The Effect of the El Nino Southern Oscillation on U.S. Corn Production and Downside Risk

El Nino Southern Oscillation (ENSO) teleconnections imply anomalous weather conditions around the globe, causing yield shortages, price changes, and even civil unrests. Extreme ENSO events may cause catastrophic damages to crop yields, thus amplifying downside risk for producers. This study presents a framework for quantifying the effects of climate on crop yield distributions. An empirical application provides estimates of the effect that ENSO events have on the means of U.S. county-level corn yield distributions, as well as the probabilities of catastrophic crop loss. Our findings demonstrate that ENSO events strongly influence these probabilities systematically over large production regions, which has important implications for research and policy analysis in the production, risk management, climate change, and civil unrest literatures.Climate, El Nino Southern Oscillation, Maximum Entropy, Risk Management, Yield Distribution, Crop Production/Industries, Environmental Economics and Policy, Production Economics,

A Mixed Effects Model of Crop Yields for Purposes of Premium Determination

Farm income is highly variable due to annual price and yield uncertainties. The federally subsidized crop insurance program is an important tool for managing this risk, and has grown from a relatively modest program to one that encompasses the majority of productive cropland in the country. The success of this program depends on identification of actuarially fair insurance premium rates, which in turn depends on accurate estimation of farm-level yield distributions. We use the confidential U.S. Department of Agriculture Risk Management Agency (RMA) panel dataset to estimate farm-specific distributions of yields and actually fair crop insurance premiums. Our ongoing work includes using the difference between our estimated actually fair premiums and RMA's to predict which insurance contracts farmers select. Ultimately, we will predict potential efficiency gains from using our empirical model for premium determination.Yield, Crop Insurance, Policy, Mixed Model, Agricultural and Food Policy,

Agricultural Arbitrage, Adjustment Costs, and the Intensive Margin

Farmland and capital are an important and rapidly expanding component of the agricultural economy, and empirical evidence suggests that these assets are quasi-fixed in that adjustment costs are incurred when holdings are altered. Increased interest in the rate of return for investing in farmland suggests that an important consideration is the effect of adjustment costs on this return. A novel theoretical model is developed that ties together contributions from the farmland pricing and adjustment cost literatures, and the first order conditions for a utility maximizing decision maker are rearranged into intertemporal arbitrage equations that are similar in spirit to traditional finance models. The common assumptions that land and capital are quasi-fixed assets, and that production is characterized by constant returns to scale are tested and the evidence supports these assumptions. An empirical application of the arbitrage equations provides evidence that risk aversion and adjustment costs are jointly significant components of agricultural production, and that adjustment costs generate significant changes in the rate of return to farmland. The results have important policy implications as sluggish supply response due to quasi-fixity can lead to dramatically inflated commodity prices, and an accurate measure of the farmland return can help determine how far the extensive margin will expand or contract in response to a variety of policy scenarios, such as the subsidization of corn for ethanol, an increase in the variety of subsidized crop insurance products, or the introduction of new revenue support programs such as ACRE.Arbitrage, Adjustment Costs, Farmland, Asset Pricing, Capital, Cost Function, Risk, Production, Agricultural Finance, Consumer/Household Economics, Crop Production/Industries, Farm Management, Financial Economics, Land Economics/Use, Production Economics, Risk and Uncertainty,

