Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?

In this paper, I assess the evidence for a structural break in labor productivity growth in the years before the Great Recession with the use of out-of-sample forecasting exercises for the years 2010 to 2019 and the recently developed Beveridge–Nelson filter. Models based on a Beveridge–Nelson filter with no structural breaks outperform those allowing for a structural break, and there is statistically significant evidence that they outperform the random walk, though all models were too optimistic about labor productivity growth. Recently developed statistical tests do point to the presence of a structural break before the Great Recession, but uncertainty about the data-generating process for labor productivity growth or the timing and magnitude of the break may be too great to be helpful in forecast preparation.     

渠道合作情境下合同双元功能对主动和被动投机行为的影响差异研究

基于交易成本理论，在渠道合作情境下，以制造商的合同监督和企业间联合行动为工具测量合同治理的保障功能和协作功能，探讨二者对经销商主动投机行为和被动投机行为的影响差异。通过对512份问卷数据的统计分析，得到以下结论：第一，合同监督有助于抑制经销商的主动投机行为，但对其被动投机行为的影响不显著；第二，企业间联合行动有助于抑制经销商的被动投机行为，但对其主动投机行为的影响不显著；第三，经销商的主动投机行为和被动投机行为均会负向影响合作绩效；第四，经销商的主动投机行为中介合同监督对合作绩效的正向影响，被动投机行为中介企业间联合行动对合作绩效的正向影响。     

乘积型指数滤波器及其在多目标时延估计中的应用

指数滤波器是一类新构造出来的输出信噪比和目标时延分辨力随指数变化的滤波器，该滤波器在损失一定输出信噪比的前提下可以有效提高目标时延分辨力，从而提高目标时延估计精度,但仅采用单个指数滤波器仍存在输出信噪比和目标时延分辨力均达不到实际需求的情况。在乘积型高阶模糊函数乘积运算的启发下，在指数滤波器的基础上提出了一种新的乘积型指数滤波器，并分析了该乘积型指数滤波器的输出信噪比及目标时延分辨力等性能。仿真实验表明，所提的乘积型指数滤波器在低信噪比情况下可以更有效提高多目标时延估计精度，且算法简单易于实现，适用于背景复杂的多目标参数估计任务。     

我国大麦价格波动特征及其影响因素分析

[目的]大麦价格剧烈波动会直接影响大麦种植户的生产积极性和大麦产业的平稳发展,研究大麦价格波动特征及其影响因素,有助于提升大麦产业链相关主体识别和应对市场风险的能力,促进大麦产业的健康发展。[方法]文章先采用HP滤波法和ARCH类模型分析了2011年4月至2017年2月我国大麦价格波动特征,然后采用脉冲响应函数分析了我国大麦价格波动影响因素。[结果]我国大麦价格波动存在明显的季节性和周期性,样本期内总体上呈现逐渐下降趋势;我国大麦价格具有显著的波动集聚性,我国大麦价格具有显著的不对称性;在该文选择的影响因素中,大麦进口量和国际大麦价格是影响我国大麦价格波动的主要因素。[结论]该文提出必须保障并提高国内大麦合理产能、完善大麦价格监测预警体系、加强国内大麦进口企业整合和推动大麦进口来源多元化的政策建议。     

Equally Weighted Strategic Allocation and Balanced Funds in Brazil

This article analyzes equally weighted strategic asset allocation portfolios in Brazil between 2004 and 2016 and shows that their average returns are not always statistically greater than those of balanced funds, with significance changing in sub-periods. Fixed-income portfolios frequently outperform balanced funds, whose active management underperforms their declared benchmark portfolios. Balanced funds underperformed probably because they deviated from their investment policy. Transaction costs and other rebalancing frequencies do not change the conclusions. Robustness tests indicate that this evidence is valid out-of-the-sample. Investors can mimic balanced-fund policy and possibly do better by means of indexing according to this policy.     

采用目标假设的三被动式传感器数据关联算法

被动式传感器目标跟踪是多传感器多目标跟踪领域的一个重要研究方向。针对三被动式传感器多目标定位系统全局最优数据关联的三维分配问题，在允许传感器漏检和虚警的情况下，通过分析拉格朗日松弛算法，提出一种假定真实目标的快速收敛算法。该算法通过粗关联假定真实目标并重新修改代价矩阵，然后进行细关联，使得拉格朗日松弛算法在保证关联精度的前提下有效地提高了收敛速度。理论分析和实验结果表明，该算法提高了数据关联的速度,并在一定程度上提高了关联准确率。     

面向卫星导航信号的外辐射源雷达软件化模拟器设计

面向全球导航卫星系统(Global Navigation Satellite System，GNSS)信号的外辐射源雷达，是一种利用环境中GNSS信号作为非合作照射源进行探测的雷达。为满足基于GNSS信号的外辐射源雷达系统仿真和信号处理算法设计评估的需要，通过对该雷达系统组成与工作原理的分析，完成了面向GNSS信号的外辐射源雷达软件化信号模拟器的设计与实现。给定仿真场景下软件化模拟器输出信号处理和分析的结果验证了该模拟器可根据输入参数与模型正确完成信号仿真。     

改进高阶容积粒子滤波的系统状态估计算法

传统粒子滤波（PF）直接采用状态转移先验分布作为重要性密度函数来近似后验概率密度函数，使得后验概率密度函数未包含量测信息。针对此问题，提出了一种改进高阶容积粒子滤波(CPF)的系统状态估计算法。算法采用七阶正交容积卡尔曼滤波（7th-CQKF）对PF的粒子进行传递，使得先验分布更新阶段融入最新量测信息；通过7th-CQKF设计重要性密度函数，提高对状态后验概率密度的逼近程度；通过反比例函数计算粒子权重，突出大噪声粒子与小噪声粒子权重差别，提高粒子有效性。仿真结果表明，改进高阶容积粒子滤波的估计精度高于容积粒子滤波（CPF）。     

What do professional forecasters actually predict?

This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by professional forecasters by regressing their forecasts on the estimated components extracted from both the spectral analysis and the state space model. For both decomposition methods, we find that, in the short run, the Survey of Professional Forecasters can predict almost all of the variation in the time series due to the trend and the business cycle, but that the forecasts contain little or no significant information about the variation in the irregular component.     

一种基于SIR结构的三通带带通滤波器

应用双指耦合结构和枝节加载谐振器（Stub-loaded Resonator，SLR）实现了一款基于阶梯阻抗谐振器（Stepped Impedance Resonator，SIR）的滤波器。该滤波器具有3个通带，带外抑制较好，工作频段提高。通过调整阻抗比可调节第二、三通带的谐振频率；SLR结构能够增加通带数量；SLR结构和双指耦合结构均能改善滤波器的S参数。HFSS软件仿真表明，3个通带的中心频率分别为3.5 GHz、6.6 GHz、9.2 GHz，对应的分数带宽分别为5.7%、3%、2%，S11分别为-18 dB、-22 dB、-24 dB，通带内的S21分别为-1.8 dB、-1 dB、-1 dB。电路的测量结果与仿真结果较为吻合。该滤波器在5G通信的低频段具有应用前景。