新冠肺炎疫情下对完善快递末端配送体系建设的思考——以重庆市为例

自新冠肺炎疫情发生以来,快递业为应急救援物资和人民群众日常基本生活物资运输和寄递服务、畅通经济循环、满足民生需要等方面做出了重要贡献,为疫情防控提供了强有力的支撑;但同时也暴露出了一些问题,集中体现在末端配送体系不健全、末端收投不畅等方面。在对电子商务和快递业发展现状进行分析的基础上,对快递末端配送的主要模式和发展趋势进行了论述,结合重庆市的实际情况,分析了其末端配送存在的不足,并从公共服务平台搭建、智能化无接触式配送构建、乡村快递服务网络完善、快递员队伍建设等方面提出了对策建议,以助推重庆经济社会高质量发展。     

Modified maximum likelihood estimator under the Jones and Faddy's skew t-error distribution for censored regression model

It is well-known that classical Tobit estimator of the parameters of the censored regression (CR) model is inefficient in case of non-normal error terms. In this paper, we propose to use the modified maximum likelihood (MML) estimator under the Jones and Faddy''s skew t-error distribution, which covers a wide range of skew and symmetric distributions, for the CR model. The MML estimators, providing an alternative to the Tobit estimator, are explicitly expressed and they are asymptotically equivalent to the maximum likelihood estimator. A simulation study is conducted to compare the efficiencies of the MML estimators with the classical estimators such as the ordinary least squares, Tobit, censored least absolute deviations and symmetrically trimmed least squares estimators. The results of the simulation study show that the MML estimators work well among the others with respect to the root mean square error criterion for the CR model. A real life example is also provided to show the suitability of the MML methodology.     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

A new regression model for bimodal data and applications in agriculture

We define the odd log-logistic exponential Gaussian regression with two systematic components, which extends the heteroscedastic Gaussian regression and it is suitable for bimodal data quite common in the agriculture area. We estimate the parameters by the method of maximum likelihood. Some simulations indicate that the maximum-likelihood estimators are accurate. The model assumptions are checked through case deletion and quantile residuals. The usefulness of the new regression model is illustrated by means of three real data sets in different areas of agriculture, where the data present bimodality.     

Regression models to dependence for exceedance

Extreme Value Theory (EVT) aims to study the tails of probability distributions in order to measure and quantify extreme events of maximum and minimum. In river flow data, an extreme level of a river may be related to the level of a neighboring river that flows into it. In this type of data, it is very common for flooding of a location to have been caused by a very large flow from an affluent river that is tens or hundreds of kilometers from this location. In this sense, an interesting approach is to consider a conditional model for the estimation of a multivariate model. Inspired by this idea, we propose a Bayesian model to describe the dependence of exceedance between rivers, where we considered a conditionally independent structure. In this model, the dependence between rivers is captured by modeling the excess marginally of one river as a consequence of linear functions of the other rivers. The results showed that there is a strong and positive connection between excesses in one river caused by the excesses of the other rivers.     

影响我国居民收入分配差距因素的实证分析

世界银行2005年发展报告显示,中国的基尼系数按由低到高排名第85位,2007年达到了0.48,超过了国际上0.4的警戒线。本文对中国1994—2007年的相关统计资料进行实证分析,以验证税收、转移支付和教育与收入分配差距之间遵从的演变路径,探讨了城乡转移支付对收入分配差距的影响力度,得出结论:教育和税收能缩小收入分配差距,但影响有限;现行的社会保障制度并没有实现制度上的公平,农村社保制度对收入差距的负面影响远大于城市社保制度。     

Supply Chain Strategies and International Tax Arbitrage

What motivates the geographic footprint of the supply chains that multinational firms (MNFs) deploy? Traditional research in the operations and supply chain management literature tends to recommend locations primarily based on differentials in production costs and the ramifications of physical distance ignoring the role of taxation. MNFs that strategically position parts of their supply chains in low‐tax locations can allocate the profits across the divisions to improve post‐tax profits. For the profit allocation to be defensible to tax authorities, the divisional operations must possess real decision authority and bear meaningful risks. Generally speaking, the greater the transfer of risk and control, the larger the allowable allocation of profit. These transfers may also create inefficiencies due to misalignment of business goals and attitudes toward risk. We model these trade‐offs in the context of placing in a low‐tax region a subsidiary that oversees product distribution (as a limited risk distributor commissionnaire, limited risk distributor, or fully fledged distributor). Our analysis demonstrates that the MNF's preferences regarding the operating structures are not necessarily an obvious ordering based on the amount of risk and decision authority transferred to the division in the low‐tax jurisdiction. We derive and analyze threshold values of the performance parameters that describe the main trade‐offs involved in selecting an operating structure. We find some of the optimal decisions to exhibit interesting non‐monotone behavior. For instance, profits can increase when the tax rate in the low‐tax jurisdiction increases. Numerical analysis shows that the Limited‐Risk Distributor structure is rarely optimal and quantifies when each alternative dominates it.     

Estimation and inference of the joint conditional distribution for multivariate longitudinal data using nonparametric copulas

In this paper we study estimating the joint conditional distributions of multivariate longitudinal outcomes using regression models and copulas. For the estimation of marginal models, we consider a class of time-varying transformation models and combine the two marginal models using nonparametric empirical copulas. Our models and estimation method can be applied in many situations where the conditional mean-based models are not good enough. Empirical copulas combined with time-varying transformation models may allow quite flexible modelling for the joint conditional distributions for multivariate longitudinal data. We derive the asymptotic properties for the copula-based estimators of the joint conditional distribution functions. For illustration we apply our estimation method to an epidemiological study of childhood growth and blood pressure.     

Uniform in bandwidth consistency for various kernel estimators involving functional data

The paper investigates various nonparametric models including regression, conditional distribution, conditional density and conditional hazard function, when the covariates are infinite dimensional. The main contribution is to prove uniform in bandwidth asymptotic results for kernel estimators of these functional operators. Then, the application issues, involving data-driven bandwidth selection, are discussed.     

农户信贷约束研究进展述评

近年,随着我国农村金融改革的不断深入,农户信贷约束问题受到了学界关注,但该领域的研究还存在相当广泛的分歧.本文从农户信贷约束的内涵、原因、影响、类别等方面系统梳理了国内外的理论与实证文献,试图全面概括其研究进展,并在文末对既有的研究进行简要的评述,同时指出未来可能的研究方向.