投资者情绪是导致我国投资者对市场信息出现反应偏差的原因吗：基于贝叶斯分位数回归模型的研究

本文使用贝叶斯分位数回归模型实证分析包含投资者情绪的投资者最优选择模型,结果表明：投资者情绪对于股票收益率存在非线性的正向影响,这是造成投资者对于市场信息出现反应偏差的一个重要原因.同时,市场信息和投资者情绪指标对于我国股票收益率都有着较大的影响作用;当股票出现不同涨跌幅时,市场信息对于股票收益率的影响有着较大的差异性.而考虑了投资者情绪指标之后,投资者对于市场信息的反应偏差明显减小,说明投资者情绪是造成我国投资者对于市场信息出现过度反应和反应不足的重要原因.我国投资者应该树立起良好的投资意识和心态,避免潜在的投资损失.     

银行危机宏观影响因素变迁的实证研究

本文选择了108个国家在1980-2009年的样本数据,采用随机系数Logit模型,研究了宏观因素冲击对于银行危机的影响作用。研究结果表明,各种宏观因素的影响程度在不同经济发展水平国家的银行危机中具有明显的差异;银行体系的资产质量和流动性风险暴露是银行危机产生的最主要原因;且随着金融自由化和国际化的发展,银行危机的发生原因也逐渐发生变化。因此,与时俱进地采取某些监管措施,例如限制银行贷款增速、监控银行跨境资本流动、控制外债规模等,有助于降低银行危机发生的概率。     

新疆能源消费碳足迹变化、影响因素及其演进分析

经济增长对能源消费的依赖性与生态环境恶化的矛盾日趋严重。本文采用 IPCC 方法测算了新疆能源消费碳足迹,利用岭回归对扩展的 STIRPAT 模型进行拟合,分析了各因素对碳足迹影响的演进规律,结果表明：1990-2011年新疆能源消费碳足迹整体上呈上升趋势,年均增长率为5.82%,其中能源消费碳足迹的构成中以煤炭为主,石油次之,天然气最小;新疆能源消费碳足迹产值在绝对数值和增长率方面都处于较低的水平,能源利用效率还有待提高;新疆不存在环境库兹涅茨曲线;各驱动因素对碳足迹增长的贡献会随着时间推移发生变化,人均GDP 从2011年起已经成为对碳足迹影响最大的驱动力,而城镇化率对碳足迹的影响相对有限。     

侧向支承作用下简支钢梁整体稳定性研究

本文对简支工形钢梁受压翼缘有两道侧向支承时的整体稳定性能进行了系统研究。首先根据能量法原理,把中梁段单独取出来,推导了3种不同荷载类型作用下钢梁整体稳定临界弯矩;其次介绍了Nethercot和Trahair建议的考虑梁段相互约束效应的计算方法（简称“NT法”）。采用ANSYS有限元分析软件,对总跨度为15 m的简支钢梁,考虑其侧向支承条件、截面形式、荷载类型的变化,共计算了144根钢梁,对其进行了特征值屈曲分析。然后对3种方法计算的整体稳定临界荷载进行了对比分析,通过分析对比评价了两种理论方法的计算精度和实用性。最后根据有限元分析的结果,拟合了满跨均布荷载作用、跨中集中荷载作用、支承处集中荷载作用下钢梁等效弯矩系数的计算公式。     

How to Construct a Random Probability Measure

This article presents an overview of several constructive methods for generating random probability measures. Applications of random probability measures include Bayesian statistics, average optimal control problems, average error bounds for numerical equation solving methods, and models for random distributions of mass in space.     

Quantile regression with sample selection: Estimating women's return to education in the U.S.

