The causal relationships in mean and variance between stock returns and foreign institutional investment in India

This paper examines the causalities in mean and variance between stock returns and Foreign Institutional Investment (FII) in India. The analysis in this paper applies the Cross Correlation Function approach from Cheung and Ng (1996), and uses daily data for the timeframe of January 1999 to March 2008 divided into two periods before and after May 2003. Empirical results showed that there are uni-directional causalities in mean and variance from stock returns to FII flows irrelevant of the sample periods, while the reverse causalities in mean and variance are only found in the period beginning with 2003. These results point to FII flows having exerted an impact on the movement of Indian stock prices during the more recent period.

Effectiveness of the monetary policy framework in present-day India : have financial variables functioned as useful policy indicators

In April 1998, the RBI, the Indian central bank, formally announced a shift in its policy framework from monetary targeting to a multiple indicator approach, and since then, under this framework, the bank has considered a range of economic and financial variables as policy indicators for drawing policy perspectives. This paper aims to examine the effectiveness of this current policy framework in India by analyzing the causal relationships of each indicator variable on the objective variables. The results reveal that, except for bank credit, all indicator variables considered in this study have a causal relationship with at least either output or price level, suggesting that most preannounced economic and financial variables have served as useful policy indicators under the multiple indicator approach.

Infrastructure development and economic growth in China

China is the fastest growing country in the world for last few decades and one of the defining features of China's growth has been investment-led growth. China's sustained high economic growth and increased competitiveness in manufacturing has been underpinned by a massive development of physical infrastructure. In this context, we investigate the role of infrastructure in promoting economic growth in China for the period 1975 to 2007. Overall, the results reveal that infrastructure stock, labour force, public and private investments have played an important role in economic growth in China. More importantly, we find that Infrastructure development in China has significant positive contribution to growth than both private and public investment. Further, there is unidirectional causality from infrastructure development to output growth justifying China's high spending on infrastructure development since the early nineties. The experience from China suggests that it is necessary to design an economic policy that improves the physical infrastructure as well as human capital formation for sustainable economic growth in developing countries.

Chapter 2 Equilibrium locations of upstream and downstream firms

This paper explores the interaction between upstream firms and downstream firms in a two-region general equilibrium model. In many countries, lower tariff rates are set for intermediate manufactured goods and higher tariff rates are set for final manufactured goods. The derived results imply that such settings of tariff rates tend to preserve a symmetric spread of upstream and downstream firms, and continuing tariff reduction may cause core-periphery structures. In the case in which the circular causality between upstream and downstream firms is focused as agglomeration forces, the present model is fully solved. Thus, we find that (1) the present model displays, at most, three interior steady states, (2) when the asymmetric steady-states exist, they are unstable and (3) location displays hysteresis when the transport costs of intermediate manufactured goods are sufficiently high.

Central bank intervention and exchange rate behaviour : empirical evidence for India

This paper examines the causal relationship between central bank intervention and exchange returns in India. Using monthly data from December 1997 to December 2011, the empirical results derived from the CCF approach of Cheung and Ng (1996) suggest that there is causality-in-variance from exchange rate returns to central bank intervention, but not vice versa. These findings are robust in the sense that they hold in cases where the returns were measured from either the spot rate or the forward rate. Therefore, the results of this paper suggest that the Indian central bank has intervened in the foreign exchange market to respond to exchange rate volatility, although the volatility has not been influenced by central bank intervention in the form of net purchases of foreign currency in the market.

Search, matching, and self-organization of a marketplace

In many developing countries, clusters of small shops are the typical market-place. We investigate an economic model in which, between buyers and sellers in a marketplace, a circular causality including the search process produces agglomeration forces, given the initial location of the marketplace location exogenously in a linear city. We conclude that initial number of buyers and sellers is important in forming a large marketplace.

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Aportación de técnicas geoespaciales para la determinación de los niveles de referencia de la deforestación y la degradación de bosques en el ámbito de proyectos REDD. análisis de factores de causalidad subyacentes y directos

