Prewhitening Bias in HAC Estimation

HAC estimation commonly involves the use of prewhitening filters based on simple autoregressive models. In such applications, small sample bias in the estimation of autoregressive coefficients is transmitted to the recoloring filter, leading to HAC variance estimates that can be badly biased. The present paper provides an analysis of these issues using asymptotic expansions and simulations. The approach we recommend involves the use of recursive demeaning procedures that mitigate the effects of small sample autoregressive bias. Moreover, a commonly-used restriction rule on the prewhitening estimates (that first order autoregressive coefficient estimates, or largest eigenvalues, greater than 0.97 be replaced by 0.97) adversely interfers with the power of unit root and KPSS tests. We provide a new boundary condition rule that improves the size and power properties of these tests. Some illustrations are given of the effects of these adjustments on the size and power of KPSS testing. Using prewhitened HAC estimates and the new boundary condition rule, the KPSS test is consistent, in contrast to KPSS testing that uses conventional prewhitened HAC estimates (Lee, 1996).Autoregression, Bias, HAC estimator, KPSS testing, Long run variance, Prewhitening, Recursive demeaning

Does Black-Letter Law Matter in Labor Rights Protection in China? - A Tale of Two Cities

This article discusses the role of black-letter law in labor protection in China in cases where employers dismiss employees on the grounds of serious breaches of internal regulations. This article presents an empirical analysis of the judicial practice of two of China’s economically developed cities, Suzhou and Wuxi. Suzhou employers have to give employees the opportunity to be heard prior to dismissal, while Wuxi does not provide that opportunity. First, this article introduces the Chinese labor legislation system, the dismissal system, and the two cities’ local labor regulations. Second, the article will analyze and discuss 140 cases from Suzhou and 234 employment cases from Wuxi. Third, this article concludes that giving employees the opportunity to be heard is essential for protecting their rights, as evidenced by the higher success rates (i.e. the combination of full win and partial win rates) for employees in Suzhou compared to those in Wuxi. The analysis highlights the significance of black-letter law in ensuring labour protection in China. Finally, this article calls for national legislation to provide more explicit and detailed guidance on dismissals, or in the alternative, to mandate local authorities to enact clear labor protection rules appropriate to local circumstances

Analyzing the role of part-of-speech in code-switching:A corpus-based study

Code-switching (CS) is a common linguistic phenomenon wherein speakers fluidly transition between languages in conversation. While the cognitive processes driving CS remain a complex domain, earlier investigations have shed light on its multifaceted triggers. This study delves into the influence of Part-of-Speech (POS) on the propensity of bilinguals to engage in CS, employing a comprehensive analysis of Spanish-English and Mandarin-English corpora. Compared with prior research, our findings not only affirm the existence of a statistically significant connection between POS and the likelihood of CS across language pairs, but notably find this relationship exhibits its maximum strength in proximity to CS instances, progressively diminishing as tokens distance themselves from these CS points

Deal exclusivity in cross-cultural e-commerce

The purpose of this paper was to investigate the effect of deal exclusivity on accommodation booking intention, with regard to both hedonic and utilitarian aspect of the offer. Also, the role of cultural background was examined to see whether the consumers from different cultures response to deal exclusivity differently. In an experimental survey, a total of 208 persons participated (113 persons from the Netherlands and 95 persons from Vietnam). They judged an online advertisement of a room accommodation (an exclusive offer for members only vs. an inclusive offer for everyone). The findings showed that deal exclusivity did not directly influence consumers' booking intention. An indirect effect emerged through deal evaluation. The relationship between perceived exclusivity and the intention to book the service was influenced by the utilitarian evaluation, i.e., the exclusive offer was evaluated as more useful than the inclusive offer. In addition, a more positive utilitarian evaluation implied a higher booking intention. In contrast, no indirect effect via the hedonic evaluation of the offer was evidenced. Culture did not moderate the strength of the effect. However, this study found supporting evidence for the effect of culture on consumer's booking intention. Specifically, Dutch consumers expressed much higher booking intention than Vietnamese consumers, regardless of the exclusivity of the deal. Moreover, the more indulgent the consumers were, the more likely they would book the room accommodation

Sensor Search Techniques for Sensing as a Service Architecture for The Internet of Things

The Internet of Things (IoT) is part of the Internet of the future and will comprise billions of intelligent communicating "things" or Internet Connected Objects (ICO) which will have sensing, actuating, and data processing capabilities. Each ICO will have one or more embedded sensors that will capture potentially enormous amounts of data. The sensors and related data streams can be clustered physically or virtually, which raises the challenge of searching and selecting the right sensors for a query in an efficient and effective way. This paper proposes a context-aware sensor search, selection and ranking model, called CASSARAM, to address the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. CASSARAM takes into account user preferences and considers a broad range of sensor characteristics, such as reliability, accuracy, location, battery life, and many more. The paper highlights the importance of sensor search, selection and ranking for the IoT, identifies important characteristics of both sensors and data capture processes, and discusses how semantic and quantitative reasoning can be combined together. This work also addresses challenges such as efficient distributed sensor search and relational-expression based filtering. CASSARAM testing and performance evaluation results are presented and discussed.Comment: IEEE sensors Journal, 2013. arXiv admin note: text overlap with arXiv:1303.244