This dataset contains information on Programa Nacional Cuna Más (Cuna Mas, hereinafter), Peru’s largest early childhood development program established in 2012. It focuses on one of the two services provided by Cuna Mas known as Servicio de Cuidado Diurno, a daycare service in marginalized urban areas that provides comprehensive care to children aged 6 to 36 months. Data were collected between November 2013 and January 2014 by the Inter-American Development Bank. The objective of the study was to estimate the association between caregiver quality and the development of very young children (6 to 24 months).

At the IDBG Annual Meeting in 2016, the Board of Governors resolved to endorse the goal of increasing the financing of climate change related projects in LAC to 30% of the IDB’s and IIC’s combined total approvals operations by 2020, subject to demand from borrowing countries and clients and access to external sources of concessional financing.

During 2017, the IDB Group invested approximately US$4.3 billion in climate finance; that is, in development activities carried out by the public and private sectors that reduce greenhouse gas (GHG) emissions and thus mitigate climate change, and/or that reduce vulnerability to climate change and contribute to an adaptation process. This amount represented 28.5% of the IDB Group’s total approvals.
Please note that only data from IDB and IDB Lab are available in this dataset.

At the IDBG Annual Meeting in 2016, the Board of Governors resolved to endorse the goal of increasing the financing of climate change related projects in LAC to 30% of the IDB’s and IIC’s combined total approvals operations by 2020, subject to demand from borrowing countries and clients and access to external sources of concessional financing.

During 2016, the IDB Group invested approximately US$2.7 billion in climate finance; that is, in development activities carried out by the public and private sectors that reduce greenhouse gas (GHG) emissions and thus mitigate climate change, and/or that reduce vulnerability to climate change and contribute to an adaptation process. This amount represented 22% of the IDB Group’s total approvals.
Please note that only data from IDB and IDB Lab are available in this dataset.

This dataset consists of indicators capturing how much students know and are able to do. It includes statistics from international learning assessments such as OECD’s PISA, UNESCO’s SERCE and TERCE, and CSEC of the Caribbean Examination Council. Main indicators: Average score, passing rate, percentage of top performers, percentage of low achievers.


Click here to access the data: https://mydata.iadb.org/d/sqwh-9zsr

This dataset consists of statistics measuring the educational attainment and average years of schooling of the adult population, how many children are actively participating in the school system, the efficiency of the school system, and youth inactivity. Main indicators: mean years of schooling, educational attainment, attendance rates, out of school children, overage rates, years in school vs schooling years, and youth inactivity.

The Brazilian Schools Panel database and Brazilian Municipal Education Panel Database combine and simplify 20 years' worth of data from the Brazilian School Census, educational testing, and educational indicators. This report provides an introduction to the data and serves as a road map to their strengths and limitations.

This dataset contains information on Programa Nacional Cuna Más (Cuna Mas, hereinafter), Peru’s largest early childhood development program established in 2012. It focuses on one of the two services provided by Cuna Mas known as Servicio de Acompañamiento a Familias (SAF), a home visiting program that operates in rural areas and provides one-hour weekly home visits to children aged 0-36 months and their caregiver.

This dataset consists of statistics measuring the financial resources available to fund the education system. Main indicators: Government expenditure on education as % of GDP, in PPP, as % of total government expenditure, expenditure on salaries as % of education expenditure, expenditure on education per student as % of pc gdp.


Click here to access the data: https://mydata.iadb.org/d/y35v-i2ux/

This dataset contains information on Programa Nacional Cuna Más (Cuna Mas, hereinafter), Peru’s largest early childhood development program established in 2012. It focuses on one of the two services provided by Cuna Mas known as Servicio de Acompanamiento a Familias (SAF), a home visiting program that operates in rural areas and provides one-hour weekly home visits to children aged 0-36 months and their caregiver.

The objective of the study was to compare different instruments to measure the quality of home visiting programs. Between August and October 2015, three instruments were administered to a sample of 554 children enrolled in Cuna Mas and receiving home visits at the time of data collection, and on their 176 home visitors who regularly work with 80 supervisors.

The following quality instruments were administered:
• Home Visit Rating Scale, version A+2 (HOVRS; Roggman et al. 2010)
• Home Visit Content and Characteristics Form (HVCCF; Boller et al. 2009)
• A supervisor checklist

The first two quality instruments are widely used among home visiting services in the United States. For each child in the sample, one home visit was filmed and the videos were later coded to create the scores, following the instruments’ manuals. The checklist, on the other hand, was designed based on record forms used by Cuna Mas and other home visiting programs in low- and middle- income countries, and was administered live during the visit by the home visitor’s supervisor.

The final, multilevel dataset includes:
• 554 visits with an identical number of distinct children
• 176 home visitors
• 80 supervisors •

Methodology available at: https://idbg.sharepoint.com/teams/EZ-RG-ESW/RG-K1423/25%20Results%20Management/Publicaciones%20-%20Base%20de%20Datos/measuring-quality-and-characterizing-cuna-mas-home-visits.pdf

This benchmarking index is a learning tool that evaluates the legal, regulatory and operating environments for Public Private Partnerships (PPPs) in transport, water/sanitation and electricity infrastructure for 19 Latin American and Caribbean countries. The analysis and scores in the model provide a comparable assessment of individual countries' readiness and facility for PPP project design and implementation. For the purpose of this index, PPP refers specifically to projects which involve a long-term contract between a public-sector body and a private-sector entity for the design, construction (or upgrading), operation and maintenance of public infrastructure; with finance usually provided by, and significant construction, operation and maintenance risks transferred to, the private-sector, which also bears either availability or demand risk; but with the public sector remaining responsible for policy oversight and regulation; and the infrastructure generally reverting to public-sector control at the end of the contract term.