staple commodities increases incentives to delay land conversion and is associated with lower levels of deforestation. Using satellite‐derived estimates of local deforestation and high‐frequency local maize prices across a panel of market catchments across 26 countries in sub‐Saharan Africa, we find strong empirical evidence that maize price volatility is negatively associated with forest loss. Our findings are driven by catchments in biomes that are relatively well‐suited to maize production. Instrumenting for changes in price levels and price volatility with spatially explicit temperature and rainfall anomalies yields results consistent with our main approach. The findings highlight important tensions between agricultural price stabilization policies, conservation efforts, and environmental externalities.

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The planting real option in cash rent valuation

Cited by 10 publications

References 44 publications

Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach

Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach

The Value of Switching Production Options in a Flexible Biorefinery

Maize price volatility and deforestation

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