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Year: 2001 Publisher: Washington, D.C. World Bank
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Year: 2001 Publisher: Washington, District of Columbia : World Bank,
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Nearly 90 percent of agricultural land in the Brazilian Amazon is used for pasture, or has been cleared and left unused. Pasture on average is used with very low productivity. Analysis based on census tract data shows that agricultural conversion of forested areas in the wetter western Amazon would be even less productive, using current technologies.
Digital
Year: 2004 Publisher: Washington, D.C. World Bank
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Year: 2005 Publisher: Washington, D.C. World Bank
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ISBN: 0821367358 9780821367353 Year: 2007 Publisher: Washington, DC: World bank,
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Deforestation --- Forest policy --- Agriculture
Book
Year: 2004 Publisher: [Washington, D.C. : World Bank,
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"A tradable development rights (TDR) program focusing on biodiversity conservation faces a crucial problem defining which areas of habitat should be considered equivalent. Restricting the trading domain to a narrow area could boost the range of biodiversity conserved but could increase the opportunity cost of conservation. The issue is relevant to Brazil, where TDR-like programs are emerging. Current regulations require each rural property to maintain a forest reserve of at least 20 percent, but nascent policies allow some tradability of this obligation. Chomitz, Thomas, and Brandao use a simple, spatially explicit model to simulate a hypothetical state-level program. They find that wider trading domains drastically reduce landholder costs of complying with this regulation and result in environmentally preferable landscapes. This paper--a product of the Infrastructure and Environment Team, Development Research Group--is part of a larger effort in the group to understand the economics of conservation"--World Bank web site.
Book
Year: 2019 Publisher: Washington, D.C. : The World Bank,
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This paper examines two new methods to generate gridded agricultural Gross Domestic Product (GDP) and compares the results with a traditional method. In the case of Brazil, these two new methods of spatial disaggregation and cross-entropy outperform the prediction of agricultural GDP from the traditional method that distributes agricultural GDP using rural population. The paper finds that the best prediction method is spatial disaggregation using a regression approach for all the key crops and contributors to agricultural GDP. However, the issue of degrees of freedom is an important limiting factor, as the approach requires sufficient subnational data. The cross-entropy method with readily available spatially distributed crop, livestock, forest, and fish allocation far outperforms the traditional method, at least in the case of Brazil, and can operate with national- and/or subnational-level data.
Agricultural Sector Economics --- Agriculture --- Cross-Entropy --- Economic Growth --- Economic Theory and Research --- GDP --- Gross Domestic Product --- Macroeconomics and Economic Growth --- Regional Development --- Spatial Disaggregation
Book
ISBN: 9789814818360 Year: 2019 Publisher: Singapore
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ISBN: 9789814818360 9789814818353 Year: 2019 Publisher: Singapore ISEAS Publishing
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