Dominance Statistics: A Simulation Study on the d Statistic

Quality &; Quantity - Cliff (1993) has proposed the use of a measure of effect size alternative to traditionalmean differences: δ {? = Pr(xi1 &;gt; xj2) - Pr(xi1 &;lt; xj2)}which,...     

Measuring Hospital Performance in the Presence of Quasi-Fixed Inputs: An Analysis of Québec Hospitals

This research proposes an approach to measure hospital performance based on a generalization of Banker and Morey (1986) and Førsund (1996). This approach considers quasi-fixed inputs explicitly, calculates their implicit cost, and quantifies returns to scale. The performance measure is decomposed into allocative and technical inefficiencies. Based on a very complete data set of Québec hospitals, we find that significant inefficiencies of up to 17% ($700 CAN million) could have been saved through improved performance. Postestimation analyses that include qualitative measures of care suggest that differences in performance are attributable to differences in management or unobservable quality of care rather than patient case mix.     

Assessment of Interjudge Reliability in the Open-Ended Questions Coding Process

In the process of coding open-ended questions, the evaluation of interjudge reliability is a critical issue. In this paper, using real data, the behavior of three coefficients of reliability among coders, Cohen’s K, Krippendorff’s α and Perreault and Leigh’s I _r are patterned, in terms of the number of judges involved and the categories of answer defined. The outcome underlines the importance of both variables in the valuations of interjudge reliability, as well as the higher adequacy of Perreault and Leigh’s I _r and Krippendorff’s α for marketing and opinion research.     

Micro-level product-market dynamics: Shared knowledge and its relationship to market development

This work draws on consumer and psychology research to explain sociocognitive aspects of product-market dynamics at a higher level of specificity than prior research. The authors extend the field’s understanding of market-shaping shared knowledge through a theory-informed discussion of how shared product knowledge comes to exist and how it changes as product markets develop. They define shared knowledge as the aspects of product representations that are common across the minds of market actors, making it possible for them to understand one another. The authors also discuss ways to track shared knowledge content that is expressed in market narratives. As the characteristics of shared knowledge are explained and linked to stages of product-market development, the authors develop a set of researchable propositions to guide future research. The theoretical arguments and propositions in this article complement extant marketing strategy research by integrating individual-level consumer theory with market evolution models. José Antonio Rosa (jose.rosa@case.edu; Ph.D., University of Michigan) is an assistant professor of marketing at Case Western Reserve University. His research interests include product markets as sociocognitive phenomena, embodied knowledge in consumer and managerial sensemaking, consumer illiteracy and coping, commitment and motivation among members of network marketing organizations, and buying group satisfaction. His research has been published in marketing and management publications, including theJournal of Marketing and theAcademy of Management Journal. Before entering academia, he worked in the automotive and information systems industries. Jelena Spanjol (jspanjol@tamu.edu; Ph.D., University of Illinois) is an assistant professor of marketing at Texas A&M University. Her research interests include product market dynamics, product portfolio management, innovation, sensemaking, and organizational and managerial cognition in marketing strategy. Her research has been published in marketing and management publications, including theJournal of Marketing and several book chapters. Before academia, she worked in the scientific software industry.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

The impact of product diversification strategy on the corporate performance of large Spanish firms

We analyze the impact of product diversification on performance. This topic has been discussed in the literature, and there is no consensus so far as to the significance or the direction of the impact. Performance is measured using Tobin's q for a sample of 103 large, non-financial Spanish firms (1992–1995). Diversification is measured by means of a categorical variable, as suggested by Varadarajan. The principal results indicate that the firms with intermediate levels of product diversification have the highest performance, while the firms with low and high levels of diversification show significantly lower performance, which performance is not significantly different between them.     

Multiple Species Boreal Forests – What Faustmann Missed

Recent research in natural sciences shows that the dynamics in boreal forests are much more complex than what many models traditionally used in forestry economics reflect. This essay analyzes some challenges of accounting for such complexity. It shows that the optimal harvesting strategy for forest owners is history dependent and for some states of the forest, more than one strategy may be optimal.This paper confirms earlier literature on shallow lakes and coral reefs and shows that this kind of phenomena seem much more common than previously thought. They are valid for a wide range of ecosystems that cover large surfaces and they do not depend on the choice of some specific function to model the non-linearity. There are also indications that theses results could be obtained even for resources with concave growth if at least one species with non-linear growth affects their dynamics.     

Endogenous structural change and crisis in a multiple time-scales growth model

The slow and endogenous twist of economic macro-structure makes up an important evolutionary feature of capitalist economies, and may be at the root of structural crisis. In this line, a Goodwinian growth model with increasing returns and profit-sharing that tries to picture a simple scenario of the seventies crisis is considered. It is shown that the exhaustion of the Kaldor-Verdoorn “productivity law” can entail, in a nonlinear framework, a “catastrophic” bifurcation from a “high” to a “low” growth path. Slow/fast dynamical systems then allow one to formalize a multiple time-scales dynamics where the growth path is shaped by the structural framework in which it takes place, but has also a long -un feedback. Structural change and crisis appear as long term and endogenous outcomes.