Convex combinations of long memory estimates from different sampling rates

Convex combinations of long memory estimates using the same data observed at different sampling rates can decrease the standard deviation of the estimates, at the cost of inducing a slight bias. The convex combination of such estimates requires a preliminary correction for the bias observed at lower sampling rates, reported by Souza and Smith (2002). Through Monte Carlo simulations, we investigate the bias and the standard deviation of the combined estimates, as well as the root mean squared error (RMSE), which takes both into account. While comparing the results of standard methods and their combined versions, the latter achieve lower RMSE, for the two semi-parametric estimators under study (by about 30% on average for ARFIMA(0,d,0) series).

Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.

Microeconomic instability and children's human capital accumulation: the effects of idiosyncratic shocks to father's income on child labor, school drop-outs and repetition rates in Brazil

This paper evaluates the long-run effects of economic instability. In particular, we study the impact of idiosyncratic shocks to father’s income on children’s human capital accumulation variables such as school drop-outs, repetition rates and domestic and non-domestic labor. Although, the problem of child labor in Brazil has declined greatly during the last decade, the number of children working is still substantial. The low levels of educational attainment in Brazil are also a main cause for concern. The large rotating panel data set used allows for the estimation of the impacts of changes in occupational and income status of fathers on changes in his child’s time allocation circumstances. The empirical analysis is restricted to families with fathers, mothers and at least one child between 10 and 15 years of age in the main Brazilian metropolitan areas during the 1982-1999 period. We perform logistic regressions controlling for child characteristics (gender, age, if he/she is behind in school for age), parents characteristics (grade attainment and income) and time and location variables. The main variables analyzed are dynamic proxies of impulses and responses, namely: shocks to household head’s income and unemployment status, on the one hand and child’s probability of dropping out of school, of repeating a grade and of start working, on the other. The findings suggest that father’s income has a significant positive correlation with child’s dropping out of school and of repeating a grade. The findings do not suggest a significant relationship between a father’s becoming unemployed and a child entering the non-domestic labor market. However, the results demonstrate a significant positive relationship between a father becoming unemployed and a child beginning to work in domestic labor. There was also a positive correlation between father becoming unemployed and a child dropping out and repeating a grade. Both gender and age were highly significant with boys and older children being more likely to work, drop-out and repeat grades.

Endogenous wage compression and aggregation boundaries in a model of hierarchical human capital

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Temporal aggregation and bandwidth selection in estimating long memory

This paper reinterprets results of Ohanissian et al (2003) to show the asymptotic equivalence of temporally aggregating series and using less bandwidth in estimating long memory by Geweke and Porter-Hudak’s (1983) estimator, provided that the same number of periodogram ordinates is used in both cases. This equivalence is in the sense that their joint distribution is asymptotically normal with common mean and variance and unity correlation. Furthermore, I prove that the same applies to the estimator of Robinson (1995). Monte Carlo simulations show that this asymptotic equivalence is a good approximation in finite samples. Moreover, a real example with the daily US Dollar/French Franc exchange rate series is provided.

Career concerns: a human capital perspective

We introduce human capital accumulation, in the form of learning by doing, in a life cycle model of career concerns and analyze how human capital acquisition a ects implicit incentives for performance. We show that standard results from the career concerns literature can be reversed in the presence of human capital accumulation. Namely, implicit incentives need not decrease over time and may decrease with the degree of uncertainty about an individual's talent. Furthermore, increasing the pre-cision of output measurement can weaken rather than strengthen implicit incentives. Overall, our results contribute to shed new light on the ability of markets to discipline moral hazard in the absence of explicit contracts linking pay to performance.

Spectral properties of temporally aggregated long memory processes

This paper derives the spectral density function of aggregated long memory processes in light of the aliasing effect. The results are different from previous analyses in the literature and a small simulation exercise provides evidence in our favour. The main result point to that flow aggregates from long memory processes shall be less biased than stock ones, although both retain the degree of long memory. This result is illustrated with the daily US Dollar/ French Franc exchange rate series.