Irrigation offsets wheat yield reductions from warming temperatures

Citation: Tack, J., Barkley, A., & Hendricks, N. (2017). Irrigation offsets wheat yield reductions from warming temperatures. Environmental Research Letters, 12(11), 114027. https://doi.org/10.1088/1748-9326/aa8d27Temperature increases due to climate change are expected to cause substantial reductions in global wheat yields. However, uncertainty remains regarding the potential role for irrigation as an adaptation strategy to offset heat impacts. Here we utilize over 7000 observations spanning eleven Kansas field-trial locations, 180 varieties, and 29 years to show that irrigation significantly reduces the negative impact of warming temperatures on winter wheat yields. Dryland wheat yields are estimated to decrease about eight percent for every one-degree Celsius increase in temperature, yet irrigation completely offsets this negative impact in our sample. As in previous studies, we find that important interactions exist between heat stress and precipitation for dryland production. Here, uniquely, we observe both dryland and irrigated trials side-by-side at the same locations and find that precipitation does not provide the same reduction in heat stress as irrigation. This is likely to be because the timing, intensity, and volume of water applications influence wheat yields, so the ability to irrigate—rather than relying on rainfall alone—has a stronger influence on heat stress. We find evidence of extensive differences of water-deficit stress impacts across varieties. This provides some evidence of the potential for adapting to hotter and drier climate conditions using optimal variety selection. Overall, our results highlight the critical role of water management for future global food security. Water scarcity not only reduces crop yields through water-deficit stress, but also amplifies the negative effects of warming temperatures

Risk Response in Agriculture

Crop production is subject to supply shocks, and both expected and realized outputs as well as output prices are unknown when inputs are chosen. The process by which producers form expectations is difficult to model, especially when working with aggregate data. We present a necessary and sufficient condition on cost and technology to allow variable input demand equations to be specified as functions of input prices, quasi-fixed inputs, and total variable cost. These all are observable when inputs are committed to production, so that ex ante demands can be estimated with observable data. A flexible, exactly aggregable, and economically regular model of variable input demands is derived and applied to aggregate U.S. agricultural data for the period 1960-1999. We use the empirical results of this model to aid in the specification of a dynamic life-cycle model for agricultural producers facing output and output price risk, with investment in an off-farm, conditionally risk free asset, risky financial assets, savings, consumption, and agricultural production opportunities. This framework admits a coherent, structural, econometric model of input use, output production, savings, investment, and consumption for agricul-ture. We apply this model to U.S. data for the period 1960-1999. Ongoing work focuses on updating the data set to the 21st century and applying both components of the model at the state-level.

Heterogeneous effects of warming and drought on selected wheat variety yields

Climate change is likely to significantly impact agricultural production in the Great Plains region of the Central United States. This study estimated the impact of changes in temperature and precipitation on wheat (triticum aestivum) variety yield distributions using the moment-based maximum entropy (MBME) model. This approach allows for quantification of potential weather impacts on the yield distribution, and allows these effects to vary across varieties. The unique data set matches wheat variety trial data for 1985 to 2011 with weather data from the exact trial site for 11 locations throughout Kansas. Ten widely-planted varieties with a range of biotic and abiotic characteristics were included for comparison. Weather scenarios were simulated for baseline, increased temperature (one-degree Celsius warming), decreased precipitation (tenth-percentile rainfall outcome), and a combination warming and drought scenario. Warming resulted in an 11 % yield reduction, drought a 22 % reduction, and warming and drought a cumulative 33 % reduction. These effects vary across varieties. Alternative measures of yield risk (e.g. yield variance and coefficient of variation) were also constructed under each scenario and a similar pattern of heterogeneous impacts emerges. The key findings are that (i) exposure to warming and drought lead to mean yield reductions coupled with increased yield risk for all varieties, and (ii) newer (post 2005) seed varieties have a yield advantage over older varieties, however this advantage is reduced under warming and drought conditions

Decreased wheat production in the USA from climate change driven by yield losses rather than crop abandonment

An increase in global average surface temperature over the 21st century will affect food production. There is still uncertainty if the source of the production losses caused by climate change could be driven either by lower yield or reduced area harvested. We use county-level production data on winter wheat coupled with fine-scale weather outcomes between 1981-2007 to examine the impact of climate change on winter wheat production in Kansas. We decompose the total impact of weather variables through both the yield and harvested acreage channels. We find that an insignificant portion—both in terms of magnitude and statistical significance—of the production losses are due to reduced harvested acres (i.e., crop abandonment). The proportion harvested only account for 14.88% and 21.71% of the total damages under RCPs 4.5 and 8.5 and neither effect is statistically significant. An implication of this result implies that studies that only examine climate impacts on harvested yields are not significantly underestimating the climate change impacts on production