La pérdida de bosques en la Tierra, principalmente en ecosistemas amazónicos, es un factor clave en el proceso del cambio climático. Para revertir esta situación, los mecanismos REDD (Reducing Emission from Deforestation and forest Degradation) están permitiendo la implementación de actividades de protección del clima a través de la reducción de emisiones por deforestación evitada, según los esquemas previstos en el Protocolo de Kioto. El factor técnico más crítico en un proyecto REDD es la determinación de la línea de referencia de emisiones, que define la expectativa futura sobre las emisiones de CO2 de origen forestal en ausencia de esfuerzos adicionales obtenidos como consecuencia de la implementación del programa REDD para frenar este tipo de emisiones. La zona del estudio se ubica en la región de San Martín (Perú), provincia cubierta fundamentalmente por bosques tropicales cuyas tasas de deforestación son de las más altas de la cuenca amazónica. En las últimas décadas del siglo XX, la región empezó un acelerado proceso de deforestación consecuencia de la integración vial con el resto del país y la rápida inmigración desde zonas rurales en busca de nuevas tierras agrícolas. Desde el punto de vista de la investigación llevada a cabo en la tesis doctoral, se pueden destacar dos líneas: 1. El estudio multitemporal mediante imágenes de satélite Landsat 5/TM con el propósito de calcular las pérdidas de bosque entre períodos. El estudio multitemporal se llevó a cabo en el período 1998-2011 utilizando imágenes Landsat 5/TM, aplicando la metodología de Análisis de Mezclas Espectrales (Spectral Mixtures Analysis), que permite descomponer la reflectancia de cada píxel de la imagen en diferentes fracciones de mezcla espectral. En este proceso, las etapas más críticas son el establecimiento de los espectros puros o endemembers y la recopilación de librerías espectrales adecuadas, en este caso de bosques tropicales, que permitan reducir la incertidumbre de los procesos. Como resultado de la investigación se ha conseguido elaborar la línea de referencia de emisiones histórica, para el período de estudio, teniendo en cuenta tanto los procesos de deforestación como de degradación forestal. 2. Relacionar los resultados de pérdida de bosque con factores de causalidad directos e indirectos. La determinación de los procesos de cambio de cobertura forestal utilizando técnicas geoespaciales permite relacionar, de manera significativa, información de los indicadores causales de dichos procesos. De igual manera, se pueden estimar escenarios futuros de deforestación y degradación de acuerdo al análisis de la evolución de dichos vectores, teniendo en cuenta otros factores indirectos o subyacentes, como pueden ser los económicos, sociales, demográficos y medioambientales. La identificación de los agentes subyacentes o indirectos es una tarea más compleja que la de los factores endógenos o directos. Por un lado, las relaciones causa – efecto son mucho más difusas; y, por otro, los efectos pueden estar determinados por fenómenos más amplios, consecuencia de superposición o acumulación de diferentes causas. A partir de los resultados de pérdida de bosque obtenidos mediante la utilización de imágenes Landsat 5/TM, se investigaron los criterios de condicionamiento directos e indirectos que podrían haber influido en la deforestación y degradación forestal en ese período. Para ello, se estudiaron las series temporales, para las mismas fechas, de 9 factores directos (infraestructuras, hidrografía, temperatura, etc.) y 196 factores indirectos (económicos, sociales, demográficos y ambientales, etc.) con, en principio, un alto potencial de causalidad. Finalmente se ha analizado la predisposición de cada factor con la ocurrencia de deforestación y degradación forestal por correlación estadística de las series temporales obtenidas. ABSTRACT Forests loss on Earth, mainly in Amazonian ecosystems, is a key factor in the process of climate change. To reverse this situation, the REDD (Reducing Emission from Deforestation and forest Degradation) are allowing the implementation of climate protection activities through reducing emissions from avoided deforestation, according to the schemes under the Kyoto Protocol. Also, the baseline emissions in a REDD project defines a future expectation on CO2 emissions from deforestation and forest degradation in the absence of additional efforts as a result of REDD in order to stop these emissions. The study area is located in the region of San Martín (Peru), province mainly covered by tropical forests whose deforestation rates are the highest in the Amazon basin. In the last decades of the twentieth century, the region began an accelerated process of deforestation due to road integration with the rest of the country and the rapid migration from rural areas for searching of new farmland. From the point of view of research in the thesis, we can highlight two lines: 1. The multitemporal study using Landsat 5/TM satellite images in order to calculate the forest loss between periods. The multitemporal study was developed in the period 1998-2011 using Landsat 5/TM, applying the methodology of Spectral Mixture Analysis, which allows decomposing the reflectance of each pixel of the image in different fractions of mixture spectral. In this process, the most critical step is the establishment of pure spectra or endemembers spectra, and the collecting of appropriate spectral libraries, in this case of tropical forests, to reduce the uncertainty of the process. As a result of research has succeeded in developing the baseline emissions for the period of study, taking into account both deforestation and forest degradation. 2. Relate the results of forest loss with direct and indirect causation factors. Determining the processes of change in forest cover using geospatial technologies allows relating, significantly, information of the causal indicators in these processes. Similarly, future deforestation and forest degradation scenarios can be estimated according to the analysis of the evolution of these drivers, taking into account other indirect or underlying factors, such as economic, social, demographic and environmental. Identifying the underlying or indirect agents is more complex than endogenous or direct factors. On the one hand, cause - effect relationships are much more diffuse; and, second, the effects may be determined by broader phenomena, due to superposition or accumulation of different causes. From the results of forest loss obtained using Landsat 5/TM, the criteria of direct and indirect conditioning that might have contributed to deforestation and forest degradation in that period were investigated. For this purpose, temporal series, for the same dates, 9 direct factors (infrastructure, hydrography, temperature, etc.) and 196 underlying factors (economic, social, demographic and environmental) with, in principle, a high potential of causality. Finally it was analyzed the predisposition of each factor to the occurrence of deforestation and forest degradation by statistical correlation of the obtained temporal series.

