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Principal component (PC) techniques are commonly used to improve the small sample properties of the linear instrumental variables (IV) estimator. Carrasco (2012) argue that PC type methods provide a natural ranking of instruments with which to reduce the size of the instrument set. This chapter shows how reducing the size of the instrument based on PC methods can lead to poor small sample properties of IV estimators. A new approach to ordering instruments termed ‘normalized principal components’ (NPCs) is introduced to overcome this problem. A simulation study shows the favourable small samples properties of IV estimators using NPC, methods to reduce the size of the instrument relative to PC. Using NPC we provide evidence that the IV setup in Angrist and Krueger (1992) may not suffer the weak instrument problem.

This paper challenges and expands commonplace assumptions about problems of time and temporality in emergencies. In traditional emergency powers theory “emergency time” is predominantly an “exceptional time.” The problem is that there is “no time” and the solution is limited “in time”: exceptional behavior is allowed for a special time only, until the emergency is over, or according to formal sunset clauses. But what is characteristic of many emergencies is not the problem of “no time” but the ways in which time is legally structured and framed to handle them. Using the Israeli High Court of Justice 1999 decision on the use of physical interrogation methods under conditions of necessity, this paper illustrates how legally significant emergency-time structures that lay beyond the problematic of exceptional time, gravely implicate the way that “exceptional measures” are practiced and regularized.

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.

OF old the public library was wont to take its reputation from the character of the newsroom. That room, as everyone knows, attracts every element in the community and it may be it attracts especially the poorer elements;—even at times undesirable ones. These people in some towns, but perhaps not so often now‐a‐days, have been unwashen and often not very attractive in appearance. It was natural, things being as they are, that the room should give a certain tone to the institution, and indeed on occasion cause it to be avoided by those who thought themselves to be superior. The whole level of living has altered, and we think has been raised, since the War. There is poverty and depression in parts of the country, it is true; but there are relief measures now which did not exist before the War. Only those who remember the grinding poverty of the unemployed in the days, especially the winter days, before the War can realise what poverty really means at its worst. This democratic levelling up applies, of course, to the public library as much as to any institution. At present it may be said that the part of the library which is most apparent to the public and by which it is usually judged, is the lending or home‐reading department. It therefore needs no apology if from time to time we give special attention to this department. Even in the great cities, which have always concentrated their chief attention upon their reference library, to‐day there is an attempt to supply a lending library service of adequate character. We recall, for example, that the Leeds Public Library of old was first and foremost a reference library, with a lending library attached; to‐day the lending library is one of the busiest in the kingdom. A similar judgment can be passed upon Sheffield, where quite deliberately the city librarian would restrict the reference library to works that are of real reference character, and would develop more fully the lending library. In Manchester, too, the new “Reference Library”—properly the new Central Library—has a lending library which issues about 1,500 volumes daily. There must be all over the country many libraries issuing up to a thousand volumes each a day from their central lending departments. This being the case the department comes in for very careful scrutiny.

The authors have three purposes in writing this paper: to share the authors' experiences “catalyzing” reconstruction of a village in southern Sri Lanka four months after its destruction by the Indian Ocean tsunami, to suggest that what the authors learned in a “developing world” setting has relevance in the authors' “developed world” classrooms and practices, and to consider the tactics that locals took both to engage and resist the authors' assistance.

The authors' approach was participatory (working as laborers for ten days), reflective (reconsidering the authors' experiences two years later and finding their influence in the authors' recent work with students), and theoretical (layering an autoethnographic framework over the authors' reflections).

It is found that traces of the Sri Lankan project can be found in the authors' work with students in the USA and Canada, and that while it is possible to find examples of locals' resistance within the village rebuilding process, incorporating such potentials and perspectives into the authors' everyday work as professors has its own complexities.

It is the authors' hope that this case study will contribute to the reversal of a dominant Western and educated perspective that “we” know what is best for “them” and that “they” must learn to appreciate what “we” have in mind. This challenge is taken by highlighting applications “here” of the authors' lessons learned “there” and by making themselves aware of how locals of all sorts and locations often resist the intentions of others, no matter how considered and shared the plans might be.

