Inference About Small-Area Distributions Using Area-Level Tabulations

• Activity Number: 114
• Type: Invited
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Survey Research Methods Section
• Author(s): Raymond Chambers*
• Companies: University of Wollongong
• Keywords: Small area estimation ; Area level data ; Distribution function ; Poverty estimation ; Estimation of proportions

Abstract

The small area distribution of a continuous random variable is the monotone non-decreasing function defined by the proportion of units (individuals, households, businesses) within the small area that have values for this variable that are less than or equal to the argument of the function. Such distributions underly virtually all small area characteristics that are of interest in official statistics, including the increasingly important work on inequality assessment. Standard methods for estimating this function depend typically on access to unit level survey data from the small areas of interest. However, in many applications this is not possible, for example poverty mapping where data confidentiality restrict access to unit level survey data with small area identifiers, or where the agency carrying out the small area analysis does not have the resources to analyse unit level data, as in many developing countries. In this paper we explore model-based methodology where published tabulated data corresponding to estimated small area counts can be used to make inferences about small area distributions. Applications to estimation of widely used poverty measures will be presented.