局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

劳动力转移对城乡居民收入差距的非线性影响研究

借鉴已有相关研究成果,将劳动力转移、农业技术水平与城乡居民收入差距联系起来思考,可以具体地考察劳动力转移对城乡居民收入差距的影响.文章以农业技术水平作为门槛变量,选取2009—2019年中国31个省份的面板数据,利用泰尔指数测定城乡收入差距,以劳动力转移作为核心解释变量构建面板门槛模型,实证得出劳动力转移对城乡居民收入差距的非线性影响.研究发现:劳动力转移可以缩小城乡居民收入差距,且该影响具有单一门槛效应.在农业技术水平较低时,劳动力转移对城乡居民收入差距收敛效应较小;当农业技术水平越过门槛值达到较高水平后,劳动力转移对缩小城乡居民收入差距的效果几乎增加了一倍.此后,通过替换解释变量泰尔指数为城乡人均可支配收入比、替换核心解释变量农业技术水平为农业生产效率重新建立面板门槛模型,发现上述结论仍然成立,其检验结果具有较强的稳健性.文章将农业技术进步、劳动力转移、城乡居民收入差距这三个重要变量纳入同一模型框架中,在加深劳动力流动影响城乡居民收入差距这一视角的研究的同时,对缩小城乡居民收入差距政策的制定提供了重要的参考意义.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covariates or regressors). Although multinomial logit is widely used in both the social and economic sciences, the interpretation of regression coefficients may be tricky, as the effect of covariates on the probability distribution of the response variable is nonconstant and difficult to quantify. The ternary plots illustrated in this article aim at facilitating the interpretation of regression coefficients and permit the effect of covariates (either singularly or jointly considered) on the probability distribution of the dependent variable to be quantified. Ternary plots can be drawn both for ordered and for unordered categorical dependent variables, when the number of possible outcomes equals three (trinomial response variable); these plots allow not only to represent the covariate effects over the whole parameter space of the dependent variable but also to compare the covariate effects of any given individual profile. The method is illustrated and discussed through analysis of a dataset concerning the transition of master’s graduates of the University of Trento (Italy) from university to employment.     

On the estimation of non linear functions in stochastic volatility models

Abstract

This paper focuses on the inference of suitable generally non linear functions in stochastic volatility models. In this context, in order to estimate the variance of the proposed estimators, a moving block bootstrap (MBB) approach is suggested and discussed. Under mild assumptions, we show that the MBB procedure is weakly consistent. Moreover, a methodology to choose the optimal length block in the MBB is proposed. Some examples and simulations on the model are also made to show the performance of the proposed procedure.     

Visualization of generalized mean estimators using auxiliary information in survey sampling

Abstract

The mean estimators with ratio depend on multiple auxiliary variables and unknown parameters in a finite population setting. We propose a new generalized approach with matrices for modeling the mutivariate mean estimators with two auxiliary variables. Our approach brings naturally a graphical analysis for comparing mean estimators.     

消费者网评使用习惯对网评效应的影响研究---网评奖励效果的中介和调节效应探索*

本文以网购旅游者为调查对象，分析其网评使用习惯及其在网评奖励效果作用下对网络评论效用发挥的影响。通过问卷调查和数据分析发现，网评使用习惯和网评奖励效果都对网评效应具有显著正向影响，但网评使用习惯的影响力大于网评奖励效果。同时，网评奖励效果对网评使用习惯与网评效应间的关系具有显著负向调节效应，它削弱了消费者网评使用习惯对网评效应的影响；但消费者的网评使用习惯不通过网站的网评奖励效果对网评效应发挥作用，网评奖励效果不具有中介作用。可见，在网评使用习惯、网评奖励效果和网评效应三者关系中，网评使用习惯是个独立的影响因素，它并不通过网评奖励效果发挥作用，并且由于网评奖励效果的加入，反而削弱了网评使用习惯对网评效应的影响。研究结论表明，对于网评奖励政策的效果，需要客观辩证地看待，不应一味夸大。     

通货紧缩的经济社会效应分析

通货紧缩作为经济运行中的一种常态现象 ,必然对经济、社会产生多方面影响。其效应表现为 :通过一般物价水平的下降以及对现存市场供求关系的破坏 ,对生产产生促退效应 ,导致失业率上升 ;总体上降低居民的消费能力 ;造成分配不公 ,导致社会财富由债务人向债权人、由国家向公众、由企业向消费者、由低收入者向高收入者的转移。针对通货紧缩的负效应 ,政府要采取措施 ,抑制分配不公 ,适当地向收入较低的普通百姓倾斜 ;企业要抓住机遇 ,尽快清理库存 ,同时狠抓技术创新、质量提高和内部管理 ,为新一轮发展作准备 ;居民要调整“买涨不买落”的传统心态 ,树立消费新观念。     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

善是什么

善恶观念的产生要从物质实践出发来解释。对什么是善的问题 ,西方伦理学家们依据自己不同的研究方法 ,各抒己见 ,这些观点有其合理性 ,同时也存在着不可避免的缺陷 ,追问善的问题 ,离不开对善恶关系的探讨 ,善恶是相对的 ,同时也存在着客观的评价标准。考察善是什么 ,必须将动机与效果统一起来才能把握