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We estimate the pricing efficiency of a livestock auction market using a two‐tier stochastic frontier model. This model captures pricing inefficiency of a hedonic pricing model for livestock via exponential error terms above and below the hedonic model specification. The direction of pricing inefficiencies, whether above or below the hedonic pricing model, represent surplus transfer from buyers to sellers or from sellers to buyers, respectively. Using data from a 7‐year period in a livestock auction market, we found that on average livestock buyers extract about 6% of surplus from sellers. That is, on average, livestock auction market underprices by about 6% below its full information price. Buyer concentration also affects the degree of surplus transfer. At low levels of buyer concentration, when the top four‐buyer market concentration is <30%, there is an overpricing of only 1.23% over the full information price, extracting surplus from buyers to sellers. At higher buyer concentrations, buyers can extract up to 7% of surplus from sellers. [ABSTRACT FROM AUTHOR]

Abstract: Contemporaneous observations on expected supply and on prices of post‐harvest futures contracts for corn are used to estimate expected demand relationships. These equations are used to estimate the prices of the post‐harvest contracts based on new supply estimates. Each estimate can be compared with a corresponding futures price, i.e. the market forecast. The differences help discern the market expectations about the expected demand for the new crop relative to historical experience, which can help support outlook analyses. We find that in recent years, a 100 million bushel change in the expected supply of corn results in about a 6 cent per bushel negative change in the price of December corn. The discussion also deepens understanding of the term ‘anticipatory prices’ as defined by Holbrook Working in his 1958 work. [ABSTRACT FROM AUTHOR]

Since the Agricultural Act of 2014, the federal crop insurance program (FCIP) has been the cornerstone agricultural policy in the United States, and is the largest such program globally, with about $100 billion in coverage annually. Given its scale and scope, the FCIP has the potential to have pervasive impacts on incentives and policy functioning if not designed and priced properly. Surprisingly, soil data are not considered by the government when establishing insurance guarantees or rates. Using soil data that could easily and feasibly be scaled nationally, we find that the pricing differentials caused by the government’s failure to handle soil information leads to large errors in rating. [ABSTRACT FROM AUTHOR]