IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v62y2016icp33-40.html
   My bibliography  Save this article

Heterogeneity in Bolsa Família outcomes

Author

Listed:
  • Barrientos, Armando
  • Debowicz, Darío
  • Woolard, Ingrid

Abstract

The paper examines heterogeneity in programme outcomes from Bolsa Família, a flagship social assistance programme in Brazil reaching 14 million households. Following a review of existing evidence on mean impacts, the paper develops and estimates the first panel data quantile regression model of the distribution of Bolsa Família outcomes across municipalities. The quantile point estimates of programme effects show no significant effects on adult labour force participation but positive and significant effects on girls’ school attendance. Girls’ attendance effects are stronger in municipalities with lowest rates in the conditional distribution of school attendance.

Suggested Citation

  • Barrientos, Armando & Debowicz, Darío & Woolard, Ingrid, 2016. "Heterogeneity in Bolsa Família outcomes," The Quarterly Review of Economics and Finance, Elsevier, vol. 62(C), pages 33-40.
    • Handle: RePEc:eee:quaeco:v:62:y:2016:i:c:p:33-40
    DOI: 10.1016/j.qref.2016.07.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062976916300552
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.qref.2016.07.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    2. Fabio Veras Soares & Sergei Suarez Dillon Soares & Marcelo Medeiros & Rafael Guerreiro Osorio, 2006. "Cash Transfer Programmes in Brazil: Impacts on Inequality and Poverty," Working Papers 21, International Policy Centre for Inclusive Growth.
    3. Abrevaya, Jason & Dahl, Christian M, 2008. "The Effects of Birth Inputs on Birthweight," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 379-397.
    4. Andrea R. Ferro & Ana Lúcia Kassouf & Deborah Levison, 2010. "The impact of conditional cash transfer programs on household work decisions in Brazil," Research in Labor Economics, in: Child Labor and the Transition between School and Work, pages 193-218, Emerald Group Publishing Limited.
    5. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    6. Sergio Firpo & Renan Pieri & Euclides Pedroso Jr. & André Portela Souza, 2014. "Evidence of eligibility manipulation for conditional cash transfer programs," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 15(3), pages 243-260.
    7. Miguel Nathan Foguel & Ricardo Paes de Barros, 2008. "The Effects of Conditional Cash Transfer Programmes on Adult Labour Supply: An Empirical Analysis Using a Time-Series-Cross-Section," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211655420, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    8. Glewwe, Paul & Kassouf, Ana Lucia, 2012. "The impact of the Bolsa Escola/Familia conditional cash transfer program on enrollment, dropout rates and grade promotion in Brazil," Journal of Development Economics, Elsevier, vol. 97(2), pages 505-517.
    9. Armando Barrientos, 2013. "Social Assistance in Developing Countries," One Pager 222, International Policy Centre for Inclusive Growth.
    10. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    11. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    12. Ana C. Dammert, 2009. "Heterogeneous Impacts of Conditional Cash Transfers: Evidence from Nicaragua," Economic Development and Cultural Change, University of Chicago Press, vol. 58(1), pages 53-83, October.
    13. Armando Barrientos, 2013. "The Rise of Social Assistance in Brazil," Development and Change, International Institute of Social Studies, vol. 44(4), pages 887-910, July.
    14. Barrientos,Armando, 2013. "Social Assistance in Developing Countries," Cambridge Books, Cambridge University Press, number 9781107039025, October.
    15. Stefan Holst Bache & Christian M. Dahl & Johannes Tang, "undated". "Headlights on tobacco road to low birthweight outcomes - Evidence from a battery of quantile regression estimators and a heterogeneous panelCreation-Date: 20080508," CREATES Research Papers 2008-20, Department of Economics and Business Economics, Aarhus University.
    16. Djebbari, Habiba & Smith, Jeffrey, 2008. "Heterogeneous impacts in PROGRESA," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 64-80, July.
    17. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    18. Jorge Abrahão de Castro & Natália Sátyro & José Aparecido Ribeiro & Sergei Soares, 2010. "Desafios Para a Inclusão Produtiva das Famílias Vulneráveis: Uma Análise Exploratória," Discussion Papers 1486, Instituto de Pesquisa Econômica Aplicada - IPEA.
    19. Tatiana Britto & Fabio Veras Soares, 2011. "Bolsa Família and the Citizen’s Basic Income: A Misstep?," Working Papers 77, International Policy Centre for Inclusive Growth.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ciula, Raffaele, 2022. "Impacts of Bolsa Familia Program on multidimensional poverty," MPRA Paper 115752, University Library of Munich, Germany.
    2. Daniele Malerba, 2018. "The heterogeneous effects of conditional cash transfers across geographical clusters: do energy factors matter?," Global Development Institute Working Paper Series 212018, GDI, The University of Manchester.
