Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity
Francisca Antman and
David McKenzie
Journal of Development Studies, 2007, vol. 43, issue 6, 1057-1083
Abstract:
Theories of poverty traps stand in sharp contrast to the view that anybody can make it through hard work and thrift. However, empirical detection of poverty traps is complicated by the lack of long panels, measurement error and attrition. This paper shows how dynamic pseudo-panel methods can overcome these difficulties, allowing estimation of nonlinear income dynamics and testing of the presence of poverty traps. The paper explicitly allows for heterogeneity in income dynamics, to account for the possibility that particular groups of individuals may face traps, even if the average individual does not. These methods are used to examine the evidence for a poverty trap in labour earnings, income and expenditure in urban Mexico and are compared to panel data estimates from a short rotating panel. The results do find evidence of nonlinearities in household income dynamics, and demonstrate large bias in the panel data estimates. Nevertheless, even after allowing for heterogeneity and accounting for measurement error, we find no evidence for the existence of a poverty trap for any group in our sample.
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (62)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/00220380701466567 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity (2005) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:jdevst:v:43:y:2007:i:6:p:1057-1083
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/FJDS20
DOI: 10.1080/00220380701466567
Access Statistics for this article
Journal of Development Studies is currently edited by Howard White, Oliver Morrissey and Ken Shadlen
More articles in Journal of Development Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().