Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Is the matching function Cobb-Douglas?

[cat] Estudiem les propietats teòriques que una funció d.emparellament ha de satisfer per tal de representar un mercat laboral amb friccions dins d'un model d'equilibri general amb emparellament aleatori. Analitzem el cas Cobb-Douglas, CES i altres formes funcionals per a la funció d.emparellament. Els nostres resultats estableixen restriccions sobre els paràmetres d'aquests formes funcionals per assegurar que l.equilibri és interior. Aquestes restriccions aporten raons teòriques per escollir entre diverses formes funcionals i permeten dissenyar tests d'error d'especificació de model en els treballs empírics.

Is the matching function Cobb-Douglas?

[cat] Estudiem les propietats teòriques que una funció d.emparellament ha de satisfer per tal de representar un mercat laboral amb friccions dins d'un model d'equilibri general amb emparellament aleatori. Analitzem el cas Cobb-Douglas, CES i altres formes funcionals per a la funció d.emparellament. Els nostres resultats estableixen restriccions sobre els paràmetres d'aquests formes funcionals per assegurar que l.equilibri és interior. Aquestes restriccions aporten raons teòriques per escollir entre diverses formes funcionals i permeten dissenyar tests d'error d'especificació de model en els treballs empírics.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Portfolio efficiency tests with conditioning information using empirical likelihood estimation

We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolios efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family presents some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase as more moment conditions are included, which is expected in conditional efficiency analysis. We found some evidences that estimators from GEL class really performs differently in small samples, where efficiency tests using GEL generate lower estimates compared to tests using the standard approach with GMM. With Monte Carlo experiments we see that GEL has better performance when distortions are present in data, especially under heavy tails and Gaussian shocks.

Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Assessment Of The Fixation Of Mandibular Symphysis Fractures Using Conical Cannulated Screws: Mechanical And Photoelastic Tests.

The aim of this study was to use mechanical and photoelastic tests to compare the performance of cannulated screws with other fixation methods in mandibular symphysis fractures. Ten polyurethane mandibles were allocated to each group and fixed as follows: group PRP, 2 perpendicular miniplates; group PLL, 1 miniplate and 1 plate, parallel; and group CS, 2 cannulated screws. Vertical linear loading tests were performed. The differences between mean values were analyzed with the Tukey test. The photoelastic test was carried out using a polariscope. The results revealed differences between the CS and PRP groups at 1, 3, 5, and 10 millimeters of displacement. The photoelastic test confirmed higher stress concentration in all groups close to the mandibular base, whereas the CS group showed it throughout the region assessed. Conical cannulated screws performed well in mechanical and photoelastic tests.

Usefulness Of Vaginal Cytology Tests In Women With Previous Hysterectomy For Benign Diseases: Assessment Of 53,891 Tests.

To assess the value of vaginal screening cytology after hysterectomy for benign disease. This cross-sectional study used cytology audit data from 2,512,039 screening tests in the metropolitan region of Campinas from 2000 to 2012; the object was to compare the prevalence of abnormal tests in women who had undergone a hysterectomy for benign diseases (n=53,891) to that of women who had had no hysterectomy. Prevalence ratios (95% confidence intervals, 95% CI) were determined, and chi-square analysis, modified by the Cochrane-Armitage test for trend, was used to investigate the effects of age. The prevalence of atypical squamous cells (ASC), low-grade squamous intraepithelial lesion (LSIL), and high-grade squamous intraepithelial lesion or squamous-cell carcinoma (HSIL/SCC) was 0.13%, 0.04% and 0.03%, respectively, in women who had undergone hysterectomy, and 0.93%, 0.51% and 0.26% in women who had not undergone hysterectomy. The prevalence ratios for ASC, LSIL and HSIL/SCC were 0.14 (0.11-0.17), 0.08 (0.06-0.13) and 0.13 (0.08-0.20), respectively, in women with a hysterectomy versus those without. For HSIL/SCC, the prevalence ratios were 0.09 and 0.29, respectively, for women <50 or ≥50years. The prevalence rates in women with a previous hysterectomy showed no significant variation with age. The prevalence rates of ASC, LSIL and HSIL/SCC were significantly lower in women with a previous hysterectomy for benign disease compared with those observed in women with an intact uterine cervix. This study reinforces the view that there is no evidence that cytological screening is beneficial for women who have had a hysterectomy for benign disease.

