Objective Bayes and Conditional Frequentist Inference

Objective Bayesian methods have garnered considerable interest and support among statisticians, particularly over the past two decades. It has often been ignored, however, that in some cases the appropriate frequentist inference to match is a conditional one. We present various methods for extending the probability matching prior (PMP) methods to conditional settings. A method based on saddlepoint approximations is found to be the most tractable and we demonstrate its use in the most common exact ancillary statistic models. As part of this analysis, we give a proof of an exactness property of a particular PMP in location-scale models. We use the proposed matching methods to investigate the relationships between conditional and unconditional PMPs. A key component of our analysis is a numerical study of the performance of probability matching priors from both a conditional and unconditional perspective in exact ancillary models. In concluding remarks we propose many routes for future research

On model selection criteria for climate change impact studies

Climate change impact studies inform policymakers on the estimated damages of future climate change on economic, health and other outcomes. In most studies, an annual outcome variable is observed, e.g. annual mortality rate, along with higher-frequency regressors, e.g. daily temperature and precipitation. Practitioners use summaries of the higher-frequency regressors in fixed effects panel models. The choice over summary statistics amounts to model selection. Some practitioners use Monte Carlo cross-validation (MCCV) to justify a particular specification. However, conventional implementation of MCCV with fixed testing-to-full sample ratios tends to select over-fit models. This paper presents conditions under which MCCV, and also information criteria, can deliver consistent model selection. Previous work has established that the Bayesian information criterion (BIC) can be inconsistent for non-nested selection. We illustrate that the BIC can also be inconsistent in our framework, when all candidate models are misspecified. Our results have practical implications for empirical conventions in climate change impact studies. Specifically, they highlight the importance of a priori information provided by the scientific literature to guide the models considered for selection. We emphasize caution in interpreting model selection results in settings where the scientific literature does not specify the relationship between the outcome and the weather variables.Comment: Additional simulation results available from authors by reques

What can Renaissance Studies Teach us about Inclusivity?

In this article I describe my pedagogical approach to sixteenth- and seventeenth-century Spanish texts. I contend that by studying the cultural output of a remote historical period, modern students can examine mechanisms of exclusion without feeling compelled to defend their own identity or group. Racial dynamics are significantly different in the early modern period, when structural inequalities targeted religious minorities—the ‘conversos’ who were descendants of Jewish and Muslim inhabitants of the Iberian Peninsula. Since students do not personally identify with either the hegemonic identity of the noble Spanish male nor with the converso, they are able to examine racial and gender inequities in a less emotionally charged milieu. Furthermore, the grafting of racial difference onto religious minority that occurs in this era invites examination of the socially constructed nature of race as an identity category. After examining the racial and gender inequities of the early modern era, students are able to discuss the dynamics of systems of exclusion that have persisted into the modern age and, I hope, feel better able to identify and examine modern forms of racial and gender discrimination. Moreover, by examining a historically distant time period, students recognize the historical contingence of ideas regarding what is ‘natural’ and of identity categories themselves

Fictions of Containment in the Spanish Female Picaresque: Architectural Space and Prostitution in the Early Modern Mediterranean

This study examines the interdependence of gender, sexuality and space in the early modern period, which saw the inception of architecture as a discipline and gave rise to the first custodial institutions for women, including convents for reformed prostitutes. Meanwhile, conduct manuals established prescriptive mandates for female use of space, concentrating especially on the liminal spaces of the home. This work traces literary prostitution in the Spanish Mediterranean through the sixteenth and seventeenth centuries, from the rise of courtesan culture in several key areas through the shift from tolerance of prostitution toward repression. Kuffner’s analysis pairs canonical and noncanonical works of fiction with didactic writing, architectural treatises, and legal mandates, tying the literary practice of prostitution to increasing control over female sexuality during the Counter Reformation. By tracing erotic negotiations in the female picaresque novel from its origins through later manifestations, she demonstrates that even as societal attitudes towards prostitution shifted dramatically, a countervailing tendency to view prostitution as an essential part of the social fabric undergirds many representations of literary prostitutes. Kuffner’s analysis reveals that the semblance of domestic enclosure figures as a primary erotic strategy in female picaresque fiction, allowing readers to assess the variety of strategies used by authors to comment on the relationship between unruly female sexuality and social order.https://digitalcommons.csbsju.edu/hispanic_studies_books/1020/thumbnail.jp

M-Club Announces $1.5 Million Gift to Forward Together Campaign

Alumni chapter\u27s donation will benefit baseball and football initiative