Understanding the critical distance in sparse distributed memory

Modelos de tomada de decisão necessitam refletir os aspectos da psi- cologia humana. Com este objetivo, este trabalho é baseado na Sparse Distributed Memory (SDM), um modelo psicologicamente e neuro- cientificamente plausível da memória humana, publicado por Pentti Kanerva, em 1988. O modelo de Kanerva possui um ponto crítico: um item de memória aquém deste ponto é rapidamente encontrado, e items além do ponto crítico não o são. Kanerva calculou este ponto para um caso especial com um seleto conjunto de parâmetros (fixos). Neste trabalho estendemos o conhecimento deste ponto crítico, através de simulações computacionais, e analisamos o comportamento desta “Critical Distance” sob diferentes cenários: em diferentes dimensões; em diferentes números de items armazenados na memória; e em diferentes números de armazenamento do item. Também é derivada uma função que, quando minimizada, determina o valor da “Critical Distance” de acordo com o estado da memória. Um objetivo secundário do trabalho é apresentar a SDM de forma simples e intuitiva para que pesquisadores de outras áreas possam imaginar como ela pode ajudá-los a entender e a resolver seus problemas.

Human resource policies in public education: empirical evidences for Brazil

Esta tese traz três exercícios empíricos sobre questões de recursos humanos em escolas públicas brasileiras, aproveitando-se de uma ampla política implantada na rede estadual de São Paulo. Esta política aumenta os salários para os professores que trabalham em escolas urbanas pobres e sua regra de alocação, baseada em um corte arbitrário em um índice socioeconômico, permite a identificação de impactos causais. Em resumo, os três artigos apontam que políticas de subsídios são capazes de, de fato, manter professores nas escolas mais pobres e este efeito, por sua vez, melhora o desempenho acadêmico dos alunos. Além disso, concluímos também que esta política também reduz o absenteísmo dos professores. No entanto, como consequência do desenho dessa política, não há evidências de que o subsídio melhora o perfil dos professores alocados nessas escolas. O primeiro artigo avalia os impactos dessa política sobre a rotatividade dos professores. Concluímos que a compensação salarial reduziu a taxa de rotatividade em 7,2 pontos percentuais, o que significa uma queda de 15% sobre a média pré-tratamento. Em um modelo em forma reduzida, encontramos também evidências de que esta política pode impactar positivamente o desempenho dos alunos. O segundo artigo analisa os impactos sobre a aprendizagem dos alunos, com foco em três possíveis mecanismos: i) a rotatividade; ii) a qualidade dos professores; iii) o aumento do salário. As estimativas mostram que o único canal através do qual esta política compensatória afeta o desempenho dos alunos é a redução da rotatividade dos professores. Ao reduzir taxa de volume de negócios em um desvio-padrão, a política reduziu a proporção de alunos de baixo desempenho em cerca de meio desvio-padrão. O terceiro artigo avalia como a diferenciação salarial criada por esta política afeta absenteísmo dos professores. Os resultados mostram que, após controlar efeitos fixos de professores e escolas, pagar um salário mais elevado (em média 26% a mais) provoca uma queda de 8-22% nas faltas dos professores. Ausências que não levam a desconto de salário, como por licenças médicas, não respondem à diferenciação salarial e o impacto é maior para os professores que recebem maior incentivo.

