We analyse the Swedish central bank, the Riksbank’s, interest setting policy in a Taylor rule framework. In particular, we examine whether or not the Riksbank has reacted to fluctuations in asset prices during the period 1995:Q1 to 2016:Q2. This is done by estimating a forward-looking Taylor rule with interest rate smoothing, augmented with stock prices, house prices and the real exchange rate, using IV GMM. In general, we find that the Riksbank’s interest setting policy is well described by a forward-looking Taylor rule with interest rate smoothing and that the use of factors as instruments, derived from a PCA, serves to alleviate the weak-identification problem that tend to plague GMM. Moreover, apart from finding evidence that the Riksbank exhibit a substantial degree of policy rate inertia and has acted so as to stabilize inflation and the real economy, we also find evidence that the Riksbank has been reacting to fluctuations in stock prices, house prices, and the real exchange rate.

The thesis investigates the nature of the relationship between the banking sector depth and long-term economic growth in the Gulf Cooperation Council (GCC) States, assesses the banking sector development status in each of the States, and underlines the policy implications in the light of the banking-growth nexus and the banking development benchmarking models’ findings for the region by undertaking three projects. The thesis examines the nature of the relationship between banking sector depth and long-term economic growth in the NRBC—as a proxy for the GCC States— vis-à-vis the rest of the world countries. For the empirical investigation, a dynamic panel data approach, i.e. Generalised Method of Moments (GMM), is adopted over the period 1961 to 2013. By utilising mixed effects and System GMM frameworks, the research identifies the countries with the strongest banking-growth relationships and establishes the banking sector development determinants in those countries. Employing a novel benchmarking process, the thesis assesses the status of the banking sector development in each of the GCC member countries and simulates the change in the banking sector depth across the Gulf region over a period of ten years to highlight the potential policy implications for the sector development. The findings of the thesis suggest that the relationship between banking sector depth and long-term economic growth in the NRBC is non-linear, where the relationship between the banking sector depth and economic growth turns from positive to negative beyond certain levels of sector depth. In comparison to other countries, the results indicate that the banking-growth nexus in the NRBC exhibits a smaller total effect magnitude as well as a shorter time between the change in the sector depth and its effect on economic growth. The benchmarking of the banking sectors in the GCC region suggests that in five of the six member countries the banking sectors are underdeveloped. The simulation results predict that the banking sectors will develop further in half of the countries in the region, given their current levels of banking sector development determinants, while two countries require reforms in terms of undertaking regulations and policies to avoid seeing their sector development levels deteriorate. The thesis contributes to theory by confirming findings in the literature and expanding the body of knowledge through novel findings. This research also contributes to policy by demonstrating the significance of the banking sector development for long-term economic growth in the NRBC, providing policymakers in the Gulf States with the status of their banking sectors, and underlining the banking sector depth determinants that ought to be considered when setting regulations and policies that are aimed at developing the banking sector further.

A common problem in regression analysis is that some covariates are measured with errors. In this dissertation we present simulation-based approach to estimation in two popular regression models with a categorical response variable and classical measurement errors in covariates. The first model is the regression model with a binary response variable. The second one is the proportional odds regression with an ordinal response variable. In both regression models we consider method of moments estimators for therein unknown parameters that are defined via minimizing respective objective functions. The later functions involve multiple integrals and make obtaining of such estimators unfeasible. To overcome this computational difficulty, we propose Simulation-Based Estimators (SBE). This method does not require parametric assumptions for the distributions of the unobserved covariates and error components. We prove consistency and asymptotic normality of the proposed SBE's under some regularity conditions. We also examine the performance of the SBE's in finite-sample situations through simulation studies and two real data sets: the data set from the AIDS Clinical Trial Group (ACTG175) study for our logistic and probit regression models and one from the Adult Literacy and Life Skills (ALL) Survey for our regression model with the ordinal response variable and mismeasured covariates. / October 2016

