Cookies?
Library Header Image
LSE Research Online LSE Library Services

Identifying the poor: a multiple indicator approach

Abul Naga, Ramses H. (1994) Identifying the poor: a multiple indicator approach. DARP, 9. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London, UK.

[img]
Preview
PDF
Download (646Kb) | Preview

Abstract

The standard approach to the study of poverty assumes the existence of an ideal variable that captures the extent of deprivation. In this paper we postulate that poverty is involved with many dimensions. We use a latent variable framework to predict the extent of an individual's hardship as a function ?i =ax1i + bx2i +..., where the x's are indicators of i's income status, yi, and the latter variable is not observed.

Item Type: Monograph (Discussion Paper)
Official URL: http://sticerd.lse.ac.uk
Additional Information: © 1994 Ramses H. Abul Naga
Library of Congress subject classification: H Social Sciences > HN Social history and conditions. Social problems. Social reform
H Social Sciences > HB Economic Theory
H Social Sciences > HV Social pathology. Social and public welfare. Criminology
Journal of Economic Literature Classification System: I - Health, Education, and Welfare > I3 - Welfare and Poverty > I32 - Measurement and Analysis of Poverty
C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C39 - Other
Sets: Collections > Economists Online
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Identification Number: 9
Date Deposited: 07 Jul 2008 15:22
URL: http://eprints.lse.ac.uk/6621/

Actions (login required)

Record administration - authorised staff only Record administration - authorised staff only

Downloads

Downloads per month over past year

View more statistics