Convergence in Brazil: recent trends and long run prospects

This paper applies to the analysis of the interstate income distribution in BraziI a set of techniques that have been widely used in the current empirical literature on growth and convergence. Usual measures of dispersion in the interstate income distribution (the coefficient of variation and Theil' s index) suggest that cr-convergence was an unequivoca1 feature of the regional growth experience in BraziI, between 1970 and 1986. After 1986, the process of convergence seems, however, to have sIowed down almost to a halt. A standard growth modeI is shown to fit the regional data well and to expIain a substantial amount of the variation in growth rates, providing estimates of the speed of (conditional) J3-convergence of approximateIy 3% p.a .. Different estimates of the long run distribution implied by the recent growth trends point towards further reductions in the interstate income inequality, but also suggest that the relative per capita incomes of a significant number of states and the number of ''very poor" and "poor" states were, in 1995, already quite c10se to their steady-state values.

The evolution of international output differences (1960-2000) : from factor to productivity

This article presents a group of exercises of leveI and growth decomposition of output per worker using cross-collntry data from 1960 to :2000. It is shown that at least llntil 197.5 factors of production (capital anel education) ",ere the main source of output dispersion across ecoIlomies and that productivity variance was considerably srnaller than in late years. Qnly after this date the prominence of productivity started to sho\\' up in the data. as the majority of the litcrature has found. The gro\\'th decomposition exercises showecl that t he reversal of relative irnportance of proeluctivity vis-a-\'is factors is explainecl by the very good (bad) performance of procluctivity of fast (slow) growing cconomies. Although growth in the pcriod, on avcragc. is mostly clue to factors accumulation. its variance is explained by productivity.

Toward convergence? The brazilian stock market concentration and the role of private equity in its diversification

Using quantitative data obtained from public available database, this paper discusses the difference between of the Brazilian GDP and the Brazilian Stock Exchange industry breakdown. I examined if, and to what extent, the industry breakdowns are similar. First, I found out that the Stock Exchange industry breakdown is overwhelming different from the GDP, which may present a potential problem to asset allocation and portfolio diversification in Brazil. Second, I identified an important evidence of a convergence between the GDP and the Stock Exchange in the last 9 years. Third, it became clear that the Privatizations in the late 90’s and IPO market from 2004 to 2008 change the dynamics of the Brazilian Stock Exchange. And fourth, I identified that Private Equity and Venture Capital industry may play an important role on the portfolio diversification in Brazil.

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.

Multilayer optimization in radio resource allocation for the packet transmission in wireless networks

In the last decade mobile wireless communications have witnessed an explosive growth in the user’s penetration rate and their widespread deployment around the globe. It is expected that this tendency will continue to increase with the convergence of fixed Internet wired networks with mobile ones and with the evolution to the full IP architecture paradigm. Therefore mobile wireless communications will be of paramount importance on the development of the information society of the near future. In particular a research topic of particular relevance in telecommunications nowadays is related to the design and implementation of mobile communication systems of 4th generation. 4G networks will be characterized by the support of multiple radio access technologies in a core network fully compliant with the Internet Protocol (all IP paradigm). Such networks will sustain the stringent quality of service (QoS) requirements and the expected high data rates from the type of multimedia applications to be available in the near future. The approach followed in the design and implementation of the mobile wireless networks of current generation (2G and 3G) has been the stratification of the architecture into a communication protocol model composed by a set of layers, in which each one encompasses some set of functionalities. In such protocol layered model, communications is only allowed between adjacent layers and through specific interface service points. This modular concept eases the implementation of new functionalities as the behaviour of each layer in the protocol stack is not affected by the others. However, the fact that lower layers in the protocol stack model do not utilize information available from upper layers, and vice versa, downgrades the performance achieved. This is particularly relevant if multiple antenna systems, in a MIMO (Multiple Input Multiple Output) configuration, are implemented. MIMO schemes introduce another degree of freedom for radio resource allocation: the space domain. Contrary to the time and frequency domains, radio resources mapped into the spatial domain cannot be assumed as completely orthogonal, due to the amount of interference resulting from users transmitting in the same frequency sub-channel and/or time slots but in different spatial beams. Therefore, the availability of information regarding the state of radio resources, from lower to upper layers, is of fundamental importance in the prosecution of the levels of QoS expected from those multimedia applications. In order to match applications requirements and the constraints of the mobile radio channel, in the last few years researches have proposed a new paradigm for the layered architecture for communications: the cross-layer design framework. In a general way, the cross-layer design paradigm refers to a protocol design in which the dependence between protocol layers is actively exploited, by breaking out the stringent rules which restrict the communication only between adjacent layers in the original reference model, and allowing direct interaction among different layers of the stack. An efficient management of the set of available radio resources demand for the implementation of efficient and low complexity packet schedulers which prioritize user’s transmissions according to inputs provided from lower as well as upper layers in the protocol stack, fully compliant with the cross-layer design paradigm. Specifically, efficiently designed packet schedulers for 4G networks should result in the maximization of the capacity available, through the consideration of the limitations imposed by the mobile radio channel and comply with the set of QoS requirements from the application layer. IEEE 802.16e standard, also named as Mobile WiMAX, seems to comply with the specifications of 4G mobile networks. The scalable architecture, low cost implementation and high data throughput, enable efficient data multiplexing and low data latency, which are attributes essential to enable broadband data services. Also, the connection oriented approach of Its medium access layer is fully compliant with the quality of service demands from such applications. Therefore, Mobile WiMAX seems to be a promising 4G mobile wireless networks candidate. In this thesis it is proposed the investigation, design and implementation of packet scheduling algorithms for the efficient management of the set of available radio resources, in time, frequency and spatial domains of the Mobile WiMAX networks. The proposed algorithms combine input metrics from physical layer and QoS requirements from upper layers, according to the crosslayer design paradigm. Proposed schedulers are evaluated by means of system level simulations, conducted in a system level simulation platform implementing the physical and medium access control layers of the IEEE802.16e standard.