Supply and demand in the World oil market are balanced through responses to price movement with considerable complexity in the evolution of underlying supply-demand expectation process. In order to be able to understand the price balancing process, it is important to know the economic forces and the behavior of energy commodity spot price processes. The relationship between the different energy sources and its utility together with uncertainty also play a role in many important energy issues. The qualitative and quantitative behavior of energy commodities in which the trend in price of one commodity coincides with the trend in price of other commodities, have always raised the questions regarding their interactions. Moreover, if there is any interaction, then one would like to know the extent of influence on each other. In this work, we undertake the study to shed a light on the above highlighted processes and issues. The presented study systematically deals with the development of stochastic dynamic models and mathematical, statistical and computational analysis of energy commodity spot price and interaction processes. Below we list the main components of the research carried out in this dissertation. (1) Employing basic economic principles, interconnected deterministic and stochastic models of linear log-spot and expected log-spot price processes coupled with non-linear volatility process are initiated. (2) Closed form solutions of the models are analyzed. (3) Introducing a change of probability measure, a risk-neutral interconnected stochastic model is derived. (4) Furthermore, under the risk-neutral measure, expectation of the square of volatility is reduced to a continuous-time deterministic delay differential equation. (5) The by-product of this exhibits the hereditary effects on the mean-square volatility process. (6) Using a numerical scheme, a time-series model is developed and utilized to estimate the state and parameters of the dynamic model. In fact, the developed time-series model includes the extended GARCH model as special case. (7) Using the Henry Hub natural gas data set, the usefulness of the linear interconnected stochastic models is outlined. (8) Using natural and basic economic ideas, interconnected deterministic and stochastic models in (1) are extended to non-linear log-spot price, expected log-spot price and volatility processes. (9) The presented extended models are validated. (10) Closed form solution and risk-neutral models of (8) are outlined. (11) To exhibit the usefulness of the non-linear interconnected stochastic model, to increase the efficiency and to reduce the magnitude of error, it was essential to develop a modified version of extended Kalman filtering approach. The modified approach exhibits the reduction of magnitude of error. Furthermore, Henry Hub natural gas data set is used to show the advantages of the non-linear interconnected stochastic model. (12) Parameter and state estimation problems of continuous time non-linear stochastic dynamic process is motivated to initiate an alternative innovative approach. This led to introduce the concept of statistic processes, namely, local sample mean and sample variance. (13) Then it led to the development of an interconnected discrete-time dynamic system of local statistic processes and (14) its mathematical model. (15) This paved the way for developing an innovative approach referred as Local Lagged adapted Generalized Method of Moments (LLGMM). This approach exhibits the balance between model specification and model prescription of continuous time dynamic processes. (16) In addition, it motivated to initiate conceptual computational state and parameter estimation and simulation schemes that generates a mean square sub-optimal procedure. (17) The usefulness of this approach is illustrated by applying this technique to four energy commodity data sets, the U. S. Treasury Bill Yield Interest Rate and the U.S. Eurocurrency Exchange Rate data sets for state and parameter estimation problems. (18) Moreover, the forecasting and confidence-interval problems are also investigated. (19) The non-linear interconnected stochastic model (8) was further extended to multivariate interconnected energy commodities and sources with and without external random intervention processes. (20) Moreover, it was essential to extend the interconnected discrete-time dynamic system of local sample mean and variance processes to multivariate discrete-time dynamic system. (21) Extending the LLGMM approach in (15) to a multivariate interconnected stochastic dynamic model under intervention process, the parameters in the multivariate interconnected stochastic model are estimated. These estimated parameters help in analyzing the short term and long term relationship between the energy commodities. These developed results are applied to the Henry Hub natural gas, crude oil and coal data sets.

