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The Congressional Budget Office (CBO) projections of USDA's mandatory farm and nutrition program outlays are important in shaping US agricultural policy. Using CBO projections and observed outcomes from 1985 through 2020, we examine the degree to which projections of farm, supplemental nutrition assistance program (SNAP), and child nutrition program outlays are unbiased, efficient, and informative. We find that projections for farm and child nutrition program outlays are unbiased, SNAP outlays are unbiased at short‐term but are downward biased beyond a 3‐year horizon. All three series of projections are inefficient. SNAP and child nutrition program outlay projections are informative up to a 5‐year horizon, but the farm program outlay projections are informative for only a 1‐year horizon. Disaggregated farm program data since 2008 suggests that the uninformativeness principally stems from conservation and commodity program projections. The findings may be valuable to CBO, as they continue to improve projections, and to projection users, in adjusting their expectations. [ABSTRACT FROM AUTHOR]

Crop insurance protects lenders by increasing the likelihood of loan repayment when revenue declines. We develop a theoretical mode that explains the role of crop insurance in agricultural lending and how impacts may be different for lenders that are not specialized in agricultural lending. We then test whether the total volume of production credit extended by commercial banks at the county level increases in response to crop insurance availability and whether the level of the response is related to bank specialization in agriculture. We use a novel difference‐in‐differences strategy based on some counties having a higher share of agricultural production that was not covered by Federal crop insurance in the 1990s. Crop insurance has a robust relationship with increased loan volumes during this period, especially in counties with fewer banks specialized in agriculture. [ABSTRACT FROM AUTHOR]

The Effect of Landscape-level Pesticide Applications on California Citrus Growers’ Decisions for California Red Scale Management.Analysis of the Influence of Open Space on Residential Values.Why Are Outside Investors Suddenly Interested in Farmland?

The United States Department of Agriculture's (USDA) agricultural baseline projections are important in shaping US agricultural policy. We investigate the degree to which previous findings of bias and inefficiency of USDA baseline projections of farm income and its components are driven by underlying macroeconomic assumptions. Once we control for the deviation of underlying macroeconomic assumptions from their observed path, we find that USDA projections of net cash income and its components are optimal for 73.3% of the projection horizons and the length of informative horizons improves. These findings may help USDA projection users, adjust their expectations when making plans and decisions. [ABSTRACT FROM AUTHOR]

Agricultural baselines facilitate policy and investment decisions by governments and market participants by providing long‐term projections about the farm sector. Despite their importance in shaping agricultural policy, the agricultural baselines have not been rigorously evaluated. This study evaluates the accuracy and informativeness of two widely used baselines for the US farm sector published by the United States Department of Agriculture (USDA) and the Food and Agricultural Policy Research Institute (FAPRI) in three steps. First, we examine the average percent errors of the projections and perform tests of bias. Second, we use a testing framework based on the encompassing principle to test the predictive content of the projections for each horizon, determining the longest informative projection horizon. Third, we compare the USDA and FAPRI baseline projections using a multi‐horizon framework that considers all projection horizons jointly. We find that prediction error and bias increase with the horizon's length. The predictive content of the baselines projections for most variables diminishes after 4–5 years. The multi‐horizon comparison suggests that neither USDA nor FAPRI projections have uniform or average superior predictive ability over the other for most variables. Our findings are useful for the agencies producing these baselines and for the policymakers, agricultural businesses, and other stakeholders who use them. The study contributes to the recent literature on long‐term agricultural projections and establishes the groundwork for future research inquiries. [ABSTRACT FROM AUTHOR]