Trading cost expectations: Evidence from S&P 500 index replacement stock announcements

This paper tests the effect on stock value of an expected change in future trading costs. The capitalized value of a reduction in trading costs is hypothesized to increase the stock value, a trading cost effect. Improved liquidity reduces trading costs. Inclusion as an S&P 500 Index replacement stock is an event hypothesized to increase liquidity. We use 114 observations between January 1, 1983 and October 12, 1989 of stocks added to the Index as replacements for stocks removed. The abnormal return of each stock is regressed against the ratio of the bidask spread to the price of the stock, the change in trading volume of the stock, and the open interest in the Index futures contracts at the close of the month prior to the replacement announcement. We find that the positive abnormal returns for replacement stocks are related to increased daily trading volume after inclusion in the Index. Further, the trading cost effect is proportional to percentage bid-ask spreads prior to inclusion. The trading cost effect increases as trading in derivatives of the Index increases. The volume and stock price changes after replacement are not transitory, indicating an improvement in liquidity. Three alternate hypotheses suggested in prior research to explain the abnormal returns for replacement stocks are tested. Testing each of the three models previously considered: price pressure, inelastic demand curves, and information, we find that none can be accepted with statistical confidence. The abnormal returns of Index replacement stocks are consistent with rational pricing of an anticipated reduction in future transaction costs. This anticipated reduction is capitalized in the value of the stock at the time of the replacement announcement. These results are consistent with a trading cost effect.     

Evaluating,Comparing, Monitoring,and Improving Representativeness of Survey Response Through R‐Indicators and Partial R‐Indicators

Non‐response is a common source of error in many surveys. Because surveys often are costly instruments, quality‐cost trade‐offs play a continuing role in the design and analysis of surveys. The advances of telephone, computers, and Internet all had and still have considerable impact on the design of surveys. Recently, a strong focus on methods for survey data collection monitoring and tailoring has emerged as a new paradigm to efficiently reduce non‐response error. Paradata and adaptive survey designs are key words in these new developments. Prerequisites to evaluating, comparing, monitoring, and improving quality of survey response are a conceptual framework for representative survey response, indicators to measure deviations thereof, and indicators to identify subpopulations that need increased effort. In this paper, we present an overview of representativeness indicators or R‐indicators that are fit for these purposes. We give several examples and provide guidelines for their use in practice.     

Screening‐oriented recruitment messages: Antecedents and relationships with applicant pool quality

The ability of firms to attract qualified job applicants is a critical component of the human resource management process. However, while a large body of research has examined the relationship between firm recruitment practices and applicant pool attributes, very little research has investigated what factors are associated with organizational decision makers' utilization of specific recruitment tactics. We draw on labor economics, sociological, and agency theoretical perspectives to make predictions regarding the use of screening‐oriented recruitment messages in actual web‐based job advertisements. Results suggest that perceptions of labor supply, recruiting firm reputation, and the use of quality‐based compensation incentives are associated with use of screening‐oriented messages, which in turn are associated with applicant pool quality. These findings hold important theoretical insights into the factors shaping firm recruitment activity and provide practical strategic implications for managing firm recruitment objectives. © 2012 Wiley Periodicals, Inc.     

An analysis of asymmetric demand response to price changes: The case of local telephone calls

Asymmetric demand responses to price changes are not an observable implication of classical demand theory, which predicts that consumers will react to a small price increase in much the same way as they do to a small price decrease. Yet applied researchers have long speculated that consumers are more sensitive to price increases than they are to price decreases. In addition, recent empirical studies generally support the theory of asymmetric demand responses. We construct a dynamic model based on data gathered from monthly telephone bills for 128 New York Telephone customers over a five-year period. Our results support the conclusion that customers react more quickly and strongly when prices go up than they do when prices go down.We would like to thank Manny Haas and Bernie Reddy for their comments and suggestions.     

Reasoning under uncertainty and multi-criteria decision making in data privacy

By means of an integration of decision theory and probabilistic models, we explore and develop methods for improving data privacy. Our work encompasses disclosure control tools in statistical databases and privacy requirements prioritization; in particular we propose a Bayesian approach for the on-line auditing in Statistical Databases and Pairwise Comparison Matrices for privacy requirements prioritization. The first approach is illustrated by means of examples in the context of statistical analysis on the census and medical data, where no salary (resp. no medical information), that could be related to a specific employee (resp. patient), must be released; the second approach is illustrated by means of examples, such as an e-voting system and an e-banking service that have to satisfy privacy requirements in addition to functional and security ones. Several fields in the social sciences, economics and engineering will benefit from the advances in this research area: e-voting, e-government, e-commerce, e-banking, e-health, cloud computing and risk management are a few examples of applications for the findings of this research.     

The dimensional assessment of personality in drug addicts: a mixed-effects Rasch model approach

Drug abuse results from a series of different factors, such as social and family issues. Subjects more vulnerable to develop an addiction are, for instance, people living in high-stress environments who may resort to addiction in order to cope with their circumstances, such as demanding jobs, family crisis or other situations or people living in low-income households where violence occurs, who may be triggered into addiction as a way to escape negative emotions or ignore any underlying problems or issues. Psychometric research in the field of drug dependence has focused on identifying certain personality characteristics. It is now generally agreed that personality may influence, precipitate or perpetuate substance abuse. The aim of this paper is to perform a dimensional assessment of personality in a sample of drug addicts. To better understand the complexity of addictive behaviours of substance-using individuals, the Cloninger’s temperament and character inventory test is employed while the item response data analysis is performed by mixed-effects Rasch models. These models combine the advantages both of Rasch measurement framework for latent variables and of models with hierarchical data. To evaluate the differences in dimensions of temperament and character inventory test in subjects with drug addiction, we fit and compare a sequence of mixed-effects Rasch models. Results from models fitting are compared and discussed for a data set of 84 participants.     

The M/M\1 queue in a heavy-tailed random environment

We consider an M / M /1 queue with the special feature that the speed of the server alternates between two constant values s_L and s_H > s_L . The high-speed periods are exponentially distributed, and the low-speed periods have a regularly varying distribution. We obtain explicit asymptotics for the tail of the workload distribution. The two cases in which the offered traffic load is smaller respectively larger than the low service speed are shown to result in completely different asymptotics.