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This paper considers stationary regression models with near-collinear regressors. Limit theory is developed for regression estimates and test statistics in cases where the signal matrix is nearly singular in finite samples and is asymptotically degenerate. Examples include models that involve evaporating trends in the regressors that arise in conditions such as growth convergence. Structural equation models are also considered and limit theory is derived for the corresponding instrumental variable (IV) estimator, Wald test statistic, and overidentification test when the regressors are endogenous. It is shown that near-singular designs of the type considered here are not completely fatal to least squares inference, but do inevitably involve size distortion except in special Gaussian cases. In the endogenous case, IV estimation is inconsistent and both the block Wald test and Sargan overidentification test are conservative, biasing these tests in favor of the null.

The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.

The paper introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.

Information is provided about each source, and the paper discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

A key challenge for cost-effective Intelligent Tutoring Systems (ITSs) is the ability to create generalizable domain, learner, and pedagogical models so they can be re-used many times over. Investment in this technology will be needed to succeed in developing ITSs for team training. The purpose of this chapter is to propose an instructional framework for guiding team ITS researchers in their development of these models for reuse. We establish a foundation for the framework with three propositions. First, we propose that understanding how teams develop is needed to establish a science-based foundation for modeling. Toward this end, we conduct a detailed exploration of the Kozlowski, Watola, Jensen, Kim, and Botero (2009) theory of team development and leadership, and describe a use case example to demonstrate how team training was developed for a specific stage in their model. Next, we propose that understanding measures of learning and performance will inform learner modeling requirements for each stage of team development. We describe measures developed for the use case and how they were used to understand teamwork skill development. We then discuss effective team training strategies and explain how they were implemented in the use case to understand their implications for pedagogical modeling. From this exploration, we describe a generic instructional framework recommending effective training strategies for each stage of team development. To inform the development of reusable models, we recommend selecting different team task domains and varying team size to begin researching commonalities and differences in the instructional framework.

This study explores how balanced scorecard format and reputation from environmental performances interact to influence performance evaluations.

Two general options exist for inserting environmental measures into a scorecard: embedded among the four traditional perspectives or grouped in a fifth perspective. Prior balanced scorecard research also assumes negative past environmental performances. In such settings, and when low management communication levels exist on the importance of environmental strategic objectives (a common practitioner scenario), environmental measures receive less decision weight when they are grouped in a fifth scorecard perspective. However, a positive environmental reputation would generate loss aversion concerns with reputation, leading to more decision weight given to environmental measures. Participants (N=138) evaluated performances with scorecards in an experimental design that manipulates scorecard format (four, five-perspectives) and past environmental performance operationalizing reputation (positive, negative).

The environmental reputation valence’s impact is more (less) pronounced when environmental measures are grouped (embedded) in a fifth perspective (among the four traditional perspectives), when the environmental feature of the measures is more (less) salient.

Findings provide the literature with original empirical results that support the popular, but often anecdotal, position of advocating a fifth perspective for environmental measures to help emphasize and promote environmental stewardship within an entity when common low management communication levels exist. Specifically, when positive past environmental performances exist, entities may choose to group environmental performance measures together in a fifth scorecard perspective without risking those measures receiving the discounted decision weight indicated in prior studies.

Since 2002 there has been strategic focus on inclusive tertiary provision as a means of addressing the issues of student groups who have historically not fared well in higher education. Equity groups include Māori, Pasifika and students with disabilities. This chapter charts the terrain of inclusive higher education in Aotearoa through the critical reflections of Kahurangi, a Māori student with a vision impairment. Despite a strategic focus on inclusive provision and Kahurangi’s success his experiences suggest that there is some way to go. The authors argue that given the limited ways in which inclusion and its underpinning theory of disability are theorised inclusive higher educational settings are unlikely to be realised.

The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.

The paper introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.

Information about each source is provided. The paper discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information in the paper may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

This chapter intends to contribute to the debate on the determinants of corporate social responsibility (CSR) and their impact on performance measurement and communication systems. It aims at analyzing the relationship between the reasons why firms adopt CSR and the importance given to voluntary CSR disclosure.

Two main categories of CSR determinants have been identified: the external ones, coming from the environment outside the firm, and the internal determinants, which are linked to some specific characteristics of the enterprise and to the objectives it pursues.

The analyzed sample consists of 120 large Italian manufacturing and nonmanufacturing enterprises. The research hypotheses concerning the relationship between external and internal determinants of CSR and CSR disclosure were verified using an independent sample t-test, evaluating the equal variances of clusters using the Levene’s test.

Main results point out that in companies giving importance to CSR disclosure, the internal drivers are more relevant than the external ones in determining the attitude toward CSR. Among the internal determinants, drivers related to company and management values and ethics are quite relevant.

This study is subject to the limitations that generally apply to cross-sectional survey-based research.

Our research findings show that legitimacy theory represents the most relevant theory in explaining CSR disclosure practices of Italian large firms, as well as the operational implementation of stakeholder theory, such as stakeholder management. On the contrary, institutional theory only partially explains CSR disclosure, with respect to the pressures coming from financial markets.

This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units can have different cointegration ranks and cointegration spaces. Furthermore, the parameters that characterize short-run dynamics and deterministic components are allowed to vary over cross-sectional units. In addition to a noninformative prior, we introduce an informative prior which allows for information about the likely location of the cointegration space and about the degree of similarity in coefficients in different cross-sectional units. A collapsed Gibbs sampling algorithm is developed which allows for efficient posterior inference. Our methods are illustrated using real and artificial data.