923 resultados para Applied Microeconometrics
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Thesis (Ph.D.)--University of Washington, 2016-08
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This Master Thesis consists of one theoretical article and one empirical article on the field of Microeconometrics. The first chapter\footnote{We also thank useful suggestions by Marinho Bertanha, Gabriel Cepaluni, Brigham Frandsen, Dalia Ghanem, Ricardo Masini, Marcela Mello, Áureo de Paula, Cristine Pinto, Edson Severnini and seminar participants at São Paulo School of Economics, the California Econometrics Conference 2015 and the 37\textsuperscript{th} Brazilian Meeting of Econometrics.}, called \emph{Synthetic Control Estimator: A Generalized Inference Procedure and Confidence Sets}, contributes to the literature about inference techniques of the Synthetic Control Method. This methodology was proposed to answer questions involving counterfactuals when only one treated unit and a few control units are observed. Although this method was applied in many empirical works, the formal theory behind its inference procedure is still an open question. In order to fulfill this lacuna, we make clear the sufficient hypotheses that guarantee the adequacy of Fisher's Exact Hypothesis Testing Procedure for panel data, allowing us to test any \emph{sharp null hypothesis} and, consequently, to propose a new way to estimate Confidence Sets for the Synthetic Control Estimator by inverting a test statistic, the first confidence set when we have access only to finite sample, aggregate level data whose cross-sectional dimension may be larger than its time dimension. Moreover, we analyze the size and the power of the proposed test with a Monte Carlo experiment and find that test statistics that use the synthetic control method outperforms test statistics commonly used in the evaluation literature. We also extend our framework for the cases when we observe more than one outcome of interest (simultaneous hypothesis testing) or more than one treated unit (pooled intervention effect) and when heteroskedasticity is present. The second chapter, called \emph{Free Economic Area of Manaus: An Impact Evaluation using the Synthetic Control Method}, is an empirical article. We apply the synthetic control method for Brazilian city-level data during the 20\textsuperscript{th} Century in order to evaluate the economic impact of the Free Economic Area of Manaus (FEAM). We find that this enterprise zone had positive significant effects on Real GDP per capita and Services Total Production per capita, but it also had negative significant effects on Agriculture Total Production per capita. Our results suggest that this subsidy policy achieve its goal of promoting regional economic growth, even though it may have provoked mis-allocation of resources among economic sectors.
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Adolescent idiopathic scoliosis (AIS) is the most common form of spinal deformity in paediatrics, prevalent in approximately 2-4% of the general population. While it is a complex three-dimensional deformity, it is clinically characterised by an abnormal lateral curvature of the spine. The treatment for severe deformity is surgical correction with the use of structural implants. Anterior single rod correction employs a solid rod connected to the anterior spine via vertebral body screws. Correction is achieved by applying compression between adjacent vertebral body screws, before locking each screw onto the rod. Biomechanical complication rates have been reported as high as 20.8%, and include rod breakage, screw pull-out and loss of correction. Currently, the corrective forces applied to the spine are unknown. These forces are important variables to consider in understanding the biomechanics of scoliosis correction. The purpose of this study was to measure these forces intra-operatively during anterior single rod AIS correction.
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This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.
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Inverse dynamics is the most comprehensive method that gives access to the net joint forces and moments during walking. However it is based on assumptions (i.e., rigid segments linked by ideal joints) and it is known to be sensitive to the input data (e.g., kinematic derivatives, positions of joint centres and centre of pressure, inertial parameters). Alternatively, transducers can be used to measure directly the load applied on the residuum of transfemoral amputees. So, the purpose of this study was to compare the forces and moments applied on a prosthetic knee measured directly with the ones calculated by three inverse dynamics computations - corresponding to 3 and 2 segments, and « ground reaction vector technique » - during the gait of one patient. The maximum RMSEs between the estimated and directly measured forces (i.e., 56 N) and moment (i.e., 5 N.m) were relatively small. However the dynamic outcomes of the prosthetic components (i.e., absorption of the foot, friction and limit stop of the knee) were only partially assessed with inverse dynamic methods.
