Public expenditure and the environmental management of Brazilian municipalities: a panel data model

Environmental expenditure can be classified as an indicator to measure the efforts of public agents with the environment. Cities and countries seek to understand the determinants of environmental spending over time. This research aims to analyze the variables that influence the environmental spending of Brazilian municipalities between the years 2012 and 2016. Thus, this research helps fill the gap on lack of longitudinal research that involves local contexts in relation to public municipal expenditures on the environment. The research method consists of the panel data model. Data were collected on the environmental expenditures of the municipalities and other variables of 4269 Brazilian municipalities, the collection generated 21,329 observations. The results showed that the municipalities of the state of Amapá had better relative expenditure averages, it was also observed that the municipalities in the Northeast region show the worst results. The municipality of Itamaracá, located in the state of Pernambuco, presented the best percentage of the country, 9.47% of the environmental expenditure in relation to total expenditure. Regarding the results of panel data, the variables revenue, population, density, GDP, and HDI presented significance in all models; the models estimated by fixed effects ensure the consistency of the parameters.     

Mapping the global supply and demand structure of rice

Rice plays a major role in the global supply and demand for sustainable food production. The constraints of maintaining sustainable rice production are closely linked to the relationship between the distribution patterns of human activity on the planet and economic growth. Global patterns of rice production can be mapped by using various criteria linked to domestic income, population patterns, and associated satellite brightness data of rice-producing regions. Prosperous regions have more electric lighting, and there are documented correlations between gross domestic product (GDP) and nighttime light. We chose to examine global rice production patterns on a geographical basis. For the purposes of this study, each country is considered to be made up of regions, and rice production is discussed in terms of regional distribution. A region is delineated by its administrative boundaries; the number of regions where rice is produced is about 13,839. We used gridded spatial population distribution data overlain by nocturnal light imagery derived from satellite imagery. The resultant relationship revealed a correlation between regional income (nominal values of GDP were used) and rice production in the world. The following criteria were used to examine the supply and demand structure of rice. Global rice consumption = “caloric rice consumption per capita per day” multiplied by “regional population values”. Regional rice yields = “country-based production” divided by “harvested area” (multiple harvests are taken into account). Regional rice production = “regional harvested areas” multiplied by “rice yield values”. We compared regional rice consumption and production values according to these methods. Analysis of the data sets generated a map of rice supply and demand. Inter-regional shipping costs were not accounted for. This map can contribute to the understanding of food security issues in rice-producing regions and to estimating potential population values in such regions.