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.     

New methods of evaluating physical demand at work areas

The manufacturer's requirement of increasing productivity results in the need to design work stations that are increasingly more effective and specialized. However, this procedure can bring about an overloading of the worker, a lack of motivation, and, consequently, a reduction in productivity.Ergonomics adapts the work station to the worker with the object of improving his welfare and satisfaction at his post. One aspect that this science concerns itself with is the evaluation of physical demands connected to productive tasks. Mechanical movements are also studied in order to perform tasks efficiently.We here propose a new method of physical demand analysis that determines the risk factor for muscular skeletal lesion. This method uses, as a base, the system of predetermined times, MTM-UAS. It includes a computer system that allows us to easily analyse the operations at a work station and generates charts similar to those of UAS, but, instead of times, it measures the quantity of mechanical work necessary for each movement.The information that the method provides can be used by different divisions within companies in making decisions about improvements at work stations.     

Determining factors in entry choice for international expansion. The case of the Spanish hotel industry

The hotel sector, as a service industry where it is possible to separate capital investment from management skills, is a clear example of how internationalisation can be modelled without shareholding involvement through foreign direct investment. This paper is an empirical examination of the key factors influencing the decision process carried out by Spanish hotel companies in choosing an entry mode for international expansion. The main objective is to verify whether the concepts derived from the transaction-cost, agency and the strategic theories of organisational capability and knowledge in companies can really explain the mode of foreign expansion employed by the Spanish hotel sector. This study will allow comparison of findings on holiday resort hotel chains with other analyses on the international hotel industry.     

Moore's Law and the Semiconductor Industry: A Vintage Model*

In this paper we develop a vintage model to gain a better understanding of the semiconductor industry and its role in recent U.S. productivity gains. Unlike previous work, in our model the observed price declines of individual chips are driven by the introduction of better vintages rather than by learning economies. Dominated chips, nonetheless, continue to be produced, for a time, due to sunk investments in chip‐specific production equipment. The model lends partial support to Jorgenson's hypothesis that an exogenous increase in Moore's Law could have generated the more rapid price declines, and faster productivity growth, seen after 1995.     

The Impact of Mexico's Retraining Program on Employment and Wages

This article analyzes the impact and effectiveness of the Mexicanlabor retraining program for unemployed and displaced workers—Programade Becas de Capacitación para Trabajadores (PROBECAT).The strategy followed is to compare the post-training labormarket experiences of trainees with those of a comparison group—amatched sample of unemployed individuals who were eligible for,but did not participate in, PROBECAT. The results of this exercisesuggest that participation in PROBECAT reduced the mean durationof unemployment for both men and women trainees and increasedthe monthly earnings of men, but not of women. The results alsoindicate that the post-training earnings effect varied systematicallyby level of education attained, with the largest earnings increases(of about 28 to 37 percent) found for men with six to twelveyears of education.     

Stochastic Models of Implied Volatility Surfaces

We propose a market–based approach to the modelling of implied volatility, in which the implied volatility surface is directly used as the state variable to describe the joint evolution of market prices of options and their underlying asset. We model the evolution of an implied volatility surface by representing it as a randomly fluctuating surface driven by a finite number of orthogonal random factors. Our approach is based on a Karhunen–Loeve decomposition of the daily variations of implied volatilities obtained from market data on SP500 and DAX options.
We illustrate how this approach extends and improves the accuracy of the well–known 'sticky moneyness' rule used by option traders for updating implied volatilities. Our approach gives a justification for the use of 'Vegas' for measuring volatility risk and provides a decomposition of volatility risk as a sum of independent contributions from empirically identifiable factors.
(J.E.L.: G130, C14, C31).     

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.