Testes de desempenho aeróbio relacionados a intensidades de corrida em treinamento e competição para fundistas de alto rendimento = : Aerobic performance tests related to training and competition running intensities for high performance distance runners

Universidade Estadual de Campinas . Faculdade de Educação Física

Validation of an experimental polyurethane model for biomechanical studies on implant supported prosthesis - tension tests

OBJECTIVES: The complexity and heterogeneity of human bone, as well as ethical issues, frequently hinder the development of clinical trials. The purpose of this in vitro study was to determine the modulus of elasticity of a polyurethane isotropic experimental model via tension tests, comparing the results to those reported in the literature for mandibular bone, in order to validate the use of such a model in lieu of mandibular bone in biomechanical studies. MATERIAL AND METHODS: Forty-five polyurethane test specimens were divided into 3 groups of 15 specimens each, according to the ratio (A/B) of polyurethane reagents (PU-1: 1/0.5, PU-2: 1/1, PU-3: 1/1.5). RESULTS: Tension tests were performed in each experimental group and the modulus of elasticity values found were 192.98 MPa (SD=57.20) for PU-1, 347.90 MPa (SD=109.54) for PU-2 and 304.64 MPa (SD=25.48) for PU-3. CONCLUSION: The concentration of choice for building the experimental model was 1/1.

Validation of an experimental polyurethane model for biomechanical studies on implant-supported prosthesis: compression tests

OBJECTIVES: The complexity and heterogeneity of human bone, as well as ethical issues, most always hinder the performance of clinical trials. Thus, in vitro studies become an important source of information for the understanding of biomechanical events on implant-supported prostheses, although study results cannot be considered reliable unless validation studies are conducted. The purpose of this work was to validate an artificial experimental model based on its modulus of elasticity, to simulate the performance of human bone in vivo in biomechanical studies of implant-supported prostheses. MATERIAL AND METHODS: In this study, fast-curing polyurethane (F16 polyurethane, Axson) was used to build 40 specimens that were divided into five groups. The following reagent ratios (part A/part B) were used: Group A (0.5/1.0), Group B (0.8/1.0), Group C (1.0/1.0), Group D (1.2/1.0), and Group E (1.5/1.0). A universal testing machine (Kratos model K - 2000 MP) was used to measure modulus of elasticity values by compression. RESULTS: Mean modulus of elasticity values were: Group A - 389.72 MPa, Group B - 529.19 MPa, Group C - 571.11 MPa, Group D - 470.35 MPa, Group E - 437.36 MPa. CONCLUSION: The best mechanical characteristics and modulus of elasticity value comparable to that of human trabecular bone were obtained when A/B ratio was 1:1.

Evaluating resin-enamel bonds by microshear and microtensile bond strength tests: effects of composite resin

OBJECTIVES: The aims of this study were to evaluate the effect of resin composite (Filtek Z250 and Filtek Flow Z350) and adhesive system [(Solobond Plus, Futurabond NR (VOCO) and Adper Single Bond (3M ESPE)] on the microtensile (μTBS) and microshear bond strength (μSBS) tests on enamel, and to correlate the bond strength means between them. MATERIAL AND METHODS: Thirty-six extracted human molars were sectioned to obtain two tooth halves: one for μTBS and the other one for μSBS. Adhesive systems and resin composites were applied to the enamel ground surfaces and light-cured. After storage (37(0)C/24 h) specimens were stressed (0.5 mm/min). Fracture modes were analyzed under scanning electron microscopy. The data were analyzed using two-way ANOVA and Tukey's test (α=0.05). RESULTS: The correlation between tests was estimated with Pearson's product-moment correlation statistics (α =0.05). For both tests only the main factor resin composite was statistically significant (p<0.05). The correlation test detected a positive (r=0.91) and significant (p=0.01) correlation between the tests. CONCLUSIONS: The results were more influenced by the resin type than by the adhesives. Both microbond tests seem to be positive and linearly correlated and can therefore lead to similar conclusions.