Algoritmos genéticos en control activo de ruido

Este proyecto se centra en la implementación de un sistema de control activo de ruido mediante algoritmos genéticos. Para ello, se ha tenido en cuenta el tipo de ruido que se quiere cancelar y el diseño del controlador, parte fundamental del sistema de control. El control activo de ruido sólo es eficaz a bajas frecuencias, hasta los 250 Hz, justo para las cuales los elementos pasivos pierden efectividad, y en zonas o recintos de pequeñas dimensiones y conductos. El controlador ha de ser capaz de seguir todas las posibles variaciones del campo acústico que puedan producirse (variaciones de fase, de frecuencia, de amplitud, de funciones de transferencia electro-acústicas, etc.). Su funcionamiento está basado en algoritmos FIR e IIR adaptativos. La elección de un tipo de filtro u otro depende de características tales como linealidad, causalidad y número de coeficientes. Para que la función de transferencia del controlador siga las variaciones que surgen en el entorno acústico de cancelación, tiene que ir variando el valor de los coeficientes del filtro mediante un algoritmo adaptativo. En este proyecto se emplea como algoritmo adaptativo un algoritmo genético, basado en la selección biológica, es decir, simulando el comportamiento evolutivo de los sistemas biológicos. Las simulaciones se han realizado con dos tipos de señales: ruido de carácter aleatorio (banda ancha) y ruido periódico (banda estrecha). En la parte final del proyecto se muestran los resultados obtenidos y las conclusiones al respecto. Summary. This project is focused on the implementation of an active noise control system using genetic algorithms. For that, it has been taken into account the noise type wanted to be canceled and the controller design, a key part of the control system. The active noise control is only effective at low frequencies, up to 250 Hz, for which the passive elements lose effectiveness, and in small areas or enclosures and ducts. The controller must be able to follow all the possible variations of the acoustic field that might be produced (phase, frequency, amplitude, electro-acoustic transfer functions, etc.). It is based on adaptive FIR and IIR algorithms. The choice of a kind of filter or another depends on characteristics like linearity, causality and number of coefficients. Moreover, the transfer function of the controller has to be changing filter coefficients value thought an adaptive algorithm. In this project a genetic algorithm is used as adaptive algorithm, based on biological selection, simulating the evolutionary behavior of biological systems. The simulations have been implemented with two signal types: random noise (broadband) and periodic noise (narrowband). In the final part of the project the results and conclusions are shown.

Caracterización del hormigón en relación a la difusión de gases y su correlación con el radón

