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).

Práticas de avaliação nas escolas oficiais de 1. grau, em Manaus

Este trabalho visa a examinar as práticas de avaliação das escolas oficiais da cidade de Manaus que oferecem as quatro primeiras séries do Ensino de 1o Grau, com vistas a averiguar se a execução da avaliação está de acordo com as prescrições legais em vigor. Trata-se de estudo piloto exploratório feito no período de agosto a setembro de 1977, em escolas selecionadas por amostragem estratificada proporcional, tendo sido estudadas 50% das escolas da população alvo (em número de 25) nas quais foram envolvidos os diretores e os supervisores, bem como, 300 professores selecionados pelos diretores. Na coleta de dados foram utilizados dois questionários diferentes, um aplicado aos professores e outro aos supervisores, fazendo-se ainda uma entrevista individual semi-estruturada com os diretores das escolas envolvidas. Para reduzir as fontes de erro, a própria autora entregou e recolheu pessoalmente os questionários (obtendo uma taxa de retorno de 77%) e conduziu todas as entrevistas. A análise de dados focalizou as seguintes variáveis: o preparo do professor para realizar a avaliação prescrita pela legislação; as práticas de avaliação empregadas pelos professores; o tipo de orientação dada pelo supervisor ao professor no que se refere à avaliação da aprendizagem; e as condições oferecidas ao professor, ao supervisor e às escolas para a prática da avaliação. Os resultados indicaram que, de modo geral, as práticas de avaliação escolar não correspondem aos padrões exigidos pelos textos legais. A deficiência de informações adequadas sobre a teoria atual de avaliação e sobre instrumentos e procedimentos, bem como a insuficiência de condições de prática necessárias à execução da avaliação nos moldes recomendados destacam-se como questões chave do problema.

Does mixed frequency vector error correction model add relevant information to exchange misalignment calculus? Evidence for United States

Real exchange rate is an important macroeconomic price in the economy and a ects economic activity, interest rates, domestic prices, trade and investiments ows among other variables. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that it is possible to calculate the misalignment from a mixed ointegrated vector error correction framework. An empirical exercise using United States' real exchange rate data is performed. The results suggest that the model with mixed frequency data is preferred to the models with same frequency variables

Price discovery using a regime-sensitive cointegration approach

This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.