Optimal Allocation for Comparing <Emphasis Type="Italic">k</Emphasis> Test Treatments to Positive and Negative Control with Unequal Weighting Under A-optimality and MV-optimality

Experiments in real life often involve comparisons of test treatments to more than one control. However, the controls may not always be of equal importance. In this paper we introduce weighted MV optimality criterion and present a detailed study using both weighted A and MV optimality criteria, of the problem of optimally comparing a set of test treatments to two controls (positive and a negative) that are of unequal importance to the experimenter.     

我国资本、劳动力与经济增长关系的分析——基于ARMA理论下的生产函数研究

柯布-道格拉斯生产函数用于反映经济领域中产出和各个要素投入之间的关系.本文在1978-2008年我国劳动力、资本存量和经济总产出的数据基础上,运用时间序列ARMA和回归相结合的计量模型,分析测量了柯布-道格拉斯生产函数中各个参数的数值,并对模型的拟合优良程度和其参数的数理意义进行了相关的统计检验.最后根据计量分析和经济意义分析所得出的结论为,劳动力的投入在我国的经济增长过程中起着主要的作用,当期劳动力增加1％,平均来说经济增长为0.47％.     

改革开放以来广东职工工资总额及平均工资增长研析

本文描述了改革开放以来广东职工工资增长的轨迹，通过比较分析揭示了其演变特点、成绩及不足，指出上个世纪90年代后期以来广东工资总额增长低于本省GDP增长、工资总额占国民收入的比重下降和职工平均工资增长低于本省人均GDP增长、低于全国平均工资增长、低于绝大多数省市平均工资增长；提出今后广东要创新工资宏观管理原则，传统的“职工工资总额增长低于经济效益提高，平均工资增长低于劳动生产率提高”的“两个低于”原则已经不适应我国贯彻落实科学发展观和所处发展新阶段的要求，提出用“职工工资总额增长与经济效益提高相适应，平均工资增长与劳动生产率的提高相适应”的“两个适应”原则作为新时期工资宏观管理的原则。     

陕西省城乡居民收入差距的实证分析

自1981～2005年的25年间,以5年为一个考察期,对陕西省城乡居民平均绝对收入差距、平均相对收入差距进行考察和分析,发现在5个考察期中,陕西城乡居民平均绝对收入差距呈现指数增长的趋势,平均相对收入差距也在不断的上升。笔者认为只有不断对二元制度进行一元化改革和调整,以及在对农业方面进行持续和力度足够投资的基础上,才能在根本上缩小陕西城乡居民收入差距,缓解由城乡收入差距带来的各种社会矛盾,从而有利于和谐陕西早日实现。     

一种高性能CMOS带隙基准电压源的设计

本文提出了一种采用0.25μm CMOS工艺的高性能的带隙基准参考源。该电路结构简单,性能较好。用模拟软件进行仿真,在tt模型下,其温度系数为9.6 ppm/℃,电源抑制比(PSRR)为-56 dB,电压拉偏特性为384 ppm/V。而在其它模型下,也有较低的温度系数和较高的电源抑制比。     

我国出口国(区)别分布及出口增长的影响因素

本文基于1997-2008年我国对25个主要贸易伙伴出口额等面板数据建立了6个贸易引力模型,筛选出了两国首都(城市)之间贸易平均里程等10个影响贸易流量及出口增长的因素,通过对比研究,发现不同因素对我国出口流量的国别分布以及出口增长有着不同程度的影响。同时,本文给出了某一年份我国对不同贸易伙伴的名义和实际出口增长潜力的测算方法。     

The moderating effect of average wage and number of stores on private label market share: A hierarchical linear model analysis

Existing research on private label market share is primarily in the context of the Western market. The Chinese market context research is scarce, although private labels are developing rapidly in the past several years. This study investigates how the average wage and number of stores affect the Chinese market's private label market share. More importantly, this paper examines the moderating effect of the average wage and the number of stores on the relationship between the private label market share and product assortment as well as the relationship between the private label market share and pricing. Data collected from a Chinese supply chain dyad is analyzed to study category management using hierarchical linear models. The results reveal that the average wage and the number of stores positively affect the private label market share. Furthermore, the average wage enhances the negative effect of the number of brands, weakens the negative effect of the private label price, weakens the positive effect of national brand price. Meanwhile, the number of stores enhances the positive effect of the SKU proliferation of private label, enhances the negative effects of the number of brands, and enhances the negative effect of the private label price. This study contributes to category management. Furthermore, the findings will be valuable to domestic and international grocery marketers and retailers operating private labels in China.     

Estimating the potential impact of requiring a stand-alone board-level risk committee

Motivated by the requirement under the Dodd-Frank Act that all large bank holding companies create a stand-alone, board-level risk committee, this paper investigates the association between such a committee and regulatory risk both before and during the financial crisis. I focus the analysis on the set of banks that did not have a risk committee in place prior to the Dodd-Frank Act, as these are the banks that were most affected by the regulation. I find that matched control banks with a risk committee in place had higher capital ratios during the financial crisis, but lower capital ratios during more stable economic conditions relative to the banks without a risk committee. This paper contributes to the literature by narrowly investigating the effects a board-level risk committee, by focusing on a risk measure that is of interest to the regulators who implemented the new regulation, and by documenting that this association changes over time which highlights the importance of estimating the effects of new regulations across different economic conditions.     

From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average

A sizeable percentage of investors are using social media to obtain information about companies (Cogent Research [2008]). As a consequence, social media content about firms may have an impact on stock prices (Hachman [2011]). Various studies utilize social media content to forecast stock market-related factors such as returns, volatility, or trading volume. The objective of this article is to investigate whether a bidirectional intraday relationship between stock returns and volatility and tweets exists. The study analyzed 150,180 minute-by-minute stock price and tweet data for the 30 stocks in the Dow Jones Industrial Average over a random 13-day interval from June 2 to June 18, 2014 using a BEKK-MVGARCH methodology. Findings indicate that 87% of stock returns are influenced by lagged innovations of the tweets data, but there is little evidence to support that the direction is reciprocal, with only 7% of tweets being influenced by lagged innovations of the stock returns. Results further show that the lagged innovations from 40 percent of stock returns affect the current conditional volatility of the tweets, while 73 percent of tweets affect the current conditional volatility of stock returns. Moreover, there is strong evidence to suggest that the volatility originating from the returns to the tweets persists for 33 percent of stocks; the volatility originating from the tweets to the returns persists for 73 percent of stocks. Last, 53 percent of stocks exhibit both immediate and persistent impacts from returns to tweets, while 90 percent of stocks exhibit both immediate and persistent impacts from tweets to returns. These results may help traders achieve superior returns by buying and selling individual stocks or options. Also, asset and mutual fund managers may benefit by developing a social media strategy.     

Time series momentum trading strategy and autocorrelation amplification

This paper investigates why general Moving Average (MA) trading rules are widely used by technical analysts and others. We assume general stationary processes for prices and we derive the autocorrelation function for an MA trading rule. Based on our results, we conjecture that autocorrelation amplification is one of the reasons why such trading rules are popular. Using simulated results, we show that the MA rule may be popular because it can identify price momentum and is a simple way of assessing and exploiting the price autocorrelation structure without necessarily knowing its precise structure. This paper then, provides empirical evidence of autocorrelation amplification using 15-year daily price data for 11 major international stock indices.