出口贸易与省域TFP空间维度分析

作为衡量一国科技进步的重要指标,全要素生产率的高低决定着一国生产率水平的先进与落后。在不断深化改革开放的过程中,如何利用开放倒逼我国技术水平的提高成为一项较为紧迫的任务。为此,我们运用面板DEA-Malmquist指数法可以测算出2002—2011年我国29个省份(含自治区、直辖市)全要素生产率,并在此基础上建立空间面板数据模型(SPDM),实证分析出口贸易、基础设施等对我国省域全要素生产率及其空间溢出效应的影响。经研究发现,我国省域全要素生产率存在较为明显的空间自相关性,即出口贸易、基础设施等经济活动通过影响本省TFP,并通过空间溢出效应进一步将其作用传递和迭加到邻近省域全要素生产率上,基础设施对我国省域全要素存在较为显著的负向关系,出口依存度、出口贸易及FDI对我国省域全要素生产率具有显著的推动作用。     

国外高等教育评估制度对我国高教评估的启迪

美、英、日三国各具特色的教育评估制度,对建设和完善具有中国特色的高等教育评估制度有重要的启示作用,借鉴国外高教评估体制的长处和经验,指出我国教育质量评估主要应由民间评估机构进行;高校办学质量评估中教育质量与科研质量应分别评估;把学科建设作为评估的主要内容;评估标准能充分体现高校高度的自治性。同时分析了我国高教评估的现状和发展趋向。     

Estimation of Laspeyres Price Indexes Using the Prediction Approach for Finite Population Sampling

Estimators of chain and fixed-base Laspeyres price indexes are studied using the prediction approach to finite population sampling. The estimators include some that are based on those used in several U.S. government index programs and others derived from prediction models. Biases and variances of the estimators are studied for a case in which the reference period index weights are unknown for nonsample items. Under a model for a one-period price change in which items have common within-stratum means, unbiased estimators can be constructed, but under a more general regression model, special sample balance conditions are needed for unbiasedness of those estimators. The theory for the estimators of fixed-base indexes is illustrated in an empirical study using a population of items priced for the U.S. Consumer Price Index.     

基尼系数的区间估计及其应用

 本文给出了收入为离散分布的三种计算基尼系数的新方法。利用收入份额法导出了基尼系数协方差算法的离散形式,并因此产生了计算基尼系数的回归系数法。文章重点讨论了基尼系数进行区间估计的两种方法,这些方法也适用于集中度指数,因而它们在测度社会经济领域的不平等中具有着十分广泛的用途。实际应用表明,新算法有效地简化了对基尼系数区间估计的标准差估算。     

各省区季度GDP数据质量评估

  国内外学者对我国GDP数据质量的质疑重点已从年度数据转到季度数据,从全国数据转向地方数据。本文通过设计一套较为系统且可操作性强的季度GDP评估指标体系,运用空间面板数据模型对各省区的季度GDP数据质量进行了实证检验。结果表明,整体来看,中国各省区季度GDP同各经济指标的匹配性较好,数据质量较高,并不存在明显的失真现象;从时间上来看,每年一、二季度的GDP存在一定程度的高估,而每年三、四季度的GDP则存在一定程度的低估,但是这种偏差在统计上不显著;分地区来看,尽管一半省区的季度GDP存在一定程度的高估,另一半省区存在一定程度的低估,但大部分省区高估或低估的程度在统计上不显著。文章进一步分析了其中的原因。     

Psychosocial risk factors for excessive gestational weight gain: A systematic review

BackgroundExcessive weight gain during pregnancy can have adverse health outcomes for mother and infant throughout pregnancy. However, few studies have identified the psychosocial factors that contribute to women gaining excessive weight during pregnancy.AimTo review the existing literature that explores the impact of psychosocial risk factors (psychological distress, body image dissatisfaction, social support, self-efficacy and self-esteem) on excessive gestational weight gain.MethodsA systematic review of peer-reviewed English articles using Academic Search Complete, Cumulative Index to Nursing and Allied Health Literature, MEDLINE Complete, PsycINFO, Informit, Web of Science, and Scopus was conducted. Quantitative studies that investigated psychosocial factors of excessive GWG, published between 2000 and 2014 were included. Studies investigating mothers with a low risk of mental health issues and normally-developing foetuses were eligible for inclusion. From the total of 474 articles located, 12 articles were identified as relevant and were subsequently reviewed in full.FindingsSignificant associations were found between depression, body image dissatisfaction, and social support with excessive gestational weight gain. No significant relationships were reported between anxiety, stress, self-efficacy, or self-esteem and excessive gestational weight gain.ConclusionThe relationship between psychosocial factors and weight gain in pregnancy is complex; however depression, body dissatisfaction and social support appear to have a direct relationship with excessive gestational weight gain. Further research is needed to identify how screening for, and responding to, psychosocial risk factors for excessive gestational weight gain can be successfully incorporated into current antenatal care.     