Radon gas (Rn) is a natural radioactive gas present in some soils and able to penetrate buildings through the building envelope in contact with the soil. Radon can accumulate within buildings and consequently be inhaled by their occupants. Because it is a radioactive gas, its disintegration process produces alpha particles that, in contact with the lung epithelia, can produce alterations potentially giving rise to cancer. Many international organizations related to health protection, such as WHO, confirm this causality. One way to avoid the accumulation of radon in buildings is to use the building envelope as a radon barrier. The extent to which concrete provides such a barrier is described by its radon diffusion coefficient (DRn), a parameter closely related to porosity (ɛ) and tortuosity factor (τ). The measurement of the radon diffusion coefficient presents challenges, due to the absence of standard procedures, the requirement to establish adequate airtightness in testing apparatus (referred to here as the diffusion cell), and due to the fact that measurement has to be carried out in an environment certified for use of radon calibrated sources. In addition to this calibrated radon sources are costly. The measurement of the diffusion coefficient for non-radioactive gas is less complex, but nevertheless retains a degree of difficulty due to the need to provide reliably airtight apparatus for all tests. Other parameters that can characterize and describe the process of gas transport through concrete include the permeability coefficient (K) and the electrical resistivity (ρe), both of which can be measured relatively easily with standardized procedure. The use of these parameters would simplify the characterization of concrete behaviour as a radon barrier. Although earlier studies exist, describing correlation among these parameters, there is, as has been observed in the literature, little common ground between the various research efforts. For precisely this reason, prior to any attempt to measure radon diffusion, it was deemed necessary to carry out further research in this area, as a foundation to the current work, to explore potential relationships among the following parameters: porosity-tortuosity, oxygen diffusion coefficient, permeability coefficient and resistivity. Permeability coefficient measurement (m2) presents a more straightforward challenge than diffusion coefficient measurement. Some authors identify a relationship between both coefficients, including Gaber (1988), who proposes: k= a•Dn Equation 1 Where: a=A/(8ΠD020), A = sample cross-section, D020 = diffusion coefficient in air (m2/s). Other studies (Klink et al. 1999, Gaber and Schlattner 1997, Gräf and Grube et al. 1986), experimentally relate both coefficients of different types of concrete confirming that this relationship exists, as represented by the simplified expression: k≈Dn Equation 2 In each particular study a different value for n was established, varying from 1.3 to 2.5, but this requires determination of a value for n in a more general way because these proposed models cannot estimate diffusion coefficient. If diffusion coefficient has to be measured to be able to establish n, these relationships are not interesting. The measurement of electric resistivity is easier than diffusion coefficient measurement. Correlation between the parameters can be established via Einstein´s law that relates movement of electrical charges to media conductivity according to the expression: D_e=k/ρ Equation 3 Where: De = diffusion coefficient (cm2/s), K = constant, ρ = electric resistivity (Ω•cm). The tortuosity factor is used to represent the uneven geometry of concrete pores, which are described as being not straight, but tortuous. This factor was first introduced in the literature to relate global porosity with fluid transport in a porous media, and can be formulated in a number of different ways. For example, it can take the form of equation 4 (Mason y Malinauskas), which combines molecular and Knudsen diffusion using the tortuosity factor: D=ε^τ (3/2r √(πM/8RT+1/D_0 ))^(-1) Equation 4 Where: r = medium radius obtained from MIP (µm), M = gas molecular mass, R = ideal gases constant, T = temperature (K), D0 = coefficient diffusion in the air (m2/s). Few studies provide any insight as to how to obtain the tortuosity factor. The work of Andrade (2012) is exceptional in this sense, as it outlines how the tortuosity factor can be deduced from pore size distribution (from MIP) from the equation: ∅_th=∅_0•ε^(-τ). Equation 5 Where: Øth = threshold diameter (µm), Ø0 = minimum diameter (µm), ɛ = global porosity, τ = tortuosity factor. Alternatively, the following equation may be used to obtain the tortuosity factor: DO2=D0*ɛτ Equation 6 Where: DO2 = oxygen diffusion coefficient obtained experimentally (m2/s), DO20 = oxygen diffusion coefficient in the air (m2/s). This equation has been inferred from Archie´s law ρ_e=〖a•ρ〗_0•ɛ^(-m) and from the Einstein law mentioned above, using the values of oxygen diffusion coefficient obtained experimentally. The principal objective of the current study was to establish correlations between the different parameters that characterize gas transport through concrete. The achievement of this goal will facilitate the assessment of the useful life of concrete, as well as open the door to the pro-active planning for the use of concrete as a radon barrier. Two further objectives were formulated within the current study: 1.