Đang chuẩn bị liên kết để tải về tài liệu:
Poverty Impact Analysis: Approaches and Methods - Chapter 6

Poverty Mapping and GIS Application in Indonesia: How Low Can We Go? - Mục tiêu tổng thể của Ngân hàng Phát triển Châu Á (ADB) là để xóa đói giảm nghèo, đó là phù hợp với Mục tiêu Phát triển Thiên niên kỷ (MDG) Số 1 là giảm một nửa tỷ lệ đói nghèo vào năm 2015. Trong bối cảnh này, một kỹ thuật có hệ thống để xác định các vùng nghèo là rất quan trọng trong việc cải thiện các chương trình xóa đói giảm nghèo. Hầu hết các chỉ số nghèo phát triển với các dữ. | CHAPTER 6 Poverty Mapping and GIS Application in Indonesia How Low Can We Go Uzair Suhaimi Guntur Sugiyarto Eric B. Suan and Mary Ann Magtulis Introduction The overarching goal of the Asian Development Bank ADB is to reduce poverty which is in line with Millennium Development Goal MDG No. 1 of halving poverty incidence by 2015. In this context a systematic technique for identifying poor regions is very important in improving poverty reduction programs. Most poverty indicators developed with national household survey data however are reliable only at very aggregated levels such as province or state with a possibility of further disaggregation into urban and rural. Poverty indicators in Indonesia derived from the National Socioeconomic Survey SUSENAS for instance are reliable only up to the provincial level by urban and rural areas. This level of aggregation may not be appropriate for various poverty reduction projects or programs. Therefore the availability of poverty indicators at a more disaggregated geographical area is very essential especially in the context of poverty targeting and other poverty reduction programs. One way to develop poverty indicators for smaller areas is to use poverty mapping which has been implemented in Indonesia since 1990 Suryahadi and Sumarto 2003b . The main goal of poverty mapping is to generate reliable estimates of poverty indicators at disaggregated levels to better understand local specificities. It would otherwise not be possible to obtain such disaggregated indicators given the existing household survey data. Poverty mapping results have been increasingly used to geographically target scarce resources Baschieri and Falkingham 2005 . Mapping results may also include other welfare indicators such as the health and nutritional status of the population. Box 6.1 highlights the benefits that poverty mapping can substantiate in policies while to present a balance view Box 6.2 cites different concerns underlying the efficiency of the .