Modelling multilateral trade resistance in a gravity model with exchange rate regimes

In estimating a gravity model it is essential to analyse not just bilateral trade resistance, the barriers to trade between a pair of countries, but also multilateral trade resistance (MTR), the barriers to trade that each country faces with all its trading partners. Without correctly modelling MTR, it is impossible either to obtain accurate estimates of the effects on trade of exchange rate regimes and other variables or to perform accurate counterfactual simulations of trade patterns under other assumptions about exchange rate regimes or other variables. In this paper we implement a number of different ways of modelling MTR – both for a standard gravity model and for an extended model which includes a full range of bilateral exchange rate regimes – notably several variants of the technique developed by Baier and Bergstrand (2006), which turn out to produce broadly similar results. We then illustrate our preferred approach by carrying out simulations of the effects of the creation of an East African currency union and the effects of a withdrawal from EMU by Italy.gravity, geography, trade, exchange rate regime, currency union, transactions costs, multilateral trade resistance.

Undergraduate students: interactive, online experiences and ePortfolio development

Results of a previous study by the authors into the perceived value and potential of ePortfolios to assist undergraduate students indicated that technology was an important aspect of their everyday lives. It was also felt it to be beneficial to their learning. A large percentage of students were found to be using digital techniques to store evidence of their learning, and were also using interactive, online tools in their learning activities. There was, however, little reported structured use of ePortfolio development in their learning. Students acknowledged they were discovering for themselves the value of online technologies in learning. This paper focuses on student skills and experiences of online tools on entry to university, and considers their experience of ePortfolio development using the Wordpress personal publishing platform. Results indicate that students’ skill level of online, interactive tools was high and wide-ranging. Although previous experience of using these tools was unstructured and informal, ePortfolio creation was found to be an engaging, relevant and worthwhile activity. The ePortfolio development exercise also provided an experiential learning experience, and had a positive effect on students’ attitudes to learning

Exchange rate regimes and trade

A ‘new version’ gravity model, is used to estimate the effect of a full range of de facto exchange rate regimes, as classified by Reinhart and Rogoff (2004), on bilateral trade. The results indicate that, while participation in a common currency union is typically strongly ‘pro-trade’– as first suggested by Rose (2000) – other exchange rate regimes which lower the exchange rate uncertainty and transactions costs associated with international trade between countries are significantly more pro-trade than the default regime of a ‘double float’. They suggest that the direct and indirect effects of exchange rate regimes on uncertainty and transactions costs tend to outweigh the trade-diverting substitution effects. In addition, there is evidence that membership of different currency unions by two countries has pro-trade effects, which can be understood in terms of a large indirect effect on transactions costs. Tariff-equivalent monetary barriers associated with each of the exchange rate regimes are also calculatedgravity, geography, exchange rate regime, currency union, transactions costs, tariff-equivalent barriers

Finance for development and islamic banking

Islamic banking, where fixed interest contracts are banned, needs if it is to be successful to operate within a type of financial system in which bank-industry relationships are sufficiently close and pervasive for profit- and loss-sharing arrangements to be acceptable to both sides. However, the creation of such a business culture is likely to be difficult

Cockpits to classrooms: the unique challenges faced by postgraduate students serving in the military

The University of Lincoln in the UK lies in close proximity to several military airbases. The School of Computer Science at the University of Lincoln offers taught postgraduate programmes designed for serving military personnel, delivered in partnership with the education department at one of those airbases. Almost without exception, our military students require interruptions and/or extensions to their studies before they are able to complete their programme. Some students have been ‘on our books’ for a number of years and it is possible that some of them may never complete their studies. This paper examines some of the reasons why military students find it so difficult to complete their studies and how Higher Education Institutions (HEIs) might improve the ways in which they support military students. The theoretical underpinning of the paper draws on several theories of motivation and also uses Schlossberg’s, [1], (2005) ideas of adult transitions and support to analyse the unique challenges faced by students in the military. This work is informed by the results of a survey of military students; questions in the survey were designed based on the Schlossberg 4S transition model. This survey was followed up with a number of semi-structured interviews conducted with selected respondents. The initial results of this research appear quite revealing. For example, military students are used to living and working in extremely disciplined environments where high standards and strict timescales must be strictly adhered to. Not doing so can, in many cases, risk life and limb. When presented with the more open environments that self-directed study in a HEI offer, these same students suffer a lack of focus and direction which has a detrimental impact on their engagement. By promoting independent learning and directing ownership of the process of study to the student, it may be that we inadvertently hinder them in their pursuit of higher qualifications. Respondents report that some semblance of ‘military discipline’ is preferred when it comes to things like hand-in dates and the maximum time allowed to complete the programme. Military students are justifiably proud of all that they have achieved in their military service. In some cases, however, this may lead them to the unrealistic belief that a Master’s degree will naturally follow or automatically become theirs by right. Some military students may not readily accept the discovery, early on in the programme, that working at Master’s level requires new and different skills. One challenge for programme providers, therefore, is to find ways to demonstrate the benefits that come from modifying ingrained ways of thinking. One way of doing this is by helping military students to develop and apply these new skills in the analysis of the real problems that they encounter in their military life. Keywords: Schlossberg, transition, military, postgraduate, United Kingdom

Text analysis of user-generated contents for health-care applications: case study on smoking status classification

Text mining techniques have demonstrated a potential to unlock significant patient health information from unstructured text. However, most of the published work has been done using clinical reports, which are difficult to access due to patient confidentiality. In this paper, we present an investigation of text analysis for smoking status classification from User-Generated Contents (UGC), such as online forum discussions. UGC are more widely available, compared to clinical reports. Based on analyzing the properties of UGC, we propose the use of Linguistic Inquiry Word Count (LIWC) an approach being used for the first time for such a health-related task. We also explore various factors that affect the classification performance. The experimental results and evaluation indicate that the forum classification performs well with the proposed features. It has achieved an accuracy of up to 75% for smoking status prediction. Furthermore, the utilized features set is compact (88 features only) and independent of the dataset size