Characterization of aqueous silver nitrate solutions for leakage tests

OBJECTIVE: To determine the pH over a period of 168 h and the ionic silver content in various concentrations and post-preparation times of aqueous silver nitrate solutions. Also, the possible effects of these factors on microleakage test in adhesive/resin restorations in primary and permanent teeth were evaluated. MATERIAL AND METHODS: A digital pHmeter was used for measuring the pH of the solutions prepared with three types of water (purified, deionized or distilled) and three brands of silver nitrate salt (Merck, Synth or Cennabras) at 0, 1, 2, 24, 48, 72, 96 and 168 h after preparation, and storage in transparent or dark bottles. Ionic silver was assayed according to the post-preparation times (2, 24, 48, 72, 96, 168 h) and concentrations (1, 5, 25, 50%) of solutions by atomic emission spectrometry. For each sample of each condition, three readings were obtained for calculating the mean value. Class V cavities were prepared with enamel margins on primary and permanent teeth and restored with the adhesive systems OptiBond FL or OptiBond SOLO Plus SE and the composite resin Filtek Z-250. After nail polish coverage, the permanent teeth were immersed in 25% or 50% AgNO3 solution and the primary teeth in 5% or 50% AgNO3 solutions for microleakage evaluation. ANOVA and the Tukey's test were used for data analyses (α=5%). RESULTS: The mean pH of the solutions ranged from neutral to alkaline (7.9±2.2 to 11.8±0.9). Mean ionic silver content differed depending on the concentration of the solution (4.75±0.5 to 293±15.3 ppm). In the microleakage test, significant difference was only observed for the adhesive system factor (p=0.000). CONCLUSIONS: Under the tested experimental conditions and based on the obtained results, it may be concluded that the aqueous AgNO3 solutions: have neutral/alkaline pH and service life of up to 168 h; the level of ionic silver is proportional to the concentration of the solution; even at 5% concentration, the solutions were capable of indicating loss of marginal seal in the composite restorations; the 3-step conventional adhesive system had better performance regarding microleakage in enamel on primary and permanent teeth.

Dose-response effects of systemic anandamide administration in mice sequentially submitted to the open field and elevated plus-maze tests

The endocannabinoid system is involved in the control of many physiological functions, including the control of emotional states. In rodents, previous exposure to an open field increases the anxiety-like behavior in the elevated plus-maze. Anxiolytic-like effects of pharmacological compounds that increase endocannabinoid levels have been well documented. However, these effects are more evident in animals with high anxiety levels. Several studies have described characteristic inverted U-shaped dose-response effects of drugs that modulate the endocannabinoid levels. However, there are no studies showing the effects of different doses of exogenous anandamide, an endocannabinoid, in animal models of anxiety. Thus, in the present study, we determined the dose-response effects of exogenous anandamide at doses of 0.01, 0.1, and 1.0 mg/kg in C57BL/6 mice (N = 10/group) sequentially submitted to the open field and elevated plus-maze. Anandamide was diluted in 0.9% saline, ethyl alcohol, Emulphor® (18:1:1) and administered ip (0.1 mL/10 g body weight); control animals received the same volume of anandamide vehicle. Anandamide at the dose of 0.1 mg/kg (but not of 0.01 or 1 mg/kg) increased (P < 0.05) the time spent and the distance covered in the central zone of the open field, as well as the exploration of the open arms of the elevated plus-maze. Thus, exogenous anandamide, like pharmacological compounds that increase endocannabinoid levels, promoted a characteristic inverted U-shaped dose-response effect in animal models of anxiety. Furthermore, anandamide (0.1 mg/kg) induced an anxiolytic-like effect in the elevated plus-maze (P < 0.05) after exposing the animals to the open field test.