    3. Oconnor, Christopher, 2024. "Do conditional cash transfers create resilience against poverty? Long-run evidence from Jamaica," World Development, Elsevier, vol. 176(C).
    4. Juan M. Villa & Miguel Niño-Zarazúa, 2019. "Poverty dynamics and graduation from conditional cash transfers: a transition model for Mexico’s Progresa-Oportunidades-Prospera program," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(2), pages 219-251, June.
    5. Santos, Felícia Mariana & Corseuil, Carlos Henrique Leite, 2022. "The effect of Bolsa Familia Program on mitigating adolescent school dropouts due to maternity: An area analysis," International Journal of Educational Development, Elsevier, vol. 90(C).
    6. Pavitra Dhamija, 2020. "Economic Development and South Africa: 25 Years Analysis (1994 to 2019)," South African Journal of Economics, Economic Society of South Africa, vol. 88(3), pages 298-322, September.
    7. Burger,Martijn & Hendriks,Martijn & Ianchovichina,Elena, 2022. "Anatomy of Brazil’s Subjective Well-Being : A Tale of Growing Discontent and Polarization in the 2010s," Policy Research Working Paper Series 9924, The World Bank.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Armando Barrientos & Dario Debowicz & Ingrid Woolard, 2014. "Antipoverty Transfers and Inclusive Growth in Brazil," Global Development Institute Working Paper Series iriba_wp04, GDI, The University of Manchester.
    2. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    3. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    4. Nicoletti, Cheti & Best, Nicky, 2012. "Quantile regression with aggregated data," Economics Letters, Elsevier, vol. 117(2), pages 401-404.
    5. Gamper-Rabindran, Shanti & Khan, Shakeeb & Timmins, Christopher, 2010. "The impact of piped water provision on infant mortality in Brazil: A quantile panel data approach," Journal of Development Economics, Elsevier, vol. 92(2), pages 188-200, July.
    6. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    7. Armando Barrientos & Juan Miguel Villa, 2014. "Economic and political inclusion of human development conditional transfer programmes in Latin America?," Global Development Institute Working Paper Series 20014, GDI, The University of Manchester.
    8. Raffaele Miniaci & Paolo Panteghini, 2021. "On the Capital Structure of Foreign Subsidiaries: Evidence from a Panel Data Quantile Regression Model," CESifo Working Paper Series 9085, CESifo.
    9. Brown, Caitlin & Ravallion, Martin & van de Walle, Dominique, 2018. "A poor means test? Econometric targeting in Africa," Journal of Development Economics, Elsevier, vol. 134(C), pages 109-124.
    10. T. Lakshmanasamy, 2022. "Money and Happiness in India: Is Relative Comparison Cardinal or Ordinal and Same for All?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(4), pages 931-957, December.
    11. Sakos, Grayson & Cerulli, Giovanni & Garbero, Alessandra, 2021. "Beyond the ATE: Idiosyncratic Effect Estimation to Uncover Distributional Impacts Results from 17 Impact Evaluations," 2021 Annual Meeting, August 1-3, Austin, Texas 314017, Agricultural and Applied Economics Association.
    12. Dosi, Giovanni & Virgillito, Maria Enrica & Yu, Xiaodan, 2020. "The wage-productivity nexus in the world factory economy," World Development, Elsevier, vol. 129(C).
    13. Sophie Song and Katsushi S. Imai, 2018. "Does the Hunger Safety Net Programme Reduce Multidimensional Poverty? Evidence from Kenya," OPHI Working Papers ophiwp124.pdf, Queen Elizabeth House, University of Oxford.
    14. Balestra, Simone & Backes-Gellner, Uschi, 2017. "Heterogeneous returns to education over the wage distribution: Who profits the most?," Labour Economics, Elsevier, vol. 44(C), pages 89-105.
    15. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile Regression with Panel Data," NBER Working Papers 21034, National Bureau of Economic Research, Inc.
    16. Giovanni Dosi & Maria Enrica Virgillito & Xiaodan Yu, 2023. "Gains from trade or from catching-up? Value creation and distribution in the era of China’s WTO accession," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 119-166, March.
    17. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    18. Daniel Zaga, 2014. "The Impact of Three Mexican Nutritional Programs: The Case of Dif-Puebla," CFD Working Papers 09-2015, Centre for Finance and Development, The Graduate Institute.
    19. Fang, Zheng & Niimi, Yoko, 2015. "Do Losses Bite More than Gains? Evidence from a Panel Quantile Regression Analysis of Subjective Well-being in Japan," AGI Working Paper Series 2015-18, Asian Growth Research Institute.
    20. Djebbari, Habiba & Smith, Jeffrey, 2008. "Heterogeneous impacts in PROGRESA," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 64-80, July.

    More about this item

    Keywords

    Social assistance; Inclusive growth; Latin America; Brazil;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:quaeco:v:62:y:2016:i:c:p:33-40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620167 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.