Labor supply, biased technological change and economic growth

Se utiliza un modelo de innovaciones sesgadas para estudiar los efectos de cambios exógenos en la oferta laboral. En un contexto de innovaciones sesgadas, a medida que las economías acumulan capital, el trabajo se hace relativamente más escaso y más caro, por este motivo, hay incentivos para adoptar tecnologías ahorradoras de trabajo. Del mismo modo un cambio en la oferta laboral afecta la abundancia de factores y sus precios relativos. En general, una reducción de la oferta laboral, hace que el trabajo sea más caro y genera incentivos para cambio tecnológico ahorrador de trabajo. Así, el efecto inicial que tiene el cambio en la oferta laboral sobre los precios de los factores es mitigado por el cambio tecnológico. Finalmente, los movimientos en la remuneración a los factores afectan las decisiones de ahorro y, por lo tanto, la dinámica del crecimiento. En este trabajo se exploran las consecuencias de una reducción de la oferta laboral en dos contextos teóricos diferentes: un modelo de agentes homogéneos y horizonte infinito y un modelo de generaciones traslapadas.

A practical approach to a multi-level analysis with a sparse binary outcome within a large surgical trial

Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort. (C) 2011 Elsevier BM. All rights reserved.

Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.

Realized volatility: evidence from Brazil

Using intraday data for the most actively traded stocks on the São Paulo Stock Market (BOVESPA) index, this study considers two recently developed models from the literature on the estimation and prediction of realized volatility: the Heterogeneous Autoregressive Model of Realized Volatility (HAR-RV), developed by Corsi (2009), and the Mixed Data Sampling model (MIDAS-RV), developed by Ghysels et al. (2004). Using measurements to compare in-sample and out-of-sample forecasts, better results were obtained with the MIDAS-RV model for in-sample forecasts. For out-of-sample forecasts, however, there was no statistically signi cant di¤erence between the models. We also found evidence that the use of realized volatility induces distributions of standardized returns that are closer to normal

Comparação de critérios de seleção para precocidade de crescimento em bovinos da raça Guzerá

Objetivou-se com este estudo comparar a seleção com base no ganho médio diário de peso na pré-desmama (GMD) e no número de dias para ganhar 160 kg nessa fase (D160), com e sem correção para efeitos de grupos de contemporâneos (GC), em bovinos da raça Guzerá. Utilizou-se o banco de dados de desenvolvimento ponderal da Associação Brasileira de Criadores de Zebu (ABCZ) para esta raça. A obtenção dos parâmetros e valores genéticos foi feita pelo método da máxima verossimilhança restrita utilizando-se modelo unicaracterístico com equações de modelos mistos. O modelo utilizado foi composto pelo efeito fixo de grupo genético e pelos efeitos aleatórios, genético aditivo direto e de ambiente permanente, além do erro residual. A média para D160 foi de 270,5 dias e para GMD, 642,3 g. As correlações de Spearman entre ganho médio diário e a precocidade em dias para ganhar 160 kg na pré-desmama (PD160), e GMD e PD160c (PD160 corrigido para o efeito de grupo de contemporâneo), foram iguais a 0,91 e 0,94, respectivamente. A seleção para PD160 favorece touros que produzem progênie com desempenho superior e menos variável e a padronização deste critério com base no grupo de contemporâneos melhorou sua eficiência. A classificação dos touros varia de acordo com o critério de seleção utilizado, GMD ou PD160, principalmente nos extremos, onde ocorrem seleção e descarte de reprodutores.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

Multistage and coordinated planning of the expansion of transmission systems

In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.

Reactive power dispatch and planning using a non-linear branch-and-bound algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimised placement of control and protective devices in electric distribution systems through reactive tabu search algorithm

Optimised placement of control and protective devices in distribution networks allows for a better operation and improvement of the reliability indices of the system. Control devices (used to reconfigure the feeders) are placed in distribution networks to obtain an optimal operation strategy to facilitate power supply restoration in the case of a contingency. Protective devices (used to isolate faults) are placed in distribution systems to improve the reliability and continuity of the power supply, significantly reducing the impacts that a fault can have in terms of customer outages, and the time needed for fault location and system restoration. This paper presents a novel technique to optimally place both control and protective devices in the same optimisation process on radial distribution feeders. The problem is modelled through mixed integer non-linear programming (MINLP) with real and binary variables. The reactive tabu search algorithm (RTS) is proposed to solve this problem. Results and optimised strategies for placing control and protective devices considering a practical feeder are presented. (c) 2007 Elsevier B.V. All rights reserved.

Imposing Radiality Constraints in Distribution System Optimization Problems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The application of preprocessing and cutting plane techniques for a class of production planning problems

This paper investigates properties of integer programming models for a class of production planning problems. The models are developed within a decision support system to advise a sales team of the products on which to focus their efforts in gaining new orders in the short term. The products generally require processing on several manufacturing cells and involve precedence relationships. The cells are already (partially) committed with products for stock and to satisfy existing orders and therefore only the residual capacities of each cell in each time period of the planning horizon are considered. The determination of production recommendations to the sales team that make use of residual capacities is a nontrivial optimization problem. Solving such models is computationally demanding and techniques for speeding up solution times are highly desirable. An integer programming model is developed and various preprocessing techniques are investigated and evaluated. In addition, a number of cutting plane approaches have been applied. The performance of these approaches which are both general and application specific is examined.

Optimal capacitor placement in radial distribution networks

The capacitor placement (replacement) problem for radial distribution networks determines capacitor types, sizes, locations and control schemes. Optimal capacitor placement is a hard combinatorial problem that can be formulated as a mixed integer nonlinear program. Since this is a NP complete problem (Non Polynomial time) the solution approach uses a combinatorial search algorithm. The paper proposes a hybrid method drawn upon the Tabu Search approach, extended with features taken from other combinatorial approaches such as genetic algorithms and simulated annealing, and from practical heuristic approaches. The proposed method has been tested in a range of networks available in the literature with superior results regarding both quality and cost of solutions.

An implementation of modified scatter search algorithm to transmission expansion planning

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