De lo micro a lo macro prudencial: Un análisis de la supervisión bancaria desde la econometría espacial

La crisis que se desató en el mercado hipotecario en Estados Unidos en 2008 y que logró propagarse a lo largo de todo sistema financiero, dejó en evidencia el nivel de interconexión que actualmente existe entre las entidades del sector y sus relaciones con el sector productivo, dejando en evidencia la necesidad de identificar y caracterizar el riesgo sistémico inherente al sistema, para que de esta forma las entidades reguladoras busquen una estabilidad tanto individual, como del sistema en general. El presente documento muestra, a través de un modelo que combina el poder informativo de las redes y su adecuación a un modelo espacial auto regresivo (tipo panel), la importancia de incorporar al enfoque micro-prudencial (propuesto en Basilea II), una variable que capture el efecto de estar conectado con otras entidades, realizando así un análisis macro-prudencial (propuesto en Basilea III).

Mercados laborales en entornos de conflictos armados: un análisis empírico para Colombia

Históricamente se ha reconocido que los conflictos internos afectan de manera directa variables a nivel individual como la salud de las personas, los niveles de escolaridad y el desplazamiento forzoso de los afectados. Sin embargo, solo hasta la última década las investigaciones académicas se han inclinado en documentar y cuantificar rigurosamente los efectos colaterales de la violencia sobre las condiciones de vida de los individuos. La presente investigación estudia cómo la exposición al conflicto en Colombia ha afectado las decisiones en términos de mercado laboral de las personas. La estrategia de identificación internaliza los reconocidos problemas de endogeneidad del conflicto con variables de actividad y desarrollo económico y presenta resultados robustos a fenómenos de migración interna y desplazamiento. En términos de participación laboral y desempleo, se encuentran efectos heterogéneos a nivel de género como respuestas a la violencia experimentada. En particular, la probabilidad de participación laboral de las mujeres se incremente como consecuencia de la exposición al conflicto, mientras que la de desempleo disminuye. Para los hombres, los resultados muestran una menor probabilidad de participación, efecto contrario al de las mujeres, y un efecto análogo en términos de desempleo. La investigación no encuentra efectos diferenciales en términos de informalidad laboral.

Essays on Spatial Econometrics

Esta dissertação concentra-se nos processos estocásticos espaciais definidos em um reticulado, os chamados modelos do tipo Cliff & Ord. Minha contribuição nesta tese consiste em utilizar aproximações de Edgeworth e saddlepoint para investigar as propriedades em amostras finitas do teste para detectar a presença de dependência espacial em modelos SAR (autoregressivo espacial), e propor uma nova classe de modelos econométricos espaciais na qual os parâmetros que afetam a estrutura da média são distintos dos parâmetros presentes na estrutura da variância do processo. Isto permite uma interpretação mais clara dos parâmetros do modelo, além de generalizar uma proposta de taxonomia feita por Anselin (2003). Eu proponho um estimador para os parâmetros do modelo e derivo a distribuição assintótica do estimador. O modelo sugerido na dissertação fornece uma interpretação interessante ao modelo SARAR, bastante comum na literatura. A investigação das propriedades em amostras finitas dos testes expande com relação a literatura permitindo que a matriz de vizinhança do processo espacial seja uma função não-linear do parâmetro de dependência espacial. A utilização de aproximações ao invés de simulações (mais comum na literatura), permite uma maneira fácil de comparar as propriedades dos testes com diferentes matrizes de vizinhança e corrigir o tamanho ao comparar a potência dos testes. Eu obtenho teste invariante ótimo que é também localmente uniformemente mais potente (LUMPI). Construo o envelope de potência para o teste LUMPI e mostro que ele é virtualmente UMP, pois a potência do teste está muito próxima ao envelope (considerando as estruturas espaciais definidas na dissertação). Eu sugiro um procedimento prático para construir um teste que tem boa potência em uma gama de situações onde talvez o teste LUMPI não tenha boas propriedades. Eu concluo que a potência do teste aumenta com o tamanho da amostra e com o parâmetro de dependência espacial (o que está de acordo com a literatura). Entretanto, disputo a visão consensual que a potência do teste diminui a medida que a matriz de vizinhança fica mais densa. Isto reflete um erro de medida comum na literatura, pois a distância estatística entre a hipótese nula e a alternativa varia muito com a estrutura da matriz. Fazendo a correção, concluo que a potência do teste aumenta com a distância da alternativa à nula, como esperado.