- To develop a method for measurement of gas coefficient diffusion in concrete. 2.- To model an analytic estimation of radon diffusion coefficient from parameters related to concrete porosity and tortuosity factor. In order to assess the possible correlations, parameters have been measured using the standardized procedures or purpose-built in the laboratory for the study of equations 1, 2 y 3. To measure the gas diffusion coefficient, a diffusion cell was designed and manufactured, with the design evolving over several cycles of research, leading ultimately to a unit that is reliably air tight. The analytic estimation of the radon diffusion coefficient DRn in concrete is based on concrete global porosity (ɛ), whose values may be experimentally obtained from a mercury intrusion porosimetry test (MIP), and from its tortuosity factor (τ), derived using the relations expressed in equations 5 y 6. The conclusions of the study are: Several models based on regressions, for concrete with a relative humidity of 50%, have been proposed to obtain the diffusion coefficient following the equations K=Dn, K=a*Dn y D=n/ρe. The final of these three relations is the one with the determination coefficient closest to a value of 1: D=(19,997*LNɛ+59,354)/ρe Equation 7 The values of the obtained oxygen diffusion coefficient adjust quite well to those experimentally measured. The proposed method for the measurement of the gas coefficient diffusion is considered to be adequate. The values obtained for the oxygen diffusion coefficient are within the range of those proposed by the literature (10-7 a 10-8 m2/s), and are consistent with the other studied parameters. Tortuosity factors obtained using pore distribution and the expression Ø=Ø0*ɛ-τ are inferior to those from resistivity ρ=ρ0*ɛ-τ. The closest relationship to it is the one with porosity of pore diameter 1 µm (τ=2,07), being 7,21% inferior. Tortuosity factors obtained from the expression DO2=D0*ɛτ are similar to those from resistivity: for global tortuosity τ=2,26 and for the rest of porosities τ=0,7. Estimated radon diffusion coefficients are within the range of those consulted in literature (10-8 a 10-10 m2/s).ABSTRACT El gas radón (Rn) es un gas natural radioactivo presente en algunos terrenos que puede penetrar en los edificios a través de los cerramientos en contacto con el mismo. En los espacios interiores se puede acumular y ser inhalado por las personas. Al ser un gas radioactivo, en su proceso de desintegración emite partículas alfa que, al entrar en contacto con el epitelio pulmonar, pueden producir alteraciones del mismo causando cáncer. Muchos organismos internacionales relacionados con la protección de la salud, como es la OMS, confirman esta causalidad. Una de las formas de evitar que el radón penetre en los edificios es utilizando las propiedades de barrera frente al radón de su propia envolvente en contacto con el terreno. La principal característica del hormigón que confiere la propiedad de barrera frente al radón cuando conforma esta envolvente es su permeabilidad que se puede caracterizar mediante su coeficiente de difusión (DRn). El coeficiente de difusión de un gas en el hormigón es un parámetro que está muy relacionado con su porosidad (ɛ) y su tortuosidad (τ). La medida del coeficiente de difusión del radón resulta bastante complicada debido a que el procedimiento no está normalizado, a que es necesario asegurar una estanquidad a la celda de medida de la difusión y a que la medida tiene que ser realizada en un laboratorio cualificado para el uso de fuentes de radón calibradas, que además son muy caras. La medida del coeficiente de difusión de gases no radioactivos es menos compleja, pero sigue teniendo un alto grado de dificultad puesto que tampoco está normalizada, y se sigue teniendo el problema de lograr una estanqueidad adecuada de la celda de difusión. Otros parámetros que pueden caracterizar el proceso son el coeficiente de permeabilidad (K) y la resistividad eléctrica (ρe), que son más fáciles de determinar mediante ensayos que sí están normalizados. El uso de estos parámetros facilitaría la caracterización del hormigón como barrera frente al radón, pero aunque existen algunos estudios que proponen correlaciones entre estos parámetros, en general existe divergencias entre los investigadores, como se ha podido comprobar en la revisión bibliográfica realizada. Por ello, antes de tratar de medir la difusión del radón se ha considerado necesario realizar más estudios que puedan clarificar las posibles relaciones entre los parámetros: porosidad-tortuosidad, coeficiente de difusión del oxígeno, coeficiente de permeabilidad y resistividad. La medida del coeficiente de permeabilidad (m2) es más sencilla que el de difusión. Hay autores que relacionan el coeficiente de permeabilidad con el de difusión. Gaber (1988) propone la siguiente relación: k= a•Dn Ecuación 1 En donde: a=A/(8ΠD020), A = sección de la muestra, D020 = coeficiente de difusión en el aire (m2/s). Otros estudios (Klink et al. 1999, Gaber y Schlattner 1997, Gräf y Grube et al. 1986) relacionan de forma experimental los coeficientes de difusión de radón y de permeabilidad