Do shocks permanently change output? : Local persistency in economic time series

While it is recognized that output fuctuations are highly persistent over certain range, less persistent results are also found around very long horizons (Conchrane, 1988), indicating the existence of local or temporary persistency. In this paper, we study time series with local persistency. A test for stationarity against locally persistent alternative is proposed. Asymptotic distributions of the test statistic are provided under both the null and the alternative hypothesis of local persistency. Monte Carlo experiment is conducted to study the power and size of the test. An empirical application reveals that many US real economic variables may exhibit local persistency.

After structuralism, a development alternative for Latin America

The paper, first, summarizes Latin American structuralism, and offers reasons why it was so influential and durable in the region, as it attended to real demands, and was part of 1950s’mainstream economics. Second, says why, with 1980s’Great Crisis, structuralism eventually ended itself into crisis, as it was unable to keep pace with historical new facts, particularly with the industrial revolution or takeoff, that made Latin American economies intermediary, still developing, but fully capitalist. Third, it lists the consensus that today exists on economic development. Forth, opposes “official orthodoxy” to “developmental populism”, the former deriving from neoclassical economics, the later from structuralism, and offers, in relation to six strategic issues, a progressive development alternative.

Financial globalization and economic growth

Capital mobility leads to a speed of convergence smaller in an open economy than in a closed economy. This is related to the presence of two capitals, produced with specific technologies, and where one of the capitals is nontradable, like infrastructures or human capital. Suppose, for example, that the economy is relatively less abundant in human capital, leading to a decrease of the remuneration of this capital during the transition. In a closed economy, the remuneration of physical capital will be increasing during the transition. In the open economy, the alternative investment yields the international interest rate, corresponding to the steady state net remuneration of physical capital in the closed economy. The nonarbitrage condition shows a larger difference in the remuneration of the two capitals in the closed economy. It leads to a higher accumulation of human capital and thus to a faster speed of convergence in the closed economy. This result stands in sharp contrast with that of the one-sector neoclassical growth model, where the speed of convergence is smaller in the closed economy.

Bank networks and firm credit: an agent based model approach

Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.

Contagion in financial networks: a network theory and agent-based approaches to modeling the spread of risk in financial systems

Esta dissertação estuda a propagação de crises sobre o sistema financeiro. Mais especi- ficamente, busca-se desenvolver modelos que permitam simular como um determinado choque econômico atinge determinados agentes do sistema financeiro e apartir dele se propagam, transformando-se em um problema sistêmico. A dissertação é dividida em dois capítulos,além da introdução. O primeiro capítulo desenvolve um modelo de propa- gação de crises em fundos de investimento baseado em ciência das redes.Combinando dois modelos de propagação em redes financeiras, um simulando a propagação de perdas em redes bipartites de ativos e agentes financeiros e o outro simulando a propagação de perdas em uma rede de investimentos diretos em quotas de outros agentes, desenvolve-se um algoritmo para simular a propagação de perdas através de ambos os mecanismos e utiliza-se este algoritmo para simular uma crise no mercado brasileiro de fundos de investimento. No capítulo 2,desenvolve-se um modelo de simulação baseado em agentes, com agentes financeiros, para simular propagação de um choque que afeta o mercado de operações compromissadas.Criamos também um mercado artificial composto por bancos, hedge funds e fundos de curto prazo e simulamos a propagação de um choque de liquidez sobre um ativo de risco securitizando utilizado para colateralizar operações compromissadas dos bancos.

Boundary decisions of the firm: make, buy, cooperate

Firms are not atomistic hierarchies only linked with one another at arm’s-length distance in markets. Instead, a myriad of long-lived, highly cooperative relationships between suppliers and customers are pervasively found in the B2B world. And it is within those enmeshed relationships and networks that the co-evolution of capabilities and business specialisms is brought about and developed. If that is the actual ‘topography’ of the business landscape, then the coordination of economic activities in general, and the boundary decisions of each and every firm in particular, are unlikely to be reduced to a (dual) choice between ‘making’ or ‘buying’. Inter-firm cooperation is in itself a third governance structure, in alternative to the hierarchical and the market modes of coordination. And, what is also equally important to note, it is through the make-or-buy-or-cooperate decisions that the (embedded) firm is able to change its nature and scope, redefine its (fuzzy) boundaries, and thus adapt to an ever-changing business setting.

