Global employment and decent jobs, 2010–2030: The forces of demography and automation

Globally, an estimated 734 million jobs will be required between 2010 and 2030 to accommodate recent and ongoing demographic shifts, account for plausible changes in labour force participation rates, and achieve target unemployment rates of at or below 4 per cent for adults and at or below 8 per cent for youth. The facts that most new jobs will be required in countries where “decent” jobs are less prevalent and workers in many occupations are increasingly subject to risks of automation further compound the challenge of job creation, which is already quite sizable in historical perspective. Failure to create the jobs that are needed through 2030 would put currently operative social security systems under pressure and undermine efforts to guarantee the national social protection floors enshrined in the Sustainable Development Goals (SDGs).     

A general central limit theorem and a subsampling variance estimator for α‐mixing point processes

We establish a central limit theorem for multivariate summary statistics of nonstationary α‐mixing spatial point processes and a subsampling estimator of the covariance matrix of such statistics. The central limit theorem is crucial for establishing asymptotic properties of estimators in statistics for spatial point processes. The covariance matrix subsampling estimator is flexible and model free. It is needed, for example, to construct confidence intervals and ellipsoids based on asymptotic normality of estimators. We also provide a simulation study investigating an application of our results to estimating functions.     

The Practical Significance of Measurement Error in Pulmonary Function Testing Conducted in Research Settings

Conventional spirometry produces measurement error by using repeatability criteria (RC) to discard acceptable data and terminating tests early when RC are met. These practices also implicitly assume that there is no variation across maneuvers within each test. This has implications for air pollution regulations that rely on pulmonary function tests to determine adverse effects or set standards. We perform a Monte Carlo simulation of 20,902 tests of forced expiratory volume in 1 second (FEV₁), each with eight maneuvers, for an individual with empirically obtained, plausibly normal pulmonary function. Default coefficients of variation for inter‐ and intratest variability (3% and 6%, respectively) are employed. Measurement error is defined as the difference between results from the conventional protocol and an unconstrained, eight‐maneuver alternative. In the default model, average measurement error is shown to be ～5%. The minimum difference necessary for statistical significance at p < 0.05 for a before/after comparison is shown to be 16%. Meanwhile, the U.S. Environmental Protection Agency has deemed single‐digit percentage decrements in FEV₁ sufficient to justify more stringent national ambient air quality standards. Sensitivity analysis reveals that results are insensitive to intertest variability but highly sensitive to intratest variability. Halving the latter to 3% reduces measurement error by 55%. Increasing it to 9% or 12% increases measurement error by 65% or 125%, respectively. Within‐day FEV₁ differences ≤5% among normal subjects are believed to be clinically insignificant. Therefore, many differences reported as statistically significant are likely to be artifactual. Reliable data are needed to estimate intratest variability for the general population, subpopulations of interest, and research samples. Sensitive subpopulations (e.g., chronic obstructive pulmonary disease or COPD patients, asthmatics, children) are likely to have higher intratest variability, making it more difficult to derive valid statistical inferences about differences observed after treatment or exposure.     

基于股价预测的泛证券投资组合策略

本文基于期望效用最大化和L₁-中位数估计研究了在线投资组合选择问题。与EG（Exponential Gradient）策略仅利用单期价格信息估计价格趋势不同，本文将利用多期价格信息估计价格趋势，以提高在线策略的性能。首先，基于多期价格数据，利用L₁-中位数估计得到预期价格趋势。然后，通过期望效用最大化，提出一个新的具有线型时间复杂度的在线策略，EGLM（Exponential Gradient via L₁-Median）。并通过相对熵函数定义资产权重向量的距离，进而证明了EGLM策略具有泛证券投资组合性质。最后，利用国内外6个证券市场的历史数据进行实证分析，结果表明相较于UP（Universal Portfolio）策略和EG策略，EGLM策略有更好的竞争性能。     

汉英新闻翻译中的词汇迁移及分析

新闻翻译是对外宣传的主要途径之一，准确而有效地翻译不仅涉及信息的有效传达，而且事关我们的国际形象。本文结合新闻英译中的一些实例，从语言迁移的角度分析新闻英译过程中一些词汇翻译的不当之处进行剖析，以探讨如何实现准确、有效的翻译。     

京津冀一体化河北省钢铁产业转型升级效果评价指标体系构建及应用研究

在实施产业转型升级过程中,构建合适的效果评价指标体系是一个复杂而重要的环节。依托京津冀一体化的发展现状,在分析了评价指标体系设计原则的基础上,从河北省钢铁产业转型升级对环境的影响、对省内经济的产业贡献和产业自身高效持续发展这三个维度出发,建立了京津冀一体化背景下河北省钢铁产业转型升级效果评价指标体系,为河北省钢铁产业转型升级的效果评价提供了一种结构性方法。据此,又提出了运用这一指标体系具体实施评价的原则与思路,从而为这一宏观实践活动提供了有益的启示。     

Computing the conditional stationary distribution in Markov chains of level-dependent M/G/1-type

This paper considers the computation of the conditional stationary distribution in Markov chains of level-dependent M/G/1-type, given that the level is not greater than a predefined threshold. This problem has been studied recently and a computational algorithm is proposed under the assumption that matrices representing downward jumps are nonsingular. We first show that this assumption can be eliminated in a general setting of Markov chains of level-dependent G/G/1-type. Next we develop a computational algorithm for the conditional stationary distribution in Markov chains of level-dependent M/G/1-type, by modifying the above-mentioned algorithm slightly. In principle, our algorithm is applicable to any Markov chain of level-dependent M/G/1-type, if the Markov chain is irreducible and positive-recurrent. Furthermore, as an input to the algorithm, we can set an error bound for the computed conditional distribution, which is a notable feature of our algorithm. Some numerical examples are also provided.     

制约我国政策性农业保险发展的因素及对策

建立政策性农业保险制度对于确保农业经济的持续增长和农民收入的稳定增加具有重大的现实意义。由于我国农业保险制度的发展受到多种因素的制约,导致保险深度和保险密度尚处于较低水平。我们要借鉴发达国家的成功经验,结合中国的实际,探索政策性农业保险的发展对策。     

青海省入境旅游市场的态势分析及预测研究

随着中国入境旅游的迅速发展,青海省的入境旅游呈现出不同的态势。本文从海外游客客源地、客源国等方面对其进行了深入的分析,在此基础上进行了预测,并提出了可行性建议。     

The Frisch–Waugh–Lovell theorem for the lasso and the ridge regression

The Frisch–Waugh–Lovell (FWL) (partitioned regression) theorem is essential in regression analysis. This is partly because it is quite useful to derive theoretical results. The lasso regression and the ridge regression, both of which are penalized least-squares regressions, have become popular statistical techniques. This article describes that the FWL theorem remains valid for these penalized least-squares regressions. More precisely, we demonstrate that the covariates corresponding to unpenalized regression parameters in these penalized least-squares regression can be projected out. Some other results related to the FWL theorem in such penalized least-squares regressions are also presented.