Do greater amounts of FDI cause higher pollution levels? Evidence from OECD countries

Using an ARDL model for a panel of 15 OECD countries, this work analyses the impact that FDI, both jointly and by sector, has on CO₂ emissions. The findings reveal that these countries are yielding to the pressure on the trade sector. Unexpectedly, gross fixed capital formation shrink pollution, excluding in the mining sector. With findings supporting the Pollution Haven Hypothesis, policymakers must pay attention to FDI inflows, ensuring that FDI place high importance on the transfer of green technologies to improve the efficiency. These goals could be achieved through an increase in the stringency of environmental laws within the host countries, especially the ones related to FDI.     

Tests for homogeneity of risk differences in stratified design with correlated bilateral data

ABSTRACT

Correlated bilateral data arise from stratified studies involving paired body organs in a subject. When it is desirable to conduct inference on the scale of risk difference, one needs first to assess the assumption of homogeneity in risk differences across strata. For testing homogeneity of risk differences, we herein propose eight methods derived respectively from weighted-least-squares (WLS), the Mantel-Haenszel (MH) estimator, the WLS method in combination with inverse hyperbolic tangent transformation, and the test statistics based on their log-transformation, the modified Score test statistic and Likelihood ratio test statistic. Simulation results showed that four of the tests perform well in general, with the tests based on the WLS method and inverse hyperbolic tangent transformation always performing satisfactorily even under small sample size designs. The methods are illustrated with a dataset.     

On the power of goodness-of-fit tests for the exponential distribution under progressive Type-II censoring

The aim of this article is to review existing goodness-of-fit tests for the exponential distribution under progressive Type-II censoring and to provide some new ideas and adjustments. In particular, we consider two-parameter exponentially distributed random variables and adapt the proposed test procedures to our scenario if necessary. Then, we compare their power by an extensive simulation study. Furthermore, we propose five new test procedures that provide reasonable alternatives to those already known.     

Some count-based nonparametric tests for circular symmetry of a bivariate distribution

In this paper, we revisit the problem of testing of the hypothesis of circular symmetry of a bivariate distribution. We propose some nonparametric tests based on sector counts. These include tests based on chi-square goodness-of-fit test, the classical likelihood ratio, mean deviation, and the range. The proposed tests are easy to implement and the exact null distributions for small sample sizes of the test statistics are obtained. Two examples with small and large data sets are given to illustrate the application of the tests proposed. For small and moderate sample sizes, the performances of the proposed tests are evaluated using empirical powers (empirical sizes are also reported). Also, we evaluate the performance of these count-based tests with adaptations of several well-known tests such as the Kolmogorov–Smirnov-type tests, tests based on kernel density estimator, and the Wilcoxon-type tests. It is observed that among the count-based tests the likelihood ratio test performs better.     

Lower bound of average centered L2-discrepancy for U-type designs

Uniform designs are widely used in various scientific investigations and industrial applications. By considering all possible level permutation of the factors, a connection between average centered L₂-discrepancy and generalized wordlength pattern for asymmetrical fractional factorial designs is derived. Moreover, we present new lower bounds to the average centered L₂-discrepancy for symmetrical and asymmetrical U-type designs. For illustration of the theoretical results, the lower bounds for symmetrical and asymmetrical U-type designs are tabulated, and numerical results indicate that our lower bounds behave well and can be recommended for use in practice.     

Improved functional portmanteau tests

Functional time series is a popular method of forecasting in functional data analysis. The Box-Jenkins methodology for model building, with the aim of forecasting, includes three iterative steps of model identification, parameter estimation and diagnostic checking. Portmanteau tests are one of the most popular diagnostic checking tools. In particular, they are applied to find if the residuals of the fitted model are white noise. Gabrys and Kokoszka [Portmanteau test of independence for functional observations. J Am Stat Assoc. 2007;102(480):1338–1348.] proposed a portmanteau test of independence for functional observation based on Box and Pierce's statistic. Their statistic is too sensitive to the lag value, specially when the sample size is small. Here, two modifications of Gabrys and Kokoszka statistic are presented, which have superior properties in small samples. The efficiency of the modified statistics is demonstrated through a simulation study.     

嵌套并联结构两阶段DEA下科技创新效率测度与分解

目前有许多研究将两阶段DEA模型应用到科技创新活动当中，一般将创新活动分为研发和转化两个阶段，为了进一步探讨不同转移转化方式下科技成果的转化效率以获得更多的详细信息，本文拓展了传统的两阶段DEA模型，考虑了嵌套并联结构的两阶段网络DEA模型，将科技创新活动分为科技成果研发阶段和科技成果转化阶段，并将科技成果转化阶段分为内部转化和外部转化两个并联子系统。本文选取14家中科院院属单位作为被评价对象，应用加权加法分解方法计算整体效率和各阶段子效率。通过将本文模型与传统两阶段模型进行对比发现，传统模型会低估科技成果转化效率。结果表明：整体科技创新效率均值偏低，科技成果研发效率均值高于科技成果转化效率均值，科技成果转化效率仍有很大的提升空间。科技成果转化阶段中内部转化效率普遍较高但是外部转化效率普遍较低，较低的外部转化效率是导致科技成果转化效率低下的主要原因。最后，本文将所有被评价单位分为四类机构，分析提高科技创新效率的实现路径，可以通过重点突破模式和渐进突破模式来实现整体效率的提高。     

疫情防控期间大学生焦虑水平及其影响因素研究

为了解大学生在新型冠状病毒肺炎疫情防控期间的焦虑状况，采用汉密顿焦虑量表（HAMA），对四川、云南、重庆三省（直辖市）的3 178名大学生进行在线问卷测试。结果发现：新冠肺炎疫情防控期间大学生焦虑水平高于常模，并且与大学生的性别、就读学历层次、就读学科、每日上网时间等存在显著相关性。其中，28.48%的大学生还可能有严重焦虑；女性、专科层次、尚不清楚就读学科的大学生群体焦虑水平更为明显；精神性焦虑是新冠肺炎疫情防控期间大学生焦虑的主要特质；每日上网时间与大学生精神性焦虑水平呈显著正相关。在公共卫生事件突发时期，应积极关注大学生的心理健康状态，采取针对性措施加以有效疏导和干预，促进其心理健康发展。