An essay on economic growth: classical determinants, convergence and financial development

This dissertation surveys the literature on economic growth. I review a substantial number of articles published by some of the most renowned researchers engaged in the study of economic growth. The literature is so vast that before undertaking new studies it is very important to know what has been done in the field. The dissertation has six chapters. In Chapter 1, I introduce the reader to the topic of economic growth. In Chapter 2, I present the Solow model and other contributions to the exogenous growth theory proposed in the literature. I also briefly discuss the endogenous approach to growth. In Chapter 3, I summarize the variety of econometric problems that affect the cross-country regressions. The factors that contribute to economic growth are highlighted and the validity of the empirical results is discussed. In Chapter 4, the existence of convergence, whether conditional or not, is analyzed. The literature using both cross-sectional and panel data is reviewed. An analysis on the topic of convergence using a quantile-regression framework is also provided. In Chapter 5, the controversial relationship between financial development and economic growth is analyzed. Particularly, I discuss the arguments in favour and against the Schumpeterian view that considers financial development as an important determinant of innovation and economic growth. Chapter 6 concludes the dissertation. Summing up, the literature appears to be not fully conclusive about the main determinants of economic growth, the existence of convergence and the impact of finance on growth.

A Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Function

Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

Fecundity and reproductive output of the speckled swimming crab Arenacus cribrarius (Lamarck, 1818) (Brachyura, Portunidae)

Areanaeus cribrarius females were collected over a 12-month period with otter-trawl nets in the Ubatuba littoral zone, Brazil. Ovigerous individuals were measured (CW = carapace width excluding lateral spines) and weighed (WW = wet weight). Each egg brood was weighed (WE = wet weight), dried, and the number of eggs (EN) counted. Scatterplots from EN/CW, EN/WW, and EN/WE were submitted to regression analyses. Mean relative fecundity ((F) over bar') was calculated in each month/season to assess seasonal variation of reproductive intensity. The number of eggs showed a positive correlation with CW, WW, and WE. Fecundity of A. cribrarius ranged from 135,210 to 682,156 eggs, intermediate in comparison with other portunids. Fecundity in Portunidae is typically high; lower values are found in Polybiinae and higher ones in Portuninae. Mean fecundity did not reveal significant differences over months and seasons, but reproductive activity tended to be more intense in summer and winter, a phenomenon related to reduced temperature oscillations as found in subtropical regions.

Comparison between two methods for cardiac output measurement in propofol-anesthetized dogs: thermodilution and Doppler

ObjectiveTo compare cardiac output (CO) measured by Doppler echocardiography and thermodilution techniques in spontaneously breathing dogs during continuous infusion of propofol. To do so, CO was obtained using the thermodilution method (CO(TD)) and Doppler evaluation of pulmonary flow (CO(DP)) and aortic flow (CO(DA)).Study designProspective cohort study.AnimalsEight adult dogs weighing 8.3 +/- 2.0 kg.MethodsPropofol was used for induction (7.5 +/- 1.9 mg kg-1 IV) followed by a continuous rate infusion at 0.7 mg kg-1 minute-1. The animals were positioned in left lateral recumbency on an echocardiography table that allowed for positioning of the transducer at the 3rd and 5th intercostal spaces of the left hemithorax for Doppler evaluation of pulmonary and aortic valves, respectively. CO(DP) and CO(DA) were calculated from pulmonary and aortic velocity spectra, respectively. A pulmonary artery catheter was inserted via the jugular vein and positioned inside the lumen of the pulmonary artery in order to evaluate CO(TD). The first measurement of CO(TD), CO(DP) and CO(DA) was performed 30 minutes after beginning continuous infusion (T0) and then at 15-minute intervals (T15, T30, T45 and T60). Numeric data were submitted to two-way anova for repeated measurements, Pearson's correlation coefficient and Bland & Altman analysis. Data are presented as mean +/- SD.ResultsAt T0, CO(TD) was lower than CO(DA). CO(DA) was higher than CO(TD) and CO(DP) at T30, T45 and T60. The difference between the CO(TD) and CO(DP), when all data were included, was -0.04 +/- 0.22 L minute-1 and Pearson's correlation coefficient (r) was 0.86. The difference between the CO(TD) and CO(DA) was -0.87 +/- 0.54 L minute-1 and r = 0.69. For CO(TD) and CO(DP), the difference was -0.82 +/- 0.59 L minute-1 and r = 0.61.ConclusionDoppler evaluation of pulmonary flow was a clinically acceptable method for assessing the CO in propofol-anesthetized dogs.

Contribuições à análise de robustez de sistemas de controle usando redes neurais

This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented

Stability and convergence analysis of a neural model applied in nonlinear systems optimization

A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

LMI-based algorithm for strictly positive real systems with static output feedback

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