A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

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).

Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Extração supercrítica do óleo de linhaça: construção do extrator, estudo de parâmetros de processo, avaliação química e antioxidante do produto

The aim of the present study was to extract vegetable oil from brown linseed (Linum usitatissimum L.), determine fatty acid levels, the antioxidant capacity of the extracted oil and perform a rapid economic assessment of the SFE process in the manufacture of oil. The experiments were conducted in a test bench extractor capable of operating with carbon dioxide and co-solvents, obeying 23 factorial planning with central point in triplicate, and having process yield as response variable and pressure, temperature and percentage of cosolvent as independent variables. The yield (mass of extracted oil/mass of raw material used) ranged from 2.2% to 28.8%, with the best results obtained at 250 bar and 50ºC, using 5% (v/v) ethanol co-solvent. The influence of the variables on extraction kinetics and on the composition of the linseed oil obtained was investigated. The extraction kinetic curves obtained were based on different mathematical models available in the literature. The Martínez et al. (2003) model and the Simple Single Plate (SSP) model discussed by Gaspar et al. (2003) represented the experimental data with the lowest mean square errors (MSE). A manufacturing cost of US$17.85/kgoil was estimated for the production of linseed oil using TECANALYSIS software and the Rosa and Meireles method (2005). To establish comparisons with SFE, conventional extraction tests were conducted with a Soxhlet device using petroleum ether. These tests obtained mean yields of 35.2% for an extraction time of 5h. All the oil samples were sterilized and characterized in terms of their composition in fatty acids (FA) using gas chromatography. The main fatty acids detected were: palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2n-6) and α-linolenic (C18:3n-3). The FA contents obtained with Soxhlet dif ered from those obtained with SFE, with higher percentages of saturated and monounsaturated FA with the Soxhlet technique using petroleum ether. With respect to α-linolenic content (main component of linseed oil) in the samples, SFE performed better than Soxhlet extraction, obtaining percentages between 51.18% and 52.71%, whereas with Soxhlet extraction it was 47.84%. The antioxidant activity of the oil was assessed in the β-carotene/linoleic acid system. The percentages of inhibition of the oxidative process reached 22.11% for the SFE oil, but only 6.09% for commercial oil (cold pressing), suggesting that the SFE technique better preserves the phenolic compounds present in the seed, which are likely responsible for the antioxidant nature of the oil. In vitro tests with the sample displaying the best antioxidant response were conducted in rat liver homogenate to investigate the inhibition of spontaneous lipid peroxidation or autooxidation of biological tissue. Linseed oil proved to be more efficient than fish oil (used as standard) in decreasing lipid peroxidation in the liver tissue of Wistar rats, yielding similar results to those obtained with the use of BHT (synthetic antioxidant). Inhibitory capacity may be explained by the presence of phenolic compounds with antioxidant activity in the linseed oil. The results obtained indicate the need for more detailed studies, given the importance of linseed oil as one of the greatest sources of ω3 among vegetable oils

Development of amorphous carbon protective coatings on poly(vinyl)chloride

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelos matemáticos utilizados para descrever curvas de crescimento em aves aplicados ao melhoramento genético animal