In a paper shared at the 2004 Canadian Society for the Study of Education (CSSE), Marie Battiste urged Canadian academics and policy makers to become part of a transformative process of reconstructing Canada's colonial education system which she describes as shaping “Indigenous peoples’ trauma and disconnection with many aspects of education and themselves” (p. 2). Battiste calls for the repositioning of Indigenous knowledges in post-secondary institutions, a process through which institutional structures and practices, curriculum foundations, and traditions are substantially changed and, in particular, that these are changed in ways that value and engage the capacities of Aboriginal students. Battiste's argument is significant for both Aboriginal post-secondary students and for their communities.

The purpose of this study is to identify the antecedents and dimensions of relationship quality (RQ) between customers and providers of athletic services.

Data collection involved in‐depth, personal interviews of fitness centre customers and year‐ticket holders of football clubs in order to determine the similarities and differences between the two contexts. RQ is approached from the point of view of the customer since no other study has investigated that part of the dyad. Data were analysed with thematic content analysis.

In fitness clubs, RQ is perceived as a relationship that involves trust, customer satisfaction and commitment; social bonds with employees; effective cooperation and communication, and adaptation of services to suit customers’ needs. In contrast, the relationship of football club year‐ticket holders is simpler and is perceived as trusting; satisfying for customers and one where customers feel committed to the team. The antecedents of RQ identified do not differ between the two types of relationship studied and include the quality of the servicescape; the power of entertainment; the quality of personnel; customer experience and knowledge; customer relationship orientation; relationship duration, and circumstantial or personal factors such as free time shortage, family obligations or bad weather conditions. Based on these findings a conceptual framework is developed for analysing RQ and its antecedents in athletic services.

The study extends findings regarding RQ in athletic services. However, it is qualitative in nature. Future research should quantify the constructs identified and test them in quantitative studies.

The implications of the study are wide and include appropriate methods of selecting and training staff; the effective management of service portfolios; customer training; providing an entertaining experience for customers, and designing a good quality servicescape.

The conceptual framework developed can serve as a guide for sport managers in enhancing the value of relationships with customers.

In a recent paper, Hausman, Newey, Woutersen, Chao, and Swanson (2012) propose a new estimator, HFUL (Heteroscedasticity robust Fuller), for the linear model with endogeneity. This estimator is consistent and asymptotically normally distributed in the many instruments and many weak instruments asymptotics. Moreover, this estimator has moments, just like the estimator by Fuller (1977). The purpose of this note is to discuss at greater length the existence of moments result given in Hausman et al. (2012). In particular, we intend to answer the following questions: Why does LIML not have moments? Why does the Fuller modification lead to estimators with moments? Is normality required for the Fuller estimator to have moments? Why do we need a condition such as Hausman et al. (2012), Assumption 9? Why do we have the adjustment formula?

In many problems involving decision‐making under uncertainty, the underlying probability model is unknown but partial information is available. In some approaches to this problem, the available prior information is used to define an appropriate probability model for the system uncertainty through a probability density function. When the prior information is available as a finite sequence of moments of the unknown probability density function (PDF) defining the appropriate probability model for the uncertain system, the maximum entropy (ME) method derives a PDF from an exponential family to define an approximate model. This paper, aims to investigate some optimality properties of the ME estimates.

For n>m, when the exact model can be best approximated by one of an infinite number of unknown PDFs from an n parameter exponential family. The upper bound of the divergence distance between any PDF from this family and the m parameter exponential family PDF defined by the ME method are derived. A measure of adequacy of the model defined by ME method is thus provided.

These results may be used to establish confidence intervals on the estimate of a function of the random variable when the ME approach is employed. Additionally, it is shown that when working with large samples of independent observations, a probability density function (PDF) can be defined from an exponential family to model the uncertainty of the underlying system with measurable accuracy. Finally, a relationship with maximum likelihood estimation for this case is established.

The so‐called known moments problem addressed in this paper has a variety of applications in learning, blind equalization and neural networks.

An upper bound for error in approximating an unknown density function, f(x) by its ME estimate based on m moment constraints, obtained as a PDF p(x, α) from an m parameter exponential family is derived. The error bound will help us decide if the number of moment constraints is adequate for modeling the uncertainty in the system under study. In turn, this allows one to establish confidence intervals on an estimate of some function of the random variable, X, given the known moments. It is also shown how, when working with a large sample of independent observations, instead of precisely known moment constraints, a density from an exponential family to model the uncertainty of the underlying system with measurable accuracy can be defined. In this case, a relationship to ML estimation is established.