de distintos hormigones confirmando que existe una relación entre ambos parámetros, utilizando la expresión simplificada: k≈Dn Ecuación 2 En cada estudio concreto se han encontrado distintos valores para n que van desde 1,3 a 2,5 lo que lleva a la necesidad de determinar n porque no hay métodos que eviten la determinación del coeficiente de difusión. Si se mide la difusión ya deja de ser de interés la medida indirecta a través de la permeabilidad. La medida de la resistividad eléctrica es muchísimo más sencilla que la de la difusión. La relación entre ambos parámetros se puede establecer a través de una de las leyes de Einstein que relaciona el movimiento de cargas eléctricas con la conductividad del medio según la siguiente expresión: D_e=k/ρ_e Ecuación 3 En donde: De = coeficiente de difusión (cm2/s), K = constante, ρe = resistividad eléctrica (Ω•cm). El factor de tortuosidad es un factor de forma que representa la irregular geometría de los poros del hormigón, al no ser rectos sino tener una forma tortuosa. Este factor se introduce en la literatura para relacionar la porosidad total con el transporte de un fluido en un medio poroso y se puede formular de distintas formas. Por ejemplo se destaca la ecuación 4 (Mason y Malinauskas) que combina la difusión molecular y la de Knudsen utilizando el factor de tortuosidad: D=ε^τ (3/2r √(πM/8RT+1/D_0 ))^(-1) Ecuación 4 En donde: r = radio medio obtenido del MIP (µm), M = peso molecular del gas, R = constante de los gases ideales, T = temperatura (K), D0 = coeficiente de difusión de un gas en el aire (m2/s). No hay muchos estudios que proporcionen una forma de obtener este factor de tortuosidad. Destaca el estudio de Andrade (2012) en el que deduce el factor de tortuosidad de la distribución del tamaño de poros (curva de porosidad por intrusión de mercurio) a partir de la ecuación: ∅_th=∅_0•ε^(-τ) Ecuación 5 En donde: Øth = diámetro umbral (µm), Ø0 = diámetro mínimo (µm), ɛ = porosidad global, τ = factor de tortuosidad. Por otro lado, se podría utilizar también para obtener el factor de tortuosidad la relación: DO2=D0*-τ Ecuación 6 En donde: DO2 = coeficiente de difusión del oxígeno experimental (m2/s), DO20 = coeficiente de difusión del oxígeno en el aire (m2/s). Esta ecuación está inferida de la ley de Archie ρ_e=〖a•ρ〗_0•ɛ^(-m) y la de Einstein mencionada anteriormente, utilizando valores del coeficiente de difusión del oxígeno DO2 obtenidos experimentalmente. El objetivo fundamental de la tesis es encontrar correlaciones entre los distintos parámetros que caracterizan el transporte de gases a través del hormigón. La consecución de este objetivo facilitará la evaluación de la vida útil del hormigón así como otras posibilidades, como la evaluación del hormigón como elemento que pueda ser utilizado en la construcción de nuevos edificios como barrera frente al gas radón presente en el terreno. Se plantean también los siguientes objetivos parciales en la tesis: 1.- Elaborar una metodología para la medida del coeficiente de difusión de los gases en el hormigón. 2.- Plantear una estimación analítica del coeficiente de difusión del radón a partir de parámetros relacionados con su porosidad y su factor de tortuosidad. Para el estudio de las correlaciones posibles, se han medido los parámetros con los procedimientos normalizados o puestos a punto en el propio Instituto, y se han estudiado las reflejadas en las ecuaciones 1, 2 y 3. Para la medida del coeficiente de difusión de gases se ha fabricado una celda que ha exigido una gran variedad de detalles experimentales con el fin de hacerla estanca. Para la estimación analítica del coeficiente de difusión del radón DRn en el hormigón se ha partido de su porosidad global (ɛ), que se obtiene experimentalmente del ensayo de porosimetría por intrusión de mercurio (MIP), y de su factor de tortuosidad (τ), que se ha obtenido a partir de las relaciones reflejadas en las ecuaciones 5 y 6. Las principales conclusiones obtenidas son las siguientes: Se proponen modelos basados en regresiones, para un acondicionamiento con humedad relativa de 50%, para obtener el coeficiente de difusión del oxígeno según las relaciones: K=Dn, K=a*Dn y D=n/ρe. La propuesta para esta última relación es la que tiene un mejor ajuste con R2=0,999: D=(19,997*LNɛ+59,354)/ρe Ecuación 7 Los valores del coeficiente de difusión del oxígeno así estimados se ajustan a los obtenidos experimentalmente. Se considera adecuado el método propuesto de medida del coeficiente de difusión para gases. Los resultados obtenidos para el coeficiente de difusión del oxígeno se encuentran dentro del rango de los consultados en la literatura (10-7 a 10-8 m2/s) y son coherentes con el resto de parámetros estudiados. Los resultados de los factores de tortuosidad obtenidos de la relación Ø=Ø0*ɛ-τ son inferiores a la de la resistividad (ρ=ρ0*ɛ-τ). La relación que más se ajusta a ésta, siendo un 7,21% inferior, es la de la porosidad correspondiente al diámetro 1 µm con τ=2,07. Los resultados de los factores de tortuosidad obtenidos de la relación DO2=D0*ɛτ son similares a la de la resistividad: para la porosidad global τ=2,26 y para el resto de porosidades τ=0,7. Los coeficientes de difusión de radón estimados mediante estos factores de tortuosidad están dentro del rango de los consultados en la literatura (10-8 a 10-10 m2/s).

