The Demand for Food of Poor Urban Mexican Households: Understanding Policy Impacts Using Structural Models
Manuela Angelucci and
Orazio Attanasio
American Economic Journal: Economic Policy, 2013, vol. 5, issue 1, 146-78
Abstract:
We use Oportunidades, a conditional cash transfer to women, to show that standard demand models do not represent the sample's behavior: Oportunidades increases eligible households' food budget shares, despite food being a necessity; demand for food and high-protein food changes over time only in treatment areas; the treatment effects on food and high-protein food consumption are larger than the prediction from the Engel curves at baseline; and the curves do not change in eligible households with high baseline bargaining power for the transfer recipient. Thus, handing transfers to women is a likely determinant of the observed nutritional changes. (JEL D12, H23, J16, O12)
JEL-codes: D12 H23 J16 O12 (search for similar items in EconPapers)
Date: 2013
Note: DOI: 10.1257/pol.5.1.146
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (52)
Downloads: (external link)
http://www.aeaweb.org/articles.php?doi=10.1257/pol.5.1.146 (application/pdf)
http://www.aeaweb.org/aej/pol/data/2009-0166_data.zip (application/zip)
Access to full text is restricted to AEA members and institutional subscribers.
Related works:
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:aea:aejpol:v:5:y:2013:i:1:p:146-78
Ordering information: This journal article can be ordered from
https://www.aeaweb.org/journals/subscriptions
Access Statistics for this article
American Economic Journal: Economic Policy is currently edited by Matthew Shapiro
More articles in American Economic Journal: Economic Policy from American Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Michael P. Albert ().