Inferring Directional Migration Propensities from the Migration Propensities of Infants in the United States

Beginning with the 2010 decennial census, the U.S. Census Bureau plans to drop its long-form questionnaire and to replace it with the American Community Survey (ACS). The resulting absence of the larger sample provided by the census count will complicate the measurement and analysis of internal migration flows. In addition, the strategy of averaging accumulated samples over time will mix changing migration patterns. The migration question will refer to a one-year time interval instead of the five-year interval used in the censuses between 1960 and 2000, complicating historical comparisons and the production of multiregional projections based on five-year age groups. Consequently, students of territorial mobility increasingly will find it necessary to complement or augment possibly inadequate data collected on migration with estimates obtained by means of “indirect estimation.” A method is presented that allows one to infer age-specific directional migration propensities at the regional level from birthplace-specific infant population data, which approximates infant migration propensities, and from these infers the migration propensities of all other ages. The method is applied to at the nine-division spatial scale.     

Enhancing a Randomized Response Model to Estimate Population Means to Sensitive Questions

ABSTRACT

Candidate parametric mortality models are tested graphically. If the model is correct, the transformed data are distributed exponentially. The graphical test is based on scale and space inference. It involves smoothing of the hazard rate and simultaneous confidence intervals. It is applied to a frailty model used to set annuity reserves. Simulation and the comparison with other non-graphical tests shows that the graphical test helps localize discrepancies of empirical data with respect to the tested model.     

“五普”人口总量和结构的分析与调整

以人口普查资料为基础,运用人口存活分析方法和数值拟合思想,并辅之以其他统计数据和对比分析方法,分析五普数据中的重报和漏报,对普查人口总量和结构进行调整。研究发现,“五普”0-9岁人口存在漏报,漏报人口为3 743万;而10-60岁人口存在重报,重报人口为1 134万人;最终调整五普人口总数为127 120万,普查人口漏报率为2.05%。     

立法后评估结果的回应机制

立法后评估结果的回应机制,就是特定的国家机关针对立法后评估报告中提出来的问题,采取特定方式作出回复或反应的具体运作过程。有效的立法后评估的回应机制建立在立法后评估结果的信度与效度上,其回应主体是立法后评估报告所涉及的有关立法与执法机关或人员,同时还要求运用特定的回应方式与内容。为保障立法后评估结果顺畅的有效回应,还需要建立完善的立法后评估结果回应的监控制度。     

时间断点回归:原理框架、应用演进与估计流程

文章首先运用归纳法,提出时间断点回归的概念内涵和基本模型,并按"准随机实验"标准分析其存在的原理缺陷。然后通过梳理国外相关前沿成果,总结出时间断点回归有别于传统计量操作的方面:在适用性判断上,强调内生分组问题的理论分析和协变量连续性的提前估计;在稳定性检验上,包含更换变量指标等正向思路、对照组检验等反向思路、时间序列特征处理和其他非断点回归方法。最后,绘制时间断点回归的估计流程图,主要涉及适用性检验、处理效应的初步判定、模型构建与估计和稳健性检验四个部分。     

地理依赖、空间溢出与河南省金融发展空间分异——基于1990—2012年县域数据的空间计量分析

以河南省1990—2012年各县域金融相关比率为衡量金融发展水平指标,利用MatLab、ArcGIS工具,采用非参数核密度估计、ESDA局部空间相关分析与空间地理加权模型回归方法,从空间相互作用角度对河南省各县域金融发展的空间布局进行研究与分析,以揭示其演化特征、空间依赖性及异质性,并对形成原因进行初步探索。结果显示,河南省县域金融发展水平总体存在显著的空间集聚特征,呈现出明显的地理依赖特征;同时结合非参数核密度估计分析发现,豫北地区地域差距较小,豫东传统农业地区县域金融发展差距较大,揭示出局部空间异质问题;最后结合GWR分析,在影响河南省金融空间布局的因素中,工业发展水平始终主导着区域金融发展空间格局的演化,中心城市的工业发展对邻近县域金融发展具有显著的促进作用,但其“空间溢出”具有有限的边界。     

结合相干系数的极化干涉SAR植被高度估计方法研究

阐述了极化干涉SAR成像技术的基本理论,分析了极化干涉SAR的植被散射模型和Cloude三阶段植被高度反演算法。因三阶段法采用多参数初值迭代求解方法,其运算量较大复杂性高,该文提出基于相干系数的高度估计方法。先用干涉相位估计植被高度,再由相干系数幅度估计植被高度对前面相位估计的高度进行补偿,既保证了一定植被高度估计精度,又大大减少了反演算法的运算量,最后用极化干涉SAR仿真数据验证了该方法的有效性。     

OFDM系统二维变换域信道估计算法

着重分析OFDM系统的二维变换域(2-D transform-domain)的导频辅助信道估计。在变换域中对导频位置的信道频率响应(CFR)矩阵采用右下补零和中间补零两种方式进行插值,以获得整个信道的频率响应。考虑到上述两种方法带来的插值误差,提出了根据时间、频率方向的导频数目采用不同的补零数量和补零方式。采用Simulink构建基带仿真系统,仿真改进前后的系统误比特率(BER)并和其他二维插值方式进行比较。结果表明,该改进方法显著地提高了基于变换域信道估计的准确性,降低了系统的误比特率。     

CP不足情况下OFDM系统信道估计与均衡

正交频分复用(OFDM)系统中的循环前缀具有一定的抗码间干扰(ISI)和子载波间干扰(ICI)的能力,但是当多径衰落信道的最大信道脉冲响应(CIR)长度超过了循环前缀(CP)长度时,OFDM系统的性能将会严重下降。传统的信道估计和均衡方案面对循环前缀长度不够的情况无法避免性能的严重衰落。由此提出了一种可以估计出大于CP长度CIR的信道估计方法,并且给出了一种基于逼零(ZF)准则的低复杂度均衡器,以抵消ISI和ICI的影响。仿真结果表明所提方案与传统方案相比在复杂度上和性能上有明显的优势。     

Estimation of parameters in heavy-tailed distribution when its second order tail parameter is known

Estimating parameters in heavy-tailed distribution plays a central role in extreme value theory. It is well known that classical estimators based on the first order asymptotics such as the Hill, rank-based and QQ estimators are seriously biased under finer second order regular variation framework. To reduce the bias, many authors proposed the so-called second order reduced bias estimators for both first and second order tail parameters. In this work, estimation of parameters in heavy-tailed distributions are studied under the second order regular variation framework when the second order parameter in the distribution tail is known. This is motivated in large part by a recent work by the authors showing that the second order tail parameter is known for a large class of popular random difference equations (for example, ARCH models). The focus is on least squares estimators that generalize rank-based and QQ estimators. Though other possible estimators are also briefly discussed, the least squares estimators are most simple to use and perform best for finite samples in Monte Carlo simulations.