In high frequency computational electromagnetics, rigorous numerical methods be come unrealistic tools due to computational demand increasing with the frequency. Instead approximations to the solutions of the Maxwell equations can be employed to evaluate th electromagnetic fields. In this thesis, we present the implementations of three high frequency approximat methods. The first two, namely the Geometrical Theory of Diffraction (GTD) and th Physical Optics (PO), are commonly used approximations. The third is a new invention that will be referred to as the Surface Current Extraction-Extrapolation (SCEE). Specifically, the GTD solver is a flexible and modular software package which use Non-Uniform Rational B-spline (NURBS) surfaces to model complex geometries. The PO solver is based on a triangular description of the surfaces and includes fas shadowing by ray tracing as well as contribution from edges to the scattered fields. GTD ray tracing was combined with the PO solver by a well thought-out software architecture Both implementations are now part of the GEMS software suite, the General ElectroMag netic Solvers, which incorporates state-of-the-art numerical methods. During validations both GTD and PO techniques turned out not to be accurate enough to meet the indus trial standards, thus creating the need for a new fast approximate method providing bette control of the approximations. In the SCEE approach, we construct high frequency approximate surface currents ex trapolated from rigourous Method of Moments (MoM) models at lower frequency. T do so, the low frequency currents are projected onto special basis vectors defined on th surface relative to the direction of the incident magnetic field. In such configuration, w observe that each component displays systematic spatial patterns evolving over frequenc in close correlation with the incident magnetic field, thus allowing us to formulate a fre quency model for each component. This new approach is fast, provides good control of th error and represents a platform for future development of high frequency approximations. As an application, we have used these tools to analyse the radar detectability of a new marine distress signaling device. The device, called "Rescue-Wing", works as an inflatabl radar reflector designed to provide a strong radar echo useful for detection and positionin during rescue operations of persons missing at sea. / QC 20101004

The characteristics of slotted circular waveguides with different dimensions, including cutoff frequencies of TE and TM modes, impedance and modal field distributions will be analyzed using the generalized spectral domain approach. The Method of Moment will be applied, basis functions that include the edge conditions will be used and a computer program will be developed. Obtained results will be presented for different number, depth and thickness of coupling slots, and compared with available data to demonstrate the accuracy and the efficiency of the approach. Plots of the electric and magnetic field lines corresponding to the dominant as well as a number of higher order modes will be presented for quadruple ridge case.

Full wave analysis of microstrip lines at microwave frequencies is performed by using method of moments in conjunction with closed-form spatial domain Green&rsquo / s functions. The Green&rsquo / s functions are in general Sommerfeld-type integrals which are computationally expensive. To improve the efficiency of the technique, Green&rsquo / s functions are approximated by their closed-forms. Microstrip lines are excited by arbitrarily located current sources and are terminated by complex loads at both ends. Current distributions over microstrip lines are represented by rooftop basis functions. At first step, the current distribution over a single microstrip line is calculated. Next, the calculation of the current distributions over coupled microstrip lines is performed. The technique is then, applied to directional couplers. Using the current distributions obtained by the analysis, the scattering parameters of the structures are evaluated by using Prony&rsquo / s method. The results are compared with the ones gathered by using simulation software tools, CNL/2&trade / and Agilent Advanced Design System&trade / (ADS).

The main objective of this dissertation is to develop large-eddy simulation (LES) based computational tools for supersonic inlet and combustor design. In the recent past, LES methodology has emerged as a viable tool for modeling turbulent combustion. LES computes the large scale mixing process accurately, thereby providing a better starting point for small-scale models that describe the combustion process. In fact, combustion models developed in the context of Reynolds-averaged Navier Stokes (RANS) equations exhibit better predictive capability when used in the LES framework. The development of a predictive computational tool based on LES will provide a significant boost to the design of scramjet engines. Although LES has been used widely in the simulation of subsonic turbulent flows, its application to high-speed flows has been hampered by a variety of modeling and numerical issues. In this work, we develop a comprehensive LES methodology for supersonic flows, focusing on the simulation of scramjet engine components. This work is divided into three sections. First, a robust compressible flow solver for a generalized high-speed flow configuration is developed. By using carefully designed numerical schemes, dissipative errors associated with discretization methods for high-speed flows are minimized. Multiblock and immersed boundary method are used to handle scramjet-specific geometries. Second, a new combustion model for compressible reactive flows is developed. Subsonic combustion models are not directly applicable in high-speed flows due to the coupling between the energy and velocity fields. Here, a probability density function (PDF) approach is developed for high-speed combustion. This method requires solution to a high dimensional PDF transport equation, which is achieved through a novel direct quadrature method of moments (DQMOM). The combustion model is validated using experiments on supersonic reacting flows. Finally, the LES methodology is used to study the inlet-isolator component of a dual-mode scramjet. The isolator is a critical component that maintains the compression shock structures required for stable combustor operation in ramjet mode. We simulate unsteady dynamics inside an experimental isolator, including the propagation of an unstart event that leads to loss of compression. Using a suite of simulations, the sensitivity of the results to LES models and numerical implementation is studied. / text

