Analysis of ultra-high-frequency financial data using advanced Fourier transforms

This paper presents a novel application of advanced methods from Fourier analysis to the study of ultra-high-frequency financial data. The use of Lomb–Scargle Fourier transform, provides a robust framework to take into account the irregular spacing in time, minimising the computational effort. Likewise, it avoids complex model specifications (e.g. ACD or intensity models) or resorting to traditional methods, such as (linear or cubic) interpolation and regular resampling, which not only cause artifacts in the data and loss of information, but also lead to the generation and use of spurious information.     

Testing for the Presence of Moral Hazard Using the Regulatory Reform in the Car Insurance Market: Case of Korea

The aim of this paper is to investigate the presence of the moral hazard phenomenon in the Korean car insurance market. In the context of natural experiment, I examine whether the regulatory reform introduced in 2000 generates significant difference in accident probability between before and after the reform. Further, I analyse the different effects of regulatory reform on different parts of the outcome distribution. In any case, I do not find the significant effects of regulatory reform on accident probability.     

OPTIONAL REAL-TIME PRICING OF ELECTRICITY FOR INDUSTRIAL FIRMS

Abstract. This paper proposes a pricing mechanism, optional real-time pricing (RTP), with day-ahead hourly prices, that exploits the potential offered by a competitive wholesale power market. When an electric utility offers the option to its industrial customers, the retail prices are based on an existing Hopkinson tariff and expectations as to the wholesale market's next-day hourly spot prices. The proposed RTP mechanism is Pareto-superior to the tariff in that it assures both the utility and the customer of profits that will be at least as great as under the tariff.     

Patterns of technology life cycles: stochastic analysis based on patent citations

Patent analysis has been considered as an effective means of estimating phases of a technology life cycle. However, previous studies have not considered the dynamic and idiosyncratic aspects of a technology’s progression since they were based on deterministic methods, mainly fitting s- or double s-shaped curves to patent application counts. Moreover, previous methods cannot be executed at the individual patent level. We propose a stochastic technology life cycle analysis to trace the phases of a technology’s progression based on patent citations and identify the patterns of technology life cycles at the individual patent level. At the heart of the proposed approach are a hidden Markov model to estimate the probability of a system being at a certain hidden state from observation and cluster analysis to group a set of objects according to their similarities. A case study of patents about laser technology in lithography is presented.     

When I put on my service mask: Determinants and outcomes of emotional labor among hotel service providers according to affective event theory

This article develops and tests a model of emotional labor in the hotel industry using affective event theory. A multiple-wave longitudinal analysis using data from 424 hotel service employees and their immediate supervisors reveals how work contexts (supervisory support) affect work events (interactional justice), and thereby influence the affective (negative emotions), attitudinal (job satisfaction), and behavioral (emotional labor, service quality, and voluntary turnover) reactions of hotel service employees. The results show that (1) supervisory support relates positively to supervisory interactional justice; (2) supervisory interactional justice is negatively associated with negative emotions; (3) negative emotions relate positively to surface acting and negatively to deep acting; (4) surface acting leads to lower job satisfaction, whereas deep acting leads to higher job satisfaction; and (5) job satisfaction leads to higher service quality and lower turnover. The implications suggest important recommendations for hotel managers.     

What If Immigrants Had Not Migrated?

A bstract .   Despite strong theoretical arguments and models about international migration, very few empirical studies rigorously test these arguments and models. The purpose of the present study is to analyze determinants and consequences for international migration, focusing particularly on the returns to post-hoc international migration. The present study compares residential well-being of Korean international migrants in the United States with that of their hypothetical well-being if they had not migrated. Our suggested models of the selectivity corrected returns to various characteristics for immigrants and nonimmigrants enable us to estimate the "opportunity well-being" of individuals and households; that is, the well-being of immigrants-had-they-stayed and of nonimmigrants-if-they-had-immigrated. The data for our analyses are drawn from the 1990 Korea Census Data and the Public Use Microdata Samples (PUMS) of the 1990 U.S. Census. In either case of migrants-had-they-stayed or of nonimmigrants-had-they-migrated, international migration to the United States has a significant and positive effect on the probability of homeownership, especially for women. The results show that the predicted probability of homeownership attainment increases as a result of migration by 15 percent to 16 percent for women and by 8 percent for men. The study concludes that migrating to the United States offers better opportunities for homeownership than staying in Korea does, particularly for women.     

Open data in Nepal: a webometric network analysis

This study examines the current open data trends in Nepal based on the webometric analysis method by using search engines to trawl through websites and obtain data. The results indicate that various national and international nonprofit organizations, public sector organizations, educational institutions , and a few commercial organizations were the initial actors fostering open data in Nepal. Therefore, these organizations were analyzed in terms of their networking patterns and the extent to which they are exposed internationally in cyberspace by using Webometric Analyst 2.0. Inter-linkage analysis, co-mention analysis, and link impact analyses were conducted to explore the networking behavior in the World Wide Web. The results revealed that international organizations (IOs) were strongly interlinked. Nongovernmental organizations (NGOs), government organizations (GOs), and IOs were interlinked, but weakly. In terms of the co-mention network analysis, IOs with IOs were more significant than NGOs with NGOs, GOs, or business organizations because IOs had been working actively for many years, their web presence was high, and they worked in other fields, including open data. A link impact analysis was also conducted using its indicators of seed sites linked to external websites in terms of the estimated number of top-level domains and country-code top-level domains.     

Public trust and corruption perception: disaster relief

Public trust in government and nongovernment organizations is essential to the public’s willingness to donate and to support those organizations. We measure public trust in disaster aid using people’s perception of these organizations’ effectiveness in delivering aid relief to the victims of two recent major earthquakes in China. Based on the survey data collected in 2013 from about 2100 residents in Hong Kong, we document the vulnerability of these residents’ trust perceptions in aid delivery. We find that the sharp decline in trust perception is highly negatively correlated with their perception of corruption of local governments in China.     

Corroborating social media echelon in cancer research

Worldwide medical facilities differ, and for this reason, the causes of death can vary. Cancer is considered the second leading cause of death after heart disease worldwide, and the same causes of death are observed in the United States (US). Therefore, the purposes of this study are to explore worldwide research levels in the field of cancer and the social collaboration of researchers and institutions in this field. This article examines the structural patterns of international co-authors and co-institutions in science citation index papers in cancer research. The study uses measures from the social network analysis method, including degree centrality, betweenness centrality, eigenvector centrality, and effectiveness, to investigate the effects of social networks in the area of cancer research. Empirical analysis results identify the US is the most central country, followed by Germany, Italy, France, and China, in terms of co-authored networks in this research field. Institutional analysis results indicate that the University of Milan is at the top in terms of degree centrality. The Gustave Roussy Cancer Campus in France and German University of Düsseldorf occupy the second and fourth positions, respectively. The University of California in Los Angeles and Harvard University, both in the US, are at third and fifth positions, respectively.     

Self‐Fulfilling Early‐Contracting Rush*

In markets for entry‐level professionals, the insurance motive drives some participants to sign early contracts. The rush to early contracting can be self‐fulfilling, as both its effect on expectations about demand–supply balance in the subsequent spot market and the effect on it from changes in the demand–supply balance can be nonmonotone. Matching markets with more risk‐averse participants, a greater uncertainty regarding relative supply of positions, or a more polarized distribution of applicant qualities are more vulnerable to self‐fulfilling early‐contracting rushes. Employers can have a collective interest in preventing early offers to a few promising applicants from starting the rushes.