论清代北方乡约和保甲的关系

清代北方乡约与保甲的职能虽仍各有侧重,但两者的职能差异逐渐复杂化,且这种差异逐渐缩小,有的乡约对保甲还具有监督甚或领导作用。乡约与保甲关系的这些新变化,与清代北方乡约的普遍行政组织化有关。     

基于有理样条死亡假设的分数时点寿险净保费责任准备金

保险责任准备金是保险公司风险管理的重要度量指标,责任准备金的精确合理的测算,将会对保险公司的健康发展起着极其重要的作用。分数时点净保费责任准备金的测算依赖于精算假设,本文在提出一类有理样条死亡假设的基础上,研究了终身寿险的分数时点净保费责任准备金的计算问题。我们得到了其理论计算公式和上下界范围,探讨了调节参数的变化对净保费责任准备金的影响。数据分析表明:分数时点责任准备金对调节参数的变化比较敏感,目前常用的UDD假设下的责任准备金测算值恰是本文方法下的一个边界。所以基于有理样条估计方法的分数时点责任准备金测算在实务中具有很强的灵活性,对保险公司责任准备金风险管理具有重要的指导意义。     

Consistent Testing of Cointegrating Relationships

In this paper we investigate methods for testing the existence of a cointegration relationship among the components of a nonstationary fractionally integrated (NFI) vector time series. Our framework generalizes previous studies restricted to unit root integrated processes and permits simultaneous analysis of spurious and cointegrated NFI vectors. We propose a modified F‐statistic, based on a particular studentization, which converges weakly under both hypotheses, despite the fact that OLS estimates are only consistent under cointegration. This statistic leads to a Wald‐type test of cointegration when combined with a narrow band GLS‐type estimate. Our semiparametric methodology allows consistent testing of the spurious regression hypothesis against the alternative of fractional cointegration without prior knowledge on the memory of the original series, their short run properties, the cointegrating vector, or the degree of cointegration. This semiparametric aspect of the modelization does not lead to an asymptotic loss of power, permitting the Wald statistic to diverge faster under the alternative of cointegration than when testing for a hypothesized cointegration vector. In our simulations we show that the method has comparable power to customary procedures under the unit root cointegration setup, and maintains good properties in a general framework where other methods may fail. We illustrate our method testing the cointegration hypothesis of nominal GNP and simple‐sum (M1, M2, M3) monetary aggregates.     

Logistic模型配合家禽生长资料参数估计方法比较的Monte Carlo研究

本文用Logistic模型配合Monte Cario方法模拟的30个家禽生长资料,以比较Logis-tic模型参数估计的最小一乘法、最小二乘法和minx~2法,以及线性化方法。结果表明:最小二乘法(LS)和最小一乘法结果相当,均优于ininx~2方法;参数估计的线性化方法结果较差,以改良三点法效果较好。