The effects of conditional cash transfer programmes on adult labour supply: an empirical analysis using a time-series-cross-section sample of Brazilian municipalities

Neste trabalho, estimamos os efeitos dos Programas Condicionais de Transferência de Renda (PCTR), no Brasil, sobre a oferta de trabalho de mulheres e homens adultos. Para tanto, utilizamos o painel de municípios que são continuamente cobertos pela Pesquisa Nacional por Amostra de Domicílios (PNAD/IBGE) durante o período entre 2001 e 2005. Os efeitos dos PCTR brasileiros são estimados tanto sobre a taxa de participação quanto sobre o número médio de horas trabalhadas. Como a PNAD não investiga diretamente a participação das famílias em PCTR, utilizamos um procedimento indireto para identificar as famílias beneficiárias desses programas. Nossos resultados indicam que os efeitos de interesse não são significativos tanto do ponto de vista estatístico como em termos de magnitude.In this paper, we estimate the effects of the Conditional Cash Transfer (CCT) programmes in Brazil on the labour supply of adult males and females. We employ the panel of municipalities that are continuously investigated by the Pesquisa Nacional por Amostra de Domicílios (PNAD/IBGE) over the years 2001-2005. The effects of the Brazilian CCT programmes are estimated both on the participation rate and the mean number of hours worked. Since PNAD does not ask directly surveyed families about CCT programme participation, we use an indirect procedure to identify beneficiary families. Our results indicate that the effects of interest are not significant both on statistical grounds and in terms of magnitude

Self-Supervised Adversarial Imitation Learning

This paper has been accepted in the International Joint Conference on Neural Networks (IJCNN) 2023Preprin

Self-Supervised Adversarial Imitation Learning

Behavioural cloning is an imitation learning technique that teaches an agent how to behave via expert demonstrations. Recent approaches use self-supervision of fully-observable unlabelled snapshots of the states to decode state pairs into actions. However, the iterative learning scheme employed by these techniques is prone to get trapped into bad local minima. Previous work uses goal-aware strategies to solve this issue. However, this requires manual intervention to verify whether an agent has reached its goal. We address this limitation by incorporating a discriminator into the original framework, offering two key advantages and directly solving a learning problem previous work had. First, it disposes of the manual intervention requirement. Second, it helps in learning by guiding function approximation based on the state transition of the expert's trajectories. Third, the discriminator solves a learning issue commonly present in the policy model, which is to sometimes perform a `no action' within the environment until the agent finally halts.Comment: This paper has been accepted in the International Joint Conference on Neural Networks (IJCNN) 202

Ecología y bienestar humano

La ecología como una ciencia experimental y teórica se inicia el siglo pasado, en un proceso vertiginoso, definido por la necesidad que la sociedad humana tiene de sus aplicaciones. Esta situación, que guardando las proporciones, asemeja las establecidas en la producción por demanda, genera en muchos casos desinformación general en la medida en que se quiera utilizar la naturaleza de una forma inadecuada. Existe una campaña mediática muy bien estructurada para banalizar la ecología, adjetivando algunos conceptos importantes y complejos en expresiones del tipo “comportamiento ecológico”, que es un sinsentido por decir lo menos. Cualquier comportamiento, por nefasto que sea, hace parte de las relaciones entre ese organismo y su ambiente y su estudio es la base de la ecología. En ese contexto presentamos a continuación nuestra opinión científica y académica sobre la ecología, en contraste con la enorme cantidad de información que circula a diario en todos los medios de comunicación