Economic losses are incurred by the US livestock industries because farm animals are raised in locations and seasons where effective temperature conditions venture outside their zone of thermal comfort. The objective of this review was to estimate economic losses sustained by major US livestock industries from heat stress. Animal classes considered were: dairy cows, dairy heifers (0 to 1 yr and 1 to 2 yr), beef cows, finishing cattle, sows, market hogs, broilers, layers, and turkeys. Economic losses considered were: 1) decreased performance (feed intake, growth, milk, eggs), 2) increased mortality, and 3) decreased reproduction. USDA and industry data were used for monthly inventories of each animal class in each of the contiguous 48 states. Daily weather data from 257 weather stations over a range of 68 to 129 yr were used to estimate mean monthly maximum and minimum temperatures, relative humidity, and their variances and covariances for each state. Animal responses were modeled from literature data using a combination of maximum temperaturehumidity index, daily duration of heat stress, and a heat load index. Monte Carlo techniques were used to simulate 1000 times the weather for each month of the year, for each animal class, for each state, and for each of four intensities of heat abatement (minimum, moderate, high, and intensive). Capital and operating costs were accounted for each heat abatement intensity. Without heat abatement (minimum intensity), total losses across animal classes averaged $2.4 billion annually. Optimum heat abatement intensity reduced annual total losses to $1.7 billion.

Increasing drought and extreme rainfall are major threats to maize production in the United States. However, compared to drought impact, the impact of excessive rainfall on crop yield remains unresolved. Here, we present observational evidence from crop yield and insurance data that excessive rainfall can reduce maize yield up to −34% (−17 ± 3% on average) in the United States relative to the expected yield from the long‐term trend, comparable to the up to −37% loss by extreme drought (−32 ± 2% on average) from 1981 to 2016. Drought consistently decreases maize yield due to water deficiency and concurrent heat, with greater yield loss for rainfed maize in wetter areas. Excessive rainfall can have either negative or positive impact on crop yield, and its sign varies regionally. Excessive rainfall decreases maize yield significantly in cooler areas in conjunction with poorly drained soils, and such yield loss gets exacerbated under the condition of high preseason soil water storage. Current process‐based crop models cannot capture the yield loss from excessive rainfall and overestimate yield under wet conditions. Our results highlight the need for improved understanding and modeling of the excessive rainfall impact on crop yield.

Farmers' decisions to purchase crop insurance and their choices among alternative products are analyzed using a two-stage estimation procedure. The influences of risk perceptions, competing risk management options, as well structural and demographic differences are evaluated. The likelihood for crop insurance usage is found to be higher for larger, older, less tenured, more highly leveraged farms, and by those with higher perceived yield risks. The marginal effects of size, age, perceived yield risk, perceived importance of risk management activities, and other structural and demographic variables are identified in terms of their influences on choices among alternative crop insurance products. Copyright 2004, Oxford University Press.

Agri-food supply chains in North America have become remarkably efficient, supplying an unprecedented variety of items at the lowest possible cost. However, the initial stages of the COVID-19 pandemic and the near-total temporary loss of the foodservice distribution channel, exposed a vulnerability that many found surprising. Instead of continued shortages, however, the agri-food sector has since moved back to near normal conditions with prices and production levels similar to those typically observed in years prior to the pandemic. Ironically, the specialization in most food supply chains designed for “just-in-time” delivery to specific customers with no reserve capacity, which led to the initial disruptions, may have also been responsible for its rapid rebound. A common theme in assessing the impacts across the six commodities examined is the growing importance of understanding the whole supply chain. Over the longer term, a continuation of the pandemic could push the supply chain toward greater consolidation of firms and diversification of products given the increasing option value of maintaining flexibility. Other structural changes will be felt through input markets, most notably labour, as the trend toward greater automation will continue to accelerate as a response to meeting concerns about a consistent supply of healthy and productive workers. The economic fall out from the pandemic may lead to greater concentration in the sector as some firms are not able to survive the downturn and changes in consumer food buying behaviour, including movement toward online shopping and enhanced demand for attributes associated with resiliency, such as local. On the other hand, online shopping may provide opportunities for small producers and processors to shorten supply chains and reach customers directly. In the long term, COVID-19 impacts on global commerce and developing country production are more uncertain and could influence poverty reduction. While COVID-19's impacts on North American agriculture should have minimal effect on the Sustainable Development Goals (SDGs) through food prices, the ongoing global trends in trade and agribusiness accelerated by the pandemic are relevant for achievement of the SDGs.

