Spatial Price Competition: A Semiparametric Approach

We investigate the nature of price competition among firms that produce differentiated products and compete in markets that are limited in extent. We propose an instrumental variables series estimator for the matrix of cross price response coefficients, demonstrate that our estimator is consistent, and derive its asymptotic distribution. Our semiparametric approach allows us to discriminate among models of global competition, in which all products compete with all others, and local competition, in which products compete only with their neighbors. We apply our semiparametric estimator to data from U.S. wholesale gasoline markets and find that, in this market, competition is highly localized.     

Graphical displays for clarifying how allocation ratio affects total sample size for the two sample logrank test

For time‐to‐event data, the power of the two sample logrank test for the comparison of two treatment groups can be greatly influenced by the ratio of the number of patients in each of the treatment groups. Despite the possible loss of power, unequal allocations may be of interest due to a need to collect more data on one of the groups or to considerations related to the acceptability of the treatments to patients. Investigators pursuing such designs may be interested in the cost of the unbalanced design relative to a balanced design with respect to the total number of patients required for the study. We present graphical displays to illustrate the sample size adjustment factor, or ratio of the sample size required by an unequal allocation compared to the sample size required by a balanced allocation, for various survival rates, treatment hazards ratios, and sample size allocation ratios. These graphical displays conveniently summarize information in the literature and provide a useful tool for planning sample sizes for the two sample logrank test. Copyright © 2010 John Wiley & Sons, Ltd.     

Random Effects Estimators with many Instrumental Variables

In this paper we propose a new estimator for a model with one endogenous regressor and many instrumental variables. Our motivation comes from the recent literature on the poor properties of standard instrumental variables estimators when the instrumental variables are weakly correlated with the endogenous regressor. Our proposed estimator puts a random coefficients structure on the relation between the endogenous regressor and the instruments. The variance of the random coefficients is modelled as an unknown parameter. In addition to proposing a new estimator, our analysis yields new insights into the properties of the standard two‐stage least squares (TSLS) and limited‐information maximum likelihood (LIML) estimators in the case with many weak instruments. We show that in some interesting cases, TSLS and LIML can be approximated by maximizing the random effects likelihood subject to particular constraints. We show that statistics based on comparisons of the unconstrained estimates of these parameters to the implicit TSLS and LIML restrictions can be used to identify settings when standard large sample approximations to the distributions of TSLS and LIML are likely to perform poorly. We also show that with many weak instruments, LIML confidence intervals are likely to have under‐coverage, even though its finite sample distribution is approximately centered at the true value of the parameter. In an application with real data and simulations around this data set, the proposed estimator performs markedly better than TSLS and LIML, both in terms of coverage rate and in terms of risk.     

Nonstationary Brand Variables in Category Management: A Cointegration Perspective

Category‐management models serve to assist in the development of plans for pricing and promotions of individual brands. Techniques to solve the models can have problems of accuracy and interpretability because they are susceptible to spurious regression problems due to nonstationary time‐series data. Improperly stated nonstationary systems can reduce the accuracy of the forecasts and undermine the interpretation of the results. This is problematic because recent studies indicate that sales are often a nonstationary time‐series. Newly developed correction techniques can account for nonstationarity by incorporating error‐correction terms into the model when using a Bayesian Vector Error‐Correction Model. The benefit of using such a technique is that shocks to control variates can be separated into permanent and temporary effects and allow cointegration of series for analysis purposes. Analysis of a brand data set indicates that this is important even at the brand level. Thus, additional information is generated that allows a decision maker to examine controllable variables in terms of whether they influence sales over a short or long duration. Only products that are nonstationary in sales volume can be manipulated for long‐term profit gain, and promotions must be cointegrated with brand sales volume. The brand data set is used to explore the capabilities and interpretation of cointegration.     

