Household surveys underreport incomes from the upper tail of the distribution, affecting our assessment about inequality. This paper offers a tractable simulation method to deal with this situation in the absence of extra information (e.g., tax records). The core of the method is to draw pseudodata from a mixture between the income empirical distribution and a parametric model for the upper tail, that aggregate to a preestablished top income share. We illustrate the procedure using Peruvian surveys that, as in the rest of Latin America, have displayed a sustained decrease in the Gini index since the 2000s. In a number of experiments, we impose a larger top income share than the one observed in the data, closer to corrected estimates for less egalitarian neighbors (e.g., Chile). We find that even though the point estimates of the Gini index are biased indeed, the corrected indices still decrease in time.
Household surveys underreport incomes from the upper tail of the distribution, affecting our assessment about inequality. This paper offers a tractable simulation method to deal with this situation in the absence of extra information (e.g., tax records). The core of the method is to draw pseudodata from a mixture between the income empirical distribution and a parametric model for the upper tail, that aggregate to a preestablished top income share. We illustrate the procedure using Peruvian surveys that, as in the rest of Latin America, have displayed a sustained decrease in the Gini index since the 2000s. In a number of experiments, we impose a larger top income share than the one observed in the data, closer to corrected estimates for less egalitarian neighbors (e.g., Chile). We find that even though the point estimates of the Gini index are biased indeed, the corrected indices still decrease in time.
High consumption of clean water results in the generation of effluents that need to be treated and then safely discarded. Conventional methods for such treatment often do not offer an economical and sustainable result; therefore, new methods are needed, such as microalgae usage. Microalgae are unicellular beings capable of rapid adaptation, growth, and production of compounds of interest (pharmaceuticals, biofuels and others). This work aimed to study the effectiveness of the microalgae Selenastrum sp. in the treatment of effluents from the textile and pulp & paper industries, as well as the respective effects on its biomass development and accumulation of compounds. Four types of culture were carried out (for each type of effluent, a control, and a control with addition of glucose) lasting eight days, in duplicate, all with the addition of a standard culture medium and controlled abiotic factors. Analyses for compound removal (chemical oxygen demand and colour readings on the 200–800nm range) and biomass development (cell number, its dimensions, and weight) were performed four times during the process. At the end of the experiments, the average removal in effluents for COD and colour were 56.6% and 32.7% respectively, in addition to a biomass accumulation of 0.45 g/L. These results were comparable to those obtained for the control cultivation using glucose as a carbon source (70.0% COD removal and 0.51 g/L biomass accumulation). These results demonstrate the effectiveness of Selenastrum sp. in the treatment of industrial effluents, its resilience in stressful environments and the potential use of its accumulated compounds for biotechnological purposes. Keywords: microalgae, Selenastrum sp., industrial effluent, textile effluent, pulp effluent, effluent treatment
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