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O Atrito nas Pesquisas Longitudinais: O Caso da Pesquisa Mensal de EMPREGO (PME) do IBGE

Author

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  • Rafael Perez Ribas
  • Sergei Suarez Dillon Soares

Abstract

O objetivo deste artigo é estimar os determinantes do atrito/permanência de pessoas no painel da Pesquisa Mensal de Emprego (PME), do Instituto Brasileiro de Geografia e Estatística (IBGE) e, além disso, testar se ignorar a não-aleatoriedade deste desgaste causa algum viés na análise de regressões. O atrito pode ser de três tipos: a) aleatório, que não gera qualquer tipo de viés em estimações de parâmetros; b) função de variáveis observadas, cujo viés pode ser corrigido mediante repesagem adequada; e c) função de variáveis não-observadas, cujo viés pode ser corrigido usando-se um probit bivariado para variáveis discretas ou a correção de Heckman para variáveis contínuas. Os resultados apontam que a taxa de atrito na pesquisa tende a ser maior nos meses de férias, e que há uma forte correlação dessa taxa com as características geralmente associadas a uma mobilidade geográfica maior. Além disso, tanto características do processo de entrevista quanto fatores socioeconômicos são significativamente relacionados à probabilidade de atrito no painel. Nos modelos adotados para testar o viés do desgaste no painel, assim como de outros critérios de seleção amostral, constatamos que todos estes são endógenos, apesar de alguns não estarem diretamente correlacionados com a equação de interesse. Por fim, mostramos que a ausência do controle para seleção amostral, o que inclui a retenção no painel, pode incorrer em algumas análises enviesadas. Contudo, a inclusão do controle para somente alguns mecanismos de seleção pode fornecer estatísticas ainda mais inconsistentes do que se não fosse incluído nenhum mecanismo. Our objective is to analyze the gravity of panel attrition in the Brazilian Monthly Employment Survey (PME). There are three types of panel attrition: a) random, that does not produce any selection bias; b) function of observables, whose bias can be corrected through an appropriate re-weighing scheme; and c) function of unobservable variables, whose bias can be corrected through a bivariate probit for discrete variables or a Heckman correction for continuous ones. To test the gravity of panel attrition bias we estimated a transition to unemployment model both with and without attrition bias controls. Our results are that attrition tends to increase during school vacations and that attrition is strongly correlated to geographical mobility. Our conclusion is that while attrition bias does exist, its magnitude is small and its elimination does not substantially change analysis made using the models. In addition, in some cases, since it is not possible to control simultaneously for observable and non-observable attrition bias, in some cases the best procedure is not use on controls at all.

Suggested Citation

  • Rafael Perez Ribas & Sergei Suarez Dillon Soares, 2008. "O Atrito nas Pesquisas Longitudinais: O Caso da Pesquisa Mensal de EMPREGO (PME) do IBGE," Discussion Papers 1347, Instituto de Pesquisa Econômica Aplicada - IPEA.
  • Handle: RePEc:ipe:ipetds:1347
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    Cited by:

    1. Costas Meghir & Renata Narita & Jean-Marc Robin, 2015. "Wages and Informality in Developing Countries," American Economic Review, American Economic Association, vol. 105(4), pages 1509-1546, April.
    2. Eduardo Zylberstajn & André Portela Souza, 2016. "The Ins And Outs Of Unemployment In A Dual Labor Market," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 227, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. Ana Barufi & Eduardo Haddad & Peter Nijkamp, 2016. "A comprehensive analysis of the wage curve in Brazil: Non-linearities, urban size, and the spatial dimension," ERSA conference papers ersa16p279, European Regional Science Association.
    4. Ana Maria Bonomi Barufi & Eduardo A. Haddad, Peter Nijkamp, 2016. "New evidence on the wage curve: non-linearities, urban size, and spatial scale in Brazil," Working Papers, Department of Economics 2016_39, University of São Paulo (FEA-USP).
    5. Alvaro Forteza, 2011. "Assessing Redistribution within Social Insurance Systems.The cases of Argentina, Brazil, Chile, Mexico and Uruguay," Documentos de Trabajo (working papers) 1311, Department of Economics - dECON.

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