This study analyzed the regional concentration of the gross production value (GPV) of firewood in Paraíba from 1994 to 2014. It measured the concentration by means of the Concentration Ratio [CR(k)] of the Herfindahl-Hirschman Index (HHI), Theil's Entropy (E), the Hall-Tindelman Index (HTI), and the Gini Index (G). From the analyses performed, it was concluded that there was growth in the GPV of firewood in Paraíba from R$ 2.59 million to R$ 10.39 million (in current terms). The CR(4) and CR(8) of the municipalities indicated low concentration; the CR(4) in the microregions presented a moderately low concentration, and the CR(8) had moderately high concentration. The HHI of the municipalities and microregions has a competitive market, and the HHI of the mesoregions has moderate concentration; E corroborated the evidence of HHI; HTI presented low regional concentration; G showed medium to strong inequality for mesoregions, weak to medium in microregions and zero to weak in municipalities.

This study analyzed the evolution and degree of the global concentration of pulp exports from 1961 to 2014. In order to measure and analyze the concentration, the following indicators were used: Concentration Ratio [CR(k)]; Herfindahl-Hirschman Index (HHI); Theil Entropy Index (E); Hall and Tideman Index (HTI); Comprehensive Concentration Index (CCI); and Gini Coefficient (G). We concluded that there was a tendency of growth in the global pulp exports during the analyzed period due to an increase in demand driven by population growth and to per capita consumption, enhancing the increase in the number of exporting countries. The CR(k) of the global pulp exporting countries showed that the four [CR(4)] and eight [CR(8)] largest countries present a high concentration, with an oligopolistic market structure and competitive advantage. About 100% of exports are dominated by the 20 largest countries [CR(20)]. The HHI, E, HTI, and CCI indicators showed that there is a concentration in global pulp exportation and presented a deconcentrating tendency. Despite the increase in the number of exporting countries, there was no significant reduction in the inequality of global pulp exports. According to the Gini Coefficient, the inequality was strong to absolute.

Charcoal has an economic, social and environmental importance, because in addition to being a source of energy, it generates employment and income in the rural environment. Therefore, knowing your market is fundamental for the decision-making of those segments that depend on this raw material. This work analyzed the regional concentration of charcoal production in the state of Paraíba, Brazil, from 1994 to 2016. The data used to measure the regional production concentration (in tons) of native Paraíba charcoal were obtained from the Brazilian Institute of Geography and Statistics (IBGE) from 1994 to 2016. The indicators used were the Concentration Ratio [CR(k)], the Herfindahl-Hirschman Index (HHI), Theil's entropy index (E) and the Gini Index (G). The main results show that the mesorregions of Borborema and Sertão Paraibano present concentrations in charcoal production from Paraíba. The CR(k) of the municipalities had a low to moderately low concentration and a moderately high to a high concentration for the microregions; the HHI and E showed deconcentration tendencies from competitive markets; the G showed strong to very strong inequality for the municipalities and microregions on average. It is concluded that the concentration of charcoal production at regional levels is not concentrated, even though it presents a moderate concentration in the partial indices [CR(k)] for the Paraíba microregions.

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This work dimensioned the Brazilian development of forests planted for energy purposes. The analysis was carried out through historical and bibliographic contexts. From the analysis carried out, it was possible to conclude that: the technique of selection of potential species in the early 20th century was the first step in the development of fast growing forests; fiscal incentives provided the resumption of Brazilian economic growth and leveraged forest plantations for energy purposes; charcoal prices were influenced by economic plans, which sought economic stability; over time, real charcoal prices seem to vary without any causal link with real oil prices; the productive efficiency of charcoal in the steel industry was quite significant in the last decades.

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O crescimento do consumo de energia elétrica no Brasil gera impactos no modo de vida da sociedade moderna, quando mostra sua relevância e apresenta diversas possibilidades de estudos. Este artigo analisou a série temporal do consumo de energia elétrica no Nordeste brasileiro, no período de janeiro de 2004 a dezembro de 2013. O método utilizado foi preconizado por Box & Jenkins (1976), por meio dos modelos da família ARIMA. Para a análise da série e a escolha do modelo para previsões do ano de 2013, foi usado como base o Critério de Informação de Akaike, no teste Box-Pierce e no Erro Quadrático Médio de Previsão. Os modelos identificados pelas funções de autocorrelação e de autocorrelação parcial não apresentaram ajustes adequados, sendo necessário buscar novos modelos, de acordo com princípio da parcimônia. O modelo SARIMA(1,1,0)(0,0,1)12 foi que forneceu a melhor previsão para o consumo de energia elétrica no nordeste brasileiro.

Este artigo analisou a concentração brasileira da oferta de bioeletricidade, em 2019. Para mensuração utilizou-se a quantidade e a potência instalada das usinas brasileiras de biomassa, disponíveis no Banco de Informações Geracionais (BIG) da Agência Nacional de Energia Elétrica (ANEEL), em 2019. Utilizou-se os indicadores de Razão de Concentração [CR(k)], Índice de Herfindahl–Hirschman (HHI), Entropia de Theil (E) e Coeficiente de Gini (G). O Sudeste apresentou a maior quantidade de termoelétricas de biomassa e maior potência instalada no Brasil, em 2019. O estado de São Paulo foi o mais representativo, focado na cogeração a partir de resíduos agroindustriais. A concentração estadual para quantidade de usinas foi moderada, destacando os oito estados com maior número de firmas, como mostrado pelo CR(8). Os índices HHI’ e E’ apontaram concentração moderada, enquanto G representou desigualdade forte a muito forte. A potência instalada apresentou concentração moderadamente alta, indicado pelo CR(8), HHI, E e G e relacionado ao elevado potencial agroindustrial e florestal da região centro-sul do país. A geração a partir do agroindustrial teve maior concentração, em contrapartida o nível florestal apresentou a menor concentração, associado a distribuição espacial das filiais de grandes empresas do segmento.