Panel data are used in almost all subfields of the agricultural economics profession. Furthermore, many research areas have an important spatial dimension. This article discusses some of the recent contributions made in the evolving theoretical and empirical literature on spatial econometric methods for panel data. We then illustrate some of these tools within a climate change application using a hedonic model of farmland values and panel data. Estimates for the model are provided across a range of nonspatial and spatial estimators, including spatial error and spatial lag models with fixed and random effects extensions. Given the importance of location and extensive use of panel data in many subfields of agricultural economics, these recently developed spatial panel methods hold great potential for applied researchers.

Impacts from the coronavirus pandemic have depressed market returns to corn and soybean farmers in the Midwest, extending pressures that have existed since 2013 and which were made worse by trade disputes with China. Without large ad hoc Federal aid, income on Midwest grain farms would have been quite low and the ongoing cash flow crunch much worse. Farmland prices have not adjusted downward, in part due to continuing ad hoc Federal aid, but also because interest rates have been historically very low. The financial (solvency) position of Midwest grain farms is surprisingly strong because of the strength in land values. However, the financial condition of Midwest row‐crop agriculture could deteriorate markedly if recent and large infusions of ad hoc Federal aid dissipates or if interest rates rise sharply.

A number of problems in agricultural economics involve modeling joint distributions for which the assumption of multivariate normality may not be warranted. Yet, very little work has been conducted evaluating competing methods for modeling joint dependence. We develop a simulation framework to evaluate the bias and efficiency impacts of copula choice in the context of evaluating county-to-farm basis risk. The results suggest significant differences in performance across various copulas and approaches. The findings have important implications for risk analysis, insurance, and policy modeling problems in agriculture regarding the selection of method to model dependence among random variables.JEL classifications: Q00, Q10, Q14

Purpose -This article aims to explore recent trends in farmland rental markets using data for the state of Illinois. Trends in the types of rental agreements used and the relationship between the rental rate for those contracts, land values, crop revenues, production costs, and farm returns are examined. Design/methodology/approach -Data from various sources and at different levels of aggregation for the state of Illinois are used to provide illustrations of historical trends in farmland rental agreements and rental rates, and how they are related to various market and industry factors. Focus is placed on the more recent period since 2005 characterized by high commodity price levels and volatility. Findings -The majority of farmland in the Midwest is controlled under rental agreements which are increasingly of the fixed cash rent type. Rental rates have increased, but at a slower rate than farm returns. Average rental and interest rates imply that land values are consistent with the current market environment. Aggregate rental rates mask considerable variation in farm-level rents, only a portion of which can be explained by differences in soil productivity. Given the current level of price volatility, the tenure position of a farm operation has a significant effect on downside risk exposure. Originality/value -The illustrations provided in this paper should be of interest to researchers working in the area of farmland values and rental agreements, as well as to practitioners including farmers, landowners, and professional farm managers. The findings should motivate additional research and recognition of the importance of tenure position to the performance and risk exposure of grain farms.

The recent infusion of cash into production agriculture due to damages from retaliatory trade actions has been large. Up to $28 billion has been authorized through the Trade Mitigation Program in 2018 and 2019, accounting for a significant share of farm income and providing liquidity in an extended period of low prices. Using farm-level data from Illinois, Kansas, and Minnesota, this research examines the importance of market facilitation program payments in supporting incomes and reducing credit default risk. Results illustrate the additional liquidity provided for farms, and the distributional effects across states and among farms within each state.

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This paper analyzes the effect of landowner risk preferences and land quality on the optimal mix of vertically integrated production and contracted production of an energy crop in a region characterized by heterogeneity in landowners' risk preferences and land quality and with riskiness of returns from both energy crop and conventional crop production. We examine the determinants of the decision of landowners to grow an energy crop for biofuel production under one of three types of contracts, a land leasing contract, a fixed price contract and a revenue sharing contract and the impact of risk and time preferences, land quality and riskiness of energy crop production and prices on the optimal contract terms and effective cost of biomass. We find that as the degree of risk aversion and rate of time preference increases and as the riskiness of producing both the conventional crop and the energy crop increases, the share of vertically integrated production of energy crops increases. While low quality land is more likely to be converted to energy crop production, an increase in the degree of risk aversion results in an increase in the threshold level of land quality converted to energy crops under a land leasing contract but a decrease in the threshold level of land quality converted under a fixed price contract and a revenue sharing contract. We also find that the refinery can potentially earn a higher profit by offering a menu of different types of contracts rather than a single type of contract only; by allowing self-selection of contract type based on their risk preferences, the risk premium needed to induce production of energy crops is reduced.

Purpose -The purpose of this paper is to compare the characteristics of farms who participate in farm management associations to the wider population of farms at the state level. Design/methodology/approach -Farm-level records obtained from the USDA's Agricultural Resource Management Survey (ARMS) are compared to similar data obtained from farm management associations in three states: Illinois, Kansas, and Kentucky. Findings -Data collected through farm management associations tend to represent larger farms and a greater share of crop producers as compared to livestock producers. Association data, however, capture a greater share of younger farm operators. Originality/value -This is the first study to compare farm statistics from several farm management associations to ARMS, and the study confirms the findings of existing studies of prior USDA surveys.