Efficient electromagnetic solvers based on surface integral equations (SIEs) are developed for the analysis of scattering from large-scale and complex composite structures that consist of piecewise homogeneous magnetodielectric and perfect electrically/magnetically conducting (PEC/PMC) regions. First, a multiple-grid extension of the adaptive integral method (AIM) is presented for multi-region problems. The proposed method accelerates the iterative method-of-moments solution of the pertinent SIEs by employing multiple auxiliary Cartesian grids: If the structure of interest is composed of K homogeneous regions, it introduces K different auxiliary grids. It uses the k^{th} auxiliary grid first to determine near-zones for the basis functions and then to execute AIM projection/anterpolation, propagation, interpolation, and near-zone pre-correction stages in the k^{th} region. Thus, the AIM stages are executed a total of K times using different grids and different groups of basis functions. The proposed multiple-grid AIM scheme requires a total of O(N^{nz,near}+sum({N_k}^Clog{N_k}^C)) operations per iteration, where N^{nz,near} denotes the total number of near-zone interactions in all regions and {N_k}^C denotes the number of nodes of the k^{th} Cartesian grid. Numerical results validate the method’s accuracy and reduced complexity for large-scale canonical structures with large numbers of regions (up to 10^6 degrees of freedom and 10^3 regions). Then, a Green function modification approach and a scheme of Hankel- to Teoplitz-matrix conversions are efficiently incorporated to the multiple-grid AIM method to account for a PEC/PMC plane. Theoretical analysis and numerical examples show that, compared to a brute-force imaging scheme, the Green function modification approach reduces the simulation time and memory requirement by a factor of (almost) two or larger if the structure of interest is terminated on or resides above the plane, respectively. In addition, the SIEs are extended to cover structures composed of metamaterial regions, PEC regions, and PEC-material junctions. Moreover, recently introduced well-conditioned SIEs are adopted to achieve faster iterative solver convergence. Comprehensive numerical tests are performed to evaluate the accuracy, computational complexity, and convergence of the novel formulation which is shown to significantly reduce the number of iterations and the overall computational work. Lastly, the efficiency and capabilities of the proposed solvers are demonstrated by solving complex scattering problems, specifically those pertinent to analysis of wave propagation in natural forested environments, the design of metamaterials, and the application of metamaterials to radar cross section reduction. / text

The Method of Moments (MoM) has been used extensively to solve electromagnetic problems. Its popularity is largely attributed to its adaptability to structures with various shapes and success in predicting the equivalent induced currents accurately. However, due to its dense matrix, especially for large structures, the MoM suffers from long matrix solution time and large storage requirement. In this thesis it is shown that use of wavelet basis functions result in a MoM matrix which is sparser than the one obtained by using traditional basis functions. A new wavelet system, different from the ones found in literature, is proposed. Stabilized Bi-Conjugate Gradient Method which is an iterative matrix solution method is utilized to solve the resulting sparse matrix equation. Both a one-dimensional problem with a microstrip line example and a two-dimensional problem with a rectangular patch antenna example are studied and the results are compared.