Policy responses to COVID-19 pandemic waves: Cross-region and cross-sector economic impact

This paper proposes a modelling approach to assess the cross-region and cross-sector economic impacts of the restrictions imposed by governments to contain the COVID-19 pandemic. The nationwide lockdown imposed in Italy during the first wave of the pandemic is used as a benchmark. However, the adopted approach allows an ex-ante assessment of alternative policy responses, in the event of successive pandemic waves, in order to rationalise the policy intervention and reach the best possible compromise between containing the risk of contagion and reducing economic losses. The used approach consists of a non-linear programming model based on a multiregional Input-Output (I-O) table, which guarantees greater flexibility than traditional I-O analysis. It is applied to estimate both direct and indirect losses of GDP and employment produced by alternative policy responses represented by general and differentiated lockdowns. The evidence deriving from the Italian experience shows a sort of learning process through successive waves based on the introduction of increasingly flexible and tailored policy responses to the pandemic.     

Unbiased Estimator for a Covariance Matrix Under Two-Step Monotone Incomplete Sample

In this article, we consider an inference for a covariance matrix under two-step monotone incomplete sample. The maximum likelihood estimator of the mean vector is unbiased but that of the covariance matrix is biased. We derive an unbiased estimator for the covariance matrix using some fundamental properties of the Wishart matrix. The properties of the estimators are investigated and the accuracies are checked by a numerical simulation.     

Type I and Type II error rates in the last observation carried forward method under informative dropout

Dropout is a persistent problem for a longitudinal study. We exhibit the shortcomings of the last observation carried forward method. It produces biased estimates of change in an outcome from baseline to study endpoint under informative dropout. We developed a theoretical quantification of the effect of such bias on type I and type II error rates. We present results for a setup where a subject either completes the study or drops out during one particular interval, and also under the setup in which subjects could drop out at any time during the study. The type I error rate steadily increases when time to dropout decreases or the common sample size increases. The inflation in type I error rate can be substantially high when reasons for dropout in the two groups differ; when there is a large difference in dropout rates between the control and treatment groups and when the common sample size is large; even when dropout subjects have one or two fewer observations than the completers. Similar results are also observed for type II error rates. A study can have very low power when early recovered patients in the treatment group and worsening patients in the control group drop out even near the end of the study.     

不完全信息下企业营销团队的激励问题研究

在多变的环境与激烈的竞争中,团队作为一种行之有效的组织形式,在现代组织中发挥了积极的作用。对团队激励方式的选择逐渐成为管理实践的一个突出问题,但是关于企业营销团队激励问题的研究并不多见。文章运用博弈论,解释了营销团队中存在的＂搭便车现象＂,并阐述了在两种人性假设基础上的营销团队激励机制。     

商业银行应对出口船舶融资的博弈策略研究

造船发达国家的经验表明,金融对造船行业的发展和船舶出口的增长具有很好的促进作用。但在我国的融资环境中,商业银行是间接融资的主体,而且为出口船舶项目贷款的风险很大,这影响了商业银行的信贷决策。在信息不完全的情况下,商业银行更倾向于向大型造船企业提供贷款,而忽略中小造船企业的融资需求。     

论航海过失免责之废除

《鹿特丹规则》废除了航海过失免责,有学者认为这大大增加了承运人的负担,我国不宜加入该公约。然而,废除航海过失免责不会导致承运人的成本大幅增加,反而有利于航行事故的减少、承托双方权利义务的平衡和社会成本的降低,反映了国际海上货物运输法的发展趋势。同时,它对现今的海上保险制度、共同海损制度和碰撞责任制度也不会造成不利的影响。     

KENDALL'S TAU AND CONTINGENCY TABLES

Kendall's tau is a coefficient of concordance between two rankings of n objects. Its definition and large sample normal approximation are easily extended to the case where one of the rankings contains ties. In this paper, definition and normal approximation are extended further to the case where both rankings contain ties. The results are applied to give a fully distribution-free test for two-way contingency tables with ordered categories.     

Incomplete probability assessments in decision analysis

Summary In analysing a decision problem, in a situation ofpartial knowledge, a decision maker may be reluctant to assign acomplete probability distribution on the relevant states of nature. In order to face this difficulty, several methods, based onindeterminate probabilities or probabilityintervals, have been proposed in the literature. In this paper, arguing that it is meaningless to judge probabilistic assessments ascorrect orwrong, it is maintained that onlycoherence has anobjective andsignificant role. Then to overcome practical difficulties, an approach based on thesubjective methodology and on the use ofnumerical andqualitative probabilities, is outlined.     

《说文解字》中的不等值训释

《说文解字》训释的体例一般是先解释字义,再阐释字的构字理据。很多训释,训释词与被训释词貌似义合,实际在语义上是不等值的。这种不等值训释包括上下位关系、同位关系和整体与部分关系三类不等值训释。     

INCOMPLETE DATA IN GENERALIZED LINEAR MODELS WITH CONTINUOUS COVARIATES

This paper proposes a method for estimating the parameters in a generalized linear model with missing covariates. The missing covariates are assumed to come from a continuous distribution, and are assumed to be missing at random. In particular, Gaussian quadrature methods are used on the E-step of the EM algorithm, leading to an approximate EM algorithm. The parameters are then estimated using the weighted EM procedure given in Ibrahim (1990). This approximate EM procedure leads to approximate maximum likelihood estimates, whose standard errors and asymptotic properties are given. The proposed procedure is illustrated on a data set.