Considerable disagreement exists about the most appropriate characterization of farm-level yield distributions. Yet, the economic importance of alternative yield distribution specifications on crop insurance valuation has not been well documented. The results of this study demonstrate that large differences in expected payouts from popular crop insurance products can arise solely from the parameterization chosen to represent yield distributions. The results suggest that the frequently unexamined yield distribution specification may lead to economically significant errors in crop insurance policy rating and assessment of expected payouts from policies. Copyright 2004, Oxford University Press.

Although computer technologies have evolved rapidly, farmers have been slow to adopt these technologies. This research identities factors influencing farmers' adoption of computers and the number and type of applications for which the computer is used. Ohio commercial farmers were randomly sampled and analyzed using multinomial logit techniques. Results suggest that older farmers are less likely to adopt computers, less likely to find them useful, and make fewer applications of the computer in their business. Education level is positively associated with computer adoption and with increased numbers of applications made of the computer.Agricultural businesses increasingly use information as an input in the production process. During the past decade, information options available to farmers changed substantially. Rapid development of computer and telecommunication technologies and corresponding reductions in their costs have increased the capability of computers to assist business managers in the collection, storage, and processing of information. However, adoption of this technology has lagged behind its development. Various projections made nearly a decade ago forecasted that most commercial farmers would be using computers by 1990. These projections have proven grossly inaccurate, even though computer processing speed and software availability have improved remarkably. Recent estimates of computer adoption rates range from a mere 3% of all farmers (Willimack) to just over 25% (Puder and Zilberman).Objectives of this paper are to address computer adoption and integration within farm businesses. Specific objectives are to (a) identify factors associated with computer adoption by Ohio commercial farmers, (b) determine how The authors are, respectively, associate professors and an assistant professor, The authors are grateful to Rob King and Ed Rister for helpful comments on an earlier version of this manuscript. these factors relate to operators' computer usefulness evaluations, and (c) determine the type and number of computer applications. Multinomiallogit analyses of a random sample of Ohio commercial farmers are used to address these objectives. Previous ResearchSeveral studies have estimated farmers' adoption rates for computer technologies. Willimack, using data from the 1987 Farm Costs and Returns Survey, found that less than 3% of U.S. farmers use a computer to maintain farm records. Because her analysis focused on farm record keeping, it probably understated computer use in the sample. Furthermore, the sample employed the census ($1,000 sales) definition of a farm and thus included many small operations.Other studies of commercial-sized farm businesses have found higher adoption rates. Farm Futures magazine conducted a telephone survey of a random sample of its subscribers and found that 31% owned computers. Lazarus and Smith found that 15% of New York dairy farmers enrolled in the Farm Business Summary and Analysis program in 1986 owned computers. A follow-up study (Lazarus, Streeter, and JofreGiraudo) tr...

Patterns in loss-ratio experience in the U.S. corn insurance market are investigated with a spatial econometric model. The results demonstrate systematic geographically related misratings and provide estimates of the impacts of several observable factors on the magnitude of misrating in the program. The model is used to estimate actuarial cross-subsidizations across the primary corn-producing states and counties. The impacts of the primary factors are substantial, resulting in net premium transfers of approximately 26 percent of total premiums annually. The misratings likely have important insurance demand, welfare, and land-use implications.Insurance markets are typically best suited for risks that are uncorrelated, occur with high frequency, and have a large number of like participants-among a handful of other standard conditions. Systemic risks (such as in crop production) induce correlation in losses, violating the standard insurability conditions and potentially leading to market failures (Glauber, 2004). Complementary causes of market failures in such systemic risk markets may include capital market imperfections, inadequate reinsurance capacities, capital and information shocks due to unexpected events, fattailed distributions that prevent diversification, and agency problems (see, e.g.,

Multinomial logit models were used to examine farmers' information preferences for marketing, production, and financial decisions. Dependent variables represented the preferred information source category: Cooperative Extension Service, printed, broadcast, specialist, and other sources. Independent variables included farm and business characteristics. In general, farmers preferred information from printed sources, and the Cooperative Extension Service ranked highly as an information source. Results did not support the contention that farmers are substituting specialist services for information received from the Cooperative Extension Service.