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.     

Facilitating Global Organizational Learning in Product Development at Whirlpool Corporation

The challenges of leveraging learning about product development in a global company are complex. Whirlpool Corporation is addressing these challenges, using a multidimensional strategy that couples work in advanced products and product development with organization development and training. Deborah Durate and Nancy Snyder describe how Whirlpool has implemented training, best practices conferences, and programs focused on enhancing the performance of product development teams to facilitate learning after product development efforts and to leverage that learning on a global basis. Programs and processes are described, and lessons learned as well as guidelines for development are offered.     

Proportionate Growth and the Theoretical Foundations of Financial Ratios

The article proposes a theoretical framework for understanding financial ratios, showing that the multiplicative character of the financial variables from which financial ratios are constructed is a necessary condition of valid ratio usage, not just an assumption supported by evidence. Also, by assuming that firm size is a measurable statistical effect, the article offers an informed reappraisal of the limitations of financial ratios, particularly the well–known limitation of proportionality. The article is divided into two parts, one where ratio components are viewed as deterministic vari– ables and the other where they are random. Such an approach allows the characteristics of ratios to be more easily understood before generalizing the relationship between ratio components to encompass randomness. In the second part, when variability introduced by firm size is treated as a random effect, it is shown that if the accounting variables Y and X used to calculate a financial ratio Y/X are exponential Brownian motion, and if continuous growth rates are equal and proportionate to firm size, this may lead to ratios which are asymmetric but which do not necessarily drift.     

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.     

The structural transformation and aggregate productivity in Portugal

We document the substantial process of structural transformation—the reallocation of labor between agriculture, manufacturing, and services—and aggregate productivity growth undergone by Portugal between 1956 and 1995. We assess the quantitative role of sectoral labor productivity in accounting for these processes. We calibrate a model of the structural transformation to data for the United States and use the model to gain insight into the factors driving the structural transformation and aggregate productivity growth in Portugal. The model implies that Portugal features low and roughly constant relative productivity in agriculture and services (around 22%) and a modest but growing relative productivity in manufacturing (from 44 to 110%). We find that productivity growth in manufacturing accounts for most of the reduction of the aggregate productivity gap with the United States and that a further closing of this gap can only be accomplished via improvements in the relative productivity of services. This paper was written while the authors were affiliated with the Federal Reserve Bank of Richmond. We would like to thank the editor, two anonymous referees, and participants at the Third Conference on Portuguese Economic Development in the European Context organized by the Bank of Portugal for their comments. All errors are our own.     

Testing the conflict-performance assumption in business-to-business relationships

There is little empirical research published testing the interdependency between conflict in business-to-business relationships and commercial performance. The “conflict-performance assumption”—all other factors being equal, relationships where conflict is low will outperform relationships where conflict levels are higher—remains central in the marketing channels' literature despite insufficient and contradictory empirical evidence. There are several explanations for the lack of a clear relationship between conflict and performance. Rosenbloom [J. Mark. 37 (1973) 26] theorises that the relationship between conflict and channel performance follows an inverted U-shaped curve, where conflict is most productive at moderate levels and least productive at very low or high levels. Others have argued for a simpler, linear relationship between conflict and performance, usually negative in nature. Various theories about the conflict-performance relationship are empirically tested in a large marketing channel, using a number of dyadic and monadic measures of conflict (latent, perceived, and affective) and two objective measures of performance (effectiveness and efficiency). A linear model (performance declining as conflict increases) is adequate to explain the relationship between dyadic measures of both perceived and affective conflict and channel effectiveness. A threshold model is found to be superior to a linear model in explaining the relationship between dyadic measures of perceived and affective conflict and efficiency. Conflict increases slowly as efficiency falls until a threshold is reached when conflict escalates. Practical implications include that companies need to consider whether performance criteria affecting efficiency are as important to their business partners as those affecting effectiveness. If they are not, then business partners should be rewarded for meeting any such criteria that are more important to the one side of a relationship dyad than to the other.     

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.