An analysis of economic and social development in Barbados: a model for Small Island Developing States

Includes bibliography

Essays on the Empirical Analysis of Economic and Political Development in Sub-Saharan Africa

In Sub-Saharan Africa, non-democratic events, like civil wars and coup d'etat, destroy economic development. This study investigates both domestic and spatial effects on the likelihood of civil wars and coup d'etat. To civil wars, an increase of income growth is one of common research conclusions to stop wars. This study adds a concern on ethnic fractionalization. IV-2SLS is applied to overcome causality problem. The findings document that income growth is significant to reduce number and degree of violence in high ethnic fractionalized countries, otherwise they are trade-off. Income growth reduces amount of wars, but increases its violent level, in the countries with few large ethnic groups. Promoting growth should consider ethnic composition. This study also investigates the clustering and contagion of civil wars using spatial panel data models. Onset, incidence and end of civil conflicts spread across the network of neighboring countries while peace, the end of conflicts, diffuse only with the nearest neighbor. There is an evidence of indirect links from neighboring income growth, without too much inequality, to reduce the likelihood of civil wars. To coup d'etat, this study revisits its diffusion for both all types of coups and only successful ones. The results find an existence of both domestic and spatial determinants in different periods. Domestic income growth plays major role to reduce the likelihood of coup before cold war ends, while spatial effects do negative afterward. Results on probability to succeed coup are similar. After cold war ends, international organisations seriously promote democracy with pressure against coup d'etat, and it seems to be effective. In sum, this study indicates the role of domestic ethnic fractionalization and the spread of neighboring effects to the likelihood of non-democratic events in a country. Policy implementation should concern these factors.

Financial analysis of various strategies for the control of Neospora caninum in dairy cattle in Switzerland

The present study was conducted to estimate the direct losses due to Neospora caninum in Swiss dairy cattle and to assess the costs and benefits of different potential control strategies. A Monte Carlo simulation spreadsheet module was developed to estimate the direct costs caused by N. caninum, with and without control strategies, and to estimate the costs of these control strategies in a financial analysis. The control strategies considered were "testing and culling of seropositive female cattle", "discontinued breeding with offspring from seropositive cows", "chemotherapeutical treatment of female offspring" and "vaccination of all female cattle". Each parameter in the module that was considered to be uncertain, was described using probability distributions. The simulations were run with 20,000 iterations over a time period of 25 years. The median annual losses due to N. caninum in the Swiss dairy cow population were estimated to be euro 9.7 million euros. All control strategies that required yearly serological testing of all cattle in the population produced high costs and thus were not financially profitable. Among the other control strategies, two showed benefit-cost ratios (BCR) >1 and positive net present values (NPV): "Discontinued breeding with offspring from seropositive cows" (BCR=1.29, NPV=25 million euros ) and "chemotherapeutical treatment of all female offspring" (BCR=2.95, NPV=59 million euros). In economic terms, the best control strategy currently available would therefore be "discontinued breeding with offspring from seropositive cows".

A linked data approach to sentiment and emotion analysis of twitter in the financial domain

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities or providers, and complements existing initiatives such as FIBO. The ap- proach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.