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Recently, USDA-RMA introduced a Trend Adjusted-Actual Production History (TA-APH) program, which increases APH by a trend factor to cover yield changes over time. The purpose of this paper is to examine the effects of the TA-APH program on farmer participation, coverage election, and risk by analyzing data before and after the program.

Since the program was carried out in selected counties, the authors employ a difference in differences approach doing comparisons of insurance participation and coverage levels between eligible and ineligible counties.

The authors find that farmers within the counties where the TA-APH program was available experienced an increase in insured acres of 3 percent for corn and 5 percent for soybeans. The authors also find the farmers eligible for the program purchased lower coverage levels relative to those not eligible. However, the magnitude of that negative effect is relatively small, −0.9 percent in corn and −1.3 percent in soybeans. Collectively the evidence shows the TA-APH program does increase the guaranteed yield level mitigating farmer risk.

The data set used only permitted analysis at the county level, thus the authors could not look at the individual farmer choices.

The results suggest that if a greater level of farmer risk protection is desired from crop insurance, the authors find that the trend adjustment as implemented was a successful way to achieve this.

This paper contributes to the literature on the crop insurance by evaluating the program controlling for a non-participating groups, farming experience, liability rates, and subsidy rates. In doing this, it fulfills an identified need to study the actual impact on participation rates and coverage levels elected.

This study evaluates the impacts on gross revenue distributions of the use of alternative crop insurance products across different coverage levels and across locations with differing yield risks. Results are presented in terms of net costs, values‐at‐risk, and certainty equivalent returns associated with five types of multi‐peril crop insurance across different coverage levels. Findings show that the group policies often result in average payments exceeding their premium costs. Individual revenue products reduce risk in the tails more than group policies, but result in greater reductions in mean revenues. Rankings based on certainty equivalent returns and low frequency VaRs generally favor revenue products. As expected, crop insurance is associated with greater relative risk reduction in locations with greater underlying yield variability.

The USDA’s Risk Management Agency (RMA) made several changes to the crop insurance products available to organic growers for the 2014 crop year. Most notably, a 5 percent premium surcharge was removed and organic-specific transitional yields (t-yields) were issued for the first time. The purpose of this paper is to use farm-level organic crop yield data to analyze the impact of these reforms on producer insurance outcomes and compare the insurance options for new organic growers.

This study uses a unique panel data set of organic corn and soybean yields to analyze the impact of organic crop insurance reforms. Actual Production History values and premium rates are calculated for each farm and crop yield sequence. Producer loss ratios and subsidized premium wedges are compared for yield, revenue and area-risk products before and after the instituted reforms.

Results indicate that RMA succeeded in improving the actuarial soundness of the organic insurance program, though further refinement of organic t-yields may be necessary to accurately reflect the yield potential of organic producers and avoid reductions in program participation.

This paper provides insight into the effectiveness of reforms intended to improve the actuarial soundness of organic crop insurance and demonstrates the effect that the reforms are likely to have on new and existing organic farms. Because this analysis uses data collected independently of RMA and includes farms that may or may not have purchased crop insurance, it avoids the self-selection problems that might affect analyses using crop insurance program data.

The purpose of this paper is to analyze the effect of the 2008 Farm Bill's average crop revenue election (ACRE) program on the risk‐reducing effectiveness of crop insurance products.

Three crop/region combinations are examined, representing regions with both high and low price‐yield correlation regions. Actual production history (APH) and crop revenue coverage (CRC) insurance instruments are considered separately under the 2002 Farm Bill and under ACRE. Monte Carlo simulations, combined with the copula approach, are used to simulate net wealth distributions and to calculate the corresponding expected utilities. The outcomes are evaluated using certainty‐equivalent wealth based on different risk premium assumptions.

Crop insurance contracts appear to be more effective under the 2002 Farm Bill than under ACRE, especially for crops characterized by low yield‐price correlation. CRC insurance is found to be more effective than APH insurance for all crop/region combinations considered.

The paper only considers a static framework and farm‐level insurance contracts. Further research could investigate how ACRE affects decoupled income support, whether the results change if Supplemental Revenue Assistance is included, or how different the outcomes might be for multiple‐crop farms.

The results suggest that risk‐reducing effectiveness decreases under ACRE and that no reasonable adjustment to APH base price can make APH competitive with CRC for any crop/regions considered.

The risk‐reducing effectiveness of the 2008 Farm Bill's ACRE program is analyzed, and as a methodological contribution the copula approach is used to model the multivariate distribution of yields and prices.

This article seeks to examine the reference yield calculation method used in crop insurance rating and provides recommendations that could potentially improve actuarial performance of the Federal crop insurance program.

Conceptual, numerical, and statistical analysis is utilized to evaluate the reference yield calculation method used in the US Federal crop insurance program.

The results suggest that reference yields, which at the time of this study are calculated using National Agricultural Statistics Service (NASS) data, do not accurately represent the average actual yields of the insured pool of producers in the Federal crop insurance program. In addition, it is found that not regularly updating these NASS‐based reference yields exacerbates this problem because these reference yields do not appropriately represent the current state of technological progress.

The empirical analysis leads this paper to recommend a reference yield calculation procedure that utilizes county‐average yields from the risk management agency (RMA) participation database and an approach that uses spatially aggregated average yields in cases when data for a particular county are sparse.