A utilização de funções matemáticas para descrever o crescimento animal é antiga. Elas permitem resumir informações em alguns pontos estratégicos do desenvolvimento ponderal e descrever a evolução do peso em função da idade do animal. Também é possível comparar taxas de crescimento de diferentes indivíduos em estados fisiológicos equivalentes. Os modelos de curvas de crescimento mais utilizados na avicultura são os derivados da função Richards, pois apresentam parâmetros que possibilitam interpretação biológica e portanto podem fornecer subsídios para seleção de uma determinada forma da curva de crescimento em aves. Também pode-se utilizar polinômios segmentados para descrever as mudanças de tendência da curva de crescimento animal. Entretanto, existem importantes fatores de variação para os parâmetros das curvas, como a espécie, o sistema de criação, o sexo e suas interações. A adequação dos modelos pode ser verificada pelos valores do coeficiente de determinação (R2), do quadrado médio do resíduo (QM res), do erro de predição médio (EPm), da facilidade de convergência dos dados e pela possibilidade de interpretação biológica dos parâmetros. Estudos envolvendo modelagem e descrição da curva de crescimento e seus componentes são amplamente discutidos na literatura. Porém, programas de seleção que visem a progressos genéticos para a forma da curva não são mencionados. A importância da avaliação dos parâmetros dos modelos de curvas de crescimento é ainda mais relevante já que os maiores ganhos genéticos para peso estão relacionados com seleção para pesos em idades próximas ao ponto de inflexão. A seleção para precocidade pode ser auxiliada com base nos parâmetros do modelo associados à variáveis que descrevem esta característica genética dos animais. Esses parâmetros estão relacionados a importantes características produtivas e reprodutivas e apresentam magnitudes diferentes, de acordo com a espécie, o sexo e o modelo utilizados na avaliação. Outra metodologia utilizada são os modelos de regressão aleatória, permitindo mudanças graduais nas covariâncias entre idades ao longo do tempo e predizendo variâncias e covariâncias em pontos contidos ao longo da trajetória estudada. A utilização de modelos de regressões aleatórias traz como vantagem a separação da variação da curva de crescimento fenotípica em seus diferentes efeitos genético aditivo e de ambiente permanente individual, mediante a determinação dos coeficientes de regressão aleatórios para esses diferentes efeitos. Além disto, não há necessidade de utilizar fatores de ajuste para a idade. Esta revisão teve por objetivos levantar os principais modelos matemáticos frequentistas utilizados no estudo de curvas de crescimento de aves, com maior ênfase nos empregados com a finalidade de estimar parâmetros genéticos e fenotípicos.

Assessing the uncertainties of model estimates of primary productivity in the tropical Pacific Ocean

Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BCGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of similar to 1000 C-14 measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PR specifically yielding too few low PP (< 0.2 g Cm-2 d(-1)) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomassnormalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140 degrees W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. (C) 2008 Elsevier BY. All rights reserved.

Numero de dias de ocorrencia de orvalho em Botucatu, SP.

This paper analyses the dew occurrence in Botucatu, Sao Paulo State, Brazil, in the period from 1971 to 1984. The phenomenon was observed on the grass plot of the Climatological Station in the 'Presidente Medici' Experimental Farm. The station is installed on soil 'Terra Roxa Estruturada', on a middle slope, declivity of 8% and east exposure. Days with dew were summed for the following periods: month, year, season, no rainy period and rainy period. For each period the following values were calculated: mean, mean standard errors and mean confidence interval. Also the absolute extreme values and the amplitude of variation were determined. The confidence interval of the mean were calculated by the 't' statistic, at the level of 5% of error probability. The means were compared by using the 't' statistic, at the level of 5% of error probability. The following table of values corresponds to the regime of dew occurrence in Botucatu, expressed in number of days with dew. The dew occurrence regime in Botucatu was analysed comparatively with the regime at Itatinga, in Sao Paulo State and with the regime of Rio Grande, in Rio Grande do Sul State. -English summary

Liquid-gas phase transition in Bose-Einstein condensates with time evolution

We study the effects of a repulsive three-body interaction on a system of trapped ultracold atoms in a Bose-Einstein condensed state. The stationary solutions of the corresponding s-wave nonlinear Schrödinger equation suggest a scenario of first-order liquid-gas phase transition in the condensed state up to a critical strength of the effective three-body force. The time evolution of the condensate with feeding process and three-body recombination losses has a different characteristic pattern. Also, the decay time of the dense (liquid) phase is longer than expected due to strong oscillations of the mean-squared radius.

Modelagem de distorções entre realizações de referenciais geodésicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Metodologia para avaliação de rodovias extraídas computacionalmente em imagens digitais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimadores da resistência mecânica característica da madeira

Pós-graduação em Agronomia (Energia na Agricultura) - FCA