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Do Changes in the Labour Market Take Families Out of Poverty? Determinants of Exiting Poverty in Brazilian Metropolitan Regions

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  • Ana Flavia Machado
  • Rafael Perez Ribas

Abstract

Using survival models, we test whether short-term changes in the labour market affect poverty duration. Data are from the Brazilian Monthly Employment Survey. Such a monthly dataset permits more accurate estimations of events than using annual data, but its panel follows households for a short period. Then methods that control for both right- and left-censoring should be used. The results are as follows: households with zero income are not those with the lowest chances of exiting; changes in aggregate unemployment do not affect poverty duration; and increasing wages in the informal sector has a negative effect on poverty duration.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Journal of Development Studies.

Volume (Year): 46 (2010)
Issue (Month): 9 ()
Pages: 1503-1522

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Handle: RePEc:taf:jdevst:v:46:y:2010:i:9:p:1503-1522

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  1. Ricardo Paes de Barros & Samir Cury & Gabriel Ulyssea, 2007. "A Desigualdade de Renda no Brasil Encontra-se Subestimada? Uma Análise Comparativa com Base na PNAD, na POF e nas Contas Nacionais," Discussion Papers 1263, Instituto de Pesquisa Econômica Aplicada - IPEA.
  2. Rosholm, Michael, 2001. "An Analysis of the Processes of Labour Market Exclusion and (Re-) Inclusion," IZA Discussion Papers 332, Institute for the Study of Labor (IZA).
  3. Alessandro Tarozzi & Angus Deaton, 2009. "Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 773-792, November.
  4. Irina Denisova, 2007. "Entry to and Exit from Poverty in Russia: Evidence from Longitudinal Data," Working Papers w0098, Center for Economic and Financial Research (CEFIR).
  5. Gritz, R. Mark, 1993. "The impact of training on the frequency and duration of employment," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 21-51.
  6. Ann Huff Stevens, 1995. "Climbing Out of Poverty, Falling Back In: Measuring the Persistence of Poverty over Multiple Spells," NBER Working Papers 5390, National Bureau of Economic Research, Inc.
  7. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
  8. Luis Beccaria & Roxana Maurizio, 2009. "Factors associated to poverty mobility in Greater Buenos Aries," Journal of Income Distribution, Journal of Income Distribution, vol. 18(2), pages 35-69, June.
  9. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
  10. Rafael Perez Ribas & Ana Flávia Machado, 2007. "Distinguishing Chronic Poverty from Transient Poverty in Brazil: Developing a Model for Pseudo-Panel Data," Working Papers 36, International Policy Centre for Inclusive Growth.
  11. Anna Christina D'Addio & Michael Rosholm, . "Left-Censoring in Duration Data: Theory and Applications," Economics Working Papers 2002-5, School of Economics and Management, University of Aarhus.
  12. Lorenzo Cappellari & Stephen P. Jemkins, 2002. "Who Stays Poor? Who Becomes Poor? Evidence from the British Household Panel Survey," Economic Journal, Royal Economic Society, vol. 112(478), pages C60-C67, March.
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Cited by:
  1. Luis Beccaria & Roxana Maurizio & Ana Fernández & Paula Monsalvo & Mariana Álvarez, 2013. "Urban poverty and labor market dynamics in five Latin American countries: 2003–2008," Journal of Economic Inequality, Springer, vol. 11(4), pages 555-580, December.

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