Business reform outcomes: Why so different?

Post-crisis policy making increasingly focuses on doing business reforms. We argue that the effects of those reforms will be different across countries. To understand the reasons for the reform outcome divergence, we advance a novel firm-size distribution (FSDs) argument. At the center of the argument is the fact that FSDs are different across countries and stable over time. Then, if a given doing business reform induces firms of different size to grow differently, this will produce a variety of reform outcomes across countries. To advance the argument, we set up a tractable general equilibrium (GE) model and study how firms of different size grow after a doing business reform. The model predicts that larger firms will grow faster than smaller firms after the reform. The model predictions are tested on the Enterprise Surveys (ES) data, merged with the Doing Business indicators. We confirm that firms of different size grow differently after a Doing Business reform. Thus, based on the notable differences of firm size distributions across countries, identical reforms to start, operate and close a business will produce a variety of reform outcomes across countries.     

比较法视野下我国搜查措施之理论反思

我国有证搜查还处于内部控制、自我约束和事后监督的阶段。被搜查者的合法权利不得不严重依赖于侦查人员搜查的文明程度。而无证搜查立法的拘谨与侦查实践的现实需要之间存在显著的差异。我国搜查措施所存在的问题,显示出搜查措施对侦查机关的规范和约束力度还处于较低的水平,对被搜查者权利的保障仍有所不足。我国不仅需要完善有证搜查制度,而且更需要建立和规范以同意搜查为核心的无证搜查制度,以追随刑事诉讼现代化之步伐,实现法治中国之梦想。     

Quantile Regression for Location‐Scale Time Series Models with Conditional Heteroscedasticity

This paper considers quantile regression for a wide class of time series models including autoregressive and moving average (ARMA) models with asymmetric generalized autoregressive conditional heteroscedasticity errors. The classical mean‐variance models are reinterpreted as conditional location‐scale models so that the quantile regression method can be naturally geared into the considered models. The consistency and asymptotic normality of the quantile regression estimator is established in location‐scale time series models under mild conditions. In the application of this result to ARMA‐generalized autoregressive conditional heteroscedasticity models, more primitive conditions are deduced to obtain the asymptotic properties. For illustration, a simulation study and a real data analysis are provided.     

HRD in 2020: a hop-on,hop-off city tour

This article reports on the outcome of a Future Search Conference in the UK to consider human resource development (HRD) in 2020 and beyond. We firstly consider themes from the past into the present. This includes the persistence of solutions in HRD that are systematic, predictable, how apprenticeships in the UK have had to accommodate government policies to ameliorate youth unemployment and the long-standing difficulty for HRD of failing to demonstrate a return on investment (ROI) on activities. We then present four scenarios based on key questions for the future relating to value of HRD and whether this will be a future for HRD. Reponses to the questions form scenario logics which we present against the theme of city tour. Each scenario is explained against the presented logic with positive, negative, ambiguous and uncertain implications for HRD. We suggest that each scenario carries a glimpse of what might be.     

唐代的家族、地域与国家认同——唐代“归葬”现象考察

出土的唐代墓志中出现了较多的归葬现象：从唐帝国的边缘地区归葬于国家的中心长安、洛阳。唐代国家观念中的天下观与家国观,蕴含着地域观念和家族观念：地域上是对天下中心的王朝核心区的归属与认同,家族上以忠孝方式表达对家国的忠诚。这为分析唐代的国家认同提供了理路。迁葬或归葬这种耗资巨大的行为仪式即唐代士大夫阶层朴素的国家认同的表达方式。分析唐人的国家认同与唐代社会的互动,有助于吸取历史养分,理解影响国家认同的因素,促进现代的国家认同。     

董作宾:乡土研究的先驱

20世纪中国民间文艺学史上存在过多种流派 ,如歌谣研究会、文学人类学派、社会—民族学派、“古史辨”派神话学、民俗学派、俗文学学派、延安学派等。作为第一个流派的歌谣研究会 ,是一个颇松散的团体和流派 ,其中持乡土研究观点的学者 ,如顾颉刚、常惠、董作宾、台静农、钟敬文、罗香林、白启明、刘经等 ,在歌谣研究会流派中占主流地位。本文以董作宾的《看见她》母题研究及其他研究为个例 ,阐明乡土研究思潮是 2 0世纪中国现代民间文艺学的最早的一种研究思潮 ,董作宾 (以及顾颉刚等 )在实践和理论上的成就 ,奠定了中国民间文艺学作为一个独立的人文学科的最初的理论基础。本文从 (1)“母题”的引入和比较研究的实践 ,(2 )家乡歌谣学应时而生 ,(3)考订与考订者 ,(4)综合研究模式的尝试四个方面 ,对董作宾的民间文艺学思想遗产和历史地位作历史的考察。     

基于EaR的上市商业银行财务风险评价研究

商业银行在我国经济发展和转型中起着重要作用,近年来随着经济增速放缓、利率市场化和同业竞争加剧的影响,商业银行面临的财务风险也不断加大。为了科学合理地评价商业银行的财务风险,本文从在险价值(VaR)的概念出发引入了在险值的财务风险评价方法对上市商业银行的在险盈余和在险现金流进行测度,实证结果表明目前商业银行总体具有良好的盈利水平,但部分商业银行存在现金流风险。     

没有等价交换,就无法实现市场的双赢——四论商业原则

等价交换原则,是市场经济的基本原则,是商业原则的精髓,也是实现合作共赢的基础.传统的等价交换观念,是按照社会平均必要劳动时间对等来决定商品价格的.然而,社会平均必要劳动时间不仅在实践中无法统计,在理论上也难以对其进行深化、细化地论述.因此,应树立新的等价交换观念,即等价交换的核心是维护买卖双方的基本权益,以达到实现双赢的目的.应注意的是,等价交换不是等量交换,也难以做到等值交换.要以时代的视野、创新的观念,用新的价值观,正确对待交换价值,尽可能做到公平贸易.生财有道是实现等价交换的重要前提,这个道就是商业道德、市场规律、公平竞争和双赢战略.坚持等价交换原则,核心问题要落实一个“真”字,即“真诚待客”“真心服务”“真货经营”和“真价明码”.     

Linear Increments with Non‐monotone Missing Data and Measurement Error

Linear increments (LI) are used to analyse repeated outcome data with missing values. Previously, two LI methods have been proposed, one allowing non‐monotone missingness but not independent measurement error and one allowing independent measurement error but only monotone missingness. In both, it was suggested that the expected increment could depend on current outcome. We show that LI can allow non‐monotone missingness and either independent measurement error of unknown variance or dependence of expected increment on current outcome but not both. A popular alternative to LI is a multivariate normal model ignoring the missingness pattern. This gives consistent estimation when data are normally distributed and missing at random (MAR). We clarify the relation between MAR and the assumptions of LI and show that for continuous outcomes multivariate normal estimators are also consistent under (non‐MAR and non‐normal) assumptions not much stronger than those of LI. Moreover, when missingness is non‐monotone, they are typically more efficient.     

On conditional risk estimation considering model risk

Usually, parametric procedures used for conditional variance modelling are associated with model risk. Model risk may affect the volatility and conditional value at risk estimation process either due to estimation or misspecification risks. Hence, non-parametric artificial intelligence models can be considered as alternative models given that they do not rely on an explicit form of the volatility. In this paper, we consider the least-squares support vector regression (LS-SVR), weighted LS-SVR and Fixed size LS-SVR models in order to handle the problem of conditional risk estimation taking into account issues of model risk. A simulation study and a real application show the performance of proposed volatility and VaR models.