No previous study has investigated the reference yield calculation method in the Federal crop insurance program using both RMA and NASS data sets. Moreover, this study contributes to the small literature that examines various aspects of the actual production history (APH) rating platform and suggests refinements to improve actuarial performance.

The US platelet supply is almost exclusively dependent on apheresis donors who are “aging out.” As a result, blood centers and hospitals have been experiencing spot shortages and have resorted to transfusing low-dose platelets. This paper explores using whole blood–derived platelets (WB-PLTs) to supplement the apheresis platelet (APH-PLT) supply.

This paper reviews the history leading to the current state of the US platelet supply and includes the impact of recent events such as the COVID-19 pandemic and the implementation of the US Food and Drug Administration (FDA)-mandated bacterial mitigation strategies.

WB-PLTs represent a viable source of platelets that can be used to supplement the APH-PLT supply. Whole blood automation represents a new methodology to more easily prepare WB-PLTs. Advances in donor testing and screening as well as pre-storage leukoreduction have improved the safety of WB-PLTs to the same level as APH-PLTs. Blood services in the US and abroad transfuse WB-PLTs interchangeably in all patient populations.

This paper highlights how the US blood industry is essentially “sole-sourced” in terms of APH-PLTs. In this post-COVID-19 period, when most industries are building redundancies in their supply chains, blood centers should consider WB-PLTs as an additional source of platelets to bolster the US platelet supply.

A common feature of certain kinds of data is a high level of statistical dependence across space and time. This spatial and temporal dependence contains useful information that can be exploited to significantly reduce the uncertainty surrounding local distributions. This chapter develops a methodology for inferring local distributions that incorporates these dependencies. The approach accommodates active learning over space and time, and from aggregate data and distributions to disaggregate individual data and distributions. We combine data sets on Kansas winter wheat yields – annual county-level yields over the period from 1947 through 2000 for all 105 counties in the state of Kansas, and 20,720 individual farm-level sample moments, based on ten years of the reported actual production histories for the winter wheat yields of farmers participating in the United States Department of Agriculture Federal Crop Insurance Corporation Multiple Peril Crop Insurance Program in each of the years 1991–2000. We derive a learning rule that combines statewide, county, and local farm-level data using Bayes’ rule to estimate the moments of individual farm-level crop yield distributions. Information theory and the maximum entropy criterion are used to estimate farm-level crop yield densities from these moments. These posterior densities are found to substantially reduce the bias and volatility of crop insurance premium rates.

Returns to a model farm are simulated to assess the impact of marketing and insurance risk management tools as measured by mean net returns and returns at 5% value‐at‐risk (VaR). Results indicate that revenue insurance strategies and strategies involving a combination of price and yield protection provide substantial downside revenue protection, while mean net returns only modestly differ from the benchmark harvest sale strategy when considering all years between 1986 and 2000.

Farm level data are essential to accurate setting of crop insurance premium rates, but their time series tends to be too short to allow them to be the sole data source. County level data are available in longer time series, however. The purpose of this paper is to present a methodology to make full use of the information inherent in each of these data sets.

The paper uses a novel application of statistical tools for using farm and county level yield data to generate farm level yield densities that explicitly incorporate within county yield heterogeneity while accounting for systemic risk and other spatial or intertemporal correlations among farms within the county.

The empirical analysis shows that current approaches used by the Risk Management Agency to individualize premiums for a farm result in substantial mispricing of crop insurance premiums because they do not adequately capture farm yield variability and yield correlations between farms. The new premium setting method is empirically shown to substantially reduce government subsidies for crop insurance premiums.

The paper demonstrates how to extract more information from available data when setting crop insurance premiums, which allows the government to more closely tailor premiums to the farm than do current approaches.

Civil society played a significant role during and after the 2014 revolution in Ukraine, which led to the resignation of President Yanukovich and his government and triggered a series of political, economic and social changes. In some areas, particularly by HIV and tuberculosis, the critical gaps threatened the emergence of a public health catastrophe. The purpose of this paper is to describe how civil society expands and strengthens its role in complex crisis situations, self-regulating and re-adjusting own aims and strategy by using the case of non-governmental organisations (NGOs) active in HIV prevention in high-risk groups and harm reduction.

The paper presents the analysis of the case of Alliance of Public Health, one of the principal recipients of the Global Fund to Fight Tuberculosis, AIDS and Malaria in 2014-2016, during and after the Euromaidan Revolution in Ukraine.

In the post-Euromaidan era, NGO sector has been able to sustain the response to the HIV/AIDS epidemic at a stable level despite significant limitations of resources and the overall fragile situation. Special efforts have been undertaken to continue activities in the conflict zone in the east of the country. Furthermore, NGOs managed to extend beyond their usual responsibilities, bridging the gaps in deteriorating public health and social systems, including taking the leadership in medical procurement; advocating for national plans development; and supplying medical goods to the uncontrolled territories in the east of the country.

This paper is one of the first exploring the role of non-governmental sector in HIV/AIDS programmes in resource-scarce situation of political, social and economic crisis. Case description of the strategies and activities applied in the situation gives the possibility to reflect on raising the effectiveness of the response to existing and emerging public health issues in complex crisis, as well on the potential for HIV/AIDS prevention and treatment advocacy to grow into global health diplomacy.