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The News

Published Date: Oct 21, 2012


Professor Stephen Haslett from Massey University, New Zealand, has said that large scale national surveys are usually unable to provide detailed information at local level which necessities the use of small area estimate (SAE), a technique that provides reliable estimates from lower geographic level by using statistical modeling.

Prof Haslett was speaking at a special lecture on ‘Measuring poverty in small areas: how low can you go?’ organised by World Food Programme and Sustainable Development Policy Institute to mark World Poverty Day. Abid Qaiyum Suleri, the Executive Director of SDPI, was in the chair while Shakeel Ahmad Ramay, senior research associate, SDPI, moderated the proceedings.

Prof Haslett said that WFP and SDPI are using a specialised analysis technique called SAE to map poverty and to assess food insecurity, hunger and malnutrition in the country. He said that role of SAE in understanding the dimensions and finer details of poverty is very important.

He told the participants that SAE extracts detailed information out of existing data mostly by using both survey and census data and “borrow strength” from the relationship between observations via a statistical model. He said that it is often possible to produce and predict accurate estimates even where there is no survey data in the area.

He said that accuracy of estimates depends upon accurate statistical model, qualified statisticians, and availability of census and survey data with the same “other variables” that run at concurrent time.

Giving special remarks, Krishna Pahari, from World Food Programme said that WFP is using this technique for a long time.