Monopolistic Competition: Beyond the Constant Elasticity of Substitution

We propose a model of monopolistic competition with additive preferences and variable marginal costs. Using the concept of “relative love for variety,” we provide a full characterization of the free‐entry equilibrium. When the relative love for variety increases with individual consumption, the market generates pro‐competitive effects. When it decreases, the market mimics anti‐competitive behavior. The constant elasticity of substitution is the only case in which all competitive effects are washed out. We also show that our results hold true when the economy involves several sectors, firms are heterogeneous, and preferences are given by the quadratic utility and the translog.     

Promoting Individual and Social Changes: A Hybrid Model of Social Work with Groups

Taking as a starting point two influential, yet different approaches in group work, that is, the self-directed group work and mutual aid models, this article examines a possible alternative for conducting social work with groups. Drawing from structuration theory, which makes a strong dialectical relation between agency and structure possible, this article highlights how our alternative model could lead to a greater integration of the micro- and macrodimensions in group-work practice. The Discussion section proposes three key principles for group work, namely, a belief in people’s strengths and capacities, a focus on critical thinking, and a concern for the development of a democratic culture in groups. These principles are conveyed through the group worker’s roles as consciousness raiser and process facilitator and provide a flexible and participatory process that can be used with a broad range of service-user groups. The article concludes with a discussion on the strengths and limitations of the model.     

Unfinished business: ongoing ethical exceptionalism in the oversight of human pluripotent stem cell research in Canada

In this article, we critically examine the arguments for and against the exceptional status given human pluripotent stem cell research in Canada (through the latest [December 2010] revision of the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans), and conclude that this exceptionalism is unwarranted and ethically unsound. In our view, the three federal research granting agencies should honor their longstanding commitment that researchers, research sponsors, and Research Ethics Boards in Canada have access to "a single reference document for all research involving humans conducted under the auspices of institutions eligible for Agency funding." As well, responsibility for the development, interpretation, and implementation of Canada's research ethics guidelines should be under the authority of a single oversight body that is independent of the federal research granting Agencies.     

Computing the Exact Fisher Information Matrix of Periodic State-Space Models

The purpose of this article is to develop algorithms for computing the exact Fisher information matrix of periodic time-varying state-space models. We first present a relatively simple recursive algorithm which computes the elements of the exact information matrix without involving numerical differentiation, since all required derivatives are analytically evaluated. The proposed algorithm extends the procedure due to Cavanaugh and Shumway (1996 Cavanaugh , J. E. , Shumway , R. H. ( 1996 ). On computing the expected Fisher information matrix for state-space model parameters . Statist. Probab. Lett. 26 : 347 – 355 .[Crossref], [Web of Science ®] , [Google Scholar]) to the periodic state-space framework. Exploiting the approach used in Klein et al. (2000 Klein , A. , Mélard , G. , Zahaf , T. ( 2000 ). Construction of the exact Fisher information matrix of Gaussian time series models by means of matrix differential rules . Linear Alg. Applic. 321 : 209 – 232 .[Crossref], [Web of Science ®] , [Google Scholar]), a second algorithm is proposed in order to obtain the exact information matrix as a whole instead of element by element. The algorithms are first developed in a general framework and then specialized to the case of a periodic Gaussian vector autoregressive moving-average (PVARMA) model.     

Leverages and Influential Observations in a Regression Model with Autocorrelated Errors

This article deals with the general form of the hat matrix and the DFBETA measure to detect the influential observations and the leverages in the linear regression model with more than one regressor when the errors are from AR(1) and AR(2) processes. Previous studies dealing with the influential observations and the leverages in the constant mean model and regression through the origin model are obtained as special cases. To demonstrate the utility of the hat matrix and the DFBETA measure, two numerical examples based on the ice cream consumption data with AR(1) errors and the Fox-Hartnagel data with AR(2) errors are analyzed. The results show that the parameter of the autoregressive process affects the influential and leverage points.     

A Generalization of the Univariate Slash by a Scale-Mixtured Exponential Power Distribution

A generalization of the slash distribution is derived using the scale mixture of the exponential power distribution. The newly defined family of distributions provides a rich flexibility on the tail heaviness and yields alternative robust estimators of location and scale in non normal situations. In order to investigate asymptotically the bias properties of the estimators, a simulation study is performed. The performance of the estimators on two well-known real data sets is also illustrated.     

Estimation of Change Point in Generalized Variance Control Chart

In this study, using maximum likelihood estimation, a considerably effective change point model is proposed for the generalized variance control chart in which the required statistics are calculated with its distributional properties. The procedure, when used with generalized variance control charts, would be helpful for practitioners both controlling the multivariate process dispersion and detecting the time of the change in variance-covariance matrix of a process. The procedure starts after the chart issues a signal. Several structural changes for the variance-covariance matrix are considered and the precision and the accuracy of the proposed method is discussed.     

Some factors affecting statistical power of approximate tests in the linear mixed model for longitudinal data

Different longitudinal study designs require different statistical analysis methods and different methods of sample size determination. Statistical power analysis is a flexible approach to sample size determination for longitudinal studies. However, different power analyses are required for different statistical tests which arises from the difference between different statistical methods. In this paper, the simulation-based power calculations of F-tests with Containment, Kenward-Roger or Satterthwaite approximation of degrees of freedom are examined for sample size determination in the context of a special case of linear mixed models (LMMs), which is frequently used in the analysis of longitudinal data. Essentially, the roles of some factors, such as variance–covariance structure of random effects [unstructured UN or factor analytic FA0], autocorrelation structure among errors over time [independent IND, first-order autoregressive AR1 or first-order moving average MA1], parameter estimation methods [maximum likelihood ML and restricted maximum likelihood REML] and iterative algorithms [ridge-stabilized Newton-Raphson and Quasi-Newton] on statistical power of approximate F-tests in the LMM are examined together, which has not been considered previously. The greatest factor affecting statistical power is found to be the variance–covariance structure of random effects in the LMM. It appears that the simulation-based analysis in this study gives an interesting insight into statistical power of approximate F-tests for fixed effects in LMMs for longitudinal data.     

INDIVIDUAL WELFARE WHEN CONSUMERS CAN SHOP FOR HEALTH INSURANCE

The statewide system of health insurance exchanges established by the Affordable Care Act (ACA) of 2010 will allow millions of U.S. citizens to change their health care policies more easily than they can switch automobile or homeowner insurance coverages, because deniability based on prior claim history is illegal. Focusing on this consumer endogeneity of health insurance policy choice, we examine the individual moral hazard welfare implications of a reduction in the price of medical care, which is a potential consequence of the ACA. We show that endogenous policy choice plays a key role in determining the welfare outcome. While moral hazard welfare improvement is not precluded, a distinctly possible outcome is that the consumer revises his/her choice of insurance policy so as to retain some portion of the reduction in expenditure risk caused by the medical care price decrease. In this event, moral hazard welfare loss is higher than it was before the price decrease, although the increased loss is tempered by the endogenous contract choice effect. This result resuscitates an old conventional wisdom. (JEL I11, I13, I30)