Energy and CO2 emission relationships in the NAFTA trading bloc: a multi-regional multi-factor energy input–output approach

The North-America Free Trade Agreement (NAFTA) has brought together the economies of Canada, Mexico, and the US into forming one of the largest trading blocs worldwide (within the top CO₂ emitters). However, the current global protectionist discourse threatens the agreement. This paper analyzes the energy and energy-related CO₂ emission relationships between NAFTA countries in 2014 to gain insights into the climate change implications of current integration and the possible cancelation of the agreement. The analysis is performed with a multi-regional version of the multi-factor energy input–output model. The results show that NAFTA has not built a single integrated energy system, though it has helped reduce energy-related CO₂ emissions. Moreover, if NAFTA is not revoked, further integration would depend on the capacity of the Mexican energy sector to converge to the performance of its trade partners’ energy sectors. Conversely, a broken deal would induce negative environmental externalities.     

The raw material basis of global value chains: allocating environmental responsibility based on value generation

A new approach to allocate environmental responsibility, the ‘value added-based responsibility’ allocation, is presented in this article. This metric allocates total environmental pressures occurring along an international supply chain to the participating sectors and countries according to the share of value added they generate within that specific supply chain. We show that – due to their position in global value chains – certain sectors (e.g. services) and countries (e.g. Germany) receive significantly greater responsibility compared to other allocation approaches. This adds a new perspective to the discussions concerning a fair distribution of mitigation costs among nations, companies and consumers.     

Carbon taxes and the double dividend hypothesis in a recursive-dynamic CGE model for Spain

A carbon tax is potentially a policy that can reduce CO₂ emissions and mitigate climate risks, at lowest economy-wide costs. We develop a dynamic CGE model for Spain to assess the economic and environmental effects of a carbon tax, and test the double dividend (DD) hypothesis. We simulate the impact of three carbon taxes: €10, €20 and €30 per ton of CO₂. For each tax, four ‘revenue recycling’ scenarios are examined: a reduction of taxes on capital, on labor, on value-added tax, and a scenario in which revenues are not recycled. We find a DD for taxes of €10/ton and lower, within five to seven years of implementation. We estimate an annual CO₂ emissions reduction of around 10% with this tax. Under some circumstances, the DD can be achieved for a tax of €20/ton. In any case, recycling revenues to cut pre-existing taxes reduces costs of imposing carbon taxes.     

Do Overconfident Workers Cooperate Less? The Relationship Between Overconfidence and Cooperation in Team Production

The tendency to underestimate others' relative performance compared with one's own is widespread among individuals in all work environments. We examine the relationship between, and the driving forces behind, individual overconfidence and voluntary cooperation in team production. Our experimental data suggest an indirect and gender‐specific link: overconfident men hold more optimistic beliefs about coworkers' cooperativeness than men who lack confidence and are accordingly significantly more cooperative, whereas overconfidence, beliefs, and cooperativeness are not correlated in women. Copyright © 2014 John Wiley & Sons, Ltd.     

Creation of models for calculation of coefficients of terrain passability

Quality & Quantity - The content of this article is a paper about a complex mathematical model of terrain passability which respects geographical and meteorological conditions in terrain and...     

Visual displays: analytical study and applications to graphs and real data

Principal axis methods such as principal component analysis (PCA) and correspondence analysis (CA) are useful for identifying structures in data through interesting planar graphic displays. However, some kinds of data sets can be dealt alternatively with PCA or CA. This paper focuses on methods, such as PCA and CA, and on visual displays. Our aim is to illustrate the implications for a potential user of selecting either method, and its advantages and disadvantages, from an applied point of view. This is a matter covered broadly in textbooks and elsewhere considering theoretical arguments. Our purpose is to contribute to the comparison between these methods, over the same data set, in order to illustrate them for the practitioner. In the first part of this paper we present a novel analytical study of a binary matrix associated with a non-oriented axis-symmetric graph and show that CA outperforms standardized PCA for the reconstitution and visualization of such kind of graphs. In the second part we present a case using real data dealing with the distribution of employees in different economic sectors for the countries of the European Union, analyzed by means of standardized PCA and two-way CA, in order to see the differences between the two methods in practice.     

ASSESSING THE EFFECT OF PUBLIC SUBSIDIES ON FIRM R&D INVESTMENT: A SURVEY

This survey examines the empirical literature on the relationship between public R&D subsidies and private R&D investment over the past five decades. The survey reveals a considerable heterogeneity of empirical results that cannot be explained fully by methodological issues. We aim to provide further explanations of the possible causes of that heterogeneity. In particular, we emphasise a set of issues that, in our view, are critical to understanding the potential effect of public R&D subsidies on private R&D spending. Special attention is paid to the dynamic aspects and composition of firm R&D, the constraints faced by the firm (such as financial constraints), and the amount and source of public subsidies. None of these issues have been investigated in depth. We formulate a set of research assumptions to guide future empirical research in this field.     

Does expenditure in public governance guarantee less corruption? Non-linearities and complementarities of the rule of law

Corruption is an endemic societal problem with profound implications in the development of nations. In combating this issue, cross-national evidence supporting the effectiveness of the rule of law seems at odds with poorly realized outcomes from reforms inspired in the academic literature. This paper provides an explanation for such contradiction. By building a computational approach, we develop three methodological novelties into the empirical study of corruption: (1) modeling government expenditure as a more adequate intervention variable than traditional indicators, (2) generating large within-country variation by means of bottom-up simulations (instead of cross-national data pooling), and (2) accounting for all possible interactions between covariates through a spillover network. Our estimates suggest that, the least developed a country is, the more difficult it is to find the right combination of policies that lead to reductions in corruption. We characterize this difficulty through a rugged landscape that governments navigate when changing the total budget size and the relative expenditure towards the rule of law. Importantly our method helps identifying the—country-specific—policy issues that complement the rule of law in the fight against corruption.