General equilibrium models of environmental regulation and international trade

general equilibrium;international trade;environmental policy

Optimal investments in clean production capacity

For the mitigation of long-term pollution threats, one must consider that both the process of environmental degradation and the switchover to new and cleaner technologies are dynamic. We develop a model of a uniform good that can be produced by either a polluting technology or a clean one; the latter is more expensive and requires investment in capacity. We derive the socially optimal pollution stock accumulation and creation of nonpolluting production capacity, weighing the tradeoffs among consumption, investment and djustment costs, and environmental damages. We consider the effects of changes in the pollution decay rate, the capacity depreciation rate, and the initial state of the environment on both the steady state and the transition period. The optimal transition path looks quite different with a clean or dirty initial environment. With the former, investment is slow and the price of pollution may overshoot the long-run optimum before converging. With the latter, capacity may overshoot

High-risk pooling for mitigating risk selection incentives in health insurance markets with sophisticated risk equalization:an application based on health survey information

Background: Despite sophisticated risk equalization, insurers in regulated health insurance markets still face incentives to attract healthy people and avoid the chronically ill because of predictable differences in profitability between these groups. The traditional approach to mitigate such incentives for risk selection is to improve the risk-equalization model by adding or refining risk adjusters. However, not all potential risk adjusters are appropriate. One example are risk adjusters based on health survey information. Despite its predictiveness of future healthcare spending, such information is generally considered inappropriate for risk equalization, due to feasibility challenges and a potential lack of representativeness. Methods: We study the effects of high-risk pooling (HRP) as a strategy for mitigating risk selection incentives in the presence of sophisticated– though imperfect– risk equalization. We simulate a HRP modality in which insurers can ex-ante assign predictably unprofitable individuals to a ‘high risk pool’ using information from a health survey. We evaluate the effect of five alternative pool sizes based on predicted residual spending post risk equalization on insurers’ incentives for risk selection and cost control, and compare this to the situation without HRP. Results: The results show that HRP based on health survey information can substantially reduce risk selection incentives. For example, eliminating the undercompensation for the top-1% with the highest predicted residual spending reduces selection incentives against the total group with a chronic disease (60% of the population) by approximately 25%. Overall, the selection incentives gradually decrease with a larger pool size. The largest marginal reduction is found moving from no high-risk pool to HRP for the top 1% individuals with the highest predicted residual spending. Conclusion: Our main conclusion is that HRP has the potential to considerably reduce remaining risk selection incentives at the expense of a relatively small reduction of incentives for cost control. The extent to which this can be achieved, however, depends on the design of the high-risk pool.</p

High-risk pooling for mitigating risk selection incentives in health insurance markets with sophisticated risk equalization:an application based on health survey information

Background: Despite sophisticated risk equalization, insurers in regulated health insurance markets still face incentives to attract healthy people and avoid the chronically ill because of predictable differences in profitability between these groups. The traditional approach to mitigate such incentives for risk selection is to improve the risk-equalization model by adding or refining risk adjusters. However, not all potential risk adjusters are appropriate. One example are risk adjusters based on health survey information. Despite its predictiveness of future healthcare spending, such information is generally considered inappropriate for risk equalization, due to feasibility challenges and a potential lack of representativeness. Methods: We study the effects of high-risk pooling (HRP) as a strategy for mitigating risk selection incentives in the presence of sophisticated– though imperfect– risk equalization. We simulate a HRP modality in which insurers can ex-ante assign predictably unprofitable individuals to a ‘high risk pool’ using information from a health survey. We evaluate the effect of five alternative pool sizes based on predicted residual spending post risk equalization on insurers’ incentives for risk selection and cost control, and compare this to the situation without HRP. Results: The results show that HRP based on health survey information can substantially reduce risk selection incentives. For example, eliminating the undercompensation for the top-1% with the highest predicted residual spending reduces selection incentives against the total group with a chronic disease (60% of the population) by approximately 25%. Overall, the selection incentives gradually decrease with a larger pool size. The largest marginal reduction is found moving from no high-risk pool to HRP for the top 1% individuals with the highest predicted residual spending. Conclusion: Our main conclusion is that HRP has the potential to considerably reduce remaining risk selection incentives at the expense of a relatively small reduction of incentives for cost control. The extent to which this can be achieved, however, depends on the design of the high-risk pool.</p

Changes in the mean echogenicity and area of the puborectalis muscle during pregnancy and postpartum

INTRODUCTION AND HYPOTHESIS: Three-dimensional (3D) and four-dimensional (4D) volume transperineal ultrasound imaging is increasingly used to assess changes in the dimensions of the pelvic floor during pregnancy and after delivery. Little is known with regard to the area of the puborectalis muscle and its structural changes. Echogenicity measurement, a parameter that provides information on the structure of muscles, is increasingly used in orthopaedics and neuromuscular disease evaluation. This study is aimed at assessing the changes in the mean echogenicity of the puborectalis muscle (MEP) and the puborectalis muscle area (PMA) during first pregnancy and after childbirth. METHODS: The MEP and PMA of 254 women during first pregnancy were measured at 12 and 36 weeks’ gestation and 6 months postpartum. To determine the effect of child-birth on MEP and PMA, the results at 6 months postpartum were separately analysed for vaginal deliveries, operative vaginal deliveries (ventouse) and caesarean section deliveries. Mean differences in MEP and PMA were analysed using ANOVA statistics. RESULTS: The MEP at 6 months postpartum was, independent of manoeuvre, significantly (p < 0.001) lower than MEP values during pregnancy. After caesarean delivery, the PMA was significantly smaller at maximum pelvic floor contraction than PMA after vaginal delivery (p = 0.003) or operative vaginal delivery (p = 0.002). CONCLUSION: Our study indicates that structural changes in the puborectalis muscle during and after pregnancy, as measured by MEP, occur and can be analysed. In addition, the mode of delivery affects the area of the puborectalis during contraction after delivery. For true volume analysis, as part of an assessment of contractility of the puborectalis muscle we will need 3D volume analysis

Measuring echogenicity and area of the puborectalis muscle:method and reliability

OBJECTIVES: To develop a semi-automated method to assess puborectalis muscle echogenicity on three-dimensional/four-dimensional (3D/4D) volume transperineal ultrasound images using 4D View and Matlab® software and evaluate its intra- and interobserver reliability. METHOD: The data of 23 women in their first trimester were included. 3D/4D volume datasets were obtained at rest. Two inexperienced observers were trained by an experienced observer to construct tomographic ultrasound images (TUI) from the original data and to delineate all structures. Puborectalis muscle area (PMA) and the mean echogenicity of the puborectalis muscle (MEP) were calculated offline. Intra- and interobserver reliability were determined by intraclass correlation coefficients (ICC) and their 95% CIs. RESULTS: The development of a semi-automated method to calculate puborectalis area and echogenicity is described in detail. PMA and MEP measurements in pregnant women demonstrated almost perfect intraobserver reliability for both inexperienced observers, with ICC values ranging from 0.88 to 0.99. The interobserver reliability showed ICCs of 0.63 for PMA and almost perfect ICC values, of 0.96-0.98, for echogenicity. The majority of intraobserver mismatch between two delineations of PMA occurred near the borders. CONCLUSIONS: Matlab software can be used to provide reliable measurements of the area and echogenicity of the puborectalis muscle. As the latter can be used to assess structural changes in the puborectalis muscle, it appears a promising new tool for studying pelvic floor structural anatomy