This study uses quantile regression techniques to analyze changes in the returns to education for women. The data used is the March Current Population Survey for the years 1968, 1973, 1979, 1986 and 1990. The first step in estimating the single (linear) index selection equation uses Ichimura's (1993) semiparametric procedure. To correct for an unknown form of a sample selection bias in the quantile regression, the second step incorporates a nonparametric method, using an idea similar to one developed by Heckman (1980) and Newey (1991) for mean regression, and Buchinsky (1998) for quantile regression.  The results show that: (a) the returns to education increased enormously for the younger cohorts, but very little for the older cohorts; (b) in general the returns are higher at the lower quantiles in the beginning of the sample period and higher at the higher quantiles by the end of the sample period; (c) there is a significant sample selection bias for all age groups at almost all quantiles; (d) toward the end of the sample period there is a significant convergence of the returns at the various quantiles, especially for the younger cohorts and age groups; and (e) the semiparametric estimates of the selection equation are considerably different from those obtained for a parametric probit model.     

Statistical modelling of runway incursion occurences in the United States

Runway incursions are an important aviation safety concern; between 2002 and 2015 there were 16,785 runway incursions at United States airports ranging in size from small general aviation (GA) to large commercial airline hubs. When examining airports with the 50 highest incursion count over the past 5 years, the predominant categories were large hubs, which accounted for 21 airports and general aviation (GA) airports which accounted for 16 airports. In June 2015, the Federal Aviation Administration (FAA) announced the Runway Incursion Mitigation (RIM) program to identify airport risk factors that might contribute to a runway incursion and develop strategies to help airport stakeholders mitigate those risks. Different size airports serve different aircraft fleets, serve different operating volumes, and have different resources available (both funds and technologies) for incursion mitigation. Therefore, it is valuable to determine the correlating factors that affect incursions at different size airports. This paper uses econometrics based modelling techniques to identify statistically significant factors in data provided by the (FAA) public web sites on runway incursions. The model identified statistically significant variables that correlate with incursions, based on severity, for airports categories defined by the National Plan of Integrated Airport Systems (NPIAS).The model results indicate that operational incidents (OI) are more likely at large hub airports. In contrast, at GA/non-hub airports, pilot deviations (PD) were significant for less severe incursions (severity C and D). Only one variable, “number of years since 2002”, was found to be significant for all the three airport categories; this variable was correlated with severity A incursions and indicated a statistically significant reduction in severity A incursions, despite an overall 80% increase in incursions between 2002 and 2015.     

Inventory inaccuracies in the wholesale supply chain

The inventory level shown in the Information System contrary to popular belief and assumptions in most academic papers and in spite of the considerable amounts invested in information technology, is often inaccurate. The inventory inaccuracy occurs when the inventory shown in the Information System is not in agreement with the actually available inventory. In this paper, we first describe the major factors generating inventory inaccuracy. Then, we provide situations permitting to manage an inventory system subject to errors. We provide a general framework permitting to model the inventory inaccuracy issue. In particular, we link the inaccuracy issue with the well known random yield problem. The shown link permits us to derive the optimal ordering policy of an inventory framework where demand satisfaction is done based on the inventory records (which are subject to inaccuracies). We also propose an analysis permitting to show the added value of an advanced identification system such as the RFID technology.     

基于多变量的中国货币需求函数实证分析

随着我国经济体制改革的深化,建立货币需求模型的变量因子也在发生变化。然后,根据我国近年来货币实际需求,选取变量因子建立货币需求模型,并进行了实证分析。在实证分析的基础上,提出了提高货币政策有效性的政策建议。     

Saving–investment correlations, capital mobility and crowding out: some further results

This study attempts to reassess the evidence on the degree of capital mobility and crowding out by applying a varying coefficients model to data on 19 OECD countries over the 1971–1999 period. Our period-specific results strongly support the crowding-out effect as well as the low capital mobility argument for this group of countries as a whole. However, the strength of the crowding-out effect appears to weaken and the degree of capital mobility to increase in the 1990s as compared to the 1970s and 1980s. We also classify countries into five groups according to the relative size of the government sector. Our group-specific results indicate that the degree of capital mobility is generally lower and the crowding-out effect generally stronger, in country groups with smaller governments. The differences are especially evident when we compare the group with largest government size with all other groups, those differences between the latter being much more modest. However, significant differences in the country-specific results suggest that it is prudent to be cautious when we draw conclusions about crowding-out and capital mobility for specific countries from the period-wise or group-wise results. This is particularly important in drawing policy implications for specific countries.