Fenótipo neuropsicológico de adolescentes com síndrome de Down

This research aimed to contribute to the characterization of a neuropsychological phenotype of adolescents with Down Syndrome (DS). A multicases study of six adolescents (three males and three females, aged 13 to 14 years) diagnosed with DS and treated at two institutions in the city of Natal (Brazil), was conducted. Participants were assessed using the methodological approach developed by Luria, which is composed by four complementary stages. The first one aimed to investigate the qualitative impact of DS in school life and social development of the adolescents; dimensions of behavior and social-affective aspects of the members of the study were investigated. In the second stage participants performed a battery of neuropsychological tests in order to identify strengths and weaknesses in their cognitive functioning. The third stage was incorporated into the second in order to analyze the quality of the activity of the participants along the quantitative evaluation, highlighting strategies used, errors produced among other indicators. Lastly, the fourth stage refers to the intervention with the participants. Although this is not a specific objective of the study, it is argued that the outcome of this research will subsidize the practice of different professionals working with this clinical group. The results of the first stage emphasized the presence of difficulties in social relationships and in school life of observed adolescents. In turn, the second and third stages pointed out to the presence of difficulties in tasks involving logical and abstract thinking, as well as difficulties in expressive language. In relation to visual memory, we observed a better performance in activities of lower complexity, ie, with less interference of executive functioning, particularly in terms of the functions of planning and initiative. Finally, it was found motor and mental retardation, affecting significantly the performance related to different cognitive areas. The results highlighted here can be considered as subsidies for future interventions, suggesting the need for developping projects that take into account different aspects constituents of the human subject, involving not only the individual with developmental changes, as well as their families, teachers, schools and society in general

Modeling and Experimental Aspects of Self-healing Bolted Joint through Shape Memory Alloy Actuators

Bolted joints are a form of mechanical coupling largely used in machinery due to their reliability and low cost. Failure of bolted joints can lead to catastrophic events, such as leaking, train derailments, aircraft crashes, etc. Most of these failures occur due to the reduction of the pre-load, induced by mechanical vibration or human errors in the assembly or maintenance process. This article investigates the application of shape memory alloy (SMA) washers as an actuator to increase the pre-load on loosened bolted joints. The application of SMA washer follows a structural health monitoring procedure to identify a damage (reduction in pre-load) occurrence. In this article, a thermo-mechanical model is presented to predict the final pre-load achieved using this kind of actuator, based on the heat input and SMA washer dimension. This model extends and improves on the previous model of Ghorashi and Inman [2004, "Shape Memory Alloy in Tension and Compression and its Application as Clamping Force Actuator in a Bolted Joint: Part 2 - Modeling," J. Intell. Mater. Syst. Struct., 15:589-600], by eliminating the pre-load term related to nut turning making the system more practical. This complete model is a powerful but complex tool to be used by designers. A novel modeling approach for self-healing bolted joints based on curve fitting of experimental data is presented. The article concludes with an experimental application that leads to a change in joint assembly to increase the system reliability, by removing the ceramic washer component. Further research topics are also suggested.

Astrocytes and human cognition: Modeling information integration and modulation of neuronal activity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Proliferating cell nuclear antigen (PCNA) in non-Hodgkin's lymphomas: Correlation with working formulation and Kiel classification in formalin-fixed paraffin-embedded material

PCNA is a 36-KD proliferating cell nuclear antigen associated with the cell cycle. The immunocytochemical detection of PCNA represents a useful tool for the study of tumor proliferation activity. This study documents the detection of PCNA, using antibody PC 10 in formalin-fixed, paraffin-embedded tissue, and correlates the proliferative activity of the non-Hodgkin's lymphomas (NHL) with histological grading assessed by the International Working Formulation (WF) and Kiel classification. In 92 cases of NHLs we found a strong correlation between the PCNA index and lymphoma grading. Statistically significant differences were also found between the proliferative index (PI) in low and high grade lymphomas according to the Kiel classification (t = 9.519; p < 0.001) and between low, intermediate and high grade lymphomas according to the WF classification (F = 79.01; p < 0.001). In the Kiel classification the mean of low grade lymphomas was 39.5% and of high grade 75.7%. In the WF the average of low grade lymphomas was 29.7%, intermediate 53.1% and high 75.1%. Although the differences among the groups had been significant, we found variations inside each histological subgroup in both classifications. The intermediate lymphomas were the most heterogeneous group, with PI inside the same histologic subtypes coincident with low and high grade lymphomas. Since PCNA may be used as a marker of cell proliferation in clinical studies to estimate the biological aggressiveness of lymphomas, its determination in intermediate grade NHL could be very useful to evaluate individual cases in this group and determine prognosis and probably the appropriate therapy.