Optimal Fiscal Policy in a Small Open Economy and the Structure of International Financial Markets.

This paper characterizes the behavior of debt and tax rates in a small open economy under both complete and incomplete markets. First, I show hat when the government follows an optimal fiscal policy and agents have access to complete markets, the value of the government’s debt portfolio is negatively correlated with government spending, and positively correlated with productivity and output, while output, labor, consumption and the tax rate are uncorrelated with government spending shocks. The stochastic processes followed by these variables inherit the serial-correlation properties of the stochastic process of the productivity shock. Second, I show that if agents can only buy and sell one-period risk-free bonds, public debt shows more persistence than other variables, and it is negatively correlated with productivity and output, and positively correlated with government spending. Moreover, the tax rate is positively correlated with government spending, while consumption is negatively correlated.Complete markets, Incomplete markets, Optimal fiscal policy

An Affine Model of the Term Structure of Interest Rates in Mexico.

We develop and estimate an affine model that characterizes the dynamics of the term structure of interest rates in Mexico. Moreover, we provide empirical evidence on the relationship between the term structure factors and macroeconomic variables. First, we show that the model fits the data remarkably well. Second, we show that the first factor captures movements in the level of the yield curve, while the second factor captures movements in the slope of the curve. Third, the variance decomposition results show that the level factor accounts for a substantial part of the variance at the long end of the yield curve at all horizons. At short horizons, the slope factor accounts for much of the variance at the short end of the yield curve. Finally, we show that movements in the level of the yield curve are associated with movements in long-term inflation expectations, while movements in the slope of the curve are associated with movements in the short-term nominal interest rate.No-Arbitrage, Latent Factors, Term-Structure

A Macroeconomic Model of the Term Structure of Interest Rates in Mexico.

This paper investigates how different macroeconomic shocks affect the term-structure of interest rates in Mexico. In particular, we develop a model that combines a no-arbitrage specification of the term structure with a macroeconomic model of a small open economy. We find that shocks that are perceived to have a persistent effect on inflation affect the level of the yield curve. The effect on medium and long-term yields results from the increase in expected future short rates and in risk premia. With respect to demand shocks, our results show that a positive shock leads to an upward flattening shift in the yield curve. The flattening of the curve is explained by both the monetary policy response and the time-varying term premia.Term-Structure, No-Arbitrage, Macroeconomic Shocks.

Modulation of ligand-gated ion channels and receptors in peripheral neurons

Tesis (Doctorado en Ciencias en Biología Molecular)"El sistema nervioso periférico está integrado por nervios y ganglios (albergan los cuerpos neuronales) que regulan la transmisión de los impulsos neuronales desde los órganos de los receptores sensoriales en cada parte del cuerpo hacia el sistema nervioso central y desde éste a blancos específicos en la periferia. Las neuronas son células excitables, y son las unidades estructurales y funcionales del sistema nervioso, por consiguiente, están especializados en la comunicación rápida. Las neuronas transmiten la información en forma de señales eléctricas, a lo largo de la neurona, en respuesta a señales químicas y pueden comunicarse químicamente con otras neuronas y con diferentes tipos de células. Esta comunicación requiere de receptores, proteínas que se caracterizan por el reconocimiento selectivo de sustancias específicas como neurotransmisores y antígenos, y en respuesta generan un efecto fisiológico particular. Por lo tanto, pueden detectar cambios en el ambiente y enviar la información resultante a la corteza cerebral donde se interpretarán dichas señales (por ejemlo, una señal estresante o agradable). La desregulación de los receptores puede causar la interrupción o distorsión en la respuesta y/o la transmisión de la señal. Aumentar la información sobre los mecanismos de modulación de los receptores nos permite detectar, prevenir y tratar enfermedades, en este caso vinculados a la modulación de LGIC y TLR. En los estudios que se presentan en esta Tesis, utilizamos técnicas electrofisiológicas para: i) caracterizar la interacción inhibitoria entre los receptores nativos nACh y P2X en las neuronas del ganglios celíaco y ii) analizar el efecto de productos bacterianos en neuronas DRG que inervan el colon de ratón, que al ser estimuladas cambiaron su conducta eléctrica resultando en un aumento de la excitabilidad neuronal intrínseca posiblemente mediada por PRRs. En conclusión, mostramos dos fenómenos distintos: una interacción funcional entre LGIC y una modulación de las propiedades neuronales eléctricas por componentes bacterianos. Ambos podrían tener importantes implicaciones fisiológicas, y jugar un papel primordial en la neuroprotección y la nocicepción, respectivamente. Sin embargo, es necesario un mayor análisis para determinar su papel fisiológico.""The peripheral nervous system is integrated by nerves and ganglia (aggregates of neuronal bodies) that regulate and transmit neuronal impulses from organs of sensory receptors in each body part to the central nervous system or from the latter to specific peripheral targets. Neurons are excitable cells and they are the structural and functional units of the nervous system that specialized in rapid communication. Neurons transmit information in the form of electrical signals in response to chemical signals, and may communicate chemically with other neurons and other type of cells. Chemical communication requires the presence of receptors, which are proteins that respond to the binding of a specific substances such as neurotransmitters. This receptor activation generates a biochemical cascade and the subsequent physiologic effects. Thus, neurons are capable of detecting changes in the milieu and send the integrated information to the cerebral cortex where signals are interpreted according to their sensory modality as pain or touch, for example. Deregulation in molecular receptors may cause alterations in the sensory response and transmission of the signal. Therefore, information regarding receptor modulation may allow us to detect, prevent, and treat prevalent neurological-based illnesses that are receptor-linked. In the experiments that we performed and described here, we used electrophysiological techniques to: i) characterize the inhibitory interactions between nACh and P2X receptors expressed in celiac ganglia neurons and ii) analyze the effect of bacterial products in mouse colonic nociceptive neurons that arised from the dorsal root ganglia. These neurons increased their excitability in response to bacterial cell products and this effect are likely mediated by pattern recognition receptors. In conclusion we showed a functional interaction between LGIC and a modulation of the neuronal electrical properties by bacterial components. Both of them may have important physiological implications in synaptic neurotransmission, in neuroprotection and nociception. However, further analysis is necessary to assign specific physiological role of these observations.

