Markov-switching dynamic factor models in real time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as mixed sampling frequencies and ragged-edge data. First, we evaluate the theoretical gains of using data that are available promptly for computing probabilities of recession in real time. Second, we show how to estimate the model that deals with unbalanced panels of data and mixed frequencies, and examine the benefits of this extension through several Monte Carlo simulations. Finally, we assess its empirical reliability for the computation of real-time inferences of the US business cycle, and compare it with the alternative method of forecasting the probabilities of recession from balanced panels.     

基于MSP430单片机的流量显示表硬件CPU设计

随着计算机的发展,工业自动化水平的提高,在工程中流量显示表已得到了广泛的使用。显示仪表精确度的高低,直接影响着企业的经济效益。在我国现有经济水平下,使用单片机开发的流量显示表,在工程中是非常适用的。该表是用MSP430F135为主芯片,并辅以其他的外围模块构成的具有串行通讯功能,满足流量检测显示的嵌入式最小系统。     

Interpoint Distance Test of Homogeneity for Multivariate Mixture Models

Finite mixtures offer a rich class of distributions for modelling of a variety of random phenomena in numerous fields of study. Using the sample interpoint distances (IPDs), we propose the IPD‐test statistic for testing the hypothesis of homogeneity of mixture of multivariate power series distribution or multivariate normal distribution. We derive the distribution of the IPDs that are drawn from a finite mixture of the multivariate power series distribution and multivariate normal distribution. Based on the empirical distribution of the IPDs, we construct a bootstrap test of homogeneity for other multivariate finite mixture models. The IPD test is applied to mixture models for matrix‐valued distributions and a test of homogeneity for Wishart mixture is presented. Numerical comparisons show that IPD test has accurate type I errors and is more powerful in most multivariate cases than the expectation–maximization (EM) test and modified likelihood ratio test.     

基于JIT思想对汽车玻璃生产线WIP的控制策略

本文分析了汽车玻璃加工生产线的生产流程,生产车间不同种类的在制品(WIP)数量很庞大,为此研究生产线的瓶颈工序,得到瓶颈工序生产线的切换时间对WIP库存的影响,研究生产线的切换时间、工序之间的生产节拍比和WIP库存数三者之间的关系,结合JIT和WIP库存控制策略来保证生产线的流畅生产,归纳出关键的工序节拍比下所需的WIP库存数的动态变化情况,从而动态地控制WIP库存的变化并最大程度地降低车间的WIP库存。     

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.     

利用气井历史生产数据计算动态储量新方法

气藏动态储量是指参与渗流的地下气体地质储量,计算动储量常采用物质平衡法,但是对于难以获得平均地层压力的致密气藏不适用。本文介绍了利用气井长时间生产数据计算动态储量的方法,并研究采用叠加时间函数(Super-t)分析变产量修正时间,使计算结果更加精确;同时应用该方法对苏东南区致密砂岩气藏部分气井进行单井动态储量计算,为该区动储量估算提供借鉴。     

基于时间维度的组织学习理论——组织从过去经历中学习的模型

从经历中学习是组织学习的重要方面。从科学、严谨的研究范式出发,结合东方传统的"阴阳"哲学思想,基于时间维度提出了包含学习主体、经历样本、成功失败经历集、学习主体特征、"知"和"行"等要素的组织从过去经历中学习的模型,并对相关问题进行了探究。具体包括:学习主体从经历中学习的认知特性;不同类型经历对应的不同学习方法,成功经历和失败经历对学习效果的差异性影响,经历集影响"知"和"行"的7种自动的和有意的学习方式;"知"与"行"相互转化及其触发机制;客观世界从时间和空间两个维度客观展开的观点等。该系统模型为未来研究提供了理论框架和实证检验方向。     

Updating Input–Output Tables with Benchmark Table Series

Numerous methods have been proposed to update input–output (I–O) tables. They rely on the assumption that the economic structure will not change significantly during the interpolation period. However, this assumption may not always hold, particularly for countries experiencing rapid development. This study attempts to combine forecasting with a matrix transformation technique (MTT) to provide a new perspective on updating I–O tables. Under the assumption that changes in the trend of an economic structure are statistically significant, the method extrapolates I–O tables by combining time series models with an MTT and proceeds with only the total value added during the target years. A simulation study and empirical analysis are conducted to compare the forecasting performance of the MTT to the Generalized RAS (GRAS) and Kuroda methods. The results show that the comprehensive performance of the MTT is better than the performance of the GRAS and Kuroda methods, as measured by the Standardized Total Percentage Error, Theil's U and Mean Absolute Percentage Error indices.     

An empirical investigation of water consumption forecasting methods

Many regions on earth face daily limitations in the quantity and quality of the water resources available. As a result, it is necessary to implement reliable methodologies for water consumption forecasting that will enable the better management and planning of water resources. This research analyses, for the first time, a large database containing data from 2 million water meters in 274 unique postal codes, in one of the most densely populated areas of Europe, which faces issues of droughts and overconsumption in the hot summer months. Using the R programming language, we built and tested three alternative forecasting methodologies, employing univariate forecasting techniques including a machine-learning algorithm, with very promising results.     

京津冀城市大气环境竞争力评价

从大气环境与城市竞争力的关联性入手,将大气环境风险、现状和治理纳入评价指标体系,基于组合权重的大气环境竞争力评价模型,对2013-2017年京津冀13个城市的大气环境竞争力水平进行了测评,并结合空间自相关分析和障碍度模型揭示了其空间效应及障碍因素。结果显示:京津冀城市大气环境竞争力存在明显的空间差异,呈"北部高、南部低、局部跳跃"格局,城市差距逐渐缩小;京津冀城市大气环境竞争力呈显著的空间集聚效应且存在正向相关性,空间分布格局相对稳定。