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Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing environments are needed. This paper presents a sequential posterior simulator designed to operate efficiently in this context. The simulator makes fewer analytical and programming demands on investigators, and is faster, more reliable, and more complete than conventional posterior simulators. The paper extends existing sequential Monte Carlo methods and theory to provide a thorough and practical foundation for sequential posterior simulation that is well suited to massively parallel computing environments. It provides detailed recommendations on implementation, yielding an algorithm that requires only code for simulation from the prior and evaluation of prior and data densities and works well in a variety of applications representative of serious empirical work in economics and finance. The algorithm facilitates Bayesian model comparison by producing marginal likelihood approximations of unprecedented accuracy as an incidental by-product, is robust to pathological posterior distributions, and provides estimates of numerical standard error and relative numerical efficiency intrinsically. The paper concludes with an application that illustrates the potential of these simulators for applied Bayesian inference.

Structural models of demand founded on the classic work of Berry, Levinsohn, and Pakes (1995) link variation in aggregate market shares for a product to the influence of product attributes on heterogeneous consumer tastes. We consider implementing these models in settings with complicated products where consumer preferences for product attributes are sparse, that is, where a small proportion of a high-dimensional product characteristics influence consumer tastes. We propose a multistep estimator to efficiently perform uniform inference. Our estimator employs a penalized pre-estimation model specification stage to consistently estimate nonlinear features of the BLP model. We then perform selection via a Triple-LASSO for explanatory controls, treatment selection controls, and instrument selection. After selecting variables, we use an unpenalized GMM estimator for inference. Monte Carlo simulations verify the performance of these estimators.

Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series. The initial history, published in 2012 for the 30th Anniversary Volume, describes key events in the history of the series and provides information about key authors and contributors to Advances in Econometrics. The authors update the original history and discuss significant changes that have occurred since 2012. These changes include the addition of five new Senior Co-Editors, seven new AIE Fellows, an expansion of the AIE conferences throughout the United States and abroad, and the increase in the number of citations for the series from 7,473 in 2012 to over 25,000 by 2022.

In England and Wales, legislation pertaining to hate crime recognizes hostility based on racial identity, religious affiliation, sexual orientation, disability or transgender identity. Discussions abound as to whether this legislation should also recognize hostility based on gender or misogyny. Taking a socio-legal analysis, the chapter examines hate crime, gender-based victimization and misogyny alongside the impact of victim identity construction, access to justice and the international nature of gendered harm. The chapter provides a comprehensive investigation of gender-based victimization in relation to targeted hostility to assess the potential for its inclusion in hate crime legislation in England and Wales.

The purpose of this paper is to draw attention to the work of sociologists who laid the foundation for queer and crip approaches to disability and to address how queer and crip theory has and can help to re-conceptualize our understandings of health, illness, disability, and sexuality.

This paper is an examination of historical moments and prominent literature within medical sociology and sociology of disability. Sociological and popular understandings of disability and sexuality have often mirrored each other historically. Although this literature review focuses primarily on medical sociology and disability studies literature, some works of scholars specializing in gender studies, sexuality, literature, history, and queer studies are also included

In this paper, I argue that the medicalization and pathologization of human differences specifically as it pertains to sexuality and disability within the medical sociological literature have led to constructionist, social model, and feminist critiques. It is these critiques that then laid the foundation for the development of queer and crip theoretical approaches to both disability and sexuality.

Crip and queer approaches to disability provide a clear call for future sociological research. Few social science scholars have applied queer and crip approaches in empirical studies on disability. The majority of work in this area is located in the humanities and concerned with literary criticism. A broader array of empirical work on the intersection of sexuality and disability from queer/crip perspectives is needed both to refine these postmodern theoretical models and to examine their implications for the complex lived experience that lies at the intersection of sexuality and disability. In queering disability and cripping sexuality and gender, we may be able not only to more fully conceptualize disability, sexuality, and gender as individual social categories, but also to more fully understand the complex intersection of these social locations.

The purpose of the paper is to draw together the salient issues surrounding customer loyalty and customer relationship management (CRM) into a single coherent discussion. Various schools of academic thought are examined. The paper concludes with practical implications for managers.

The literature surrounding customer loyalty, customer satisfaction, effective CRM and managing loyalty in a profitable manner are all reviewed. The paper allows managers to consider a wide range of material in the context of their business.

The need for businesses to retain customers is an important issue in today's global marketplace. To retain customers, a business must forge loyal and long‐term relationships with profitable customers. Reasons why customers leave a company are discussed, and preventative strategies are considered. Loyalty schemes are considered and their relative merits examined.

A key implication of this paper is the need to focus attention on managing customer loyalty in a profitable manner. Certain theories hold the view that generating customer loyalty will automatically drive profits. This paper suggests that this is probably not the case. Given this, the paper calls for data analysis and database segmentation to be considered as an integral part of profitably managing customer loyalty.

The paper provides both a broad and in‐depth discussion of all the salient issues surrounding customer loyalty. By drawing together these issues into a single discussion, the paper offers a unique perspective that is not available in the current literature. Holistically considering all of the practical elements of customer loyalty allows academic researchers and marketing managers to compare and contrast different theories and principles.