标准化方法确定证券组合的有效边缘

本文在建立符号系统的基础上,推导出证券组合方差二次型的标准形式表达式,并得到线性替换的一般表达式,给出应用标准化方法求解组合的有效边缘的方法和实例验证。     

我国是否进入“刘易斯转折点”——文献述评及思考

本文梳理已有研究文献,将关于我国是否进入刘易斯转折点的观点归纳为三种:第一种观点认为我国已全面进入刘易斯转折点阶段;而第二种观点持相反意见,认为民工荒是特殊背景下的结构性失衡现象,我国农村劳动力供大于求的总体态势不会轻易发生逆转;第三种观点则认为我国经济处于中国特色的刘易斯转折点区间内。从不同视角认识这些争论有助于我们更好地把握刘易斯转折点,应对日益严峻的民工荒现象,更好地利用和兑现人口红利以及做好迎接刘易斯转折点的准备,实现我国经济由二元结构向一元结构的协调转型。     

不确定性感知与企业绿色技术创新——基于区域与企业异质性视角的分析

实现碳达峰碳中和是推动高质量发展的内在要求,企业积极开展绿色技术创新有利于实现经济的绿色可持续发展。在面对宏观环境的经济政策不确定时,企业对不确定性的感知能力能否帮助企业发挥抵抗风险作用？能否将外部经济政策不确定性转化为企业的内在发展动力实现绿色技术创新?文章探究企业经济政策不确定性的感知程度对其绿色技术创新的影响,并分析了其中的作用机制。在此基础上使用2007—2020年中国沪深A股上市公司数据和企业层面经济政策不确定性指标等数据进行实证检验,并提出政策建议。研究发现,企业经济政策不确定性感知程度的增加能够促进企业绿色技术创新水平的提高。机制分析表明,从外部融资视角看,经济政策不确定性感知的增加可以通过缩小信息不对称与减小企业融资约束提高企业的绿色技术创新能力;从企业内部管理视角看,经济政策不确定性感知的增加能够通过增强企业战略积极性和提升绿色认知能力来提高企业的绿色技术创新能力。通过企业外部地区特征与内部自身特征异质性分析发现,企业所在地区经济发展水平、数字经济发展程度与地区创新活力越高,越有利于企业经济政策不确定性感知促进绿色技术创新,对于非重污染、社会责任表现较差、自身风险承担水平较低的企业这一促进作用更为明显。进一步分析政企互动关系发挥的作用发现,国有企业与政府环境规制水平较高地区的企业拥有更强的绿色创新能力,而政府环保补贴在这一过程中发挥的作用并不充分。研究结论对我国企业实现绿色技术创新具有重要的启示:企业需要充分把握市场信息与市场机遇,树立可持续发展目标;政府需要积极缩小企业与市场、企业与政府间的信息不对称,强化地区创新活力,针对不同地区与类型企业实施经济政策;政府应当完善经济政策平稳机制,积极引导企业正确认知经济政策不确定性带给企业的机会与风险,发挥好政府调节作用,加快实现企业的绿色技术创新与绿色转型发展。     

Semiparametric analysis of transformation models with doubly censored data

Double censoring arises when T represents an outcome variable that can only be accurately measured within a certain range, [L, U], where L and U are the left- and right-censoring variables, respectively. In this note, using Martingale arguments of Chen et al. [3 Chen, K., Jin, Z. and Ying, Z. 2002. Semiparametric analysis of transformation models with censored data. Biometrika, 89: 659–668. [Crossref], [Web of Science ®] [Google Scholar]], we propose an estimator (denoted by ?β) for estimating regression coefficients of transformation model when L is always observed. Under Cox proportional hazards model, the proposed estimator is equivalent to the partial likelihood estimator for left-truncated and right-censored data if the left-censoring variables L were regarded as left-truncated variables. In this case, the estimator ?β can be obtained by the standard software. A simulation study is conducted to investigate the performance of ?β. For the purpose of comparison, the simulation study also includes the estimator proposed by Cai and Cheng [2 Cai, T. and Cheng, S. 2004. Semiparametric regression analysis for doubly censored data. Biometrika, 91: 277–290. [Crossref], [Web of Science ®] [Google Scholar]] for the case when L and U are always observed.     

