Generating gridded agricultural gross domestic product for Brazil : A comparison of methodologies
2019
Thomas, Timothy S.; You, Liangzhi; Wood-Sichra, Ulrike; Ru, Yating; Blankespoor, Brian; Kalvelagen, Erwin | http://orcid.org/0000-0002-7951-8157 Thomas, Tim; http://orcid.org/0000-0001-7930-8814 You, Liangzhi; http://orcid.org/0000-0002-0546-2074 Wood-Sichra, Ulrike; https://orcid.org/0000-0001-9071-0687 Ru, Yating
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 nationaland/or subnational-level data.
اظهر المزيد [+] اقل [-]Non-PR
اظهر المزيد [+] اقل [-]IFPRI5; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; 4 Transforming Agricultural and Rural Economies; CRP2
اظهر المزيد [+] اقل [-]EPTD; PIM
اظهر المزيد [+] اقل [-]CGIAR Research Program on Policies, Institutions, and Markets (PIM)
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل International Food Policy Research Institute