Climate regime shift detection with a trans‐dimensional,sequential Monte Carlo,variational Bayes method

We present an application study which exemplifies a cutting edge statistical approach for detecting climate regime shifts. The algorithm uses Bayesian computational techniques that make time‐efficient analysis of large volumes of climate data possible. Output includes probabilistic estimates of the number and duration of regimes, the number and probability distribution of hidden states, and the probability of a regime shift in any year of the time series. Analysis of the Pacific Decadal Oscillation (PDO) index is provided as an example. Two states are detected: one is associated with positive values of the PDO and presents lower interannual variability, while the other corresponds to negative values of the PDO and greater variability. We compare this approach with existing alternatives from the literature and highlight the potential for ours to unlock features hidden in climate data.     

中国省际人口流动与 人力资本流动差异性分析

人力资本流动与人口流动相关却不相同,本文采用2010-2016年全国流动人口动态监测数据,从流动方向和流动强度两方面对我国省际人口流动引致的人力资本流动现象加以研究。结果表明从流动方向分析,各省人口净流动方向基本呈现时间一致性并且流入流出区域具有稳定性。在调查期间人口净流出省份为16个,人口净流入省份为15个,没有明显变化。人力资本净流向与人口净流向完全一致,但省际人口净流向与高级人力资本净流向并不完全一致,山西、广西、重庆等省市的高级人力资本净流向始终与总人力资本净流向相反。本文采用流出流入比率和迁移选择中心两种指标测算人力资本流动强度,结果基本一致。人力资本流动中心与人口流动中心分布均较为固定。2010年人力资本流动强度最大的省份在2016年的流动强度也更强,流动强度在省际呈现惯性和马太效应。人力资本流入最强地区包括北京、天津、上海三个直辖市,人力资本流出最强省份始终包括安徽、四川、河南等省份。以人力资本流出弹性衡量人力资本流出强度与人口流出强度的相对强弱,东部地区、东北地区省份人力资本的流出强度始终大于人口流出强度,西部地区省份差异较大。考虑各省近五年经济增长状况,人口流动或者人力资本流动对经济增长的影响是非线性的。     

What does Brunei teach us about using Human Development Index rankings as a policy tool?

The Bruneian Government has set an ambitious target to achieve a top 10 ranking on the United Nations Development Programme's (UNDP) Human Development Index (HDI) by 2035. To achieve its objective (described in a national strategy document called the Wawasan 2035), Brunei's economy needs to grow by 6% to 7%. Is setting an HDI target a good way to govern Brunei's policy‐making? Is it a good way to govern any country's policy‐making? In this article, we look at the role of HDI‐rank targets in economic and fiscal policy. We show that such a headline target (much like a profit target in a private company) automatically sets targets for growth in various economic sectors and fiscal policy targets. As such, HDI‐rank targeting may provide a useful mechanism for co‐ordinating development policies and for monitoring progress against a wide range of development goals using only one number.     

Risk and diversification of nonprofit revenue portfolios: Applying modern portfolio theory to nonprofit revenue management

This study uses modern portfolio theory (MPT) to estimate the risk of nonprofit revenue portfolios and examines to what degree the revenue concentration measure based on Herfindahl–Hirschman Index is associated with the portfolio risk measure based on MPT. The findings suggest that nonprofits with greater revenue concentration have lower revenue portfolio risk in the whole sample analysis. However, it is plausible that this result is dominated by organizations reliant on commercial income, which comprise over half of the sample. In fact, when examined separately, the relationship varies by an organization's primary funding structure. While higher revenue concentration is positively associated with portfolio risk for organizations relying on donations or those without a consistent primary funding source, it appears to associate with a lower portfolio risk for commercial organizations and those relying on government grants. This study reflects on the concept of diversification derived from portfolio theory and calls attention to a more nuanced approach to nonprofit revenue strategy.