Planificación de actividades en un curso sobre la adquisición de competencias en la modelización matemática y uso de calculadora con posibilidades gráficas

Nuestra posición sobre el uso de la tecnología en el aula de matemáticas es que éste debe ser un uso reflexivo tomando en consideración el contexto matemático en donde se utiliza. Existen muchos profesores de matemáticas que consideran que el uso de la tecnología inhibe el desarrollo de ciertas habilidades matemáticas; otros, con un entusiasmo desbordado, consideran que la tecnología es aplicable en todo, promoviendo en los alumnos un uso de la tecnología que consiste a apretar botones sin promover una reflexión sobre lo que se está realizando. El punto de equilibrio todavía no ha sido alcanzado, los investigadores no han logrado convencer al profesor que rechaza la tecnología sobre lo apropiado de su uso en el aula de matemáticas. Debemos alcanzar ese punto de equilibrio para poder promover un uso más complejo de la tecnología que ayude en la adquisición de conocimientos. En este documento, nos interesamos en el diseño de actividades para el desarrollo de competencias matemáticas en torno a la modelización matemática y uso de calculadora con posibilidades gráficas

Jointly modelling of cluster dependent pro les of fractional and binary variables from a Bayesian point of view

En la presente tesis se proponen modelos de clasificación basados en regresiones beta inflacionadas cero-uno con efectos mixtos para modelar perfiles longitudinales de variables fraccionarias mixtas y variables binarias de forma conjunta con formación de clústeres. Las distintas parametrizaciones de los modelos propuestos permiten modelar distintos efectos, como modelar directamente la media marginal a través de covariables e interpretar fácilmente su efecto sobre ella o modelar la media condicional y las probabilidades de inflación de forma separada. Además, se forman clústeres de grupos de individuos con perfiles longitudinales similares a través de una variable latente, asumiendo que las variables respuesta siguen un modelo de mixtura finita. Debido a la complejidad de los modelos, los parámetros se estiman desde un punto de vista bayesiano, a partir de simulaciones MCMC utilizando el software JAGS en R. Se prueban los modelos propuestos sobre diferentes bases de datos simulados para medir el desempeño de los mismos y se comparan con otros modelos a fin de verificar cual ajusta mejor los perfiles longitudinales de variables fraccionarias mixtas y variables binarias. Por último, se aplican los modelos propuestos a datos reales de un banco peruano, con información del ratio de uso de tarjetas de crédito en el periodo de un año, estado de default del cliente y otras covariables correspondientes al cliente poseedor de la tarjeta, con el objetivo de obtener clústeres de individuos con similar ratio de uso de tarjeta de crédito y relacionarlos con la probabilidad de caer en default que presenta cada grupo.The following thesis proposes classi cation models that consist of jointly tting longitudinal pro les of mixed fractional and binary variables modelled by zero-one beta in ated mixed regressions with cluster formation. The distinct proposed parametrizations allow di erent effects to be modelled, such as modelling the marginal mean directly through independent variables and easily interpret its e ect on it or modelling the conditional mean and the in- ation probabilities separately. In addition, individuals with similar fractional longitudinal pro les are grouped into a cluster through a latent variable, assuming that the response variables follow a nite mixture model. Due to the complexity of the models, the parameters are estimated from a Bayesian point of view by simulating a MCMC using JAGS software in R. The proposed models are tted in various simulated datasets and are compared against other models to measure performance in tting fractional longitudinal pro les and binary variables. Finally, an application on real data is conducted, consisting on longitudinal information of credit card utilization ratio and default status as dependants variables and covariates corresponding to client information, aiming to obtain clusters of clients with similar behaviour in evolution of credit card utilization and relate them to their probability of default.Tesi

Multidimensional model of assessment of economic thinking in college students

The Economic Thinking in undergraduates is a strategic aspect of research in the framework of higher education, given its critical impact on the development of skills and professional standards expected in front of the Scientific and Technological Innovation. The main contribution of this study focuses on the development of a Multidimensional Model of Assessment of Economic Thinking, from the perspective of Self-Organizing Systems. The methodology has an approach empirical-analytic. In relation to the instruments and results correspond to a perspective of Adaptative System based in Item Response Theory (IRT), Complexity Theory and Fractal Models (L-system) about the competence in solving economic problems, knowledge of financial aspects, responsible consumption, sustainable development, and the attitudes to understanding the economic world

A Distributed Model Predictive Control (D-MPC) for modular robots in chain configuration

Ingeniero (a) ElectrónicoPregrad

An Empirical Analysis of the Mexican Term Structure of Interest Rates.

We study the dynamics of the term-structure of interest rates in Mexico. Specifically, we investigate time variation in bond risk premia and the common factors that have influenced the behavior of the yield curve. We find that term-premia in government bonds appear to be time-varying. We then estimate a principal components model. We find that over 95% of the total variation in the yield curve can be explained by two factors. The first factor captures movements in the level of the yield curve, while the second one captures movements in the slope. Moreover, we find that the level factor is positively correlated with measures of long-term inflation expectations and that the slope factor is negatively correlated with the overnight interest rate.Term-Structure, Time-Varying Risk Premia, Principal Components