VAR models and methods for monetary and health economics

Negli ultimi anni i modelli VAR sono diventati il principale strumento econometrico per verificare se può esistere una relazione tra le variabili e per valutare gli effetti delle politiche economiche. Questa tesi studia tre diversi approcci di identificazione a partire dai modelli VAR in forma ridotta (tra cui periodo di campionamento, set di variabili endogene, termini deterministici). Usiamo nel caso di modelli VAR il test di Causalità di Granger per verificare la capacità di una variabile di prevedere un altra, nel caso di cointegrazione usiamo modelli VECM per stimare congiuntamente i coefficienti di lungo periodo ed i coefficienti di breve periodo e nel caso di piccoli set di dati e problemi di overfitting usiamo modelli VAR bayesiani con funzioni di risposta di impulso e decomposizione della varianza, per analizzare l'effetto degli shock sulle variabili macroeconomiche. A tale scopo, gli studi empirici sono effettuati utilizzando serie storiche di dati specifici e formulando diverse ipotesi. Sono stati utilizzati tre modelli VAR: in primis per studiare le decisioni di politica monetaria e discriminare tra le varie teorie post-keynesiane sulla politica monetaria ed in particolare sulla cosiddetta "regola di solvibilità" (Brancaccio e Fontana 2013, 2015) e regola del GDP nominale in Area Euro (paper 1); secondo per estendere l'evidenza dell'ipotesi di endogeneità della moneta valutando gli effetti della cartolarizzazione delle banche sul meccanismo di trasmissione della politica monetaria negli Stati Uniti (paper 2); terzo per valutare gli effetti dell'invecchiamento sulla spesa sanitaria in Italia in termini di implicazioni di politiche economiche (paper 3). La tesi è introdotta dal capitolo 1 in cui si delinea il contesto, la motivazione e lo scopo di questa ricerca, mentre la struttura e la sintesi, così come i principali risultati, sono descritti nei rimanenti capitoli. Nel capitolo 2 sono esaminati, utilizzando un modello VAR in differenze prime con dati trimestrali della zona Euro, se le decisioni in materia di politica monetaria possono essere interpretate in termini di una "regola di politica monetaria", con specifico riferimento alla cosiddetta "nominal GDP targeting rule" (McCallum 1988 Hall e Mankiw 1994; Woodford 2012). I risultati evidenziano una relazione causale che va dallo scostamento tra i tassi di crescita del PIL nominale e PIL obiettivo alle variazioni dei tassi di interesse di mercato a tre mesi. La stessa analisi non sembra confermare l'esistenza di una relazione causale significativa inversa dalla variazione del tasso di interesse di mercato allo scostamento tra i tassi di crescita del PIL nominale e PIL obiettivo. Risultati simili sono stati ottenuti sostituendo il tasso di interesse di mercato con il tasso di interesse di rifinanziamento della BCE. Questa conferma di una sola delle due direzioni di causalità non supporta un'interpretazione della politica monetaria basata sulla nominal GDP targeting rule e dà adito a dubbi in termini più generali per l'applicabilità della regola di Taylor e tutte le regole convenzionali della politica monetaria per il caso in questione. I risultati appaiono invece essere più in linea con altri approcci possibili, come quelli basati su alcune analisi post-keynesiane e marxiste della teoria monetaria e più in particolare la cosiddetta "regola di solvibilità" (Brancaccio e Fontana 2013, 2015). Queste linee di ricerca contestano la tesi semplicistica che l'ambito della politica monetaria consiste nella stabilizzazione dell'inflazione, del PIL reale o del reddito nominale intorno ad un livello "naturale equilibrio". Piuttosto, essi suggeriscono che le banche centrali in realtà seguono uno scopo più complesso, che è il regolamento del sistema finanziario, con particolare riferimento ai rapporti tra creditori e debitori e la relativa solvibilità delle unità economiche. Il capitolo 3 analizza l’offerta di prestiti considerando l’endogeneità della moneta derivante dall'attività di cartolarizzazione delle banche nel corso del periodo 1999-2012. Anche se gran parte della letteratura indaga sulla endogenità dell'offerta di moneta, questo approccio è stato adottato raramente per indagare la endogeneità della moneta nel breve e lungo termine con uno studio degli Stati Uniti durante le due crisi principali: scoppio della bolla dot-com (1998-1999) e la crisi dei mutui sub-prime (2008-2009). In particolare, si considerano gli effetti dell'innovazione finanziaria sul canale dei prestiti utilizzando la serie dei prestiti aggiustata per la cartolarizzazione al fine di verificare se il sistema bancario americano è stimolato a ricercare fonti più economiche di finanziamento come la cartolarizzazione, in caso di politica monetaria restrittiva (Altunbas et al., 2009). L'analisi si basa sull'aggregato monetario M1 ed M2. Utilizzando modelli VECM, esaminiamo una relazione di lungo periodo tra le variabili in livello e valutiamo gli effetti dell’offerta di moneta analizzando quanto la politica monetaria influisce sulle deviazioni di breve periodo dalla relazione di lungo periodo. I risultati mostrano che la cartolarizzazione influenza l'impatto dei prestiti su M1 ed M2. Ciò implica che l'offerta di moneta è endogena confermando l'approccio strutturalista ed evidenziando che gli agenti economici sono motivati ad aumentare la cartolarizzazione per una preventiva copertura contro shock di politica monetaria. Il capitolo 4 indaga il rapporto tra spesa pro capite sanitaria, PIL pro capite, indice di vecchiaia ed aspettativa di vita in Italia nel periodo 1990-2013, utilizzando i modelli VAR bayesiani e dati annuali estratti dalla banca dati OCSE ed Eurostat. Le funzioni di risposta d'impulso e la scomposizione della varianza evidenziano una relazione positiva: dal PIL pro capite alla spesa pro capite sanitaria, dalla speranza di vita alla spesa sanitaria, e dall'indice di invecchiamento alla spesa pro capite sanitaria. L'impatto dell'invecchiamento sulla spesa sanitaria è più significativo rispetto alle altre variabili. Nel complesso, i nostri risultati suggeriscono che le disabilità strettamente connesse all'invecchiamento possono essere il driver principale della spesa sanitaria nel breve-medio periodo. Una buona gestione della sanità contribuisce a migliorare il benessere del paziente, senza aumentare la spesa sanitaria totale. Tuttavia, le politiche che migliorano lo stato di salute delle persone anziane potrebbe essere necessarie per una più bassa domanda pro capite dei servizi sanitari e sociali.

