Understanding changes in Māori incomes and income inequality 1997–2003

This paper examines recent changes in weekly income levels and dispersion for Māori, New Zealand’s indigenous ethnic group. Changes in the Māori income distribution between 1997 and 2003 reflect rapid increases in economic growth and employment rate. A reduced proportion of people had zero or benefit-level incomes and a higher proportion had high incomes. Income inequality declined for working-aged Māori and was stable for employed Māori. The average income gap between Māori and Europeans declined. The increased Māori employment rate during this period was the single most important driver of changes in the Māori income distribution.

Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.     

Analysis of Competing Risks by Using Bayesian Smoothing

We consider the competing risks set-up. In many practical situations, the conditional probability of the cause of failure given the failure time is of direct interest. We propose to model the competing risks by the overall hazard rate and the conditional probabilities rather than the cause-specific hazards. We adopt a Bayesian smoothing approach for both quantities of interest. Illustrations are given at the end.     

Bayesian prediction of waiting times in stochastic models

The authors show how saddlepoint techniques lead to highly accurate approximations for Bayesian predictive densities and cumulative distribution functions in stochastic model settings where the prior is tractable, but not necessarily the likelihood or the predictand distribution. They consider more specifically models involving predictions associated with waiting times for semi‐Markov processes whose distributions are indexed by an unknown parameter θ. Bayesian prediction for such processes when they are not stationary is also addressed and the inverse‐Gaussian based saddlepoint approximation of Wood, Booth & Butler (1993) is shown to accurately deal with the nonstationarity whereas the normal‐based Lugannani & Rice (1980) approximation cannot, Their methods are illustrated by predicting various waiting times associated with M/M/q and M/G/1 queues. They also discuss modifications to the matrix renewal theory needed for computing the moment generating functions that are used in the saddlepoint methods.     

On optimal testing for the equality of equicorrelation: An example of loss in power

Sen Gupta (1988) considered a locally most powerful (LMP) test for testing nonzero values of the equicorrelation coefficient of a standard symmetric multivariate normal distribution. This paper constructs analogous tests for the symmetric multivariate normal distribution. It shows that the new test is uniformly most powerful invariant even in the presence of a nuisance parameter, σ². Further applications of LMP invariant tests to several equicorrelated populations have been considered and an extension to panel data modeling has been suggested.     

Asymptotic Bias in Parameter Estimation of AR-Processes Using Recursive Least Squares with Exponential Forgetting

The recursive least squares technique is often extended with exponential forgetting as a tool for parameter estimation in time-varying systems. The distribution of the resulting parameter estimates is, however, unknown when the forgetting factor is less than one. In this paper an approximative expression for bias of the recursively obtained parameter estimates in a time-invariant AR( n_a ) process with arbitrary noise is given, showing that the bias is non-zero and giving bounds on the approximation errors. Simulations confirm the approximation expressions.     

光谱法测量等离子体离子温度和再循环粒子流速

利用多道光学分析仪（OSMA）测量HT-6M托卡马克限制器前Hα线形分布,通过高斯拟合由多普勒展宽和多普勒频移分别得出等离子体离子温度和再循环粒子流速。     

广东普通工科高等教育的办学效益分析研究

对广东普通工科高等教育的办学效益问题,从结构布局效益、层次与规模效益进行了讨论,提出了提高办学效益的基本对策。     

人力资本、公平感知与农村居民基本医疗保险参与——基于四川农村地区的实证分析

城乡居民基本医疗保险作为构成我国社会保障体系的核心内容,既是农村居民获得所需医疗服务、应对健康危机的兜底性保障,也是国家推进基本医疗卫生服务公平均等的基础性政策。然而,基于四川省农村地区的调研发现,仍然存在农村居民没有购买基本医疗保险的现象。深入剖析其影响因素,结果发现：(1)人力资本水平、对基本医疗保险政策的公平感知均会显著作用于农村居民基本医疗保险购买行为;(2)外出务工经历、缴费便捷程度、家庭收入水平等也对农村居民基本医疗保险购买行为有显著影响;(3)当前对基本医疗保险政策知识宣传不够,难以满足农村居民对政策知识的需求。基于以上研究结果,为进一步提高基本医疗保险参与率,提出了优化基本医疗保险政策宣传、提高基本医疗保险政策的认同感和加快医保管理服务系统信息化建设等对策建议。     

农户土地流转有助于农户群体“提低扩中”吗?

提高中低收入农户群体的收入水平是缩小居民收入差距、实现共同富裕的关键任务。利用CFPS 2018数据,使用基于RIF的ITE模型等计量方法进行分析研究发现：(1)土地流转的增收效应具有非对称性,转出土地的中低收入农户能显著增收,但转入土地的中低收入农户增收不明显;(2)东部和西部地区转出土地的中低收入农户收入增长显著;(3)土地流转(尤其是转出)有助于缩小农户间收入差距、优化农户群体的收入分配结构。实证结果稳健地说明农户土地流转对实现农户群体“提低扩中”目标具有积极意义,在此基础上提出在西部和东中部欠发达农村地区,鼓励和支持中低收入农户流转土地,以增加其兼业和非农收入等政策建议。