Factors driving embodied carbon in international trade: a multiregional input–output gravity model

ABSTRACT

Concerns about the effects and consequences of climate change have notably increased in recent decades. Despite large advances in the understanding of this phenomenon, further research into the determinants of gas emissions is necessary, to shed light on the responsibilities of producers and consumers, and their potential contribution to mitigation strategies. This paper studies the trajectories and determinants of carbon embodied in world trade during a period of 15 years. Our methodology relies on a multiregional input–output model, environmentally extended. Drawing on data from the World Input–Output Database, we estimate embodied emissions in bilateral flows. Then, we assess the determinants of CO₂ emissions embodied in trade, combining input–output modelling with trade gravity panel data analysis. This paper offers a methodological approach that explains and quantifies the underlying factors of carbon trade, integrating the production and consumption perspectives and considering the geographical, structural and institutional context of countries.     

Feature selection methods involving support vector machines for prediction of insolvency in non‐life insurance companies

We propose two novel approaches for feature selection and ranking tasks based on simulated annealing (SA) and Walsh analysis, which use a support vector machine as an underlying classifier. These approaches are inspired by one of the key problems in the insurance sector: predicting the insolvency of a non‐life insurance company. This prediction is based on accounting ratios, which measure the health of the companies. The approaches proposed provide a set of ratios (the SA approach) and a ranking of the ratios (the Walsh analysis ranking) that would allow a decision about the financial state of each company studied. The proposed feature selection methods are applied to the prediction the insolvency of several Spanish non‐life insurance companies, yielding state‐of‐the‐art results in the tests performed. Copyright © 2005 John Wiley & Sons, Ltd.     

Developing a tutoring module for presentation of computerized patient management problems

The simulation problem is one of the most commonly used formats in computer-assisted instruction (CAI). In medical education, a patient simulation problem is known as a patient management problem (PMP). A number of computerized PMP systems are currently available. However, to date, there is no record of PMP systems having been developed using artificial intelligence. This is noteworthy since artificial intelligence techniques could help in the generation of more effective and intelligent instructional systems.

This paper analyzes and evaluates existing instructional simulation software in clinical medicine in terms of effective educational design attributes. Components of effective PMP systems thus identified are incorporated into a computerized instructional system which uses artificial intelligence techniques for teaching problem-solving and diagnostic skills to undergraduate medical students.     

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.     

Estimating Krugman’s Economic Geography Model for the Spanish Regions

This paper estimates Krugman’s (J Polit Econ 99:413–499, 1991) economic geography model using data from the Spanish NUTS 3 regions. The econometric formalization endogenously determines wages in a region as a function of income and wages in other regions. The specification adopted also allows us to study the relation between the agglomeration of economic activity, increasing returns and market access. The first result obtained is that the Spanish economy exhibits a spatial wage structure: wages in a region are positively determined by income and wages in neighboring regions. In second place it is found support for the structural relations of the underlying theoretical model, indicating the importance of scale economies and transport costs in shaping the Spanish economic geography.     

Price Discrimination with Private and Imperfect Information

In this paper, I investigate the competitive and welfare effects of the improvements in information accuracy in markets where firms can price discriminate after observing a private and noisy signal about a consumer's brand preference. I show that when firms believe that consumers have a brand preference for them, then they charge more to these consumers, and this price has an inverse U‐shaped relationship with the signal's accuracy. In contrast, the price charged after a disloyal signal has been observed falls as the signal's accuracy rises. While industry profit and overall welfare fall monotonically when price discrimination is based on increasingly more accurate information, the reverse happens to consumer surplus.     

Corporate recidivism in emerging economies

Prior research on corporate misconduct pays extensive attention to single misconduct behaviors. However, little research has addressed recidivism – the repeated behaviors of corporate misconduct. Based on institutional theory and using the context of emerging economies where recidivism plays a considerable role, we propose the path dependency of corporate recidivism and suggest that three influential factors exist: internal preconditioning, inter‐organizational imitation, and the prevailing external evaluation. Our event history analysis of 1,036 listed companies in China over the period 2001–2008 statistically confirms our hypotheses. We conclude the paper by outlining the implications for both theory and practice.