Program Conditionality and Food Security: The Impact of PROGRESA and PROCAMPO Transfers in Rural Mexico

This paper examines the PROGRESA and PROCAMPO cash transfer programs in Mexico and evaluates their impact on household food security and nutrition. These two programs differ in their targeting and design: PROGRESA is aimed at women and program conditionality is linked to current consumption and human capital investment; PROCAMPO benefits male farmers and program conditionality is linked to agricultural production. The main question addressed by the paper is whether a cash transfer program geared to agricultural production can have the same impact on food security as a cash transfer program geared to consumption through purchases. Our results suggest that monetary payments linked to a productive asset -land- can have as large or larger impact on food security as cash transfers not linked to a productive asset. We show that both programs boost total food consumption and caloric intake in similar proportions. However, increased food security is achieved through different channels - for PROGRESA through purchases while for PROCAMPO through investment in home production. This suggests that the choice of program design depends on objectives beyond total food consumption and caloric intake, such as consumption from specific food categories, diversity of food consumption, investment in agricultural production, and the degree of access to retail food markets.Cash Transfer Programs, PROGRESA, PROCAMPO, Food Security

Kerangka Dasar Sistem Informasi Manajemen Bagian II Struktur Dan Pengembangannya

xiv.300 hlm. : - ; 24 cm

Akuntansi Usaha Kecil Untuk Berkembang

viii,98 hlm., 21 cm

Using device detection techniques in M-learning scenarios

Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses