The impact of the Bolsa Escola/Familia conditional cash transfer program on enrollment, dropout rates and grade promotion in Brazil

We examine the impact of Brazil's Bolsa Escola/Familia program on Brazilian children's education outcomes. Bolsa provides cash payments to poor households if their children (ages 6 to 15) are enrolled in school. Using school census data to compare changes in enrollment, dropping out and grade promotion across schools that adopted Bolsa at different times, we estimate that the program has: increased enrollment by about 5.5% (6.5%) in grades 1-4 (grades 5-8); lowered dropout rates by 0.5 (0.4) percentage points in grades 1-4 (grades 5-8); and raised grade promotion rates by 0.9 (0.3) percentage points in grades 1-4 (grades 5-8). About one third of Brazil's children participate in Bolsa, so assuming no spillover effects onto non-participants implies that Bolsa's impacts are three times higher than these estimates. However, simple calculations using enrollment impacts suggest that Bolsa's benefits in terms of increased wages may not exceed its costs. (C) 2011 Elsevier B.V. All rights reserved.

Gradients in N-cycling attributes along forestry and agricultural land-use systems are indicative of soil capacity for N supply

Indicators of soil quality associated with N-cycling were assessed under different land-use systems (native forest NAT, reforestation with Araucaria angustifolia or Pinus taeda and agricultural use AGR) to appraise the effects on the soil potential for N supply. The soil total N ranged from 2 to 4 g/kg (AGR and NAT, respectively), and the microbial biomass N ranged from 80 to 250 mg/kg, being higher in NAT and A. angustifolia, and lower in P. taeda and AGR sites. Activities of asparaginase (ca. 50200 mg NH4+-N/kg per h), glutaminase (ca. 200800 mg NH4+-N/kg per h) and urease (ca. 80200 mg NH4+-N/kg/h) were also more intense in the NAT and A. angustifolia-reforested soils, indicating greater capacity for N mineralization. The NAT and AGR soils showed the highest and the lowest ammonification rate, respectively (ca. 1 and 0.4 mg NH4+-N/kg per day), but the inverse for nitrification rate (ca. 12 and 26%), indicating a low capacity for N supply, in addition to higher risks of N losses in the AGR soil. A multivariate analysis indicated more similarity between NAT and A. angustifolia-reforested sites, whilst the AGR soil was different and associated with a higher nitrification rate. In general, reforestation with the native species A. angustifolia had less impact than reforestation with the exogenous species P. taeda, considering the soil capacity for N supply. However, AGR use caused more changes, generally decrease in indicators of N-cycling, showing a negative soil management effect on the sustainability of this agroecosystem.

Cash balance management: A comparison between genetic algorithms and particle swarm optimization

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.