Linguistic Diversity and Its Impact on Economic Policies and Political Decisions

The paper addresses the issue of linguistic diversity and its impact on economic policy and political decisions. Importance of the topic is illustrated by examination of optimal sets of official languages in the European Union. It is shown that alternative estimation methods of language disenfranchisement alter the order in which the languages enter the list of the official ones. Also, we present an overview of gametheoretic models of language acquisition, where individuals weigh costs and benefits of studying new languages. These models are used to predict actual distribution of language skills in a society and to compare it with the first-best outcome. The paper ends with estimation of our predictions on the basis of empirical analysis of European data.Game theory, linguistic models, communication benefits, costs of studying, official languages of the European Union, Nash equilibrium, public efficiency

"Come Together!": Interactions of Language Networks and Multilingual Communities on Twitter

Emerging tools and methodologies are providing insight into the factors that promote the propagation of information in online social networks following significant activities, such as high-profile international social or societal events. This paper presents an extensible approach for analysing how different language communities engage and interact on the social networking platform Twitter via an analysis of the Eurovision Song Contest held in Stockholm, Sweden, in May 2016. By utilising language information from user profiles (N=1,226,959) and status updates (N=7,926,746) to identify and categorise communities, our approach is able to categorise these interactions, as well as construct network graphs to provide further insight on these multilingual communities. The results show that multilingualism is positively correlated with activity whilst negatively correlated with posting in the user’s own language

A Proposal for the Attribution of Market Leakage to CDM Projects

Economic models suggest that in many cases, market leakage rates of greenhouse gas abatement reach the two-digit percentage range. Consequently, the Marrakesh Accords require Clean Development Mechanism (CDM) projects to account for leakage. Despite this, most project proponents neglect market leakage for their project, because the influence of an individual project on market prices seems to be negligible. Insufficient leakage accounting is facilitated by a lack of theories and applicable proposals regarding the quantification and attribution of leakage effects. The aim of this paper is to develop a proposal for the attribution of market leakage effects to CDM projects. To this purpose, we identify the transmission mechanisms for CDM project leakage, investigate the current practice of leakage accounting, and analyse alternative attribution methods for leakage effects that are transmitted through price changes. We find that project-specific approaches must fail to take account of such leakage effects. Consequently, we propose to estimate aggregate market leakage effects and attribute them proportionally to individual projects. Our proposal is based on commodity-specific leakage factors which can be applied by project developers to any emission reductions that are associated with a project's leakage-relevant demand or supply changes. The proposal is conservative, equitable, incentive compatible and applicable at manageable costs

Modelling Dynamic Conditional Correlations in WTI Oil Forward and Futures Returns

This paper estimates the dynamic conditional correlations in the returns on WTI oil one-month forward prices, and one-, three-, six-, and twelve-month futures prices, using recently developed multivariate conditional volatility models. The dynamic correlations enable a determination of whether the forward and various futures returns are substitutes or complements, which are crucial for deciding whether or not to hedge against unforeseen circumstances. The models are estimated using daily data on WTI oil forward and futures prices, and their associated returns, from 3 January 1985 to 16 January 2004. At the univariate level, the estimates are statistically significant, with the occasional asymmetric effect in which negative shocks have a greater impact on volatility than positive shocks. In all cases, both the short- and long-run persistence of shocks are statistically significant. Among the five returns, there are ten conditional correlations, with the highest estimate of constant conditional correlation being 0.975 between the volatilities of the three-month and six-month futures returns, and the lowest being 0.656 between the volatilities of the forward and twelve-month futures returns. The dynamic conditional correlations can vary dramatically, being negative in four of ten cases and being close to zero in another five cases. Only in the case of the dynamic volatilities of the three-month and six-month futures returns is the range of variation relatively narrow, namely (0.832, 0.996). Thus, in general, the dynamic volatilities in the returns in the WTI oil forward and future prices can be either independent or interdependent over time