Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework

This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting US home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.

The history of technology in education. A comparative study and forecast

Area, launched in 1999 with the Bologna Declaration, has bestowed such a magnitude and unprecedented agility to the transformation process undertaken by European universities. However, the change has been more profound and drastic with regards to the use of new technologies both inside and outside the classroom. This article focuses on the study and analysis of the technology’s history within the university education and its impact on teachers, students and teaching methods. All the elements that have been significant and innovative throughout the history inside the teaching process have been analyzed, from the use of blackboard and chalk during lectures, the use of slide projectors and transparent slides, to the use of electronic whiteboards and Internet nowadays. The study is complemented with two types of surveys that have been performed among teachers and students during the school years 1999 - 2011 in the School of Civil Engineering at the Polytechnic University of Madrid. The pros and cons of each of the techniques and methodologies used in the learning process over the last decades are described, unfolding how they have affected the teacher, who has evolved from writing on a whiteboard to project onto a screen, the student, who has evolved from taking handwritten notes to download information or search the Internet, and the educational process, that has evolved from the lecture to acollaborative learning and project-based learning. It is unknown how the process of learning will evolve in the future, but we do know the consequences that some of the multimedia technologies are having on teachers, students and the learning process. It is our goal as teachers to keep ourselves up to date, in order to offer the student adequate technical content, while providing proper motivation through the use of new technologies. The study provides a forecast in the evolution of multimedia within the classroom and the renewal of the education process, which in our view, will set the basis for future learning process within the context of this new interactive era.

Economics and forecast of energy consumption in NGN networks: the case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”.

Energy Consumption Forecast in 4G Networks: The Case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”. • Next Generation Networks (NGN)  One of the most relevant upcoming ICT development • The role of energy consumption seems mostly absent from the main analysis and the debate on NGN deployment.

Contribution to energy consumption modelling and forecast in next generation access networks

La contribución del sector de las tecnologías de la información y las comunicaciones (TICs) al consumo de energía a nivel global se ha visto incrementada considerablemente en la última década al mismo tiempo que su relevancia dentro de la economía global. Se prevé que esta tendencia continúe debido al uso cada vez más intensivo de estas tecnologías. Una de las principales causas es el tráfico de datos de banda ancha generado por el uso de las redes de telecomunicaciones. De hecho como respuesta a esta demanda de recursos por parte de los usuarios, de la industria de las telecomunicaciones está iniciando el despliegue de las redes de nueva generación. En cualquier caso, el consumo de energía es un factor generalmente ausente del debate sobre el despliegue de estas tecnologías, a pesar de la posible repercusión que pueda llegar a tener en los costes y la sostenibilidad de estos proyectos. A lo largo de este trabajo se desarrollan modelos para evaluar el consumo energético de las redes de acceso de nueva generación (NGAN). Estos servirán tanto para llevar a cabo cálculos en un escenario global estático, como en cualquiera otro que determine la potencial evolución de la red de acceso a lo largo de su despliegue. Estos modelos combinan tres factores: la penetración prospectiva de cada una de las tecnologías de banda ancha analizadas, el tráfico generado por usuario y su futura evolución, y el perfil de consumo de energía de cada uno de los dispositivos de red desplegados. Tras evaluar los resultados derivados de la aplicación de los modelos en el caso demográfico específico de España, se obtienen conclusiones acerca de las diferencias tecnológicas en cuanto al consumo energético, sus implicaciones económicas, y la sensibilidad de los cálculos atendiendo a posibles modificaciones en los valores de referencia de diferentes parámetros de diseño. Se destaca por tanto el efecto en el consumo energético de los desarrollos tecnológicos, tecno-económicos, y de las decisiones en el ámbito regulatorio. Aunque como se ha dicho, se ha ejemplificado el cálculo para un caso particular, tanto los modelos como las conclusiones extraídas se pueden extrapolar a otros países similares.

