Stock market reactions to monetary policy surprises under uncertainty

This article investigates how uncertainty impacts the effect of monetary policy surprises on stock returns. Using high-frequency US data, we demonstrate that stock markets respond more aggressively to monetary policy surprises during periods of high uncertainty. We also show that uncertainty asymmetrically influences the transmission of positive and negative monetary policy surprises to stock market prices. The amplifying effect of uncertainty is found to be stronger for expansionary shocks than for contractionary shocks. Our robustness analysis confirms that financial uncertainty has a significant role in shaping the influence of monetary policy on the stock market.     

基于区块链技术的建筑材料供应链质量数据安全共享方法

传统方法在建筑材料供应链质量数据安全共享中应用效果不佳，不仅数据误码率比较高，而且数据共享时延比较长，无法达到预期的数据安全共享效果。为此提出基于区块链技术的建筑材料供应链质量数据安全共享方法。利用区块链技术对建筑材料供应链质量数据属性加密，建立建筑材料供应链质量数据安全共享链，整合建筑材料供应链质量数据加密、解密程序，通过对用户身份验证实现对质量数据安全共享，以此完成基于区块链技术的建筑材料供应链质量数据安全共享。实验证明，设计方法的数据误码率在1%以内，数据共享时延在1s以内，具有良好的数据安全共享效果。     

利用大数据分析技术的智能化网络故障诊断系统

随着网络技术的快速发展以及各种新网络业务的出现，网络的规模日益扩大和复杂。同时，各种网络服务对于网络可靠性的要求也逐渐提高，这就对网络的维护提出了更高的要求。在这种情况下，传统的网络维护模式逐渐不能适应现代网络发展的需求。针对现代大型网络的故障诊断问题，利用大数据分析技术，设计并完成了一套整体的智能化故障诊断系统。在此系统中，针对不同的故障类型，利用能够获取到的数据类型，针对性地设计了相关的故障诊断模块和算法。系统整体基于开源的数据处理平台构建，具备良好的可扩展性。通过实际案例数据的验证，结果表明此系统具备良好的处理实际网络故障的能力，将大数据分析技术应用于网络故障诊断领域也具备较强的可行性。     

Does Twitter chatter matter? Online reviews and box office revenues

ABSTRACT

With a rapid rise of text-based social media and online Word-of-Mouth (WOM) activity, millions of people express their thoughts and opinions on a variety of topics. Considering that nowadays WOM is a most influential source of information when guiding consumers’ choice and purchase decisions, in this paper we look at the relationship between Twitter messages (tweets) and cinema box office revenues. Using static and dynamic panel data regression approaches, we show that the frequency, sentiment and timing of tweets posted about a film are correlated to different extent with the movie’s box office revenues, with negative tweets being particularly damaging to the box office revenues. From a managerial perspective, this is important to know, such that film production companies and distributors can adjust their strategy accordingly.     

Measuring Farm and Market Level Economic Impacts of Improved Maize Production Technologies in Ethiopia: Evidence from Panel Data

While it is often recognised that agricultural technology adoption decisions are intertwined and best characterised by multivariate models, typical approaches to examining adoption and impacts of agricultural technology have focused on single technology adoption choice and ignored interdependence among technologies. We examine farm‐ and market‐level impacts of multiple technology adoption choices using comprehensive household survey data collected in 2010/11 and 2012/13 in Ethiopia. Economic surplus analysis combined with panel data switching endogenous regression models are used to compute the supply shift parameter (K‐shift parameter), while at the same time controlling for the endogeneity inherent in agricultural technology adoption among farmers. We find that our improved technology set choices have significant impacts on farm‐level maize yield and maize production costs, where the greatest effect appears to be generated when various technologies are combined. The change in maize yield and production costs results in an average 26.4% cost reduction per kilogram of maize output (the K‐shift parameter). This increases the producer and consumer surpluses by US$ 140 and US$ 105 million per annum, respectively. These changes in economic surplus help to reduce the number of poor people by an estimated 788 thousand per year. We conclude that deliberate extension efforts and other policies that encourage integration of technologies are important for maize technologies to yield their full potential at both farm and market levels.     

Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach

This paper uses a spatial econometrics approach to study the industry risks in China’s stock market. We comprehensively consider the real linkage and information risk transmission channels and analyze the risk spillovers of specific determinants. Our empirical results show the following: 1) The real linkage channel and information channel are both effective transmission channels for driving spillover effects, and the information channel is of the utmost importance. 2) The spillover effects of specific determinants exist and are persistent. The superposition of spillover effects may lead to extreme risk. 3) The transmission channels and spillover effects are asymmetric in different regimes.     

Semiparametric time series regression modeling with a diverging number of parameters

Variable selection and error structure determination of a partially linear model with time series errors are important issues. In this paper, we investigate the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation penalty for a partially linear model with a divergent number of covariates and finite order autoregressive time series errors. Both consistency and asymptotic normality of the proposed penalized estimators are derived. The oracle property of the resultant estimators is proved. Simulation studies are carried out to assess the finite‐sample performance of the proposed procedure. A real data analysis is made to illustrate the usefulness of the proposed procedure as well.     

A continuous income-based grade gap decomposition on university course grades

The earnings premium for education, and higher education in particular, is well documented. This article examines the college achievement gap between students coming from positions of high and low socio-economic status. Other papers have also looked at this issue, often by employing, at least in part, an Oaxaca decomposition. Past papers artificially divided socio-economic status into binary groups of high and low, in order to employ the decomposition. Socio-economic status is innately a continuous variable. Therefore, we implement a continuous version of the Oaxaca decomposition. Higher socio-economic students are both slightly better prepared in terms of observable characteristics and have better returns to their characteristics than lower socio-economic students. Notable differences across results obtained from the binary and continuous decomposition methods are discussed.     

Factors predicting attitude toward disclosing personal data online

To test a theoretical model, this study explores the effect of anxiety, trust, personality, and perceived benefits on the disclosure of personal information online. An online survey conducted among participants in the United States (n = 248, age range: 20–82 years) examined attitudes toward disclosing personal data online. Specifically, the study researches the impact of anxiety disclosing personal data, trust (both in the Internet and in institutions), the Big Five personality traits, and four sets of perceived shopping benefits (opportunity, bargain, purchase, and expected privacy benefits) in e-commerce disclosure and their role as antecedents for adoption and use of e-commerce. The study aligns with existing trust literature and corroborates other findings on how perceived purchase benefits impact individuals’ attitudes toward disclosing personal data online. The data suggest that both trust in the Internet and trust in institutions positively influence attitude toward disclosing personal data online. Perceived purchase benefits were also significant positive predictors for attitude toward disclosing personal data online. Furthermore, personality dimensions can affect attitude toward disclosing: the more neurotic a person is, the more negative their attitude is about disclosing personal data online. The study underscores that consumers have a responsibility to educate themselves about online disclosure and marketing practices, and about how to protect their online privacy. Most importantly, fostering trust, reducing anxiety, and promoting benefits are essential to the future of e-commerce. Implications for theory, consumers, marketing practice, and public policy are also discussed.