Institutional sustainability: at what price? UNDP and the new cost‐sharing model in Brazil

By the turn of the twenty‐first century, UNDP had embraced a new form of funding based on ‘cost sharing’, with this source accounting for 51 per cent of the organisation's total expenditure worldwide in 2000. Unlike the traditional donor–recipient relationship so common with development projects, the new cost‐sharing modality has created a situation whereby UNDP local offices become ‘subcontractors’ and agencies of the recipient countries become ‘clients’. This paper explores this transition in the context of Brazil, focusing on how the new modality may have compromised UNDP's ability to promote Sustainable Human Development, as established in its mandate. The great enthusiasm for this modality within the UN system and its potential application to other developing countries increase the importance of a systematic assessment of its impact and developmental consequences.     

Assessment of Perceived Parenting Behaviors: The Exposure to Abusive and Supportive Environments Parenting Inventory (EASE-PI)

Due to an awareness of the frequency of child abuse and lack of a single instrument to assess the extent of exposure to both the abusive and supportive environments provided by parents, a 70 item inventory (the EASE-PI) was developed that is a self-report on how both mother and father treated the respondent. A factor analysis, which was subsequently replicated, revealed three abusive factors (representing emotional, physical, and sexual abusiveness) and three supportive factors (love/support, promotion of independence, and positive modeling/fairness). The same factors emerged regardless of gender of respondent and gender of parent. The inventory provides a means to investigate the differential and interactive effects of exposure to emotional, physical, and sexual abusiveness and the possible mitigating effects of different types of supportive behaviors by each parent.     

Rationing,defective inputs and Bayesian updates under central planning

The enterprise manager anticipates that he will be rationed in his input markets and is required to meet an output target. In order to avoid a penalty for missing the output target, he can purchase the inputs at an earlier time, when rationing is not in effect, but then he must incur an inventory cost. The inputs themselves are defective with a known mean rate but unknown variability; the manager has a prior density over this parameter. He can solve the relevant expected-cost minimisation problem in three ways: (a) by simultaneously determining the optimal amounts to be ordered on the two dates, (b) by dynamic programming, and (c) by dynamic programming combined with Bayesian learning. The paper investigates the properties of the optimal solution under the three scenarios with respect to variations in the defective rate, the level of uncertainty and the relative costs of inventories and of missing the target.