英国自由放任经济发展战略述评

自由放任政策是英国重商主义之后发展经济的指导性政策。但深究英国自由放任经济政策的实质,不难看出,在自由放任理念盛行的年代,国家在理论和道义上遵循了占主流的经济发展理念,而其战略和政策的出发点则在于经济运作最核心的一点——利益。而如何实现最大利益化,也是推动英国经济发展政策从自由放任向国家干预转变的内在动力。     

劳动力外流对农户技术持续使用意愿的非线性影响

在农村劳动力大量外流的现实背景下，以专业化食用菌种植为例，探析家庭劳动力外流对农户专业化技术持续使用意愿的影响以及产生影响的内在作用机理，并采用10个省份的农户调研数据进行实证检验。研究发现：①家庭劳动力外流对农户专业化技术持续使用意愿的影响效应呈倒U型态势，即家庭劳动力外流对农户专业化技术持续使用意愿的影响先增强后减弱。②因果中介效应分析表明，劳动力外流的影响还部分通过改变农户的技术认知和技术评价间接影响农户技术持续使用意愿，两条路径共同解释了77.95%的总效应。③受教育年限、是否村干部、种植规模、成本预期和收益预期等亦是影响农户专业化生产技术持续使用意愿的因素。提出应完善劳动力流动的体制机制，减少劳动力流动的障碍，提升其正向影响；同时，完善社会化服务和社会保障体系，削弱其负向影响，有助于新技术的推广和提升食用菌生产的专业化水平。     

Win statistics (win ratio,win odds,and net benefit) can complement one another to show the strength of the treatment effect on time-to-event outcomes

Conventional analyses of a composite of multiple time-to-event outcomes use the time to the first event. However, the first event may not be the most important outcome. To address this limitation, generalized pairwise comparisons and win statistics (win ratio, win odds, and net benefit) have become popular and have been applied to clinical trial practice. However, win ratio, win odds, and net benefit have typically been used separately. In this article, we examine the use of these three win statistics jointly for time-to-event outcomes. First, we explain the relation of point estimates and variances among the three win statistics, and the relation between the net benefit and the Mann–Whitney U statistic. Then we explain that the three win statistics are based on the same win proportions, and they test the same null hypothesis of equal win probabilities in two groups. We show theoretically that the Z-values of the corresponding statistical tests are approximately equal; therefore, the three win statistics provide very similar p-values and statistical powers. Finally, using simulation studies and data from a clinical trial, we demonstrate that, when there is no (or little) censoring, the three win statistics can complement one another to show the strength of the treatment effect. However, when the amount of censoring is not small, and without adjustment for censoring, the win odds and the net benefit may have an advantage for interpreting the treatment effect; with adjustment (e.g., IPCW adjustment) for censoring, the three win statistics can complement one another to show the strength of the treatment effect. For calculations we use the R package WINS, available on the CRAN (Comprehensive R Archive Network).