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Despite the increasing popularity of social networking websites (SNWs), very little is known about the psychosocial variables which predict people’s use of these websites. The present study used an extended model of the theory of planned behaviour (TPB), including the additional variables of self-identity and belongingness, to predict high level SNW use intentions and behaviour in a sample of young people aged between 17 and 24 years. Additional analayses examined the impact of self-identity and belongingness on young people’s addictive tendencies towards SNWs. University students (N = 233) completed measures of the standard TPB constructs (attitude, subjective norm and perceived behavioural control), the additional predictor variables (self-identity and belongingness), demographic variables (age, gender, and past behaviour) and addictive tendencies. One week later, they reported their engagement in high level SNW use during the previous week. Regression analyses partially supported the TPB, as attitude and subjective norm signficantly predicted intentions to engage in high level SNW use with intention signficantly predicting behaviour. Self-identity, but not belongingness, signficantly contributed to the prediction of intention, and, unexpectedly, behaviour. Past behaviour also signficantly predicted intention and behaviour. Self-identity and belongingness signficantly predicted addictive tendencies toward SNWs. Overall, the present study revealed that high level SNW use is influenced by attitudinal, normative, and self-identity factors, findings which can be used to inform strategies that aim to modify young people’s high levels of use or addictive tendencies for SNWs.
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Matrix function approximation is a current focus of worldwide interest and finds application in a variety of areas of applied mathematics and statistics. In this thesis we focus on the approximation of A^(-α/2)b, where A ∈ ℝ^(n×n) is a large, sparse symmetric positive definite matrix and b ∈ ℝ^n is a vector. In particular, we will focus on matrix function techniques for sampling from Gaussian Markov random fields in applied statistics and the solution of fractional-in-space partial differential equations. Gaussian Markov random fields (GMRFs) are multivariate normal random variables characterised by a sparse precision (inverse covariance) matrix. GMRFs are popular models in computational spatial statistics as the sparse structure can be exploited, typically through the use of the sparse Cholesky decomposition, to construct fast sampling methods. It is well known, however, that for sufficiently large problems, iterative methods for solving linear systems outperform direct methods. Fractional-in-space partial differential equations arise in models of processes undergoing anomalous diffusion. Unfortunately, as the fractional Laplacian is a non-local operator, numerical methods based on the direct discretisation of these equations typically requires the solution of dense linear systems, which is impractical for fine discretisations. In this thesis, novel applications of Krylov subspace approximations to matrix functions for both of these problems are investigated. Matrix functions arise when sampling from a GMRF by noting that the Cholesky decomposition A = LL^T is, essentially, a `square root' of the precision matrix A. Therefore, we can replace the usual sampling method, which forms x = L^(-T)z, with x = A^(-1/2)z, where z is a vector of independent and identically distributed standard normal random variables. Similarly, the matrix transfer technique can be used to build solutions to the fractional Poisson equation of the form ϕn = A^(-α/2)b, where A is the finite difference approximation to the Laplacian. Hence both applications require the approximation of f(A)b, where f(t) = t^(-α/2) and A is sparse. In this thesis we will compare the Lanczos approximation, the shift-and-invert Lanczos approximation, the extended Krylov subspace method, rational approximations and the restarted Lanczos approximation for approximating matrix functions of this form. A number of new and novel results are presented in this thesis. Firstly, we prove the convergence of the matrix transfer technique for the solution of the fractional Poisson equation and we give conditions by which the finite difference discretisation can be replaced by other methods for discretising the Laplacian. We then investigate a number of methods for approximating matrix functions of the form A^(-α/2)b and investigate stopping criteria for these methods. In particular, we derive a new method for restarting the Lanczos approximation to f(A)b. We then apply these techniques to the problem of sampling from a GMRF and construct a full suite of methods for sampling conditioned on linear constraints and approximating the likelihood. Finally, we consider the problem of sampling from a generalised Matern random field, which combines our techniques for solving fractional-in-space partial differential equations with our method for sampling from GMRFs.
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Applied Theatre is an umbrella term for a range of drama-based techniques, all of which align with a lineage of pedagogical theory and practice: (e.g.) Freire, Moreno, Heathcote. It encompasses methods and forms including Drama Education (O’Neill); Forum Theatre (Boal); and Process Drama (Haseman, O’Toole). Applied theatre often occurs in non-theatrical settings (schools, hospitals, prisons) with the aim of helping participants address issues of local concern. Increasingly, Applied Theatre practices are utilised in the corporate environment. Appied Theatre adopts artistic principles in production, but posits a practical utility beyond simple entertainment.