Uncertainty Shocks in a Model of Effective Demand

Can increased uncertainty about the future cause a contraction in output and its components? An identified uncertainty shock in the data causes significant declines in output, consumption, investment, and hours worked. Standard general‐equilibrium models with flexible prices cannot reproduce this comovement. However, uncertainty shocks can easily generate comovement with countercyclical markups through sticky prices. Monetary policy plays a key role in offsetting the negative impact of uncertainty shocks during normal times. Higher uncertainty has even more negative effects if monetary policy can no longer perform its usual stabilizing function because of the zero lower bound. We calibrate our uncertainty shock process using fluctuations in implied stock market volatility, and show that the model with nominal price rigidity is consistent with empirical evidence from a structural vector autoregression. We argue that increased uncertainty about the future likely played a role in worsening the Great Recession. The economic mechanism we identify applies to a large set of shocks that change expectations of the future without changing current fundamentals.     

Markov chain Monte Carlo exact tests for incomplete two-way contingency tables

We consider testing the quasi-independence hypothesis for two-way contingency tables which contain some structural zero cells. For sparse contingency tables where the large sample approximation is not adequate, the Markov chain Monte Carlo exact tests are powerful tools. To construct a connected chain over the two-way contingency tables with fixed sufficient statistics and an arbitrary configuration of structural zero cells, an algebraic algorithm proposed by Diaconis and Sturmfels [Diaconis, P. and Sturmfels, B. (1998). The Annals of statistics, 26, pp. 363–397.] can be used. However, their algorithm does not seem to be a satisfactory answer, because the Markov basis produced by the algorithm often contains many redundant elements and is hard to interpret. We derive an explicit characterization of a minimal Markov basis, prove its uniqueness, and present an algorithm for obtaining the unique minimal basis. A computational example and the discussion on further basis reduction for the case of positive sufficient statistics are also given.     

零时间高校:"即时定制"教育模式之必然

近些年我国的高等教育规模每年以30%的增速扩张,教育市场日趋饱和,教育需要理性回归.本文借鉴管理学的四种时间组织理论,构建"零时间高校"和教师的"即时定制"工作模式,将高校的可持续发展定格在核心竞争力的提升上.     

Reinforcement‐based vs. Belief‐based Learning Models in Experimental Asymmetric‐information Games

This paper examines the abilities of learning models to describe subject behavior in experiments. A new experiment involving multistage asymmetric‐information games is conducted, and the experimental data are compared with the predictions of Nash equilibrium and two types of learning model: a reinforcement‐based model similar to that used by Roth and Erev (1995), and belief‐based models similar to the ‘cautious fictitious play’ of Fudenberg and Levine (1995, 1998) These models make predictions that are qualitatively similar cycling around the Nash equilibrium that is much more apparent than movement toward it. While subject behavior is not adequately described by Nash equilibrium, it is consistent with the qualitative predictions of the learning models. We examine several criteria for quantitatively comparing the predictions of alternative models. According to almost all of these criteria, both types of learning model outperform Nash equilibrium. According to some criteria, the reinforcement‐based model performs better than any version of the belief‐based model; according to others, there exist versions of the belief‐based model that outperform the reinforcement‐based model. The abilities of these models are further tested with respect to the results of other published experiments. The relative performance of the two learning models depends on the experiment, and varies according to which criterion of success is used. Again, both models perform better than equilibrium in most cases.     

莎士比亚十四行诗第十八首的三种译文比较

莎士比亚是欧洲文艺复兴时期的巨人,他的诗歌代表作《十四行诗集》,将当时英国的十四行诗创作推向顶峰,被誉为莎士比亚体。国内译介莎翁十四行诗的学者专家不胜枚举。本文从国内十四行诗的三个全译本中,选择了其中的第十八首的三种译文,从其语言,标点等方面进行了比较。     

A generalized Bayesian nonlinear mixed‐effects regression model for zero‐inflated longitudinal count data in tuberculosis trials

In this paper, we investigate Bayesian generalized nonlinear mixed‐effects (NLME) regression models for zero‐inflated longitudinal count data. The methodology is motivated by and applied to colony forming unit (CFU) counts in extended bactericidal activity tuberculosis (TB) trials. Furthermore, for model comparisons, we present a generalized method for calculating the marginal likelihoods required to determine Bayes factors. A simulation study shows that the proposed zero‐inflated negative binomial regression model has good accuracy, precision, and credibility interval coverage. In contrast, conventional normal NLME regression models applied to log‐transformed count data, which handle zero counts as left censored values, may yield credibility intervals that undercover the true bactericidal activity of anti‐TB drugs. We therefore recommend that zero‐inflated NLME regression models should be fitted to CFU count on the original scale, as an alternative to conventional normal NLME regression models on the logarithmic scale.     

论语法偏离与修辞

偏离概念的引入对中国修辞学具有积极的意义,但并不是所有的偏离都是修辞,只有语言偏离（包括语音偏离、语义偏离、语法偏离）才是修辞。偏离有正、负之分,正偏离是修辞,负偏离则不是修辞。语法正偏离对于修辞有积极意义,但语法偏离要保持一定的“度”。语法与修辞的关系是互相依存、彼此制约的。     

语言学研究重要方法论——零度与偏离理论

零度与偏离理论不但是修辞学研究,更是语言学研究中的重要方法论。由于这一理论在解释语言现象,揭示语言规律方面有很强的操作性,因而受到越来越多的关注。本文对这一理论发生背景、理论地位、理论的发展完善三个方面进行了梳理,并认为准确把握上述三点是理解和运用这一理论的关键。     

基于句法信息的书读前后非分句语言片段识别

基于句法信息的书读前后非分句语言识别和标注是现代汉语复句语料库建设工作的一部分.首先对文章的题目进行了阐释,接着论述了句法知识在中文信息处理中的作用,然后基于有关的句法信息制定了五条可程序化后供计算机执行的规则,最后给出了实验结果及分析.     

汉译西书与汉语新式标点符号的形成

汉语新式标点符号的形成与西方传教士的汉译西书在中国的传播有一定的关系。晚清的汉译西书中很早就出现了西式标点符号。1838年出版的《美理哥合省国志略》中，美国传教士裨治文首次强调了文章中标点符号的重要性。此后，包括接受了西学教育的中国知识分子也相继在各种书籍中介绍并使用了西式标点符号，客观上推动了20世纪初汉语新式标点符号系统的颁布。