基于全要素生产率的中国GDP数据准确性评估

 中国GDP数据的准确性评估问题,一直受到国内外各方面的关注。本文从反逻辑思路,考察作为技术进步的替代性指标全要素生产率（TFP）,反观GDP及其增长率是否准确或可信。运用隐性变量法通过建立状态空间模型测算中国1979－2008年间TFP增长率,分析GDP数据是否存在误差。结果表明1981年、1988年和2000年的TFP增长率的下降,找不到非正常情况下外生因素的影响,本文认为这是GDP核算误差造成的结果。     

Two-dimensional density estimation using smooth invertible transformations

We investigate the problem of estimating a smooth invertible transformation f when observing independent samples X₁,…,X_n∼P°f where P is a known measure. We focus on the two-dimensional case where P and f are defined on R². We present a flexible class of smooth invertible transformations in two dimensions with variational equations for optimizing over the classes, then study the problem of estimating the transformation f by penalized maximum likelihood estimation. We apply our methodology to the case when P°f has a density with respect to Lebesgue measure on R² and demonstrate improvements over kernel density estimation on three examples.     

Construction of optimal supersaturated design with large number of levels

Inspired by the ideas of column and row juxtaposition in Liu and Lin (2009) and level transformation in Yamada and Lin (1999), this paper presents a new method for constructing optimal supersaturated designs (SSDs). This method provides a convenient way to construct mixed-level designs with relatively large numbers of levels, avoiding the blind search and numerous calculations by computers. The goodness of the resulting SSDs is judged by the χ² (Yamada and Lin, 1999 and Yamada and Matsui, 2002) and J₂ (Xu, 2002) criteria. Some nice properties of the new designs are also provided.     

Distribution-free test in Tobit mean regression model

This paper discusses the problem of fitting a parametric model in Tobit mean regression models. The proposed test is based on the supremum of the Khamaladze-type transformation of a partial sum process of calibrated residuals. The asymptotic null distribution of this transformed process is shown to be the same as that of a time-transformed standard Brownian motion. Consistency of this sequence of tests against some fixed alternatives and asymptotic power under some local nonparametric alternatives are also discussed. Simulation studies are conducted to assess the finite sample performance of the proposed test. The power comparison with some existing tests shows some superiority of the proposed test at the chosen alternatives.     

Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity

The proportional hazard model with unobserved heterogeneity gives the hazard function of a random variable conditional on covariates and a second random variable representing unobserved heterogeneity. This paper shows how to estimate the baseline hazard function and the distribution of the unobserved heterogeneity nonparametrically. The baseline hazard function and heterogeneity distribution are assumed to satisfy smoothness conditions but are not assumed to belong to known, finite-dimensional, parametric families. Existing estimators assume that the baseline hazard function or heterogeneity distribution belongs to a known parametric family. Thus, the estimators presented here are more general than existing ones.     

Variable Royalty Rates for Improving Franchise Channel Coordination*

A business format franchisor obtains a major part of its revenues from franchise royalties, which are typically a fixed percentage of franchisee gross sales. When a fixed royalty rate is used and the marginal costs of operating the franchise are increasing, the franchisee does not have an incentive to increase sales beyond a certain “optimal” volume. We present a model that recommends the use of a variable franchise royalty rate for extending this optimal sales volume. For a general convex cost function, we show that a new lower rate can be applied to incremental sales beyond the original optimal level. We show that this new rate should be less than half of the original rate when a quadratic cost function is applicable. Adopting a variable royalty rate increases franchisor royalty revenues and franchisee profits.