Texto para discussão n. 15: can education targets be met without increasing public spending? An analysis for Brazilian municipalities

O objetivo deste artigo é avaliar se os recursos que os municípios destinam à educação são suficientes para atingir as metas fixadas para o IDEB em 2021. Para tanto, são usadas funções distância direcionais (directional distance functions) em que se especifica apenas a proporção na qual os insumos discricionários podem ser reduzidos. Assume-se que a escolaridade é um insumo fixo no curto prazo, tendo este controle somente sobre seus gastos em educação. Depois de medir o desperdício de recursos, resolve-se um problema de programação linear semelhante ao do DEA cujo resultado é o gasto mínimo necessário para um município atingir a sua meta do IDEB. Os resultados indicam que o desperdício de recursos é expressivo. Para o conjunto dos municípios, o desperdício representa 47,3% e 40,1% do total dos gastos efetivamente realizados quando são assumidas as hipóteses de retornos constantes e variáveis de escala, respectivamente. O gasto efetivamente realizado é muito maior do que o gasto mínimo necessário para atingir as metas. Mesmo quando são feitas simulações a partir do estabelecimento de metas mais duras, fica claro que a restrição não é a escassez de recursos.The purpose of this paper is to evaluate if the resources that municipalities devote to education are sufficient to guarantee that the targets established for 2021 can be reached. In order to do so we use directional distance functions that determine only the proportion by which discretionary inputs should be reduced. We assume that education is a fixed input in the short run, and that the municipalities have control only over the amount of spending on education. After measuring the waste of resources, we solve a linear programming problem similar to DEA which result is the minimum amount of spending required to achieve the target. The results indicate that the amount of resources wasted is expressive. For all the municipalities as a whole the waste represents 47,3% and 40,1% of expenditures in education when we assume constant returns to scale and variables returns to scale, respectively. The effective spending is much higher than the minimum required to achieved the target. Even when we assume more strict targets, we still conclude that the problem is not the scarcity of financial resources.19 páginasOrçamento e FinançasPolíticas EconômicasPolíticas Pública

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Texto para discussão n. 28: os condicionantes do endividamento público importam para prever recessões?

Neste trabalho avaliamos se aspectos relacionados ao endividamento público são úteis para prever recessões, considerando a abordagem de dados em painel não balanceado para 20 países entre 1995 e 2014. Os resultados mostraram a importância de alguns condicionantes do endividamento público para previsão de recessões e a relevância do tratamento para heterogeneidade não observada. O modelo selecionado apresentou critérios estatísticos robustos e conseguiu prever corretamente 75,4% das recessões, dado o cut-off da amostra. Os resultados também sugeriram que, em termos de gestão econômica, a combinação de estabilidade monetária e crescimento do produto pode mitigar as probabilidades de recessão, a despeito do nível da dívida pública. Adicionalmente, o modelo pode ser utilizado para previsão de recessões em países com séries de tempo mais curtas.In this paper we evaluate whether aspects related to public debt are useful to predict recessions, considering unbalanced panel data approach for 20 countries between 1995 and 2014. The results showed the importance of some determinants of public debt for recession forecasting and the treatment relevant for unobserved heterogeneity. The selected model presented robust statistical criteria and was able to predict 75.4% of recessions, given the cut-off of the sample. The results also suggested that, in terms of economic management, the combination of monetary stability and output growth can mitigate the likelihood of a recession, despite the level of public debt. In addition, the model can be used to predict recessions in countries with shorter time series.32 páginasOrçamento e FinançasPolíticas Econômica

Texto para discussão n. 28: os condicionantes do endividamento público importam para prever recessões?

Neste trabalho avaliamos se aspectos relacionados ao endividamento público são úteis para prever recessões, considerando a abordagem de dados em painel não balanceado para 20 países entre 1995 e 2014. Os resultados mostraram a importância de alguns condicionantes do endividamento público para previsão de recessões e a relevância do tratamento para heterogeneidade não observada. O modelo selecionado apresentou critérios estatísticos robustos e conseguiu prever corretamente 75,4% das recessões, dado o cut-off da amostra. Os resultados também sugeriram que, em termos de gestão econômica, a combinação de estabilidade monetária e crescimento do produto pode mitigar as probabilidades de recessão, a despeito do nível da dívida pública. Adicionalmente, o modelo pode ser utilizado para previsão de recessões em países com séries de tempo mais curtas.In this paper we evaluate whether aspects related to public debt are useful to predict recessions, considering unbalanced panel data approach for 20 countries between 1995 and 2014. The results showed the importance of some determinants of public debt for recession forecasting and the treatment relevant for unobserved heterogeneity. The selected model presented robust statistical criteria and was able to predict 75.4% of recessions, given the cut-off of the sample. The results also suggested that, in terms of economic management, the combination of monetary stability and output growth can mitigate the likelihood of a recession, despite the level of public debt. In addition, the model can be used to predict recessions in countries with shorter time series.32 páginasOrçamento e FinançasPolíticas Econômica

Recent cambial appreciation and the evolution of the brazilian exportations: an empirical analysis

It should be emphasized that, as a consequence of the real appreciation, one would expect a negative effect on foreign sales. The empiric analysis shows that the successive all-time records, that have been seen with regard to export financial volumes, have been mainly due to the higher prices of manufactured goods. However, the picture is different when we look at semi manufactured and basic goods, in which cases the results have shown a loss of price competitivity in world markets, which has probably played a major part in bringing about the slowdown of the quantum exported

Texto para Discussão n. 09: os determinantes da eficiência dos estados no gasto público em saúde

O artigo analisa como os critérios técnicos definidos no art. 35 da Lei no 8.080/1990 para distribuição de recursos se relacionam com a eficiência na gestão dos serviços de saúde nas Unidades da Federação. Para este fim, utiliza-se uma medida de eficiência baseada em Fronteira Estocástica onde o insumo é o gasto público em saúde, ao passo que os produtos de saúde são consultas, internações, exames e número de leitos no Sistema Único de Saúde (SUS) no período de 2000 a 2008. Os resultados obtidos evidenciam que o gasto com saúde responde, de maneira positiva, a um aumento na demanda por consultas e exames. Além disso, observa-se que o aumento da eficiência da prestação de serviços de saúde está associado à cobertura dos serviços de saneamento, às características demográficas da população, ao nível de renda e à incidência de epidemias.The paper examines how the technical criteria set out in art. 35 of Law 8.080/1990 for distribution of resources relate to the efficient management of health services in the Federal States. To this end, we use a measure of efficiency based on Stochastic Frontier where the input is public spending on health, whereas health care products are consultations, hospitalizations, tests and number of beds in the Unified Health System (SUS) for the period 2000 to 2008. The results show that spending on health responds positively to an increase in demand for consultations and examinations. Moreover, it is observed that an increasing in the efficiency of delivery of health services is associated with the coverage of sanitation services, the demographic characteristics of the population, income level and the incidence of epidemics.17 páginasOrçamento e FinançasPolíticas Econômica