Sensoriamento automático e participativo em cidades.

As cidades estão a seu tempo e a seu modo, modernizando os serviços prestados à população. Entre os diversos fatores que estão contribuindo para esta evolução estão a diversificação e proliferação de sensores, nos diversos domínios de serviços das cidades, e os novos canais de comunicação com os munícipes, entre eles, as redes sociais e mais recentemente os sistemas crowdsensing, motivados pelos anseios sociais, por melhores serviços públicos e pela popularização dos dispositivos móveis. Nesta direção, a eficiência administrativa é um fator essencial, uma vez que as cidades estão se mostrando mais complexas na medida em que cresce a população nas áreas urbanas. A utilização de técnicas de sistemas distribuídos para que múltiplos domínios de serviços usufruam da mesma infraestrutura computacional, pode auxiliar na eficiência das cidades, evitando gastos administrativos duplicados e até mesmo, possibilitando a correlação de eventos entre os serviços, favorecendo a identificação de fatores de causalidades e assim, a tomada de decisões administrativas mais objetivas e precisas. Neste contexto, este trabalho concentra-se na análise de um middleware direcionado à gestão de cidades para coleta, integração e interpretação dos dados de sensores, pertencentes aos serviços disponíveis da própria cidade, junto com os dados do sensoriamento colaborado pelos cidadãos. Para avaliação do conceito foi investigado o cenário de monitoração da conservação de vias públicas. Após 3 meses de coletas de dados por um sistema de sensoriamento automático, totalizando mais de 360 mil pontos e também mais de 90 relatórios pelo sensoriamento participativo, verificou-se que um sistema distribuído pode realizar a interpretação de séries históricas, engajar os munícipes apoiar a manutenção dos serviços da cidade e também indicar objetivamente aos gestores públicos os pontos que devem ser prioritariamente atendidos. Aliar ferramentas pelas quais o cidadão pode, de acordo com sua necessidade, convicção e altruísmo, exercer influência nos gestores públicos com o suporte de informação contínua e critérios objetivos das redes de sensores, pode estimular a continua excelência dos serviços públicos.