Forecasting with serially correlated regression models

In this article we investigate the asymptotic and finite-sample properties of predictors of regression models with autocorrelated errors. We prove new theorems associated with the predictive efficiency of generalized least squares (GLS) and incorrectly structured GLS predictors. We also establish the form associated with their predictive mean squared errors as well as the magnitude of these errors relative to each other and to those generated from the ordinary least squares (OLS) predictor. A large simulation study is used to evaluate the finite-sample performance of forecasts generated from models using different corrections for the serial correlation.

Utilizing robustness of positive buck-boost converter against input voltage and load current disturbances

A Positive Buck- Boost (PBB) converter is a known DC-DC converter that can operate in step up and step down modes. Unlike Buck, Boost, and Inverting Buck Boost converters, the inductor current of a PBB can be controlled independently of its voltage conversion ratio. In other words, the inductor of PBB can be utilised as an energy storage unit in addition to its main function of energy transfer. In this paper, the capability of PBB to store energy has been utilised to achieve robustness against input voltage fluctuations and output current changes. The control strategy has been developed to keep accuracy, affordability, and simplicity acceptable. To improve the efficiency of the system a Smart Load Controller (SLC) has been suggested. Applying SLC extra current storage occurs when there is sudden loads change otherwise little extra current is stored.

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.

Train control to reduce delays upon service disturbances at railway junctions

Train delay is one of the most important indexes to evaluate the service quality of the railway. Because of the interactions of movement among trains, a delayed train may conflict with trains scheduled on other lines at junction area. Train that loses conflict may be forced to stop or slow down because of restrictive signals, which consequently leads to the loss of run-time and probably enlarges more delays. This paper proposes a time-saving train control method to recover delays as soon as possible. In the proposed method, golden section search is adopted to identify the optimal train speed at the expected time of restrictive signal aspect upgrades, which enables the train to depart from the conflicting area as soon as possible. A heuristic method is then developed to attain the advisory train speed profile assisting drivers in train control. Simulation study indicates that the proposed method enables the train to recover delays as soon as possible in case of disturbances at railway junctions, in comparison with the traditional maximum traction strategy and the green wave strategy.

Sleep Disturbances and Nightmares in Combat Veterans

Book Description: Life is a mix of good and bad happenings and sometimes terrible things happen to people. Trauma is evident across our lifespan; it is part of our lives. Trauma may not exert the same demands on the individual when they get on with their lives or experience other positive aspects of what life has to offer; however, it does not change its form from trauma to growth – it stays there etched into our psyche as trauma. In simple terms, growth occurs alongside the traumatic etchings. This is a book that will provide some answers to psychologists, counselors, social workers and mental health workers about what happens to people who are traumatized and how they ‘get on with their lives’; it also gives some excellent examples of how therapies can assist them in moving forward in life’s journey.

Control of infrastructure inspection aircraft vertical dynamics in the presence of thermal disturbances

The low-altitude aircraft inspection of powerlines, or other linear infrastructure networks, is emerging as an important application requiring specialised control technologies. Despite some recent advances in automated control related to this application, control of the underactuated aircraft vertical dynamics has not been completely achieved, especially in the presence of thermal disturbances. Rejection of thermal disturbances represents a key challenge to the control of inspection aircraft due to the underactuated nature of the dynamics and specified speed, altitude, and pitch constraints. This paper proposes a new vertical controller consisting of a backstepping elevator controller with feedforward-feedback throttle controller. The performance of our proposed approach is evaluated against two existing candidate controllers.

Power system stability enhancement using flux control for excitation system

This paper proposes a new controller for the excitation system to improve rotor angle stability. The proposed controller uses energy function to predict desired flux for the generator to achieve improved first swing stability and enhanced system damping. The controller is designed through predicting the desired value of flux for the future step of the system and then obtaining appropriate supplementary control input for the excitation system. The simulations are performed on Single-Machine-Infinite-Bus system and the results verify the efficiency of the controller. The proposed method facilitates the excitation system with a feasible and reliable controller for severe disturbances.

A stochastic neighborhood conditional autoregressive model for spatial data

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the neighborhood depends on unknown parameter(s). This extension is called a Stochastic Neighborhood CAR (SNCAR) model. The resulting model shows flexibility in accurately estimating covariance structures for data generated from a variety of spatial covariance models. Specific examples are illustrated using data generated from some common spatial covariance functions as well as real data concerning radioactive contamination of the soil in Switzerland after the Chernobyl accident.

On optimal control of constrained linear systems with imperfect state information and stochastic disturbances

We address the problem of finite horizon optimal control of discrete-time linear systems with input constraints and uncertainty. The uncertainty for the problem analysed is related to incomplete state information (output feedback) and stochastic disturbances. We analyse the complexities associated with finding optimal solutions. We also consider two suboptimal strategies that could be employed for larger optimization horizons.