Climate Change and Aflatoxin in Corn

The possible impacts of climate change on field crop production are many; however, most attention to date has been paid to projecting locational effects on yield and commercial viability (e.g., Zhao et al. 2017). But an altered climate will also have more nuanced effects through impacts on grain composition, safety, and quality. Our interest here is in how changing summertime weather patterns in the US central Corn Belt can provide an opening for increased aflatoxin damage in corn

Climate change will increase aflatoxin presence in US Corn

The impacts of climate change on agricultural production are a global concern and have already begun to occur (Kawasaki 2018 Am. J. Agric. Econ. 101 172–92; Ortiz-Bobea et al 2021 Nat. Clim. Change 11 306–12), with major drivers including warmer temperatures and the occurrence of extreme weather events (Lobell and Field 2007 Environ. Res. Lett. 2 014002; Challinor et al 2014 Nat. Clim. Change 4 287; Rosenzweig et al 2001 Glob. Change Hum. Health 2 90–104; Schlenker and Roberts 2009 Proc. Natl Acad. Sci. USA 106 15594–8; Lobell et al 2014 Science 344 516–9; Ortiz-Bobea et al 2019 Environ. Res. Lett. 14 064003). An important dimension of the climate change-crop yield relationship that has often been overlooked in the empirical literature is the influence that warming temperatures can have on plant damage arriving through biotic channels, such as pest infestation or fungal infection (Rosenzweig et al 2001 Glob. Change Hum. Health 2 90–104). Aflatoxins are carcinogenic chemicals produced by the fungi Aspergillus flavus and A. parasiticus, which commonly infect food crops. Currently, in the United States, aflatoxin is a perennial contaminant in corn grown in the South, but rare in the Corn Belt and northern states. Climate change may expand aflatoxin's geographical prevalence, however; because hot, dry summers promote aflatoxin accumulation. Here we model aflatoxin risk as a function of corn plant growth stages and weather to predict US regions with high aflatoxin risk in 2031–2040, based on 16 climate change models. Our results suggest that over 89.5% of corn-growing counties in 15 states, including the Corn Belt, will experience increased aflatoxin contamination in 2031–2040 compared to 2011–2020. Interestingly, the results are spatially heterogeneous and include several southern counties expected to have lower aflatoxin risk, because the causative fungi become inactivated at very high temperatures.This article is published as Yu, Jina, David A. Hennessy, Jesse Tack, and Felicia Wu. "Climate change will increase aflatoxin presence in US Corn." Environmental Research Letters 17, no. 5 (2022): 054017. doi:10.1088/1748-9326/ac6435. © 2022 The Author(s). Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI

Weather, disease, and wheat breeding effects on Kansas wheat varietal yields, 1985 to 2011.

Wheat (Triticum aestivum L.) yields in Kansas have increased due to wheat breeding and improved agronomic practices, but are subject to climate and disease challenges. The objective of this research is to quantify the impact of weather, disease, and genetic improvement on wheat yields of varieties grown in 11 locations in Kansas from 1985 to 2011. Wheat variety yield data from Kansas performance tests were matched with comprehensive location-specific disease and weather data, including seasonal precipitation, monthly air temperature, air temperature and solar radiation around anthesis, and vapor pressure deficit (VPD). The results show that wheat breeding programs increased yield by 34 kg ha⁻¹ yr⁻¹. From 1985 through 2011, wheat breeding increased average wheat yields by 917 kg ha⁻¹, or 27% of total yield. Weather was found to have a large impact on wheat yields. Simulations demonstrated that a 1°C increase in projected mean temperature was associated with a decrease in wheat yields of 715 kg ha⁻¹, or 21%. Weather, diseases, and genetics all had significant impacts on wheat yields in 11 locations in Kansas during 1985 to 2011