人民币汇率失衡及贸易壁垒对我国出口行业影响异质性研究

贸易摩擦、新冠疫情使我国经济贸易面临严峻挑战,人民币汇率波动及贸易壁垒将常态化地影响我国出口贸易.在加快形成以国内大循环为主体、国内国际双循环相互促进的新发展格局背景下,文章基于HS分类原则,选取WTO等机构的贸易数据,通过构建BEER模型测算了人民币汇率失衡程度;通过建立固定效应面板模型研究了人民币汇率失衡及贸易壁垒双因素对我国出口行业影响的异质性.研究表明:人民币汇率失衡对我国出口贸易整体上具有显著负向影响,非关税壁垒对我国出口贸易整体上具有显著正向影响;关税和非关税构成的贸易壁垒与人民币汇率失衡双因素对我国出口贸易具有显著抑制作用,并对不同出口行业的影响存在异质性;人民币汇率失衡与非关税壁垒双因素对大多行业均具有显著负向影响,人民币汇率失衡与关税壁垒双因素对不同行业影响的正负效应及程度大小有异质性.因此,建议通过运行逆周期因子等完善人民币汇率自我修正机制;通过引导出口企业了解使用外汇衍生品等促进外汇衍生品市场运行机制的健全;通过加强"海外仓"建设及深耕RCEP框架下的东盟十国市场等实施出口行业差异化贸易策略;通过提升自主科技创新能力等加快出口行业产业转型升级,推动双循环,实现我国出口贸易高质量发展.     

How do countries choose their monetary policy frameworks?

This paper investigates the determinants of countries’ choices of monetary policy framework. A brief narrative focused on groupings of countries motivates an econometric analysis which draws on previous work on the determinants of exchange rate regimes, bringing in standard factors as well as the trade networks of potential anchor currency blocs and the financial market depth that are emphasised in the narrative. The model turns out to be able to predict three quarters of countries’ choices, and there is no obvious systematic pattern in the errors. The results have important implications for how countries should choose their monetary policy frameworks.     

汇率货币模型的非线性协整关系检验——基于深度GRU神经网络

本文采用深度门控循环单元（GRU）神经网络探讨三种汇率货币模型（弹性价格、前瞻性和实际利率差模型）的非线性协整关系。GRU技术在深度学习中具有智能记忆、自主学习和强逼近能力等优点。为此，本文运用该技术对6组典型浮动汇率制国别数据进行了非线性Johansen协整检验。结果表明，汇率与宏观经济基本面之间存在非线性协整关系，从而说明了货币模型在非线性条件下的有效性，以及先进的深度学习工具在检验经济理论中的优势。     

储层岩石矿物成分对酸蚀裂缝导流能力的影响

储层岩石矿物成分是酸压改造效果影响因素之一。研究认为，在储层岩石矿物成分中易溶物的含量及分布方式决定了酸蚀裂缝导流能力大小，易溶蚀物的含量越多，岩石溶蚀速率越快。室内测试了不同溶蚀速率下的灰岩和白云岩的酸蚀裂缝导流能力，研究了岩石溶蚀速率、易溶蚀物含量对酸蚀裂缝导流能力的影响，对酸压工艺设计方案提出了指导性建议。研究结果表明，储层岩石溶蚀速率与酸蚀裂缝导流能力增加倍比存在抛物线关系，易溶蚀物占30%40% 时酸蚀裂缝导流能力保持较好。     

Uniform consistency rate of kNN regression estimation for functional time series data

In this paper, we investigate the k-nearest neighbours (kNN) estimation of nonparametric regression model for strong mixing functional time series data. More precisely, we establish the uniform almost complete convergence rate of the kNN estimator under some mild conditions. Furthermore, a simulation study and an empirical application to the real data analysis of sea surface temperature (SST) are carried out to illustrate the finite sample performances and the usefulness of the kNN approach.     

Frontier spaces of vulnerability: Regional change,urbanization, drought and fire hazard in Santarém,Pará, Brazil

Fire hazard is a mounting concern in tropical rainforests of the Brazilian Amazon and has raised awareness within the science community of the links between agricultural fire use, drought and accidental fire. As a result, fire is being addressed as a crisis event with mitigation focused on those who light fires, particularly smallholder agriculturalists. Little attention is paid to the historical and ongoing ways in which Amazon landscapes and peoples have been made more susceptible to fire. Frontier regions of the Brazilian Amazon serve a variety of functions within the larger Brazilian society, including as extractive reserves for economic development, as social safety valves to reduce population pressures, and as areas to support urban regional integration. Each of these functions has impacted frontier environments in ways that create more flammable landscapes and/or shape the vulnerability of people to fire hazard. This paper uses a case study inthe Brazilian Lower Amazon to understand how vulnerability to fire hazard develops. It argues that if fire mitigation remains centered on fire as a crisis event, an understanding of what constitutes frontier spaces of vulnerability, both in landscape and in populations, will be limited.     

Kernel Estimation of Rate Function for Recurrent Event Data

Abstract.  Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce a curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.     

浅析影响因子的局限性

目前大量的机构用论文的被引用率、期刊的影响因子和被 SCI收录的情况作为评价个人、期刊和科研机构之影响力或水平高低的一个重要指标。但却忽略了不同学科的特殊性以及学科的规模、发展速度等非科学的因素对影响因子的局限 ,这就形成了对许多专业的不公平评价 ,因而必须对普通的影响因子加以修正     

Book Reviews

Books reviewed:
M Hollander and D Wolfe, Nonparametric Statistical Methods
T Leonard and J.S.J Hsu, Bayesian Methods     

论证券市场化解委托代理风险的作用机制

本文首先探讨了证券市场化解股份有限公司代理人道德风险问题的作用机制 ,并进一步详尽地分析了该机制发挥作用需要具备的条件 ,包括 :证券市场存在、证券市场具有完善的信息交流功能、证券市场有效性较高等。文章继而对照上述条件分析了我国证券市场的现状。最后提出了改进的对策