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Tables and Figures for: Development in the Americas 2016

By Department of Research and Chief Economist (VPS/RES/RES)

This dataset contains the tables and figures for the 2016 edition of Development in the Americas. Book description: Why should people--and economies--save? The typical answer usually focuses on the need to protect against future shocks, to smooth consumption during hard times, in short, to save for the proverbial rainy day. This book approaches the question from a slightly different angle. While saving to survive the bad times is important, saving to thrive in the good times is what really counts. People must save so they can invest in their own and their children's health and education, live productive fulfilling lives, and end their days in comfort and peace. Firms must save so they can grow productive enterprises that employ more workers in better jobs to produce quality goods for domestic and international markets. Governments must save to build bridges, highways, and airports that support a productive economy, to provide quality services such as education, health, water, and sanitation to their citizens, and to assure their senior citizens a dignified, worry-free retirement. In short, countries must save for a sunny day -a time when everyone can bask in the benefits of growth, prosperity, and well-being.

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Metadata & use

Identifier https://doi.org/10.60966/9bdjiwtb
License Creative Commons Attribution–NonCommercial–NoDerivs 3.0 IGO
Citation

Cavallo, Eduardo A.;Serebrisky, Tomás;Frisancho, Verónica;Karver, Jonathan;Powell, Andrew;Margot, Diego;Suárez-Alemán, Ancor;Fernández-Arias, Eduardo;Marzani, Matías;Berstein, Solange;Bosch, Mariano;Oliveri, María Laura;Izquierdo, Alejandro;Busso, Matías;Fernandez, Andres;Rud, Juan Pablo, 2016, Tables and Figures for: Development in the Americas 2016, IDB Open Data, https://doi.org/10.60966/9bdjiwtb
Published date 2016-06-01
Modified date 2025-04-10
Language English
Temporal coverage 1980-2014
Country
Region Latin America and the Caribbean
Publisher
Author
Data collection type Observational Data
Data structure Semistructured Data

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