Using geocoded survey data to improve the accuracy of multilevel small area synthetic estimates

This paper examines the secondary data requirements for multilevel small area synthetic estimation (ML-SASE). This research method uses secondary survey data sets as source data for statistical models. The parameters of these models are used to generate data for small areas. The paper assesses the impact of knowing the geographical location of survey respondents on the accuracy of estimates, moving beyond debating the generic merits of geocoded social survey datasets to examine quantitatively the hypothesis that knowing the approximate location of respondents can improve the accuracy of the resultant estimates. Four sets of synthetic estimates are generated to predict expected levels of limiting long term illnesses using different levels of knowledge about respondent location. The estimates were compared to comprehensive census data on limiting long term illness (LLTI). Estimates based on fully geocoded data were more accurate than estimates based on data that did not include geocodes.     

Application of copulas to multivariate control charts

The most popular multivariate control chart for monitoring the mean of a distribution is probably the Hotelling T² rule. Unfortunately, this rule relies on the assumption that the distribution under control is Gaussian, which is rarely true in practice. The objective of this paper is to propose a new approach for the non-normal multivariate case. It consists in the construction of a tolerance region obtained from a density level set estimation. The method follows a “plug-in” approach in which the density of the observations is previously estimated. This estimation is conducted using copulas modeling, an increasingly popular tool in multivariate modeling.     

Critical Bellman–Harris branching processes with infinite variance allowing state-dependent immigration

The branching processes with state-dependent immigration are considered as alternating regenerative processes. The main purpose is to demonstrate some new “regenerative” methods. Critical Bellman–Harris branching processes with state-dependent immigration are investigated and new limit theorems are obtained in the case of an infinite offspring variance and possibly infinite mean of the immigrants.     

Selection of Single Sampling Attributes Plan for Given Acceptable Quality Level and Limiting Quality Level Involving Minimum Risks

A table and a procedure are given for finding the single sampling attributes plan involving minimum sum of producer's and consumer's risks for specified Acceptable Quality Level and Limiting Quality Level.     

On some properties of variable size simple random sampling and a limit theorem

This paper introduces a sampling plan for finite populations herein called “variable size simple random sampling” and compares properties of estimators based on it with results from the usual fixed size simple random sampling without replacement. Necessary and sufficient conditions (in the spirit of Hajek (1960)) for the limiting distribution of the sample total (or sample mean) to be normal are given.     

Brazil and the Shifting Consensus on Development Co‐operation: Salutary Diversions from the ‘Aid‐effectiveness’ Trail?

Emerging economies emphasise horizontality and mutual opportunity in their relationship with developing countries, promising an alternative to the failings of traditional North‐South co‐operation. This article draws on research on Brazil's technical co‐operation and its health dimension to compare the Brazilian model with established aid‐effectiveness' principles and to discuss the appropriateness of the latter as standards against which to appraise emerging donors' co‐operation. The analysis shows that, despite progress towards greater dialogue between traditional and emerging donors, the ‘aid‐effectiveness’ framework still falls short of capturing the idiosyncrasies of South‐South co‐operation and therefore offers an incomplete international standard on how best to conduct development co‐operation.     

工业机器人使用与制造业就业：来自中国的证据

本文使用我国2006-2017年制造业分行业数据,实证研究了工业机器人使用对于制造业就业的影响。结果显示,工业机器人使用对制造业行业存在就业效应,其中对岗位数量有显著的负向冲击,工业机器人保有量每上升1%,就业岗位减少约4.6%;对工资水平的影响整体上不明显。在考虑了劳动力市场的动态调节后,工业机器人使用对就业岗位的负面影响仍然存在,并随着“工业4.0”概念的提出有所增强,对工资水平的影响则表现出时间异质性。进一步地,本文尝试使用工具变量解决潜在的内生性问题,结果稳健。最后,文章还探讨了工业机器人就业效应的行业异质性。本文的发现有助于正确认清“机器换人”对我国制造业就业市场的全面影响,并为引导人工智能技术的发展和确保就业稳定提供相应的政策建议。     

A Numerical Study of Small Parameter Behavior of Some Families of Distributions

Limiting distributions play an important role in approximating the exact distributions, especially when they have a rather cumbersome analytic form, or simply when they do not have a closed from. The question that naturally arises is how good the approximation is. In this article, we propose a procedure for the numerical assessment of the “goodness” of some easy-to-calculate limiting distributions, originally proposed in Bar-Lev and Enis, in various cases of the underlying distributions, some of which are inherently computationally challenging. The details of the procedure are provided in three examples. The first example deals with the gamma distributions; the second deals with Bessel distributions related to a symmetric random walk, and the third example deals with positive stable distributions. The details of two additional variations of these examples are also discussed. These examples illustrate the ease with which the limiting approximations could be applied in the various cases, well-demonstrating their computational simplicity and attractiveness.     

新疆人口生育水平的变化及其影响因素

利用"六普"数据对新疆人口生育水平的变化及其影响因素进行相关分析,发现:新疆人口生育水平与少数民族人口比重、计划生育利益导向政策执行情况、妇女受教育程度存在高度相关性,而经济发展水平与生育水平之间却是中度相关关系。这与目前有研究认为经济社会发展水平对经济较发达东部地区的生育率有显著影响,而对经济相对落后的中、西部地区作用不明显的结论相一致。     

人口老龄化对我国财政支出规模的影响——从社会保障角度出发

以我国1995—2008年财政支出规模和社会保障水平为样本,采用回归模型对两者关系进行了实证分析。此外,在该模型的基础上,加入人口老龄化变量,对老年人数量、老年抚养比与财政支出的关系进行实证分析。研究结果发现:社会保障水平与财政支出规模有着显著的正向关系;老年人数量的增加、老年抚养比的增高对财政支出规模的扩大也起了一定作用。