2016farmdoc dailyRequires access

Forming Corn and Soybean Price Expectations for 2016-17

Darrel Good, Scott H. Irwin

Open publisher page 4 citations

Abstract

In the farmdoc daily article of April 6, 2016 we offered a new specification for the relationship between the marketing year ending stocks-to-use ratio and the marketing year average farm price for corn and soybeans. Forecasting the marketing year average price using the new stocks-to-use and price model is a two-step process. The stocks-to-use ratio must be projected first and then the appropriate scenario for demand has to be specified. Here, we illustrate that two-step process for the 2016-17 marketing year using two alternative balance sheet projections for corn and soybeans. Based on this analysis, we draw broader conclusions about the likelihood and drivers of lower and higher prices.

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What this paper is about

In the farmdoc daily article of April 6, 2016 we offered a new specification for the relationship between the marketing year ending stocks-to-use ratio and the marketing year average farm price for corn and soybeans. Forecasting the marketing year average price using the new stocks-to-use and price model is a two-step process. The stocks-to-use ratio must be projected first and then the appropriate scenario for demand has to be specified. Here, we illustrate that two-step process for the 2016-17 marketing year using two alternative balance sheet projections for corn and soybeans. Based on this analysis, we draw broader conclusions about the likelihood and drivers of lower and higher prices.

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Available abstract

In the farmdoc daily article of April 6, 2016 we offered a new specification for the relationship between the marketing year ending stocks-to-use ratio and the marketing year average farm price for corn and soybeans. Forecasting the marketing year average price using the new stocks-to-use and price model is a two-step process. The stocks-to-use ratio must be projected first and then the appropriate scenario for demand has to be specified. Here, we illustrate that two-step process for the 2016-17 marketing year using two alternative balance sheet projections for corn and soybeans. Based on this analysis, we draw broader conclusions about the likelihood and drivers of lower and higher prices.

Key concepts: Economics, Balance (ability), Balance sheet, Agribusiness, Agricultural economics, Process (computing), Econometrics, Computer science

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