Financial Futures Markets and Their Impact on the Real Economy in Middle and Low Income Countries

This project analyses the influence of the futures market on middle and low income countries. In it, I attempt to show that investments made by large investment funds in this market, as well as by certain pension plans, bring major consequences whose effects are more evident in less developed countries. The cornerstones of the work are as follows; to attempt to see the existing relationship between the commodity futures market and its underlying assets; analysing products such as wheat, rice and corn in-depth, because these are the most basic foodstuffs at a global level; to determine how an increase in trading in these markets can affect the lives of people in the poorest countries; to analyse investor concern regarding the consequences that their investments may have. Throughout the project we will see how large speculators use production forecasting models to determine the shortage of a commodity in order to take a position in the futures market to profit from it. In addition we will see how an increase in trading in this market causes an increase in the price of the underlying asset in the spot market. As for investor concern, I can say it is negligible, but the idea of running pension plans or investment funds that follow some social criteria has been welcomed by those interviewed, which makes me think that different legislation is possible. This legislation will only come into existence if it is demanded by the people. A fact that now becomes complicated because without a minimum financial basis, they cannot even know how the large investment funds trade with hunger in the world. The day when most people understand how large speculators profit from famine will be the day to put pressure on governments to begin to put limits on speculation. This makes financial awareness necessary in order to achieve a curb in excessive speculation.

Prices and the Real Exchange Rate in Hong Kong: 1985-2006

This paper has been presented at the XIII Encuentros de Economía Aplicada, Sevilla, Spain, 2010.

On the Informational Role of Term Structure in the U.S. Monetary Policy Rule

This paper uses a structural approach based on the indirect inference principle to estimate a standard version of the new Keynesian monetary (NKM) model augmented with term structure using both revised and real-time data. The estimation results show that the term spread and policy inertia are both important determinants of the U.S. estimated monetary policy rule whereas the persistence of shocks plays a small but significant role when revised and real-time data of output and inflation are both considered. More importantly, the relative importance of term spread and persistent shocks in the policy rule and the shock transmission mechanism drastically change when it is taken into account that real-time data are not well behaved.

The Effect of Data Revisions on the Basic New Keynesian Model

This paper proposes an extended version of the basic New Keynesian monetary (NKM) model which contemplates revision processes of output and inflation data in order to assess the importance of data revisions on the estimated monetary policy rule parameters and the transmission of policy shocks. Our empirical evidence based on a structural econometric approach suggests that although the initial announcements of output and inflation are not rational forecasts of revised output and inflation data, ignoring the presence of non well-behaved revision processes may not be a serious drawback in the analysis of monetary policy in this framework. However, the transmission of inflation-push shocks is largely affected by considering data revisions. The latter being especially true when the nominal stickiness parameter is estimated taking into account data revision processes.

Role of G protein coupled inwardly rectifier K+ channels (GIRK) on the neurobiology depression

353 págs.

On the economics of the "meeting competition defense" under the Robinson-Patman Act

Documento de trabajo

Keep an "eye" on the text: The Use of Self-mention in the Academic Writing of Experts

One of the most controversial inquiries in academic writing is whether it is admissible to use first person pronouns in a scientific paper or not. Many professors discourage their students from using them, rather favoring a more passive tone, and thus causing novices to avoid inserting themselves into their texts in an expert-like manner. Abundant research, however, has recently attested that negotiation of identity is plausible in academic prose, and there is no need for a paper to be void of an authorial identity. Because in the course of the English Studies Degree we have received opposing prompts in the use of I, the aim of this dissertation is to throw some light upon this vexed issue. To this end, I compiled a corpus of 16 Research Articles (RAs) that comprises two sub-corpora, one featuring Linguistics RAs and the other one Literature RAs, and each, in turn, consists of articles written by American and British authors. I then searched for real occurrences of I, me, my, mine, we, us, our and ours, and studied their frequency, rhetorical functions and distribution along each paper. The results obtained certainly show that academic writing is no longer the faceless prose that it used to be, for I is highly used in both disciplines and varieties of English. Concerning functions, the most typically used roles were the use of I to take credit for the writer’s research process, and also those involving plural forms. With respect to the spatial disposition, all sections welcomed first person pronouns, but the Method and the Results/Discussion sections seem to stimulate their appearance. On the basis of these findings, I suggest that an L2 writing pedagogy that is mindful not only of the language proficiency, but also of the students’ own identity may have a beneficial effect on the composition of their texts.

Contributions to High-Throughput Computing Based on the Peer-to-Peer Paradigm

XII, 116 p.

Feedback on the Rate and Depth of Chest Compressions during Cardiopulmonary Resuscitation Using Only Accelerometers

Background Quality of cardiopulmonary resuscitation (CPR) is key to increase survival from cardiac arrest. Providing chest compressions with adequate rate and depth is difficult even for well-trained rescuers. The use of real-time feedback devices is intended to contribute to enhance chest compression quality. These devices are typically based on the double integration of the acceleration to obtain the chest displacement during compressions. The integration process is inherently unstable and leads to important errors unless boundary conditions are applied for each compression cycle. Commercial solutions use additional reference signals to establish these conditions, requiring additional sensors. Our aim was to study the accuracy of three methods based solely on the acceleration signal to provide feedback on the compression rate and depth. Materials and Methods We simulated a CPR scenario with several volunteers grouped in couples providing chest compressions on a resuscitation manikin. Different target rates (80, 100, 120, and 140 compressions per minute) and a target depth of at least 50 mm were indicated. The manikin was equipped with a displacement sensor. The accelerometer was placed between the rescuer's hands and the manikin's chest. We designed three alternatives to direct integration based on different principles (linear filtering, analysis of velocity, and spectral analysis of acceleration). We evaluated their accuracy by comparing the estimated depth and rate with the values obtained from the reference displacement sensor. Results The median (IQR) percent error was 5.9% (2.8-10.3), 6.3% (2.9-11.3), and 2.5% (1.2-4.4) for depth and 1.7% (0.0-2.3), 0.0% (0.0-2.0), and 0.9% (0.4-1.6) for rate, respectively. Depth accuracy depended on the target rate (p < 0.001) and on the rescuer couple (p < 0.001) within each method. Conclusions Accurate feedback on chest compression depth and rate during CPR is possible using exclusively the chest acceleration signal. The algorithm based on spectral analysis showed the best performance. Despite these encouraging results, further research should be conducted to asses the performance of these algorithms with clinical data.