Relações interorganizacionais e confiança no setor da carcinicultura: um estudo de caso na camanor produtos marinhos

This study investigated how the types of confidence based on competence and good will act in the formation and maintenance of cooperation relationships between the Camanor and its partners (Aquatec, Purina, Caçuá, Uvifrios and Malta / Cleyton). It used organizational approaches on networks based primarily on studies of Powell (1987, 1990), Das and Teng (2000, 2001), Child (2001) and Contractor and Lorange (2004) which have described the advantages that cooperative relationships can provide, as well as their limits as alternative governance structures. Confidence has been considered an important factor affecting the actions and development of organizations involved in networks or in strategic alliances (ZAHEER; HARRIS, 2006) and is the most appropriate control mechanism in these situations (SYDOW, 1998). Confidence is seen from two different approaches: the economic and the sociological (ZAHEER; HARRIS, 2006). To facilitate the understanding of confidence some typologies have been created, as proposed by Barney and Hansen (1994), Lane (1998), Das and Teng (2000), Child (2001) and Wever, Martens and Vandenbempt (2005). This study made use of the case study as proposition of Yin (2005). Semi-structured interviews were held with pre-determined routes, in a single stage performed in early 2008. The research subjects were owners and / or responsible for Camanor and its business partners (Aquatec, Purina, Caçuá, Uvifrios and Malta / Cleyton). Also secondary data were collected in several sites related to the industry and enterprises studied, in addition to data collected by previous studies conducted by CARCINEREDES (2006). The primary data were analyzed using the analysing technique of the content proposed by Bardin (1994). Regarding the secondary data, they were qualitatively analyzed according to documentary analysis technique (BARDIN, 1994). Thus, through the data collected, could be concluded that although there is confidence based on good faith in relationships(UZZI, 1998; OF; TENG, 2001), their presence does not determine the formation and / or maintenance of a partnership, serves only in order to facilitate the relationship, making them more flexible. The confidence based on competence (DAS; TENG, 2001) influenced the formation and maintenance of relations studied. Because whether or not to form a relationship with another organization it is used the perception of the partner acts, namely the reputation (image) as decision basis. And it is through the verification of the performance of the partner activities that will determine the continuation of the partnership

Lima beans production and economic revenue as function of organic and mineral fertilization

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Economic analysis of the intercropping of lettuce and tomato in different seasons under protected cultivation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks

The accurate identification of the nitrogen content in crop plants is extremely important since it involves economic aspects and environmental impacts. Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification involves a lot of nonlinear parametes and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought spectral reflectance of plant leaves using artificial neural networks. The network acts as identifier of relationships among pH of soil, fertilizer treatment, spectral reflectance and nitrogen content in the plants. So, nitrogen content can be estimated and generalized from an input parameter set. This approach can be form the basis for development of an accurate real time nitrogen applicator.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Designing a modified Hopfield network to solve an Economic Dispatch problem with nonlinear cost function

Economic Dispatch (ED) problems have recently been solved by artificial neural networks approaches. In most of these dispatch models, the cost function must be linear or quadratic. Therefore, functions that have several minimum points represent a problem to the simulation since these approaches have not accepted nonlinear cost function. Another drawback pointed out in the literature is that some of these neural approaches fail to converge efficiently towards feasible equilibrium points. This paper discusses the application of a modified Hopfield architecture for solving ED problems defined by nonlinear cost function. The internal parameters of the neural network adopted here are computed using the valid-subspace technique, which guarantees convergence to equilibrium points that represent a solution for the ED problem. Simulation results and a comparative analysis involving a 3-bus test system are presented to illustrate efficiency of the proposed approach.

Neural networks in chemosystematic studies of asteraceae: A classification based on a dichotomic approach

This paper describes the application of artificial neural nets as an alternative and efficient method for the classification of botanical taxa based on chemical data (chemosystematics). A total of 28,000 botanical occurrences of chemical compounds isolated from the Asteraceae family were chosen from the literature, and grouped by chemical class for each species. Four tests were carried out to differentiate and classify different botanical taxa. The qualifying capacity of the artificial neural nets was dichotomically tested at different hierarchical levels of the family, such as subfamilies and groups of Heliantheae subtribes. Furthermore, two specific subtribes of the Heliantheae and two genera of one of these subtribes were also tested. In general, the artificial neural net gave rise to good results, with multiple-correlation values R > 0.90. Hence, it was possible to differentiate the dichotomic character of the botanical taxa studied.

An alternative approach to solve convergence problems in the backpropagation algorithm

The multilayer perceptron network has become one of the most used in the solution of a wide variety of problems. The training process is based on the supervised method where the inputs are presented to the neural network and the output is compared with a desired value. However, the algorithm presents convergence problems when the desired output of the network has small slope in the discrete time samples or the output is a quasi-constant value. The proposal of this paper is presenting an alternative approach to solve this convergence problem with a pre-conditioning method of the desired output data set before the training process and a post-conditioning when the generalization results are obtained. Simulations results are presented in order to validate the proposed approach.