Parenthood,Gender and Work‐Family Time in the United States,Australia, Italy,France, and Denmark

Research has associated parenthood with greater daily time commitments for fathers and mothers than for childless men and women, and with deeper gendered division of labor in households. How do these outcomes vary across countries with different average employment hours, family and social policies, and cultural attitudes to family care provision? Using nationally representative time‐use data from the United States, Australia, Italy, France, and Denmark (N = 5,337), we compare the paid and unpaid work of childless partnered adults and parents of young children in each country. Couples were matched (except for the United States). We found parents have higher, less gender‐equal workloads than nonparents in all five countries, but overall time commitments and the difference by parenthood status were most pronounced in the United States and Australia.     

Ethical and legal considerations regarding disputed authorship with the use of shared data

Little guidance is currently available for handling disputes between research mentors and students when working with shared data. This article analyzes how the ethical guidelines from the American Psychological Association (APA), the Office of Research Integrity (ORI), and the American Educational Research Association (AERA) can inform common disputes in this area. Additional insights about the nature of the research relationship are derived from contract and copyright law. Practice guidelines are proposed to safeguard student and faculty welfare in research collaboration, and recommendations are provided to help prevent and resolve disputes between students and faculty.     

A case study comparing a randomized withdrawal trial and a double-blind long-term trial for assessing the long-term efficacy of an antidepressant

Assessing long-term efficacy in psychiatric drugs involves a number of complex questions, and the priaority of these questions is different for different disorders and for different stakeholders. Therefore, it is essential that we not adopt a one-method-fits-all approach, but rather adapt the specific details of the designs and analysis of data from long-term trials to individual disease states. Randomized withdrawal (RW) designs, even though addressing a specific question of particular interest, face some difficult methodological and ethical challenges. A less common alternative design, termed the double-blind long-term efficacy (DBLE) design, is logistically similar to traditional responder extension designs. However, use of an analytic approach that includes all randomized patients rather than only the selected subset that continued beyond acute treatment avoids the major criticism of the extender design. The present paper illustrates the attributes of the RW and DBLE designs by analyzing data from trials adopting these designs. The RW and DBLE designs address different questions, and are thus not directly comparable. Potential benefits of the DBLE design include: (1) the parsimonious use of patients and the resultant reduced exposure to placebo as each patient can contribute to multiple developmental objectives; (2) the results are generalizable to actual clinical practice as the design matches treatment guidelines; and, (3) results of safety assessments are meaningful as they involve all randomized patients. Our case study suggests that the DBLE design can provide definitive answers to important questions and may be a useful design for assessing long-term treatment effects.     

A COMMENT ON THE COST OF NEW ISSUES OF COMMON STOCK

According to the constant growth model and perceived finance theory, the cost of new external equity exceeds the cost of retained earnings due to flotation costs and underpricing. Carlson and Dietz [1] have recently argued that the constant growth model is operationally inadequate whenever the net proceeds from the issuance of a new share differ from book value. Specifically, they contend that the cost of new external equity is less than the cost of retained earnings whenever the net proceeds from a new share exceed book value. We show that these conclusions stem from an error in interpretation and therefore that the constant growth model is valid regardless of the relationship between market prices and book value.     

The Impact of Information System Personnel Skill Discrepancies on Stakeholder Satisfaction

System development efforts depend to a large degree upon how well information systems (IS) managers, IS specialists, and IS users work together in a project team structure. Yet, these individuals frequently work under different perceptions about matters of importance to development, management, and success. This paper introduces a framework for examining IS specialists' skill requirements from a multiple‐stakeholder perspective. Derived from discrepancy theory, the framework concedes that different stakeholders hold a variable set of expectations for IS personnel skill levels as well as a perception of skills held by IS personnel. We examine differences in expectation and performance expressed by each group and describe the impact of the discrepancy on user satisfaction, career satisfaction of IS specialists, and on job performance evaluations by IS managers. Results confirm that a discrepancy between an IS specialist's expectations of skill and their perceived skill self‐proficiency impacts career satisfaction. Similar relations hold for IS managers and users. Since different stakeholders may hold different perceptions, satisfaction of all parties becomes problematic unless a common frame of reference can be determined.