Estrategia de desarrollo de negocio para el producto Atos RTTF (Real Time Traffic Forecast)

El objetivo del presente proyecto de fin de máster es desplegar la estrategia de negocio completa, desde las declaraciones y premisas hasta la implantación y ejecución, para una solución novedosa de la compañía AtoS. Esta solución se denomina RTTF (Real Time Traffic Forecast), y sus objetivos principales, a alto nivel, son los siguientes: a) Conseguir unas mejores ciudades en la que vivir y trabajar. b) Realizar una gestión de tráfico proactiva para un uso de recursos de las ciudades optimizado. Nuestro planteamiento en este trabajo es, basado en las el módulo de estrategia del máster, diseñar un plan de negocio para desarrollar y potenciar la anterior solución. Para ello también necesitaremos herramientas de otros módulos del máster, como el de marketing, operaciones, o finanzas. Para ello, comenzaremos analizando el entorno desde el punto de vista de la posible receptividad al producto, así como de los posibles competidores, con objeto de posicionar de manera inicial nuestra solución, y reflexionar sobre si ese posicionamiento es el adecuado. Añadiendo también el estudio interno de la compañía y de la propia solución sobre la que versa el proyecto. El principal entregable del presente trabajo será un plan de negocio, con fechas, objetivos y un listado de clientes por orden de prioridad, con el objetivo final de desarrollar la solución.

PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.

On the forecast accuracy and consistency of exchange rate expectations: The Spanish PwC Survey.

We examine the predictive ability and consistency properties of exchange rate expectations for the dollar/euro using a survey conducted in Spain by PwC among a panel of experts and entrepreneurs. Our results suggest that the PwC panel have some forecasting ability for time horizons from 3 to 9 months, although only for the 3-month ahead expectations we obtain marginal evidence of unbiasedness and efficiency in the forecasts. As for the consistency properties of the exchange rate expectations formation process, we find that survey participants form stabilising expectations in the short-run and destabilising expectations in the long- run and that the expectation formation process is closer to fundamentalists than chartists.

The Climate-system Historical Forecast Project: do stratosphere-resolving models make better seasonal climate predictions in boreal winter?

Using an international, multi-model suite of historical forecasts from the World Climate Research Programme (WCRP) Climate-system Historical Forecast Project (CHFP), we compare the seasonal prediction skill in boreal wintertime between models that resolve the stratosphere and its dynamics (high-top') and models that do not (low-top'). We evaluate hindcasts that are initialized in November, and examine the model biases in the stratosphere and how they relate to boreal wintertime (December-March) seasonal forecast skill. We are unable to detect more skill in the high-top ensemble-mean than the low-top ensemble-mean in forecasting the wintertime North Atlantic Oscillation, but model performance varies widely. Increasing the ensemble size clearly increases the skill for a given model. We then examine two major processes involving stratosphere-troposphere interactions (the El Niño/Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO)) and how they relate to predictive skill on intraseasonal to seasonal time-scales, particularly over the North Atlantic and Eurasia regions. High-top models tend to have a more realistic stratospheric response to El Niño and the QBO compared to low-top models. Enhanced conditional wintertime skill over high latitudes and the North Atlantic region during winters with El Niño conditions suggests a possible role for a stratospheric pathway.

An economy with unrealistic indicators: an evaluation of the economic situation in Belarus and a forecast for 2013. OSW Commentary No. 103, 2013-02-20

The macroeconomic results achieved by Belarus in 2012 laid bare the weakness and the inefficiency of its economy. Belarus’s GDP and positive trade balance were growing in the first half of last year. However, this trend was reversed when Russia blocked the scheme of extremely lucrative manipulations in the re-export of Russian petroleum products by Belarus and when the demand for potassium fertilisers fell on the global market. It became clear once again that the outdated Belarusian model of a centrally planned economy is unable to generate sustainable growth, and the Belarusian economy needs thorough structural reforms. Nevertheless, President Alyaksandr Lukashenka consistently continues to block any changes in the system and at the same time expects that the economic indicators this year will reach levels far beyond the possibilities of the Belarusian economy. Therefore, there is a risk that the Belarusian government may employ – as they used to do – instruments aimed at artificially stimulating domestic demand, including money creation. This may upset the relative stability of state finances, which the regime managed to achieve last year. The worst case scenario would see a repeat of what happened in 2011, when a serious financial crisis occurred, forcing Minsk to make concessions (including selling the national network of gas pipelines) to Moscow, its only real source of loans. It thus cannot be ruled out that also this time the only way to recover from the slump will be to receive additional loan support and energy subsidies from Russia at the expense of selling further strategic companies to Russian investors.